title: AI based pre-screening of large bowel cancer via weakly supervised learning of colorectal biopsy histology images

abstract: Histopathological examination is a pivotal step in the diagnosis and treatment planning of many major diseases. To facilitate the diagnostic decision-making and reduce the workload of pathologists, we present an AI-based pre-screening tool capable of identifying normal and neoplastic colon biopsies. To learn the differential histological patterns from whole slides images (WSIs) stained with hematoxylin and eosin (H&E), our proposed weakly supervised deep learning method requires only slide-level labels and no detailed cell or region-level annotations. The proposed method was developed and validated on an internal cohort of biopsy slides (n=4 292) from two hospitals labeled with corresponding diagnostic categories assigned by pathologists after reviewing case reports. Performance of the proposed colon cancer pre-screening tool was evaluated in a cross-validation setting using the internal cohort (n=4 292) and also by an external validation on The Cancer Genome Atlas (TCGA) cohort (n=731). With overall cross-validated classification accuracy (AUROC = 0.9895) and external validation accuracy (AUROC = 0.9746), the proposed tool promises high accuracy to assist with the pre-screening of colorectal biopsies in clinical practice. Analysis of saliency maps confirms the representation of disease heterogeneity in model predictions and their association with relevant pathological features. The proposed AI tool correctly reported some slides as neoplastic while clinical reports suggested they were normal. Additionally, we analyzed genetic mutations and gene enrichment analysis of AI-generated neoplastic scores to gain further insight into the model predictions and explore the association between neoplastic histology and genetic heterogeneity through representative genes and signaling pathways.

category: pathology


title: PreScription DigitaL ThErapEutic for Patients with Insomnia (SLEEP-I): A Protocol for a Pragmatic Randomized Controlled Trial

abstract:
IntroductionCognitive behavioral therapy for insomnia (CBT-I) is effective at treating chronic insomnia, yet in-person CBT-I can often be challenging to access. Prior studies have used technology to bridge barriers but have been unable to extensively assess the impact of the digital therapeutic on real-world patient experience and multi-dimensional outcomes. Among patients with insomnia, our aim is to determine the impact of a Prescription Digital Therapeutic (PDT) (PEAR-003b, FDA-authorized as Somryst; herein called PDT) that provides mobile-delivered CBT-I on patient-reported outcomes (PROs) and healthcare utilization.

Methods and AnalysisWe are conducting a pragmatically designed, prospective, multi-center randomized controlled trial that leverages Hugo, a unique patient-centered health data-aggregating platform for data collection and patient follow-up from Hugo Health. A total of 100 participants with insomnia from two health centers will be enrolled onto the Hugo Health platform, provided with a linked Fitbit (Inspire 2) to track activity, and then randomized 1:1 to receive (or not) the PDT for mobile-delivered CBT-I (Somryst). The primary outcome is a change in the insomnia severity index score (ISI) score from baseline to 9-weeks post-randomization. Secondary outcomes include healthcare utilization, health utility scores, and clinical outcomes; change in sleep outcomes as measured with sleep diaries; and a change in individual PROs including depressive symptoms, daytime sleepiness, health status, stress, and anxiety. For those allocated to the PDT, we will also assess engagement with the PDT.

Ethics and DisseminationThe Institutional Review Boards at Yale University and the Mayo Clinic have approved the trial protocol. This trial will provide important data to patients, clinicians, and policymakers about the impact of the PDT device delivering CBT-I on PROs, clinical outcomes, and healthcare utilization. Findings will be disseminated to participants, presented at professional meetings, and published in peer-reviewed journals.

Trial Registration NumberNCT04909229

Strengths and limitations of this studyO_LIThis is the first controlled study to examine the impact of a mobile-delivered, prescription digital therapeutic (PDT) delivering Cognitive Behavioral Therapy for Chronic Insomnia (i.e., PEAR-003b, FDA-authorized as Somryst) on real-world patients outcomes of care that includes a multi-dimensional analysis of patient benefit across guideline-recommended health domains (e.g., insomnia severity index) and healthcare utilization (e.g., emergency department visits).
C_LIO_LIThis randomized clinical trial will use Hugo, a novel patient-centered health data-aggregating platform for data collection and patient follow-up, which gathers and collates patient-reported outcomes, clinical outcomes, and healthcare utilization metrics for real-world patients with chronic insomnia. The participant has ownership over their data and contributes it to research.
C_LIO_LIFuture studies should focus on patients with chronic insomnia as well as co-morbid conditions such as major depression and whether sleep improvements can be sustained, particularly in the long-term.
C_LI

category: psychiatry and clinical psychology


title: Resting-State Amygdala Subregion and Precuneus Connectivity Provide Evidence for a Dimensional Approach to Studying Social Anxiety Disorder

abstract:
BackgroundSocial anxiety disorder (SAD) is a prevalent and disabling mental health condition, characterized by excessive fear and anxiety in social situations. Resting-state functional magnetic resonance imaging (fMRI) paradigms have been increasingly used to understand the neurobiological underpinnings of SAD in the absence of threat-related stimuli. Previous studies have primarily focused on the role of the amygdala in SAD. However, the amygdala consists of functionally and structurally distinct subregions, and recent studies have highlighted the importance of investigating the role of these subregions independently.

MethodUsing multiband fMRI, we analyzed resting-state data from 135 participants (42 SAD, 93 healthy controls). By employing voxel-wise permutation testing, we examined group differences of fMRI connectivity and associations between fMRI connectivity and social anxiety symptoms to further investigate the classification of SAD as a categorical or dimensional construct.

ResultsSeed-to-whole brain functional connectivity analysis using multiple  seeds including the amygdala and its subregions and the precuneus, revealed no statistically significant group differences. However, social anxiety severity was significantly negatively correlated with functional connectivity of the precuneus - perigenual anterior cingulate cortex and positively correlated with functional connectivity of the amygdala (specifically the superficial subregion) - parietal/cerebellar areas.

ConclusionOur findings demonstrate clear links between symptomatology and brain connectivity in the absence of diagnostic differences, with evidence of amygdala subregion-specific alterations. The observed brain-symptom associations did not include disturbances in the brains fear circuitry (i.e., disturbances in connectivity between amygdala - prefrontal regions) likely due to the absence of threat-related stimuli.


title: Semantic speech networks linked to formal thought disorder in early psychosis

abstract:
Background and HypothesisMapping a patients speech as a network has proved to be a useful way of understanding formal thought disorder in psychosis. However, to date, graph theory tools have not incorporated the semantic content of speech, which is altered in psychosis.

Study DesignWe developed an algorithm, "netts", to map the semantic content of speech as a network, then applied netts to construct semantic speech networks for a general population sample, and a clinical sample comprising patients with first episode psychosis (FEP), people at clinical high risk of psychosis (CHR-P), and healthy controls.

Study ResultsSemantic speech networks from the general population were more connected than size-matched randomised networks, with fewer and larger connected components, reflecting the non-random nature of speech. Networks from FEP patients were smaller than from healthy participants, for a picture description task but not a story recall task. For the former task, FEP networks were also more fragmented than those from controls; showing more, smaller connected components. CHR-P networks showed fragmentation values in-between FEP patients and controls. A clustering analysis suggested that semantic speech networks captured novel signal not already described by existing NLP measures. Network features were also related to negative symptom scores and scores on the Thought and Language Index, although these relationships did not survive correcting for multiple comparisons.

ConclusionsOverall, these data suggest that semantic networks can enable deeper phenotyping of formal thought disorder in psychosis. We are releasing Netts as an open Python package alongside this manuscript.


title: Optimal protocol design for diffusion-weighted imaging of the prostate: an estimation theory examination of parameter estimate variance

abstract:
Diffusion-weighted imaging (DWI) is routinely used to aid in the detection and characterization of prostate cancer. Given imaging time constraints in a clinical setting, it is important to maximize the statistical efficiency of a DWI examination of the prostate. The objective is to maximize the accuracy with which microstructural information about the prostate can be obtained while minimizing diffusion scan time.

In this study, we apply estimation theory to evaluate the statistical efficiency of different DWI acquisitions and methods. Specifically, we show that the variance of DWI parameters estimated using nonlinear multiexponential signal models is considerably higher than the variance observed using linear signal models. We then derive a simple analytical expression for the efficiency of a linear estimator and use it to optimize b-value sampling for DWI of the prostate.

category: radiology and imaging


title: Multimodal MRI examination of structural and functional brain changes in older women with breast cancer in the first year of antiestrogen hormonal therapy

abstract:
PurposeCancer patients are concerned about treatment-related cognitive problems. We examined effects of antiestrogen hormonal therapy on brain imaging metrics in older women with breast cancer.

MethodsWomen aged 60+ treated with hormonal therapy only and matched non-cancer controls (n=29/group) completed MRI and objective and self-reported cognitive assessment at pre-treatment/enrollment and 12 months later. Gray matter was examined using voxel-based morphometry (VBM), FreeSurfer, and brain age calculations. Functional MRI (fMRI) assessed working memory-related activation. Analyses examined cross-sectional and longitudinal differences and tested associations between brain metrics, cognition, and days on hormonal therapy.

ResultsThe cancer group showed regional reductions over 12 months in frontal, temporal, and parietal gray matter on VBM, reduced FreeSurfer cortical thickness in prefrontal, parietal, and insular regions, and increased working memory-related fMRI activation in frontal, cingulate, and visual association cortex. Controls showed only reductions in fusiform gyrus on VBM and FreeSurfer temporal and parietal cortex thickness. Women with breast cancer showed higher estimated brain age and lower regional gray matter volume than controls at both timepoints. The cancer group showed a trend toward decreased performance in attention, processing speed, and executive function over time. There were no significant associations between brain imaging metrics and cognition or days on hormonal therapy.

ConclusionOlder women with breast cancer showed brain changes in the first year of hormonal therapy. Increased brain activation during working memory processing may be a sign of functional compensation for treatment-related structural changes. This hypothesis should be tested in larger samples over longer time periods.

category: oncology


title: Plasma metabolomics of primary open-angle glaucoma in three prospective US cohorts and the UK Biobank.

abstract:
PurposeTo better understand the etiologic pathways in glaucoma, we aimed to identify pre-diagnostic plasma metabolites associated with glaucoma risk.

