title: Comparative evaluation of oral lesions: Tale - the Covid 19 Tells

abstract:
Introduction & ObjectivesThe COVID-19 pandemic has been raging across the globe since early January 2020. India has reported over 27 million cases and more than 3, 00,000 deaths. This study was planned to analyze the differences in demographic, clinical features and oral manifestations of COVID 19 patients hospitalized during COVID-19 pandemic.

MethodsThis observational pilot study had total 36 participants, 12 each of mild, moderate and severe RT-PCR positive COVID cases hospitalized during COVID 19 pandemic. All demographic, clinical features, treatment details and oral manifestations were noted from first day of admission to hospital till treatment completion with follow up of minimum 7 days.

ResultsMean age of the patients was 39.44 {+/-}9.13 years with M: F ratio of 5:4. Most common clinical presentation was fever, shortness of breath and treatment involved was symptomatic with supplemental oxygen & mechanical ventilation. Most common oral site involved was tongue & oral lesions observed were herpes labialis, mucositis, burning sensation, dryness of oral cavity, angular chelitis, aphthous ulcers, geographic tongue, fissuring of tongue, candidiasis, coated tongue, sublingual varicosity, & scalloped tongue.

Interpretation and ConclusionAll demographic, clinical and oral manifestations were significantly different in mild, moderate and severe cases of covid hospitalized patients. Though clinical symptoms were improved, oral lesions were worsened. Oral Lesions seen in covid patients were associated with multiple drug therapy for illness along with poor oral hygiene, but further etiology for lesions needs to be evaluated. Sublingual varicosity was observed in our hospitalised covid patients, but large sample observation is required for confirmation of findings and may be an early oral feature for covid detection. Prevention is always better than cure, so all patients positive for Covid should have a full mouth examination. Oral health should be priority during overall management of COVID patients and dentists should be a part of Covid management team.

category: dentistry and oral medicine


title: Associations between prenatal exposure to maternal diabetes and child adiposity markers: mediating effects of brain structure

abstract:
ImportanceChildren prenatally exposed to maternal diabetes have a higher risk of developing obesity and metabolic disorders. Alterations in the brain development is hypothesized as a potential mechanism underlying this relationship but has not been fully tested in humans.

ObjectivesTo examine the mediating role of child brain structure in the relationships between prenatal exposure to maternal diabetes and child adiposity.

Design, setting and participantsThis was a cross-sectional study of children (ages 9-to-10-years-old) from the baseline assessment of the Adolescent Brain and Cognitive Development (ABCD) Study(R) (N=11,875).

ExposuresPrenatal exposure to maternal diabetes was determined via self-reported questionnaire.

Main outcomes and measuresChild adiposity markers included age- and sex-specific body mass index (BMI z-scores), waist circumference, and waist-to-height ratio (WHtR). T1-weighted magnetic resonance imaging (MRI) was used to assess brain structure. Linear mixed effects models examined associations of prenatal exposure to maternal diabetes with child adiposity markers and brain structure controlling for sociodemographic covariates. Mediation models were performed to investigate the mediating role of brain structure on the association between maternal diabetes exposure and child adiposity markers.

ResultsThe sample consisted of 8,521 children (agem: 9.92{+/-}0.63 years; sex: 51.4% males; 7% exposed to maternal diabetes). Children prenatally exposed vs. unexposed to maternal diabetes had greater BMI z-scores ({beta} (95% CI) = 0.175 (0.093, 0.256; FDR corrected P<0.001), waist circumference ({beta} (95% CI) = 0.201 (0.121, 0.281); FDR corrected P<0.001), WHtR ({beta} (95% CI) = 0.199 (0.119, 0.280); FDR corrected P<0.001). Prenatal exposure to maternal diabetes was associated with reduction in global ({beta} (95% CI) = -0.096 (-0.168, - 0.025); FDR corrected P=0.043) and regional cortical gray matter volume primarily in the frontal, temporal, and occipital areas. Whole-brain cortical gray matter volume partially mediated the association between prenatal exposure to maternal diabetes and WHtR (indirect path {beta} (95% CI) = 0.0027 (0.0002, 0.0067), P=0.034).

Conclusion and relevanceCortical gray matter volume partially mediated the link between prenatal exposure to maternal diabetes and WHtR. These results demonstrate a potential neurobiological mechanism by which prenatal exposure to maternal diabetes may be associated with increased risk for obesity and metabolic disorders in children.

Key Points

QuestionHow does prenatal exposure to maternal diabetes relate to brain structure, and does this relationship predict child adiposity markers.

FindingsCortical gray matter volume was reduced in children prenatally exposed to maternal diabetes; and it partially mediated the link between prenatal exposure to maternal diabetes and waist-to-height ratio in children.

MeaningThe association between prenatal exposure to maternal diabetes and increased risk for obesity and metabolic disorders in children may be driven in part by aberrant brain structure development.

category: endocrinology


title: Use of machine learning for comparing disease risk scores and propensity scores under complex confounding and large sample size scenarios: a simulation study

abstract:
BackgroundThe surge of treatments for COVID-19 in the ongoing pandemic presents an exemplar scenario with low prevalence of a given treatment and high outcome risk. Motivated by that, we conducted a simulation study for treatment effect estimation in such scenarios. We compared the performance of two methods for addressing confounding during the process of estimating treatment effects, namely disease risk scores (DRS) and propensity scores (PS) using different machine learning algorithms.

MethodsMonte Carlo simulated data with 25 different scenarios of treatment prevalence, outcome risk, data complexity, and sample size were created. PS and DRS matching with 1: 1 ratio were applied with logistic regression with least absolute shrinkage and selection operator (LASSO) regularization, multilayer perceptron (MLP), and eXtreme Gradient Boosting (XgBoost). Estimation performance was evaluated using relative bias and corresponding confidence intervals.

ResultsBias in treatment effect estimation increased with decreasing treatment prevalence regardless of matching method. DRS resulted in lower bias compared to PS when treatment prevalence was less than 10%, under strong confounding and nonlinear nonadditive data setting. However, DRS did not outperform PS under linear data setting and small sample size, even when the treatment prevalence was less than 10%. PS had a comparable or lower bias to DRS when treatment prevalence was common or high (10% - 50%). All three machine learning methods had similar performance, with LASSO and XgBoost yielding the lowest bias in some scenarios. Decreasing sample size or adding nonlinearity and non-additivity in data improved the performance of both PS and DRS.

ConclusionsUnder strong confounding with large sample size DRS reduced bias compared to PS in scenarios with low treatment prevalence (less than 10%), whilst PS was preferable for the study of treatments with prevalence greater than 10%, regardless of the outcome prevalence.

Key MessagesO_LIWhen handling nonlinear nonadditive data with strong confounding, DRS estimated by machine learning methods outperforms PS in scenarios with low treatment prevalence (less than 10%).
C_LIO_LIHowever, if having linear data and small sample size data with strong confounding, we did not observe DRS outperformed PS even when treatment prevalence was less than 10%.
C_LIO_LIOur results suggested that using PS performed better compared to DRS in tackling strong confounding problems with treatment prevalence greater than 10%.
C_LIO_LISmall sample size increased bias for both DRS and PS methods, and it affected DRS more than PS.
C_LI

category: epidemiology


title: Serious hospital events following symptomatic infection with Sars-CoV-2 Omicron and Delta variants: an exposed-unexposed cohort study in December 2021 from the COVID-19 surveillance databases in France

abstract:
BackgroundA rapid increase in incidence of the SARS-CoV-2 Omicron variant occurred in France in December 2021, while the Delta variant was prevailing since July 2021. We aimed to determine whether the risk of a severe hospital event following symptomatic SARS-CoV-2 infection differs for Omicron versus Delta.