MethodsIn a case-control study from the Nurses Health Study (NHS), NHSII and Health Professionals Follow-Up Study (HPFS), 599 incident primary open-angle glaucoma (POAG) cases (mean time between blood draw and diagnosis was 10.3 years) were 1:1 matched to 599 controls. Plasma metabolites were measured with LC-MS/MS at the Broad Institute (Cambridge, MA, USA); 367 metabolites from 17 metabolite classes passed quality control analyses. For comparison, in a cross-sectional study in the UK Biobank, 168 NMR metabolites (Nightingale, Finland; version 2020) were measured in serum samples from 2,238 prevalent glaucoma cases and 44,723 controls. Metabolites were probit-score transformed for normality; multiple logistic regression was used to identify metabolites associated with POAG in NHS/NHSII/HPFS and glaucoma in UK Biobank. In NHS/NHSII/HPFS, we also used Metabolite Set Enrichment Analysis to identify metabolite classes associated with POAG. All analyses adjusted for established glaucoma risk factors. False discovery rate (FDR) and number of effective tests (NEF) were used to adjust for multiple comparisons.

ResultsNine metabolite classes were associated (FDR<0.05) with POAG in NHS/NHSII/HPFS: triglycerides, diglycerides, two lysophospholipids classes [lysophosphatidylcholines and lysophosphatidylethanolamines], and two phospholipid class [phosphatidylethanolamines and phosphatidylcholines] were positively associated, while cholesteryl esters, carnitines, and organic acids and derivatives were inversely associated with POAG risk; further adjustment for covariates minimally altered the results. These associations were particularly stronger for POAG with paracentral visual field loss. In the UK Biobank, notably, triglycerides and phospholipids (from which lysophospholipids are derived through hydrolysis), were confirmed to be associated (p<0.05) with higher glaucoma risk. Also, in the UK Biobank, the metabolites of tyrosine, glucose, and glutamine were positively associated (NEF<0.2) while 3-hydroxybutyrate, acetate, citrate, pyruvate, and lactate (the latter 4 being anionic organic acids) were inversely associated with glaucoma (NEF<0.05).

ConclusionsHigher levels of glycerides (diglycerides and triglycerides) and phospholipids were adversely associated with glaucoma in both the NHS/NHSII/HPFS and the UK Biobank, suggesting that they play an important role in glaucoma pathogenesis.

PRECISHigher glyceride and phospholipid levels in pre-diagnostic plasma was associated with glaucoma risk in three cohorts and were associated with prevalent glaucoma in the UK Biobank. Altered lipid metabolism may be etiologically important in glaucoma.

category: ophthalmology


title: OLFACTORY TRAINING EFFICIENCY IN POST-COVID-19 PERSISTENT OLFACTORY DISORDERS

abstract:
BackgroundPersistent post-viral olfactory disorders (PPVOD) are widely reported after a COVID-19 and estimate to 30% one year after infection. Parosmias are the main qualitative dysosmia associated with olfaction recovery. No treatment is, to date, significantly efficient on PPVOD except olfactory training (OT). The main objective of this work was to evaluate OT efficiency on post-COVID-19 PPVOD.

MethodsConsecutive patients consulting to the ENT department with post-COVID-19 PPVOD were included after mainly clinical examination, the complete Sniffin Stick Test (TDI), the short version of the Questionnaire of olfactory disorders and the SF-36. Patients were trained to practice a self-olfactory training (professional manufactured olfactory training kit) twice a day for 6 months before coming back and undergo the same complete evaluation.

ResultsForty-three patients were included and performed 3,5 months of OT in average. There was a significant improvement in the mean TDI score increasing from 24,7 ({+/-}8,9) before the OT to 30,9 ({+/-}9,8) (p<0,001). Parosmias increased significantly from 8 (18,6%) to 27 (62.8%) (p<0,001). Based on normative data divided by sex and age, a significant increase in the number of normosmic participants was only found for the Threshold values (p<0,001). Specific and general olfaction-related quality of life improved after the OT.

ConclusionsOT seems to be efficient in post-COVID-19 PPVOD, probably on the peripheral regenerative part of the olfactory recovery. Future therapeutic strategies may focus on the central aspects of the post-COVID-19 PPVOD.

category: otolaryngology


title: Modeling and Interpreting Patient Subgroups in Hospital Readmission: Visual Analytical Approach

abstract:
BackgroundA primary goal of precision medicine is to identify patient subgroups and infer their underlying disease processes, with the aim of designing targeted interventions. However, while several studies have identified patient subgroups, there is a considerable gap between the identification of patient subgroups, and their modeling and interpretation for clinical applications.

ObjectivesTo develop and evaluate a novel analytical framework for modeling and interpreting patient subgroups (MIPS) using a three-step modeling approach. (1) Visual analytical modeling to automatically identify patient subgroups and their co-occurring comorbidities, and determine their statistical significance and clinical interpretability. (2) Classification modeling to classify patients into subgroups and measure its accuracy. (3) Prediction modeling to predict a patients risk for an adverse outcome, and compare its accuracy with and without patient subgroup information.

MethodsThe MIPS framework was developed using (1) bipartite networks to identify patient subgroups based on frequently co-occurring high-risk comorbidities; (2) multinomial logistic regression to classify patients into subgroups; and (3) hierarchical logistic regression to predict the risk of an adverse outcome using subgroup membership, compared to standard logistic regression without subgroup membership. The MIPS framework was evaluated on three hospital readmission conditions: chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), and total hip/knee arthroplasty (THA/TKA). For each condition, we extracted cases defined as patients readmitted within 30 days of hospital discharge, and controls defined as patients not readmitted within 90 days of discharge, matched by age, gender, race, and Medicaid eligibility (n[COPD]=29,016, n[CHF]=51,550, n[THA/TKA]=16,498).

ResultsIn each condition, the visual analytical model identified patient subgroups that were statistically significant (Q=0.17, 0.17, 0.31; P<.001, <.001, <.05), were significantly replicated (RI=0.92, 0.94, 0.89; P<.001, <.001, <.01), and were clinically meaningful to clinicians. (2) In each condition, the classification model had high accuracy in classifying patients into subgroups (mean accuracy=99.60%, 99.34%, 99.86%). (3) In two conditions (COPD, THA/TKA), the hierarchical prediction model had a small but statistically significant improvement in discriminating between the readmitted and not readmitted patients as measured by net reclassification improvement (NRI=.059, .11), but not as measured by the C-statistic or integrated discrimination improvement (IDI).

ConclusionsWhile the visual analytical models identified statistically and clinically significant patient subgroups, the results pinpoint the need to analyze subgroups at different levels of granularity for improving the interpretability of intra- and inter-cluster associations. The high accuracy of the classification models reflects the strong separation of the patient subgroups despite the size and density of the datasets. Finally, the small improvement in predictive accuracy suggests that comorbidities alone were not strong predictors for hospital readmission, and the need for more sophisticated subgroup modeling methods. Such advances could improve the interpretability and predictive accuracy of patient subgroup models for reducing the risk of hospital readmission and beyond.

category: health informatics


title: GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Records

abstract:
ObjectiveTo develop a large pretrained clinical language model from scratch using transformer architecture; systematically examine how transformer models of different sizes could help 5 clinical natural language processing (NLP) tasks at different linguistic levels.

MethodsWe created a large corpus with >90 billion words from clinical narratives (>82 billion words), scientific literature (6 billion words), and general English text (2.5 billion words). We developed GatorTron models from scratch using the BERT architecture of different sizes including 345 million, 3.9 billion, and 8.9 billion parameters, compared GatorTron with three existing transformer models in the clinical and biomedical domain on 5 different clinical NLP tasks including clinical concept extraction, relation extraction, semantic textual similarity, natural language inference, and medical question answering, to examine how large transformer models could help clinical NLP at different linguistic levels.

Results and ConclusionGatorTron scaled up transformer-based clinical language models to a size of 8.9 billion parameters and achieved state-of-the-art performance on 5 clinical NLP tasks of different linguistic levels targeting various healthcare information documented in unstructured electronic health records (EHRs). The proposed GatorTron models performed remarkably better in much complex clinical NLP tasks such as natural language inference (9.6% and 7.5% improvements) and question answering (9.5% and 7.77% improvements) compared with existing smaller clinical transformer models (i.e., BioBERT and ClinicalBERT), demonstrating the potential of large transformer-based clinical models for advanced medical artificial intelligent (AI) applications such as question answering.


title: Japanese national well-being survey shows that living alone results in lower satisfaction and affects other relationships, while social networking service usage is related to life satisfaction: A cross-sectional study

abstract: This study examined how social isolation and subjective loneliness impacted subjective well-being across Japan, with the aim of offering policy recommendations. We analyzed data (N = 5,234, age:15-89) obtained through a Japanese population-based national survey conducted in March 2021. First, we found that mean life satisfaction was statistically lowest among the subgroup of respondents who lived alone (approximately 20% of the total), with more pronounced impacts in males. We also found that the frequency of social networking site (SNS) usage was significantly associated with overall life satisfaction, exhibiting a J-curve (three to four times per week was better than everyday usage). The frequency of interaction with others, number of SNS friends, employment/wage satisfaction, family budget/asset satisfaction, subjective health satisfaction, and subjective connectedness were also related to well-being in a dose-dependent manner (Trend P<0.001). Second, our multiple logistic regression model showed that the above relationships were independently and statistically significant (p<0.05). Moreover, a stratified analysis showed that living alone significantly affected these relationships, which suggests that this condition should specifically be addressed in the context of efforts aimed at enhancing subjective well-being. In addition, respondents who lived alone had low subjective connectedness, which also independently influenced well-being, as shown by our multivariate logistic model. In sum, these findings indicate that national well-being enhancement policies should particularly consider social isolation and loneliness, including issues stemming from low social connectedness.

category: health policy


title: Discriminatory ability of gas chromatography-ion mobility spectrometry to identify patients hospitalised with COVID-19 and predict prognosis

abstract:
BackgroundTests that can diagnose COVID-19 rapidly and predict prognosis would be significantly beneficial. We studied the ability of breath analysis using gas chromatography-ion mobility spectrometry (GC-IMS) for diagnosis of COVID-19 and as a predictor for subsequent requirement for Continuous Positive Airway Pressure (CPAP).

MethodsWe undertook a single centre prospective observational study in patients with COVID-19, other respiratory tract infections and healthy controls. Participants provided one breath sample for GC-IMS analysis. We used cross validation analysis to create models that were then tested against the original cohort data. Further multivariable analysis was undertaken to adjust for differences between the comparator groups.