MethodsWe conducted a retrospective cohort study to compare severe hospital events (admission to intensive care unit or death) between Omicron and Delta symptomatic cases matched according to week of virological diagnosis and age. The analysis was adjusted for age, sex, vaccination status, presence of comorbidities and region of residence, using Cox proportional hazards model.

FindingsBetween 06/12/2021-28/01/2022, 184 364 cases were included, of which 931 had a severe hospital event (822 Delta, 109 Omicron). The risk of severe event was lower among Omicron versus Delta cases; the difference in severity between the two variants decreased with age (aHR=0{middle dot}11 95%CI: 0{middle dot}07-0{middle dot}17 among 40-64 years, aHR=0{middle dot}51 95%CI: 0{middle dot}26-1{middle dot}01 among 80+ years). The risk of severe event increased with the presence of comorbidities (for very-high-risk comorbidity, aHR=4{middle dot}18 95%CI: 2{middle dot}88-6{middle dot}06 among 40-64 years) and in males (aHR=2{middle dot}29 95%CI: 1{middle dot}83-2{middle dot}86 among 40-64 years) and was higher in unvaccinated compared to primo-vaccinated (aHR=6{middle dot}90 95%CI: 5{middle dot}26-9{middle dot}05 among 40-64 years). A booster dose reduced the risk of severe hospital event in 80+ years infected with Omicron (aHR=0{middle dot}27; 95%CI: 0{middle dot}11-0{middle dot}65).

InterpretationThis study confirms the lower severity of Omicron compared to Delta. However, the difference in disease severity is less marked in the elderly.


title: Severe hospital events following symptomatic infection with Sars-CoV-2 Omicron and Delta variants in France, December 2021 - January 2022: a retrospective, population-based, matched cohort study


title: Pediatric Croup during the COVID-19 Omicron Variant Surge

abstract: Croup is a common upper respiratory disease usually associated with parainfluenza virus, resulting in stridor, hoarse voice, barky cough, and variable respiratory distress. Here we examine the data at our center confirming a sharp increase in cases of croup associated with the Omicron variant. Data was retrospectively extracted from patient charts among those seen in the Emergency Department at Seattle Childrens Hospital. Inclusion criteria were patients who were assigned a diagnosis containing "croup" during either 5/30/2021-11/30/2021, a time period correlating with predominance of the COVID-19 Delta variant (B.1.617.2), or the initial phase of the Omicron variant surge (12/1/2021-1/15/2022). Contemporaneous publicly available local data on the proportion of SARS-CoV-2 samples in surrounding King County, Washington, with spike gene target failure on TaqPath PCR assays was used as a proxy for the proportion of infections caused by the Omicron variant. A total of 401 patients were diagnosed with croup during the Delta surge and 107 patients were diagnosed with croup during the Omicron surge. Patients who presented during the Omicron surge were more likely to test positive for COVID-19 (48.2% vs 2.8%, p < 0.0001). Children with a clinical diagnosis of croup during the Omicron surge were more likely to be prescribed racemic epinephrine as part of their care (21.5% vs 13.0%, p = 0.032). There were no differences in presenting age, rate of admission, rate of return to the ED within 72 hours, or admission among those who returned within 72 hours. During the Omicron surge, the incidence of croup nearly doubled compared to the rate in prior months, while at the same time the number of cases of parainfluenza virus identified decreased. Consistent with prior case reports, we have identified a sharp rise in cases of croup seen in our pediatric ED in parallel with the replacement of the SARS-CoV-2 Delta variant by Omicron as the dominant variant in our community.

category: pediatrics


title: Croup during the COVID-19 Omicron Variant Surge


title: Development of machine learning models for the prediction of complications after colonic, colorectal and small intestine anastomosis in psychiatric and non-psychiatric patient collectives (P-Study)

abstract:
Psychiatric and psychosomatic diseases are an increasingly cumbersome burden for the medical system. Indeed, hospital costs associated with mental health conditions have been constantly on the rise in recent years. Moreover, psychiatric conditions are likely to have a negative effect on the treatment of other medical conditions and surgical outcomes, in addition to their direct effects on the overall quality of life. Our study aims to investigate the impact of preoperative Risk factor, psychiatric and psychosomatic diseases on the outcomes of colorectal surgery and length of hospital stay via predictive modeling techniques.