ResultsBetween 01/02/2021 and 24/05/2021 we recruited 113 participants, of whom 72 (64%) had COVID-19, 20 (18%) had another respiratory tract infection and 21 (19%) were healthy controls. Differentiation between patients with COVID-19 and healthy controls, and patients with COVID-19 and those with other respiratory tract infections, was achieved with high accuracy. Identification of patients with subsequent requirement for CPAP was completed with moderate accuracy and was not independently associated on multivariable analysis.

ConclusionsWe have shown that GC-IMS has a high capability to distinguish between acute COVID-19 infection and other disease states. Breath analysis shows promise as a predictor of subsequent requirement for CPAP in hospitalised patients with COVID-19. This platform has considerable benefits due to the test being rapid, non-invasive and not requiring specialist laboratory processing.

category: infectious diseases


title: Assessment of indoor biological air quality at a mass gathering event in an unimproved exhibition facility during the COVID-19 pandemic using a novel air sampling technology.

abstract:
The objective was to evaluate the determination of biomarkers of air quality during a mass gathering event at a convention center using a novel air sampling device, AirAnswers(R). This sampler has previously only been used in smaller locations. Here it was run at five crowded locations within the exhibit area for the four days duration of a trade show. The AirAnswers(R) device uses electro-kinetic flow to sample air at high rates and capture bio-aerosols on grounded electrodes in assayable form. Cartridges were removed from the devices and immediately conveyed to the Inspirotec facility in North Chicago, where assays were performed.

Biomarkers determined were for allergens and molds previously described for this system. Testing for a new marker, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA was also included. The method was validated by determination of capture efficiency with reference to an impinger sampler in a Class III controlled environment chamber. Average capture efficiency for triplicate runs was 14%. One SARS-CoV-2 positive sample as found at the registration area, which was physically separate from the main exhibit area.

Cat allergen Fel d 1was found in four of the locations, dog allergen Can f 1 at two. The airborne biomarker of mold proliferation, (1[->]3)-{beta}-D-Glucan, was above the assay range in all locations. The widespread presence of this mold marker could be accounted for by signs of water leakage. A generic 18S RNA marker for mold was developed and similarly showed the presence of mold in all locations, as was a genus marker for penicillium. A species marker for Cladosporium cladosporioides was in two locations. Species markers for Eurotium amstelodami and Trichoderma viride were each in a single location.

The main findings were of the widespread presence of mold markers, and the sporadic appearance of SARS-CoV-2. Masking was recommended but not enforced.


title: Metabolomic profiles of chronic distress predict future cardiovascular disease risk

abstract:
BackgroundChronic psychological distress has been associated with increased risk of cardiovascular disease (CVD). However, mechanistic evidence explaining the observed associations remains limited and, with data are particularly sparse among women. This study examined if a metabolite profile linked with distress would be associated with increased risk of CVD.

MethodsA plasma metabolite-based distress score (MDS) of twenty metabolites was derived in a cross-sectional, 1:1 matched case-control dataset (n=558 women) in the Nurses Health Study (NHS). We then calculated this score in two other cohorts, the Womens Health Initiative Observational Cohort (WHI-OS) and the Prevencion con Dieta Mediterranea (PREDIMED) trial, and tested association with risk of developing adjudicated measures of CVD in each cohort. We considered incident coronary heart disease (CHD) in the WHI-OS dataset which included 944 postmenopausal women (472 CHD cases; mean time to event of 5.8 years), and incident CVD (including stroke, myocardial infarction, CVD death) in the PREDIMED dataset which included 980 men and women (224 CVD cases, mean time to event of 3.1 years).

ResultsIn the WHI-OS, a 1-SD increase in the plasma MDS was associated with a 14% increased risk of incident CHD (odds ratio [OR]=1.14, 95% CI: 1.03 - 1.26), adjusting for known CVD risk factors excluding total and HDL cholesterol. This association was attenuated after including total and HDL cholesterol (OR=1.09; 95% CI: 0.98 - 1.21). Of the component metabolites in the MDS, tryptophan and threonine were inversely associated with incident CHD risk. In PREDIMED, each one SD increase in the MDS was associated with a 17% increased incident CVD risk (OR=1.17, 95% CI: 1.00 - 1.38), after adjusting for risk factors including total and HDL cholesterol. Similar associations were observed in men and women. Four individual metabolites in the MDS were associated with incident CVD risk in fully adjusted models in PREDIMED. Biliverdin and C36:5 PC plasmalogen had inverse associations, whereas C16:0 ceramide and C18:0 LPE each had positive associations with CVD risk.

ConclusionsOur study sheds light on the key molecular alterations that characterize chronic distress and are predictive of subsequent CVD risk in men and women. These findings provide additional evidence for the role of distress in CVD development.

category: cardiovascular medicine


title: Development and validation of a cardiovascular diseases risk prediction model for Chinese males (CVDMCM)

abstract:
AimsDeath due to cardiovascular diseases (CVD) increased significantly in China. One way to reduce CVD is to identify people at risk and provide targeted intervention. We aim to develop and validate a CVD risk prediction model for Chinese males (CVDMCM) to help clinicians identify those at risk of CVD and provide targeted intervention.

Methods and ResultsWe conducted a retrospective cohort study of 2331 Chinese males without prior CVD to develop and internally validate the CVDMCM. These participants had a baseline physical examination record (2008-2016) and one revisit record by September 2019. With the full cohort, we used single factor cox regression to examine each candidate predictor adjusted for age. 16 sequential prediction models were built on significant predictors. CVDMCM was selected based on the Akaike information criterion, the area under the ROC curve, and the percentage of variation in outcome values explained by the model (R2). This model, the Framingham CVD risk model, and the Wus simplified model were all validated by bootstrapping with 1000 repetitions. CVDMCMs C statistics (0.779, 95% CI: 0.733-0.825), D statistic (4.738, 95% CI: 3.270-6.864), and calibration plot demonstrated that CVDMCM outperformed the other two models.

ConclusionsWe developed and internally validated CVDMCM, which predicted 4-year CVD risk for Chinese males with a better performance than Framingham CVD model and Wus simplified model. In addition, we developed a web calculator for physicians to conveniently generate CVD risk scores and identify those with a higher risk of CVD. We believe CVDMCM had great potential for clinical usage.


title: Effect of an Integrated Maternal and Neonatal Health Intervention on Maternal Healthcare Utilization addressing Inequity in Rural Bangladesh

abstract:
BackgroundAlthough Bangladesh has made significant improvements in maternal, neonatal, and child health, the disparity between rich and poor remains a matter for concern.

ObjectiveThe study aimed to increase coverage of women in seeking skilled maternal healthcare services while minimizing inequity gap among different socioeconomic groups.

Methodsicddr, b implemented an integrated maternal and neonatal health (MNH) intervention between 2009 and 2012, in Shahjadpur sub-district of Shirajganj district, Bangladesh. The study was pre- and post-test in design for evaluation including baseline and endline surveys. The baseline and endline surveys were conducted among 3158 and 3540 recently delivered mothers respectively. Asset index derived from household assets using principal component analysis was categorized into five ordinal categories, i.e. Poor, Less poor, Middle, Upper middle, Rich. Inequity in maternal healthcare utilization was calculated for the baseline and endline periods using rich- to-poor ratio and the concentration index.

ResultMean age of mothers were 23.5 and 24.3 years in baseline and endline, respectively. Reduction in rich-poor ratio was quite large in utilization of skilled 4+ antenatal care (ANC) (2.4:1 to 1.1:1), childbirth (1.7:1 to 1.0:1), and postnatal care (PNC) (2.5:1 to 1.0:1) from trained providers between these two surveys. The concentration indices (CI) in endline for skilled 4+ ANC (CI: 0.220 and 0.013), delivery (CI: 0.161 and -0.021), and PNC (CI: 0.197 and -0.004) were found to be lower than the indices in baseline period respectively.

ConclusionThe MNH intervention was successful in reducing inequity in receiving skilled 4+ ANC, delivery, and PNC in rural Bangladesh. Improvements in maternal healthcare utilizations by poor mothers would be influenced by the properly designed and integrated demand- and supply-side MNH interventions package.

category: epidemiology


title: Impact of the representation of contact data on the evaluation of interventions in infectious diseases simulations

abstract: Computational models offer a unique setting to test strategies to mitigate infectious diseases spread, providing useful insights to applied public health. To be actionable, models need to be informed by data, which can be available at different levels of detail. While high resolution data describing contacts between individuals are increasingly available, data gathering remains challenging, especially during a health emergency: many models thus use synthetic data or coarse information to evaluate intervention protocols. Here, we evaluate how the representation of contact data might affect the impact of various strategies in models, in the realm of COVID-19 transmission in educational and work contexts. Starting from high resolution contact data, we use data representations ranging from very detailed to very coarse to inform a model for the spread of SARS-CoV-2 and simulate several mitigation strategies. We find that coarse data representations underestimate the risk of super-spreading events. However, the rankings of protocols according to their efficiency or cost remain coherent across representations, ensuring the consistency of model findings to inform public health advice. Caution should be taken, however, on the quantitative estimations of those benefits and costs that may trigger the adoption of protocols, as these may depend on data representation.


title: Vaccination and Variants: retrospective model for the evolution of Covid-19 in Italy

abstract: The last year of Covid-19 pandemic has been characterized by the continuous chase between the vaccination campaign and the appearance of new variants that put further obstacles to the possibility of eradicating the virus and returning to normality in a short period. In the present paper we consider a deterministic compartmental model to discuss the evolution of the Covid-19 in Italy as a combined effect of vaccination campaign, new variant spreading, waning immunity and mobility restrictions. We analyze the role that different mechanisms, such as behavioral changes due to variable risk perception, variation of the population mobility, seasonal variability of the virus infectivity, and spreading of new variants have had in shaping the epidemiological curve. The fundamental impact of vaccines in drastically reducing the total increase in infections and deaths is also estimated. This work further underlines the crucial importance of vaccination and adoption of adequate individual protective measures in containing the pandemic.


title: Motor Neuron Disease is not clustered or associated with socioeconomic deprivation in Scotland.

abstract:
Background and ObjectivesUnderstanding risk factors and spatial variation of risk may provide insights into the pathological mechanism of motor neuron disease (MND). Socioeconomic status (SES) has been hypothesised as a risk factor, but results from previous studies are inconsistent. No spatial epidemiology studies examining geographic clustering of MND have been performed in Scotland to date. We investigated the effect of SES and geography on MND risk in Scotland using the highly curated and nationally representative Scottish MND Register (CARE-MND) that has over 95% case ascertainment.

MethodsPatients on the Scottish Clinical Audit Research Evaluation for Motor Neurone Disease platform, with date of diagnosis between 01 Jan 2015 and 28 Feb 2021 were included and geocoded with data zones using their residence at diagnosis. Indirectly standardised incidence ratio (SIR) accounting for age and sex was calculated for each health board. Poisson regression was used to examine the effect of SES on MND risk, adjusted for age and sex of population at risk. Geographic clustering was assessed using global Morans Index, Bayesian conditional autoregressive models and SaTScan software.

ResultsAmong 1149 patients included, 1126 (98%) were successfully geocoded. Significantly lower SIR was shown in Highland (0.60, 95% CI 0.44 - 0.80, p<0.001). After adjusting for age and sex in Poisson regression, there was no significant effect of SES on MND risk. Morans Index indicated a weak but significant spatial autocorrelation (I=0.017, p=0.008). However, risk maps using Bayesian modelling showed a relatively homogeneous distribution without distinct patterns across Scotland. Similarly, SaTScan did not detect any significant cluster of high or low risks.

DiscussionOur findings support the notion that MND risk is mostly random-distributed and independent of SES in Scotland. Our results are generalizable to other MND populations.


title: Early Childhood Reading for Pleasure: Evidence from the ABCD Study for Benefits to Cognitive Performance and Mental Health and Associated Changes in Brain Structure

abstract:
BACKGROUNDEarly childhood has increasingly been recognized as an important neurodevelopmental period. However, the links between specific forms of early educational activities and cognition and mental health remain unclear.

METHODSA large-scale analysis on the attainments of childhood Reading for Pleasure (early RfP) and its relationship with young adolescent measures of cognition, mental health and brain structure was conducted, using linear mixed-effects model, structural equation and mediation analyses. Participants were from the Adolescent Brain and Cognitive Development (ABCD) study, a USA national cohort (n=11,878). A two-sample Mendelian randomization (MR) analysis using genetic instruments from two independent genome-wide association studies (GWAS) based on ABCD and GWAS meta-analyses including UK-biobank datasets were conducted to assess potential causal inference.

RESULTSEarly RfP was positively associated with cognitive assessments, which in contrast, was negatively associated with dimensional psychiatric problems in young adolescents. MR analysis revealed a beneficial relationship between early RfP and later-life cognitive performance, and a trend towards a protective relationship between early RfP and later-life attention disorder. Brain regions in which larger cortical areas were positively associated with early RfP included the superior temporal, prefrontal, left angular, parahippocampal, right anterior cingulate (ACC), occipital, supramarginal and orbital regions and subcortical ventral diencephalon (DC), thalamus, and brainstem volumes. Mediation analysis indicated that the brain regions significantly mediated the effects of early RfP with better cognitive performance and lower psychiatric problems.

INTERPRETATIONOur results highlight the importance of encouraging RfP in young children during the critical early childhood stage, as it was associated with beneficial outcomes for cognition, mental health, and brain structure later in life.


title: Phantom-based quantification of the spectral accuracy in dual-layer spectral CT for pediatric imaging at 100 kVp

abstract:
ObjectivesTo determine the spectral accuracy in detector-based dual-energy CT (DECT) at 100 kVp and wide (8 cm) collimation width for dose levels and object sizes relevant to pediatric imaging.

MethodsA spectral CT phantom containing tissue-equivalent materials and iodine inserts of varying concentrations was scanned on the latest generation detector-based DECT system. Two 3D-printed extension rings were used to mimic varying pediatric patient sizes. Scans were performed at 100 and 120 kVp, 4 and 8 cm collimation widths, and progressively reduced radiation dose levels, down to 10% of the nominal value for the standard pediatric abdominal protocol. Virtual mono-energetic, iodine density, effective atomic number, and electron density results were quantified and compared to their expected values for all acquisition settings and phantom sizes.

ResultsDECT scans at 100 kVp provided highly accurate spectral results; however, a size dependence was observed for iodine quantification. For the medium phantom configuration (15 cm diameter), measurement errors in iodine density, effective atomic number, and electron density (ED) were below 0.3 mg/ml, 0.2 and 1.8 %EDwater, respectively. The average accuracy was slightly different from scans at 120 kVp; however, not statistically significant for all configurations. Collimation width had no substantial impact. Spectral results were accurate and reliable for radiation exposures down to 0.9 mGy CTDIvol.

ConclusionsDetector-based DECT at 100 kVp can provide on-demand or retrospective spectral information with high accuracy even at extremely low doses, thereby making it an attractive solution for pediatric imaging.

Key pointsO_LIDual-layer spectral CT at 100 kVp enables high-quality spectral imaging for smaller patients
C_LIO_LILarger collimation width does not affect the accuracy of spectral results
C_LIO_LIAccurate and reliable spectral quantification is achievable at radiation doses down to 0.9 mGy
C_LI


title: NEURONAL AND ASTROCYTIC TETRAPLOIDY IS INCREASED IN DRUG-RESISTANT EPILEPSY

abstract:
BackgroundEpilepsy is one of the most prevalent neurological diseases, a third of patients remain drug-resistant. The exact etiology of drug-resistant epilepsy (DRE) is still unknown. Neural tetraploidy has been associated with neuropathology. The aim of this study was to assess the presence of tetraploid neurons and astrocytes in DRE.

Materials & methodsCortex, hippocampus and amygdala samples were obtained from patients subjected to surgical resection of the epileptogenic zone. Postmortem brain tissue of subjects without previous records of neurological, neurodegenerative or psychiatric diseases were used as controls. The percentage of tetraploid cells was measured by immunostaining of neurons (NeuN) or astrocytes (S100{beta}) followed by flow cytometry analysis. Results were confirmed by image cytometry (ImageStream X Amnis System Cytometer) and with an alternative astrocyte biomarker (NDRG2). Statistical comparison was performed using univariate tests.

ResultsA total of 22 patients and 10 controls were included. Tetraploid neurons and astrocytes were found both in healthy individuals and DRE patients in the three brain areas analyzed: cortex, hippocampus and amygdala. DRE patients presented a higher number of tetraploid neurons (p=0.020) and astrocytes (p=0.002) in the hippocampus compared to controls. These results were validated by image cytometry.

ConclusionWe demonstrated the presence of both tetraploid neurons and astrocytes in healthy subjects and increased levels of both cell types in DRE patients. This is the first time that tetraploid astrocytes are described in healthy subjects. Furthermore, these results provide new insights into epilepsy, opening new avenues for future treatment.

category: neurology


title: Genetic Examination of Hematological Parameters in SARS-CoV-2 Infection and COVID-19

abstract:
BackgroundPeople hospitalized with COVID-19 often exhibit hematological alterations, such as lower lymphocyte and platelet counts, which have been reported to associate with disease prognosis. It is unclear whether inter-individual variability in baseline hematological parameters prior to acute infection influences risk of SARS-CoV-2 infection and progression to severe COVID-19.

MethodsWe assessed the association of blood cell counts and indices with incident SARS-CoV-2 infection and severe COVID-19 in UK Biobank and the Vanderbilt University Medical Center Synthetic Derivative (VUMC SD). Since genetically determined blood cell measures better represent cell abundance across the lifecourse, we used summary statistics from genome-wide association studies to assess the shared genetic architecture of baseline blood cell counts and indices on COVID-19 outcomes.

ResultsWe observed inconsistent associations between measured blood cell indices and both SARS-CoV-2 infection and COVID-19 hospitalization in UK Biobank and VUMC SD. In Mendelian randomization analyses using genetic summary statistics, no putative causal relationships were identified between COVID-19 related outcomes and hematological indices after adjusting for multiple testing. We observed overlapping genetic association signals between hematological parameters and COVID-19 traits. For example, we observed overlap between infection susceptibility-associated variants at PPP1R15A and red blood cell parameters, and between disease severity-associated variants at TYK2 and lymphocyte and platelet phenotypes.

ConclusionsWe did not find convincing evidence of a relationship between baseline hematological parameters and susceptibility to SARS-CoV-2 infection or COVID-19 severity, though this relationship should be re-examined as larger and better-powered genetic analyses of SARS-CoV-2 infection and severe COVID-19 become available.

category: genetic and genomic medicine


title: Imported SARS-COV-2 Variants of Concern Drove Spread of Infections Across Kenya During the Second Year of the Pandemic

abstract:
BackgroundUsing classical and genomic epidemiology, we tracked the COVID-19 pandemic in Kenya over 23 months to determine the impact of SARS-CoV-2 variants on its progression.

MethodsSARS-CoV-2 surveillance and testing data were obtained from the Kenya Ministry of Health, collected daily from 306 health facilities. COVID-19-associated fatality data were also obtained from these health facilities and communities. Whole SARS-CoV-2 genome sequencing were carried out on 1241 specimens.

ResultsOver the pandemic duration (March 2020 - January 2022) Kenya experienced five waves characterized by attack rates (AR) of between 65.4 and 137.6 per 100,000 persons, and intra-wave case fatality ratios (CFR) averaging 3.5%, two-fold higher than the national average COVID-19 associated CFR. The first two waves that occurred before emergence of global variants of concerns (VoC) had lower AR (65.4 and 118.2 per 100,000). Waves 3, 4, and 5 that occurred during the second year were each dominated by multiple introductions each, of Alpha (74.9% genomes), Delta (98.7%), and Omicron (87.8%) VoCs, respectively. During this phase, government-imposed restrictions failed to alleviate pandemic progression, resulting in higher attack rates spread across the country.

ConclusionsThe emergence of Alpha, Delta, and Omicron variants was a turning point that resulted in widespread and higher SARS-CoV-2 infections across the country.


title: Real-world Effectiveness of Casirivimab and Imdevimab in Patients With COVID-19 in the Ambulatory Setting: An Analysis of Two Large US National Claims Databases

abstract:
Background

In a phase III clinical trial, casirivimab and imdevimab (CAS+IMD) reduced the composite endpoint of COVID-19-related hospitalizations or all-cause mortality in outpatients at risk of severe disease. This study assessed real-world effectiveness of CAS+IMD.

Methods

Data from Optum(R) Clinformatics(R) Data Mart (CDM) and IQVIA Pharmetrics Plus (PMTX+) were used to identify patients diagnosed with COVID-19 in ambulatory settings between December 2020 and March 2021 (PMTX+) and June 2021 (CDM), and either treated with CAS+IMD or untreated but treatment-eligible under Emergency Use Authorization. CAS+IMD-treated patients were matched to untreated patients and followed up to 30 days for the outcome of all-cause mortality or COVID-19-related hospitalizations (CDM) and COVID-19-related hospitalizations (PMTX+). Kaplan-Meier estimators were used to calculate outcome risks; Cox proportional-hazard models estimated adjusted hazard ratios (aHR) with 95% confidence intervals (CI).