MethodPatient data will be collected from several participating national and international surgical centers The machine learning models will be calculated and coded, but also published according to the TRIPOD guidelines (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis).

ResultIt is conceivable to arrive at generalizable models predicting the abovementioned endpoints through large amounts of data from several centers. The models will be subsequently deployed as a free-to-use web-based prediction tool using the Shiny environment [47]. The cost for the hosting server and digital infrastructure will be covered by Dr. Anas Taha. The sponsor will store the data for ten years.

category: surgery


title: Development of machine learning models for the prediction of complications after colonic, colorectal and small intestine anastomosis in psychiatric and non-psychiatric patient collectives (PSTUDY)


title: Development of machine learning models for the prediction of complications after colorectal and small intestine surgery in psychiatric and non-psychiatric patient collectives (P-Study)


title: Vital signs as a source of racial bias

abstract:
AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSracial bias has been shown to be present in clinical data, affecting patients unfairly based on their race, ethnicity and socio-economic status. This problem has the potential to be significantly exacerbated in the light of Artificial Intelligence-aided clinical decision making. We sought to investigate whether bias can be introduced from sources that are considered neutral with respect to ethnicity and race and consequently routinely used in modelling, specifically vital signs.

Methodsto perform our analysis, we extracted vital signs from 49,610 admissions from a cohort of adult patients during the first 24 hours after the admission to the Intensive Care Units (ICU), derived from multi-centre eICU-CRD database and single-centre MIMIC-III database, spanning over 208 hospitals and 335 ICUs. Using heart rate, SaO2, respiratory rate, systolic, diastolic, and mean blood pressure, we develop machine learning models based on Logistic Regression and eXtreme Gradient Boosting and investigate their performance in predicting patients self-reported race. To balance the dataset between the three ethno-races considered in our study, we use a matching cohort based on age, gender, and admission diagnosis.

Findingsstandard machine learning models, derived solely on six vital signs can be used to predict patients self-reported race with AUC of 75%. Our findings hold under diverse patient populations, derived from multiple hospitals and intensive care units. We also show that oxygen saturation is a highly predictive variable, even when measured through methods other than pulse oximetry, namely arterial blood gas analysis, suggesting that addressing bias in routinely collected clinical variables will be challenging.

Interpretationour finding that machine learning models can predict self-reported race using solely vital signs creates a significant risk in clinical decision making, further exacerbating racial inequalities, with highly challenging mitigation measures.

FundingThe funders had no role in the design of this study.

category: medical ethics


title: Machine learning-based prediction of cognitive outcomes in de novo Parkinson's disease

abstract: Cognitive impairment is a debilitating symptom in Parkinsons disease (PD). We aimed to establish an accurate multivariate machine learning (ML) model to predict cognitive outcome in newly diagnosed PD cases from the Parkinsons Progression Markers Initiative (PPMI). Annual cognitive assessments over an eight-year time span were used to define two cognitive outcomes of i) cognitive impairment, and ii) dementia conversion. Selected baseline variables were organized into three subsets of clinical, biofluid and genetic/epigenetic measures and tested using four different ML algorithms. Irrespective of the ML algorithm used, the models consisting of the clinical variables performed best and showed better prediction of cognitive impairment outcome over dementia conversion. We observed a marginal improvement in the prediction performance when clinical, biofluid, and epigenetic/genetic variables were all included in one model. Several cerebrospinal fluid measures and an epigenetic marker showed high predictive weighting in multiple models when included alongside clinical variables.

category: neurology


title: Choice of Intraoperative Ultrasound adjuncts for Brain Tumor Surgery

abstract:
BackgroundGliomas are among the most typical brain tumors tackled by neurosurgeons. During navigation for surgery of glioma brain tumors, preoperatively acquired static images may not be accurate due to shifts. Surgeons use intraoperative imaging technologies (2-Dimensional and navigated 3 Dimensional ultrasound) to assess and guide resections. This paper aims to precisely capture the importance of preoperative parameters to decide which type of ultrasound to be used for a particular surgery.