Results

For CDM, 1116 CAS+IMD-treated patients were matched to 5294 untreated patients; for PMTX+, 3280 CAS+IMD-treated patients were matched to 16,284 untreated patients. The 30-day outcome risk was 2.1% and 5.3% in treated and untreated cohorts, respectively (CDM), and the 30-day risk of COVID-19-related hospitalization was 1.9% and 4.8%, respectively (PMTX+); translating to a 61% lower adjusted outcome risk (CDM aHR 0.39 (95% CI 0.26-0.60; PMTX+ aHR 0.39 (95% CI 0.30-0.51). The benefit of treatment was maintained across multiple subgroups of high-risk patients; earlier intervention was associated with improved outcomes.

Conclusions

This real-world study further supports randomized clinical trial findings that treatment with CAS+IMD reduces the risk of hospitalization and mortality in patients infected with susceptible variants.


title: Oropharyngeal Microbiome Profiled at Admission is Predictive of the Need for Respiratory Support Among COVID-19 Patients

abstract:
The clinical course of infection due to respiratory viruses such as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2), the causative agent of Coronavirus Disease 2019 (COVID-19) is thought to be influenced by the community of organisms that colonizes the upper respiratory tract, the oropharyngeal microbiome. In this study, we examined the oropharyngeal microbiome of suspected COVID-19 patients presenting to the Emergency Department and an inpatient COVID-19 unit with symptoms of acute COVID-19. Of 115 enrolled patients, 74 were confirmed COVID-19+ and 50 had symptom duration of 14 days or less; 38 acute COVID-19+ patients (76%) went on to require respiratory support. Although no microbiome features were found to be significantly different between COVID-19+ and COVID-19-patients, when we conducted random forest classification modeling (RFC) to predict the need of respiratory support for the COVID-19+ patients our analysis identified a subset of organisms and metabolic pathways whose relative abundance, when combined with clinical factors (such as age and Body Mass Index), was highly predictive of the need for respiratory support (F1 score 0.857). Microbiome Multivariable Association with Linear Models (MaAsLin2) analysis was then applied to the features identified as predicative of the need for respiratory support by the RFC. This analysis revealed reduced abundance of Prevotella salivae and metabolic pathways associated with lipopolysaccharide and mycolic acid biosynthesis to be the strongest predictors of patients requiring respiratory support. These findings suggest that composition of the oropharyngeal microbiome in COVID-19 may play a role in determining who will suffer from severe disease manifestations.

ImportanceThe microbial community that colonizes the upper airway, the oropharyngeal microbiome, has the potential to affect how patients respond to respiratory viruses such as SARS-CoV2, the causative agent of COVID-19. In this study, we investigated the oropharyngeal microbiome of COVID-19 patients using high throughput DNA sequencing performed on oral swabs. We combined patient characteristics available at intake such as medical comorbidities and age, with measured abundance of bacterial species and metabolic pathways and then trained a machine learning model to determine what features are predicative of patients needing respiratory support in the form of supplemental oxygen or mechanical ventilation. We found that decreased abundance of some bacterial species and increased abundance of pathways associated bacterial products biosynthesis was highly predictive of needing respiratory support. This suggests that the oropharyngeal microbiome affects disease course in COVID-19 and could be targeted for diagnostic purposes to determine who may need oxygen, or therapeutic purposes such as probiotics to prevent severe COVID-19 disease manifestations.


title: In vitro potency of combinatorial antifungal drugs towards Candida isolates from patients.

abstract: Candidiasis is a fungal infection (mycosis) caused by an opportunistic yeast with only 8-10 pathogenic species. In spite of the multiple classes of antifungal drugs available to combat these infections, the treatment is hampered by drug toxicity, tolerability, emergence of drug resistant isolates and many more. Combination therapy has been suggested as a possible approach to improve these treatment outcomes. This study is, therefore, aimed at the analysis of the sensitivity of Candida isolates obtained from patients towards different classes of drugs affecting multiple pathways in the pathogen life cycle. Four different individual drugs with different mechanisms of action and six different combinations of these drugs at three different proportions (1:1, 1:3, and 3:1) were used for the study. All the drug sensitivity assays were performed by the agar well diffusion method. The results were statistically analyzed using Prism software. Results have shown synergistic effects of drug combinations on the sensitivity of the isolates without much variation in the stoichiometric ratios, thereby providing an alternative to monotherapy to combat the emergence of drug resistant isolates and drying existing drug pipelines.


title: Medium-term impacts of the waves of the COVID-19 epidemic on treatments for non-COVID-19 patients in intensive care units: a retrospective cohort study in Japan

abstract:
BackgroundMaintaining critical care for non-Coronavirus-disease-2019 (non-COVID-19) patients is a key pillar of tackling the impact of the COVID-19 pandemic. This study aimed to reveal the medium-term impacts of the COVID-19 epidemic on case volumes and quality of intensive care for critically ill non-COVID-19 patients.

MethodsAdministrative data were used to investigate the trends in case volumes of admissions to intensive care units (ICUs) compared with the previous years. Standardized mortality ratios (SMRs) of non-COVID-19 ICU patients were calculated in each wave of the COVID-19 epidemic in Japan.

ResultsThe ratios of new ICU admissions of non-COVID-19 patients to those in the corresponding months before the epidemic: 21% in May 2020, 8% in August 2020, 9% in February 2021, and 14% in May 2021, approximately concurrent with the peaks in COVID-19 infections. The decrease was greatest for new ICU admissions of non-COVID patients receiving mechanical ventilation (MV) on the first day of ICU admission: 26%, 15%, 19%, and 19% in the first, second, third, and fourth waves, respectively. No statistically significant change in SMR was observed in any wave of the epidemic; SMRs were 0.990 (95% confidence interval (CI), 0.962-1.019), 0.979 (95% CI, 0.953-1.006), 0.996 (95% CI, 0.980-1.013), and 0.989 (95% CI, 0.964-1.014), in the first, second, third, and fourth waves of the epidemic, respectively.

ConclusionsCompared to the previous years, the number of non-COVID-19 ICU patients continuously decreased over the medium term during the COVID-19 epidemic. The decrease in case volumes was larger in non-COVID-19 ICU patients initially receiving MV than those undergoing other initial treatments. The standardized in-hospital mortality of non-COVID-19 ICU patients did not change in any waves of the epidemic.

EYWORDSIntensive care unit, COVID-19, mechanical ventilation, in-hospital mortality

category: intensive care and critical care medicine


title: Influence of landscape patterns on the exposure of LASV across diverse regions within the Republic of Guinea

abstract: Lassa fever virus (LASV) is the causative agent of Lassa fever, a disease endemic in West Africa. Exploring the relationships between environmental factors and LASV transmission across ecologically diverse regions can provide crucial information for the design of appropriate interventions and disease monitoring. We measured LASV-specific IgG seropositivity in 1286 sera collected in Coastal and Forested Guinea. Our results showed that exposure to LASV was heterogenous between the sites. The LASV IgG seropositivity was 11.9% (95% CI 9.7-14.5) in Coastal site, while it was 59.6% (95% CI 55.5-63.5) in Forested region. Interestingly, exposure was significantly associated with age, with seropositivity increasing with age in the Coastal site. Finally, we also found significant associations between exposure risk to LASV and landscape fragmentation in Coastal and Forested regions. This study may help to define the regions with an increased exposure risk to LASV where a close surveillance of LASV circulation is needed.


title: Hereditary haemochromatosis beyond liver cancer: increased risk of prostate cancer during an 11-year follow-up

abstract:
In European ancestry populations, the iron overload disorder Hereditary Haemochromatosis (HH) is predominantly caused by the HFE p.C282Y mutation. Male p.C282Y homozygotes have markedly increased hepatic malignancy risks but risks for other cancers in both male and female homozygotes are unclear. We studied data from 451,143 UK Biobank European ancestry community participants (aged 40-70 years; 54.3% female) followed for a mean 11.6 years via hospital admission and national cancer registry data. We estimated risks of incident bladder, blood (with sub-analyses of leukemia and lymphoma), bone, brain, breast, colorectal, kidney, lung, melanoma, oesophageal, ovarian, pancreatic, prostate and stomach cancers in the 2,890 p.C282Y homozygotes, compared to participants without HFE mutations. Male p.C282Y homozygotes (12.1% with baseline diagnosed HH) had increased risks of prostate cancer (6.8% versus 5.4% without mutations, hazard ratio HR=1.32, 95% CI=1.07-1.63, p=0.01,). In lifetable estimates from ages 40-75 years, 14.4% of male p.C282Y homozygotes are projected to develop prostate cancer (versus 10.7% without mutations, excess 3.8%, 95% CI = 1.3-6.8). There was no excess of studied cancers in female p.C282Y homozygotes, or in p.C282Y/p.H63D compound heterozygotes of either sex. In a large community sample of male p.C282Y homozygotes, there was a 32% increase in prostate cancer risk, in addition to the known increased liver cancer risk. Those reporting HFE genotype status or monitoring p.C282Y homozygous males may need to ensure clinical monitoring for both liver and prostate cancers.

Novelty and impact of the workMale HFE p.C282Y homozygotes, at risk of iron overload disorder hereditary haemochromatosis, have known increased liver cancer risks. We have shown, for the first time, that the male p.C282Y homozygotes also have a 32% increased risk of prostate cancer; with an excess proportion of 3.8% by age 75 compared to those without mutations. Those reporting HFE genotype status or monitoring p.C282Y homozygous males need to ensure vigilance for both excess liver and prostate cancers.


title: Safety and immunogenicity of heterologous boost immunization with an adenovirus type-5-vectored and protein-subunit-based COVID-19 vaccine (Convidecia/ZF2001): a randomized, observer-blinded, placebo-controlled trial

abstract:
BackgroundHeterologous boost vaccination has been proposed as an option to elicit stronger and broader, or longer-lasting immunity. We assessed the safety and immunogenicity of heterologous immunization with a recombinant adenovirus type-5-vectored COVID-19 vaccine (Convidecia) and a protein-subunit-based COVID-19 vaccine (ZF2001).