MethodsThis paper proposes two bagging algorithms considering base classifier logistic regression and random forest. These algorithms are trained on different subsets of the original data set. The goodness of fit of Logistic regression-based bagging algorithms is established using hypothesis testing. Furthermore, the performance measures for random-forest-based bagging algorithms used are AUC under ROC and AUC under the precision-recall curve. We also present a composite model without compromising the explainability of the models.

ResultsThese models were trained on the data of 350 patients who have undergone brain surgery from 2015 to 2020. The hypothesis test shows that a single parameter is sufficient instead of all three dimensions related to the tumor (p < 0.05). We observed that the choice of intraoperative ultrasound depends on the surgeon making a choice, and years of experience of the surgeon could be a surrogate for this dependence.

ConclusionThis study suggests that neurosurgeons may not need to focus on a large set of preoperative parameters in order to decide on ultrasound. Moreover, it personalizes the use of a particular ultrasound option in surgery. This approach could potentially lead to better resource management and help healthcare institutions improve their decisions to make the surgery more effective.

category: health informatics


title: COMPARATIVE PERFORMANCE OF TWO AUTOMATED MACHINE LEARNING PLATFORMS FOR COVID-19 DETECTION BY MALDI-TOF-MS

abstract: The 2019 novel coronavirus infectious disease (COVID-19) pandemic has resulted in an unsustainable need for diagnostic tests. Currently, molecular tests are the accepted standard for the detection of SARS-CoV-2. Mass spectrometry (MS) enhanced by machine learning (ML) has recently been postulated to serve as a rapid, high-throughput, and low-cost alternative to molecular methods. Automated ML is a novel approach that could move mass spectrometry techniques beyond the confines of traditional laboratory settings. However, it remains unknown how different automated ML platforms perform for COVID-19 MS analysis. To this end, the goal of our study is to compare algorithms produced by two commercial automated ML platforms (Platforms A and B). Our study consisted of MS data derived from 361 subjects with molecular confirmation of COVID-19 status including SARS-CoV-2 variants. The top optimized ML model with respect to positive percent agreement (PPA) within Platforms A and B exhibited an accuracy of 94.9%, PPA of 100%, negative percent agreement (NPA) of 93%, and an accuracy of 91.8%, PPA of 100%, and NPA of 89%, respectively. These results illustrate the MS methods robustness against SARS-CoV-2 variants and highlight similarities and differences in automated ML platforms in producing optimal predictive algorithms for a given dataset.

category: infectious diseases


title: Express yourself: Quantitative real-time PCR assays for rapid chromosomal antimicrobial resistance detection in Pseudomonas aeruginosa