Methods and FindingsWe did a randomized, observer-blinded, placebo-controlled trial in healthy adults previously received one dose of Convidecia. Participants were randomly assigned (2:1) to receive either ZF2001 (vaccine group) or a trivalent inactivated influenza vaccine (TIV) (placebo group) at either 28-day or 56-day intervals. For both regimens, all participants received the 2nd injection with ZF2001 at 4 months after a dose of ZF2001 or TIV, with three-dose schedules of Convidecia/Convidecia/ZF2001 at day 0, day 28 and month 5 (referred to as CV/ZF/ZF (D0-D28-M5)) and CV/ZF/ZF (D0-D56-M6), and two-dose schedules of CV/ZF (D0-M5) and CV/ZF (D0-M6). The primary outcome was the geometric mean titer (GMT) of the neutralizing antibodies against live SARS-CoV-2 virus 14 days after each boost vaccination. The safety outcome was 7-day reactogenicity, measured as solicited local or systemic adverse reactions after each vaccination. Between April 7, 2021, and May 6, 2021, 120 participants were enrolled, among whom 60 were randomly assigned to receive ZF2001 (n=40) or TIV (n=20) at a 28-day interval, and 60 were randomly assigned to receive ZF2001 (n=40) or TIV (n=20) at a 56-day interval. 113 (94.2%) participants received the 2nd injection with ZF2001 4 months after a dose of ZF2001 or TIV.

A total of 26 participants (21.7%) reported solicited adverse events within 7 days post boost vaccinations, and all the reported adverse reactions were mild. Among participants receiving ZF001 as second dose, the GMTs of neutralizing antibodies increased to 58.4 IU/ml (42.8-79.8) in 0-28 regimen, and to 80.8 IU/ml (53.1-122.9) in 0-56 regimen at 14 days post first boost dose. The GMTs of neutralizing antibodies increased to 334.9 IU/ml (95% CI 230.4, 486.9) in C/Z/Z (D0-D28-M5) regimen, and 441.2 IU/ml (260.8, 746.4) in C/Z/Z (D0-D56-M6) regimen at 14 days after the third dose. Two-dose schedules of CV/ZF (D0-M5) and CV/ZF (D0-M6) induced comparable antibody level comparable with that elicited by three-dose schedules, with the GMTs of 282.9 IU/ml (142.5, 561.8) and 293.9 IU/ml (137.6, 627.9), respectively. Study limitations include the absence of vaccine effectiveness in real-world, and current lack of immune persistence data and the neutralizing antibodies to Omicron.

ConclusionsHeterologous boosting with ZF001 following primary vaccination of Convidecia is safe and more immunogenic than a single dose of Convidecia. These results support flexibility in cooperating viral vectored vaccines and recombinant protein vaccine.

Trial RegistrationClinicalTrial.gov NCT04833101


title: Association of Trends in Child Undernutrition and Implementation of the National Rural Health Mission in India: A Nationally Representative Serial Cross-Sectional Study on Data from 1992 - 2015

abstract:
BackgroundIndia launched the National Rural Health Mission (NRHM) in 2005 to strengthen its primary healthcare system in high-focus and northeast focus states. One of the NRHM objectives was to reduce child undernutrition in India.

Methods and FindingsWe used data from 1992, 1998, 2005, and 2015 National Family Health Surveys of India to evaluate trends in child undernutrition prevalence before and after NRHM and across different categories of focus states. Stunting, Wasting, and Comprehensive Index of Anthropometric Failure (CIAF) was assessed using WHO growth curves to assess chronic, acute, and overall undernutrition. The study included 187,452 children aged 3 years or under. Survey-weighted and confounder-adjusted average annualized reduction rates (AARR) and predicted probability ratios were used to assess trends and socioeconomic disparities for child undernutrition, respectively. Nationwide, the prevalence of all types of undernutrition decreased from 1992 to 2015. However, the trends varied before and after NRHM implementation and differentially by focus states. After NRHM, acute undernutrition declined more rapidly among high-focus states (AARR 1.0%) but increased in normal-focus states (AARR -1.9% per year; p<0.001). In contrast, the prevalence of chronic undernutrition declined more rapidly (AARR 1.6%) in the normal focus states in comparison to high-focus states (0.3%; p=0.01). Income and caste-based disparities in acute undernutrition decreased but did not disappear after the implementation of the NRHM. However, similar disparities in prevalence of chronic undernutrition appear to be exacerbated after the implementation of the NRHM. Major limitations of this study include the observational and cross-sectional design, which preclude our ability to draw causal inferences.

ConclusionOur results suggests that NRHM implementation might be associated with improvement in wasting (acute) rather than stunting (chronic) forms of undernutrition. Strategies to combat undernutrition equitably, especially in high-focus states are needed.

AUTHOR SUMMARYO_ST_ABSWhy was this study done?C_ST_ABSO_LIIndia has the largest number of undernourished children of any country worldwide
C_LIO_LIIndias government launched a public health program called National Rural Health Mission (NRHM) that had a focus on improving maternal and child health
C_LIO_LIImpact of the NRHM has been studied on infant mortality rate but nationwide estimates of association of NRHM with child undernutrition rates remains unelucidated
C_LI

What did the researchers do and find?O_LIWe carried out a cross-sectional study based on nationally representative serial data gathered through the National Family Health Surveys in 1992, 1998, 2005, and 2015 on a total 187,452 children, which represented national population of children aged 3 years and under residing in India in the respective survey years
C_LIO_LIThe study reports that the prevalence of undernutrition and trends in its changes before and after implementation of NRHM differed across different indicators of undernutrition.
C_LIO_LIThe prevalence of wasting (acute undernutrition) declined at a faster rate in the post-NRHM period among the states where NRHM was prioritized while the prevalence of acute undernutrition increased during the post-NRHM where NRHM was not implemented. Conversely, prevalence of stunting (chronic undernutrition) declined at a faster rate among the normal focus states in the post-NRHM period in comparison to high and northeast focus states.
C_LIO_LISocioeconomic disparities for chronic and overall undernutrition persisted or widened over time. We observed a decline in wealth, maternal-education, rural, and caste-based disparities for acute undernutrition after the implementation of the NRHM.
C_LI

What do these findings mean?O_LIPolicies enacted under the NRHM may be associated with a reduction in acute form of child undernutrition
C_LIO_LIPolicies enacted under the NRHM may be associated with modest reduction in wealth, education, or caste-based disparities for acute form of child undernutrition, however, the disparities for chronic undernutrition among children were not associated by the NRHM
C_LI

category: public and global health


title: An Immunobridging study to evaluate the neutralizing antibody titer in adults immunized with two doses of either ChAdOx1-nCov-19 (AstraZeneca) or MVC-COV1901.

abstract:
BackgroundRapid development and deployment of vaccine is crucial to control the continuously evolving COVID-19 pandemic. Placebo-controlled phase 3 efficacy trial is still standard for authorizing vaccines in majority of the world. However, due to lack of cases or participants in parts of the world, this has not always been feasible. An alternative to efficacy trial is immunobridging, in which the immune response or correlates of protection of a vaccine candidate is compared against an approved vaccine. Here we describe a case study where our candidate vaccine, MVC-COV1901, has been granted for emergency use authorization (EUA) locally based on the non-inferiority immunobridging process.

MethodsThe per protocol immunogenicity (PPI) subset from the MVC-COV1901 phase 2 trial was used for this study and consisted of 903 subjects who have received two doses of MVC-COV1901 as scheduled in the clinical trial. The comparator set of population consisted of 200 subjects of [≥] 20 years of age who were generally healthy and have received two doses of AstraZeneca ChAdOx nCOV-19 (AZD1222) recruited from Taoyuan General Hospital, Ministry of Health and Welfare.

ResultsMVC-COV1901 was shown to have a geometric mean titer (GMT) ratio lower bound 95% confidence interval (CI) of 3.4 against the comparator vaccine and a seroconversion rate of 95.5% at the 95% CI lower bound, which both exceeded the criteria set by the Taiwan regulatory authority for EUA approval. These results supported the EUA approval of MVC-COV1901 by the Taiwanese regulatory authority in July 2021. Following the consensus of the International Coalition of Medicines Regulatory Authorities (ICMRA), countries from the Access Consortium has recently adopted the use of immunobridging studies as acceptable for authorizing COVID-19 vaccines in lieu of efficacy data.

ConclusionThe data presented in the study showed that it is reasonably likely that the vaccine efficacy of MVC-COV1901 is similar or superior to that of AZ. Data could be used in support of further vaccine development and regulatory approval.


title: The Serological Sciences Network (SeroNet) for COVID-19: Depth and Breadth of Serology Assays and Plans for Assay Harmonization

abstract:
BackgroundIn October 2020, the National Cancer Institute (NCI) Serological Sciences Network (SeroNet) was established to study the immune response to COVID-19, and "to develop, validate, improve, and implement serological testing and associated technologies." SeroNet is comprised of 25 participating research institutions partnering with the Frederick National Laboratory for Cancer Research (FNLCR) and the SeroNet Coordinating Center. Since its inception, SeroNet has supported collaborative development and sharing of COVID-19 serological assay procedures and has set forth plans for assay harmonization.

MethodsTo facilitate collaboration and procedure sharing, a detailed survey was sent to collate comprehensive assay details and performance metrics on COVID-19 serological assays within SeroNet. In addition, FNLCR established a protocol to calibrate SeroNet serological assays to reference standards, such as the U.S. SARS-CoV-2 serology standard reference material and First WHO International Standard (IS) for anti-SARS-CoV-2 immunoglobulin (20/136), to facilitate harmonization of assay reporting units and cross-comparison of study data.

ResultsSeroNet institutions reported development of a total of 27 ELISA methods, 13 multiplex assays, 9 neutralization assays, and use of 12 different commercial serological methods. FNLCR developed a standardized protocol for SeroNet institutions to calibrate these diverse serological assays to reference standards.