abstract: The rise of antimicrobial-resistant (AMR) bacteria is a global health emergency. One critical facet in tackling this epidemic is more rapid AMR diagnosis in serious multi-drug resistant pathogens like Pseudomonas aeruginosa. Here, we designed and then validated two multiplex quantitative real-time PCR (qPCR) assays to simultaneously detect differential expression of the resistance-nodulation-division efflux pumps MexAB-OprM, MexCD-OprJ, MexEF-OprN, MexXY-OprM, the AmpC {beta}-lactamase, and the porin OprD, which are commonly associated with chromosomally-encoded AMR. Next, qPCRs were tested on 15 sputa from 11 participants with P. aeruginosa respiratory infections to determine AMR profiles in vivo. We confirm multiplex qPCR testing feasibility directly on sputa, representing a key advancement in in vivo AMR diagnosis. Notably, comparison of sputa with their derived isolates grown in Luria-Bertani broth ({+/-}2.5% NaCl) or a 5-antibiotic cocktail showed marked expression differences, illustrating the difficulty in replicating in vivo expression profiles in vitro. Cystic fibrosis sputa showed significantly reduced mexE and mexY expression when compared with chronic obstructive pulmonary disease sputa, despite harbouring fluoroquinolone- and aminoglycoside-resistant strains, indicating that these loci are not contributing to AMR in vivo. oprD was also significantly downregulated in cystic fibrosis sputa, even in the absence of contemporaneous carbapenem use, suggesting a common adaptive trait in chronic infections that may affect carbapenem efficacy. Sputum ampC expression was highest in participants receiving carbapenems (6.7-15x), some of whom were simultaneously receiving cephalosporins, the latter of which would be rendered ineffective by the upregulated ampC. Our qPCR assays provide valuable insights into the P. aeruginosa resistome, and their use on clinical specimens will permit timely treatment alterations that will improve patient outcomes and antimicrobial stewardship measures.


title: Clustering analysis based on PiCCO parameters in patients with septic shock

abstract: The current study identified three septic shock phenotypes according to the pulse index continuous cardiac output parameters: Phenotype-1: normal cardiac output and vascular resistance, high blood volume; Phenotype-2: low cardiac output, normal blood volume, and high vascular resistance. Phenotype-3: normal vascular resistance and blood volume, high cardiac output. The mortality was significantly high in phenotype-1, but comparable between phenotype-2 and phenotype-3 (13/17 (76.4) vs. 13/35 (37.1) vs. 16/46 (34.7), p <0.001). Compared to phenotype 1 and 3, phenotype 2 had a higher AKI incidence and higher creatinine level at discharge.

category: intensive care and critical care medicine


title: Managing Endothelial Dysfunction in COVID-19: A Pilot, Double-Blind, Placebo-Controlled, Randomized Clinical Trial at the Lebanese American University Medical Center - Rizk Hospital (MEDIC-LAUMCRH)

abstract:
BackgroundCoronavirus disease 2019 (Covid-19) is associated with endothelial dysfunction. Pharmacologically targeting the different mechanisms of endothelial dysfunction may improve clinical outcomes and lead to reduced morbidity and mortality

MethodsIn this pilot, double-blind, placebo-controlled, randomized clinical trial we assigned patients who were admitted to the hospital with mild, moderate, or severe COVID-19 infection to receive, on top of optimal medical therapy, either an endothelial protocol consisting of (Nicorandil, L-arginine, Folate, Nebivolol, and Atorvastatin) or placebo for up to 14 days. The primary outcome was time to recovery, measured by an 8 category ordinal scale and defined by the time to being discharged from the hospital or hospitalized for infection-control or other nonmedical reasons. Secondary outcomes included the composite outcome of ICU admission or the need for mechanical ventilation, all-cause mortality, and the occurrence of side effects

ResultsOf 42 randomized patients, 37 were included in the primary analysis. The mean age of the patients was 57 years; the mean BMI of study participants was 29.14. History of hypertension was present in 27% of the patients, obesity in 45%, and Diabetes Mellitus in 21.6%. The median(Interquartile range) time to recovery was not significantly different between the endothelial protocol group (6 [4-12] days) and the placebo group (6 [5-8]days)(p-value = 0.854). Furthermore, there were no statistically significant differences in the need for mechanical ventilation or ICU admission, all-cause mortality, and the occurrence of side effects between the endothelial protocol group and the placebo group.