ConclusionsSeroNet institutions have established a diverse array of COVID-19 serological assays to study the immune response to SARS-CoV-2 virus and vaccines. Calibration of SeroNet serological assays to harmonize results reporting will facilitate future pooled data analyses and study cross-comparisons.


title: Effect of booster vaccination against Delta and Omicron variants in Iceland

abstract: By the end of July 2021, the majority of the Icelandic population had received vaccination against COVID-19. In mid-July a wave of SARS-CoV-2 infections, dominated by the delta variant, spread through the population, followed by an omicron wave in December. A booster vaccination campaign was initiated to curb the spread of the virus. We estimated the risk of infection for different vaccine combinations using vaccination data from 276,028 persons and 963,557 qPCR tests for 277,687 persons. We measured anti-Spike-RBD antibody levels and ACE2-Spike binding inhibitory activity in 371 persons who received one of four recommended vaccination schedules with or without an mRNA vaccine booster. Overall, we found different antibody levels and inhibitory activity between recommended vaccination schedules, which was reflected in the observed risk of SARS-CoV-2 infections. We observed an increased protection following mRNA boosters, against both omicron and delta variant infections, although BNT162b2 boosters provided greater protection against omicron than mRNA-1273 boosters.


title: Vaccine hesitancy strongly correlates with COVID-19 deaths underreporting

abstract: Vaccine acceptance is a key factor in achieving high immunization coverage and reducing the death toll of COVID-19 pandemic. Analyzing data from Europe and Americas we demonstrated that vaccine hesitancy strongly correlates with underreporting of COVID-19 deaths and cases. This correlation cannot be explained by the differences in economic indexes: GDP and Gini coefficient (measure of income inequalities). There is no correlation of vaccination percentage and Gini coefficient and the correlation with GDP is decreasing in time. The most striking is the comparison of Eastern European and South American countries; the latter group of countries shows significantly higher vaccination percentage while having a lower or comparable GDP and higher Gini coefficient. The analysis suggests that timely and reliable information about the COVID-19 cases and the associated deaths plays a key role in achieving population-wide vaccine acceptance.


title: COVID-19 testing: disparity between national and institution-based case detection

abstract: Reports of COVID-19 prevalence through national statistics, community surveys and targeted testing at places of work or study have guided national and institutional responses to the pandemic. The University of Edinburgh established a mass testing programme, TestEd, for detection of COVID-19 in asymptomatic staff and students who are studying or working on campus. The study has tested more than 100,000 samples with more than 170 confirmed positive results. Since the introduction of a change in policy in England and the UK devolved nations in early January 2022, to limit eligibility for PCR testing in the community to those with symptoms, we have noticed a divergence between the reports in Scottish and UK-wide prevalence, and the magnitude and frequency of positive results in the University datasets. While the national UK-wide and Scottish case figures show declining or stable prevalence, University case reports have risen more than five-fold since early December 2021 and continue to rise. These observations could be important in the face of future variants of concern and emphasise the need for continued access to high sensitivity PCR testing and other forms of surveillance.


title: Relationships of Prescription Opioid Sales to Opiate Treatment Admissions and Overdose Deaths: A Reanalysis of Relationships -- United States 2010-2019

abstract:
BackgroundIn 2016, the United States Centers for Disease Control and Prevention (CDC) issued "CDC Guideline for Prescribing Opioids for Chronic Pain". The guideline used data from 1999 to 2010 that related Opioid Sales to Opiate Treatment Admissions (a measure of drug addiction rates) Opioid Deaths. The CDCs analysis indicated that opioid prescriptions are directly correlated1-8 with drug addiction and overdose mortality outcomes. As a result, prescription opioid sales have been curtailed, making it difficult for sufferers of severe chronic pain to access an effective treatment option. In this paper, the relationships between opioid sales, drug addiction, and opioid deaths are reexamined using data from 2010 to 2019.

MethodsLinear regression models were fit to each response separately. Opioid sales (measured as MME per capita) was the independent variable. Total overdose deaths (TOD), any opioid overdose deaths (AOD), prescription opioid overdose deaths (POD) and opiate treatment admissions (OTA) were the dependent, response variables. The models were assessed using three criteria: the statistical significance of the model (Overall P-Value), the quality of the fit (R2), and the sign of the slope coefficient.

ResultsThe analyses revealed that the direct correlations (significant, positive slopes) reported by the CDC based on data from 1999 to 2010 no longer exist based on data from 2010 to 2019. The relationships either have reversed (i.e., significant negative slopes) or are non-existent (no significant model).

ConclusionsThe basis for the CDC guideline no longer holds. The guideline should be updated or annulled based on the current relationships that have existed for a decade. This is especially relevant for people suffering from severe, chronic pain, whose access to prescription opioids has been severely curtailed under the current guideline and to ensure that government resources are directed to an effective approach to reducing overdose deaths.


title: Use of Convalescent Plasma Therapy with Best Available Treatment (BAT) among Hospitalized COVID-19 Patients: A Multi-Center Study

abstract:
The COVID-19 disease caused by SARS-CoV2 virus has gripped the whole world with overwhelming strain in our health system. Currently, there are no standard guidelines in its treatment but the possible benefits of convalescent plasma in limiting complications and severity of the COVID-19 disease have emerged.

OBJECTIVEThis study aims to determine the effectiveness and safety of using convalescent plasma in improving the clinical course of hospitalized patients diagnosed with COVID-19 disease admitted at University of Santo Tomas and Makati Medical Center.

METHODSThis study is a quasi-experimental (prospective analytical), and multi-center study involving 65 patients diagnosed with COVID-19 Disease who received convalescent plasma, with 65 patients who only received best available treatment serving as age-gender-matched control.

RESULTSMedian age of the population who received convalescent plasma was 60 years old, mostly male (68%), and manifested severe pneumonia (47%). There was noted statistically signifcant decrease between the pre-and post-treatment values of hemoglobin (p=0.04) and LDH (p=0.086). There was also statistically significant increase in platelet counts (p=0.01). WBC and PaO2 increased while ferritin and PFR decreased after convalescent plasma transfusion, however, these were not statistically significant. Length of stay and clinical outcome of those who received convalescent plasma were then compared to age-gender matched controls who only received best available treatment. There was noted statistically significant difference between length of stay (p=0.00) among those who received convalescent plasma as compared to those who did not. This was seen across severe and critically ill COVID-19 patients. There was also more mortality seen in the best available treatment alone group, but this was non-significant.

CONCLUSIONSConvalescent plasma use showed no significant impact in the recovery rate and outcome of patients who received it as compared to those who did not, however, its use was proven to be safe among all patients regardless of the level of severity and clinical profile.

category: hematology


title: Placental telomere length shortening is not associated with preeclampsia but the gestational age

abstract:
STRUCTURED ABSTRACTO_ST_ABSBackgroundC_ST_ABSPreeclampsia is a severe pregnancy complication that affects about 2-8% of pregnant women globally and is one of the leading causes of maternal and fetal mortality and morbidity. Telomere length change has been associated with aging, environmental stress, and various diseases. Studying the telomere length change in preeclampsia complicated placentas may shed light on the pathophysiology of preeclampsia.

ObjectivesIn this study, we aimed to explore if associations exist between placental telomere length and preeclampsia, gestational age, and other demographic, clinical and physiological factors related to pregnancy.

Study DesignWe collected placentas samples from 120 severe preeclamptic deliveries and 129 healthy full-term deliveries in Hawaii between year 2006 and 2013 and measured the average absolute placental telomeres with quantitative polymerase chain reaction (qPCR). We retrieved their pre-recorded demographic, clinical and physiological data and conducted multiple linear regressions to associate placental telomeres with preeclampsia and other variables.

ResultsPlacental telomere length of severe preeclampsia cases showed no significant difference (P=0.20) from healthy controls after controlling for gestational age difference. Instead, we identified that placental telomere length consistently decreases as gestation progresses (P=6.10e-05). Male babies have shorter placental telomere than female babies in the early trimester (p = 0.024), but the placentas of male babies have a reduced rate of telomere shortening along pregnancies, compared to those of female babies (p = 0.029). Latino mothers show longer placenta telomeres than other ethnicities (P=0.012), whereas mothers of blood type O have shorter placenta telomeres than those of other blood types (P=0.039).

ConclusionsUsing the largest multiethnic cohort to date, we showed the lack of association between preeclampsia and placental telomere length. Rather, gestational age is the most dominant variable associated with placental telomere shortening.

CondensationPlacental telomere length shows no significant association with preeclampsia but significantly shortens with the progressing gestational age at different rates for male and female babies.

AJOG At A GlanceA. Why was this study conducted?O_LIUnderstanding the TL change in healthy and preeclampsia complicated placenta may help us better understand the physio-pathological impact of preeclampsia.
C_LI

B. What are the key findings?O_LIWe found no significant association between severe preeclampsia and placental TL in the largest multi-ethnic cohort to date.
C_LIO_LIPlacental TL shortens consistently largely due to gestational age increase.
C_LIO_LIPlacentas of male babies have shorter TLs at the early third trimester but slower TL shortening compared to those of female babies.
C_LIO_LILatino mothers have longer placental TL compared to non-Latino mothers.
C_LIO_LIMothers of blood type O have shorter placenta TL than others.
C_LI

C. What does this study add to what is already known?O_LIWe showed that placental telomere length shortening is not associated with preeclampsia but the gestational age in a large multi-ethnical cohort.
C_LI

category: obstetrics and gynecology


title: Investigating a possible causal relationship between maternal serum urate concentrations and offspring birthweight: A Mendelian randomization study

abstract:
BackgroundHigher urate levels associate with higher systolic blood pressure (SBP) in adults, and in pregnancy, with lower offspring birthweight. Mendelian randomization (MR) analyses suggest a causal effect of higher urate on higher SBP and of higher maternal SBP on lower offspring birthweight. If urate causally reduces birthweight, it might confound the effect of SBP on birth weight. We therefore tested for a causal effect of maternal urate on offspring birthweight.

MethodsWe tested the association between maternal urate levels and offspring birthweight using multivariable linear regression in UK Biobank (UKB; n=133,187) and Exeter Family Study of Childhood Health (EFSOCH; n=872). We conducted two-sample MR to test for a causal effect of maternal urate (114 single nucleotide polymorphisms [SNPs]; n=288,649 European-ancestry) on offspring birthweight (n=406,063 European-ancestry; maternal SNP effect estimates adjusted for fetal effects). Using one-sample MR (n=199,768 UKB women), we also tested for a causal relationship between urate and SBP.

ResultsHigher maternal urate was associated with lower offspring birthweight in UKB (28g lower birthweight per 1-SD higher urate [95% CI: -31, -25]; P=1.8x10-75), with a similar effect estimate in EFSOCH (22g [95%CI: -50, 6]; P=0.13). The MR causal effect estimate was directionally consistent, but smaller (-11g [95% CI: -25, 3]; PIVW=0.13). In women, higher urate was causally associated with higher SBP (1.7 mmHg higher SBP per 1-SD higher urate [95% CI: 1.4, 2.1]; P=7.8x10-22) consistent with that previously published in women and men.

ConclusionsThe marked attenuation of the MR result of maternal urate on offspring birthweight, compared to the multivariable regression result suggests previous observational associations may be confounded. The 95% CIs of the MR result included the null but suggest a possible weak effect on birthweight. Maternal urate levels are unlikely to be an important contributor to offspring birthweight.

Key MessagesO_LIPrevious research suggests higher maternal serum urate in pregnancy is associated with lower offspring birthweight, and Mendelian randomization studies suggest a causal relationship between urate and systolic blood pressure (SBP), and SBP and birthweight; a causal effect of urate on birthweight has not yet been estimated, and thus it is also unknown whether it confounds maternal SBP-birthweight effects.
C_LIO_LIThe causal effect estimate of urate on offspring birthweight was directionally consistent, but weaker than, observational estimates; the estimate had 95% confidence intervals which included the null.
C_LIO_LIThis study confirmed a causal association between serum urate and higher SBP in women consistent with that published from a sample of both women and men.
C_LIO_LIMaternal urate is unlikely to be a major determinant of birthweight or an important confounder of the causal relationship between SBP and lower birthweight.
C_LI


title: Whole exome sequencing in multi-incident families identifies novel candidate genes for multiple sclerosis

abstract: Multiple sclerosis (MS) is a degenerative disease of the central nervous system in which auto-immunity-induced demyelination occurs. MS is thought to be caused by a complex interplay of environmental and genetic risk factors. While most genetic studies have focused on identifying common genetic variants for MS through genome-wide association studies, the objective of the present study was to identify rare genetic variants contributing to MS susceptibility. We used whole exome sequencing (WES) followed by co-segregation analyses in nine multi-incident families with 2 to 4 affected individuals. WES was performed in 31 family members with and without MS. After applying a suite of selection criteria, co-segregation analyses for a number of rare variants selected from the WES results were performed, adding 24 family members. This approach resulted in 12 exonic rare variants that showed acceptable co-segregation with MS within the nine families, implicating the genes MBP, PLK1, MECP2, MTMR7, TOX3, CPT1A, SORCS1, TRIM66, ITPR3, TTC28, CACNA1F, and PRAM1. Of these, three genes (MBP, MECP2, and CPT1A) have been previously reported as carrying MS-related rare variants. Six additional genes (MTMR7, TOX3, SORCS1, ITPR3, TTC28, and PRAM1) have also been implicated in MS through common genetic variants. The proteins encoded by all twelve genes containing rare variants interact in a molecular framework that points to biological processes involved in (de-/re-)myelination and auto-immunity. Our approach provides clues to possible molecular mechanisms underlying MS that should be further studied in cellular and/or animal models.


title: Transcriptional patterns of coexpression across autism risk genes converge on established and novel signatures of neurodevelopment

abstract: Autism spectrum disorder (ASD) is a highly heritable neurodevelopmental disorder characterized by deficits in social interactions and communication. Protein function altering variants in many genes have been shown to contribute to ASD risk; however, understanding the biological convergence across so many genes has been difficult. Here, we demonstrate that coexpression patterns from human post-mortem brain samples (N=993) are significantly correlated with the transcriptional consequences of CRISPR perturbations (gene editing, interference and activation) of 15 neurodevelopmental genes in neuronal cell models. We find that across 70 ASD risk genes, there is significant tissue-specific transcriptional convergence that implicates synaptic pathways. We further show that the degree of convergence is significantly correlated with the level of association to ASD from sequencing studies (rho = -0.14, P = 4.75x10-63) as well as differential expression from transcription studies in post-mortem ASD brains (rho = -0.22, P = 3.62x10-41). After removing genes with minimal evidence of association with ASD, the remaining positively convergent genes are intolerant to mutation, have shorter coding lengths and are enriched for genes with suggestive evidence of contribution to ASD. These results indicate that leveraging convergent coexpression can identify novel ASD risk genes that are more likely to be underpowered and therefore missed by current large-scale sequencing studies. This work ultimately provides a simple approach to functionally proxy CRISPR perturbation, demonstrates significant context-specific transcriptional convergence among known ASD risk genes, and proposes several novel ASD risk gene candidates.


title: Performance Drift in a Clinical Prognostic Algorithm during the SARS-CoV-2 Pandemic

abstract:
Research ObjectiveHealth systems use clinical predictive algorithms to allocate resources to high-risk patients. Such algorithms are trained using historical data and are later implemented in clinical settings. During this implementation period, predictive algorithms are prone to performance changes ("drift") due to exogenous shocks in utilization or shifts in patient characteristics. Our objective was to examine the impact of sudden utilization shifts during the SARS-CoV-2 pandemic on the performance of an electronic health record (EHR)-based prognostic algorithm.

Study DesignWe studied changes in the performance of Conversation Connect, a validated machine learning algorithm that predicts 180-day mortality among outpatients with cancer receiving care at medical oncology practices within a large academic cancer center. Conversation Connect generates mortality risk predictions before each encounter using data from 159 EHR variables collected in the six months before the encounter. Since January 2019, Conversation Connect has been used as part of a behavioral intervention to prompt clinicians to consider early advance care planning conversations among patients with [≥]10% mortality risk. First, we descriptively compared encounter-level characteristics in the following periods: January 2019-February 2020 ("pre-pandemic"), March-May 2020 ("early-pandemic"), and June-December 2020 ("later-pandemic"). Second, we quantified changes in high-risk patient encounters using interrupted time series analyses that controlled for pre-pandemic trends and demographic, clinical, and practice covariates. Our primary metric of performance drift was false negative rate (FNR). Third, we assessed contributors to performance drift by comparing distributions of key EHR inputs across periods and predicting later pandemic utilization using pre-pandemic inputs.

Population Studied237,336 in-person and telemedicine medical oncology encounters.

Principal FindingsAge, race, average patient encounters per month, insurance type, comorbidity counts, laboratory values, and overall mortality were similar among encounters in the pre-, early-, and later-pandemic periods. Relative to the pre-pandemic period, the later-pandemic period was characterized by a 6.5-percentage-point decrease (28.2% vs. 34.7%) in high-risk encounters (p<0.001). FNR increased from 41.0% (95% CI 38.0-44.1%) in the pre-pandemic period to 57.5% (95% CI 51.9-63.0%) in the later pandemic period. Compared to the pre-pandemic period, the early and later pandemic periods had higher proportions of telemedicine encounters (0.01% pre-pandemic vs. 20.0% early-pandemic vs. 26.4% later-pandemic) and encounters with no preceding laboratory draws (17.7% pre-pandemic vs. 19.8% early-pandemic vs. 24.1% later-pandemic). In the later pandemic period, observed laboratory utilization was lower than predicted (76.0% vs 81.2%, p<0.001). In the later-pandemic period, mean 180-day mortality risk scores were lower for telemedicine encounters vs. in-person encounters (10.3% vs 11.2%, p<0.001) and encounters with no vs. any preceding laboratory draws (1.5% vs. 14.0%, p<0.001).

ConclusionsDuring the SARS-CoV-2 pandemic period, the performance of a machine learning prognostic algorithm used to prompt advance care planning declined substantially. Increases in telemedicine and declines in laboratory utilization contributed to lower performance.

Implications for Policy or PracticeThis is the first study to show algorithm performance drift due to SARS-CoV-2 pandemic-related shifts in telemedicine and laboratory utilization. These mechanisms of performance drift could apply to other EHR clinical predictive algorithms. Pandemic-related decreases in care utilization may negatively impact the performance of clinical predictive algorithms and warrant assessment and possible retraining of such algorithms.

category: health systems and quality improvement


title: Traditional treatment of HIV and the role of family members as barriers to access to HIV care service or antiretroviral therapy among people living with HIV

abstract: Access to HIV care service or antiretroviral therapy (ART) is essential for the improvement of health outcomes of people living with HIV (PLHIV) and in reducing HIV transmission and HIV-related deaths. As a part of a qualitative study in Belu, this paper describes the use of traditional treatment and the role of families in determining traditional treatment for their HIV-positive family member as barriers to access to HIV care service or ART among PLHIV. One-on-one in-depth interviews were employed to collect data from 46 PLHIV (26 women and 20 men) and 10 healthcare professionals recruited using the snowball sampling technique. Data analysis was performed using NVivo 12 software and guided by a qualitative data analysis framework. The findings showed that the use of traditional treatment, a well-known cultural practice in Belu, was a barrier to access to HIV care service or ART among PLHIV. The role of family in determining traditional treatment for HIV, supported by the lack of knowledge of ART, effectiveness of traditional medicines in treating other health issues, and social influence of families, neighbours and friends, were also significant barriers to PLHIVs access to HIV care service or ART. The findings indicate the need for dissemination of HIV care-related information for PLHIV, family and community members to increase their knowledge on the service, ART and its function, and to support and improve access to ART by PLHIV.

category: hiv aids


title: Impact of diabetes mellitus on the stabilization and osseointegration of dental implants: a systematic review

abstract:
IntroductionDiabetes mellitus is a chronic metabolic disorder leading to hyperglycemia, which causes various complications due to vasculopathy. Adequate dental rehabilitation including dental implants plays a key role in promoting the eating habits of diabetics and better metabolic control.

AimWe performed a systematic literature review to investigate the effect of diabetes mellitus on the stabilization and osseointegration of dental implants.

MethodsWe searched PubMed and Scopus until October 2021. We used the following inclusion criteria: (i) study population included diabetics type I or II, (ii) outcomes were the dental implant failure or resonance frequency analysis, (iii) studies that investigate the effect of diabetes mellitus on the stabilization and osseointegration of dental implants, (iv) studies that were published in English, (v) studies that were published in journals with peer review system, (vi) studies including humans and not animals, (vii) studies that compared diabetics with non-diabetics, and (ix) quantitative studies.

ResultsTwenty-nine studies met the inclusion criteria. Regarding implant failure, four studies found statistically significant more frequent implant failure in diabetics, while five studies found that implant failure was more frequent in diabetics but was not statistically significant. In contrast, ten studies found that implant failure was more frequent in non-diabetics but was not statistically significant. In addition, seven studies found that all diabetics and non-diabetics retained their implant during the study. In six studies that performed the resonance frequency analysis, no statistically significant difference was found between diabetics and non-diabetics. In three studies, the mean value of the implant stability quotient increased statistically significant in non-diabetics, while in three studies the mean value of the implant stability quotient increased statistically significant in diabetics.

ConclusionsThe results of this review suggest that implant failure is not higher for diabetics than for non-diabetics. Diabetics seem to be able to achieve a rate of dental implants survival like that of non-diabetics. With regards to the resonance frequency analysis, no difference is found between diabetics and non-diabetics.

category: dentistry and oral medicine