ConclusionAmong patients hospitalized with mild, moderate, or severe COVID-19 infection, targeting endothelial dysfunction by administering Nicorandil, L-arginine, Folate, Nebivolol, and Atorvastatin on top of optimal medical therapy did not decrease time to recovery. However, this treatment protocol was associated with an excellent safety profile. Adequately sized prospective randomized controlled trials are needed for the evaluation of the role of treating endothelial dysfunction in COVID-19 infection.

category: cardiovascular medicine


title: Placental microRNAs associate with early childhood growth characteristics

abstract: Poor placental function is a common cause of intrauterine growth restriction, which in turn is associated with increased risks of perinatal morbidity, mortality and long-term adverse health outcomes. Our prior work suggests that birthweight and childhood obesity-associated genetic variants functionally impact placental function and that placental microRNA are associated with birthweight. To address the influence of the placenta beyond birth, we assessed the relationship between placental microRNAs and early childhood growth. Using the SITAR package, we generated two parameters that describe individual weight trajectories of children (0-5 years) in the New Hampshire Birth Cohort Study (NHBCS). Using negative binomial generalized linear models, we identified placental microRNAs that associate with growth parameters (FDR<0.05), while accounting for sex, gestational age at birth, and maternal parity. Genes targeted by the six growth trajectory-associated microRNAs are enriched (FDR<0.02) in growth factor signaling (TGF/beta: miR-1290; EGF/R: miR-155, Let-7c; FGF/R: miR-155; IGF/R: Let-7c, miR-155, miR-1290), cyclic AMP signaling (miR-1246), calmodulin signaling (miR-216a, miR-1246), and NOTCH signaling (miR-629). These pathways function in placental proliferation, differentiation and function. Our results support the hypothesis that fetal environment, specifically placental cellular dynamics and function guided by microRNA expression, can have impacts beyond birth, into early childhood.


title: Investigating the genetic pathways of insomnia in Autism Spectrum Disorder.

abstract:
BackgroundSleep problems are common in children with autism spectrum disorder (autism). There is sparse research to date to examine whether insomnia in people with autism is related to autism genetics or insomnia genetics. Moreover, there is a lack of research examining whether circadian-rhythm related genes share potential pathways with autism.

AimsTo address this research gap, we tested whether polygenic scores of insomnia or autism are related to risk of insomnia in people with autism, and to test whether the circadian genes are associated with insomnia in people with autism.

Methods and proceduresWe tested these questions using the phenotypically and genotypically rich MSSNG dataset (N=1,049) as well as incorporating in the analyses data from the Vanderbilt University Biobank (BioVU) (N=349).

Outcomes and resultsIn our meta-analyzed sample, there was no evidence of associations between the polygenic scores (PGS) for insomnia and a clinical diagnosis of insomnia, or between the PGS of autism and insomnia. We also did not find evidence of a greater burden of rare and disruptive variation in the melatonin and circadian genes in individuals with autism and insomnia compared to individuals with autism without insomnia.

Conclusions and implicationsOverall, we did not find evidence for strong effects of genetic scores influencing sleep in people with autism, however, we cannot rule out the possibility that smaller genetic effects may play a role in sleep problems. Our study indicated the need for a larger collection of data on sleep problems and sleep quality among people with autism.

category: psychiatry and clinical psychology


title: Working from home due to the COVID-19 pandemic abolished the sleep disturbance vulnerability of late chronotypes relieving their predisposition to depression

abstract:
Background and aimsEveningness is distinctively associated with sleep disturbances and depression symptoms due to the misalignment between biological and social clock. The widespread imposition of remote working due to the COVID-19 pandemic allowed a more flexible sleep schedule. This scenario could promote sleep and mental health of evening-type subjects. We investigated the effect of working from home on sleep quality/quantity and insomnia symptoms within the morningness-eveningness continuum, and its indirect repercussions on depressive symptomatology.

Methods610 Italian office workers (mean age {+/-} standard deviation, 35.47 {+/-} 10.17 yrs) and 265 remote workers (40.31 {+/-} 10.69 yrs) participated in a web-based survey during the second contagion wave of COVID-19 (28 November-11 December 2020). We evaluated chronotype, sleep quality/duration, insomnia, and depression symptoms through validated questionnaires. Three moderated mediation models were performed, testing the mediation effect of sleep variables on the association between morningness-eveningness continuum and depression symptoms, with working modality (office vs. remote working) as moderator of the relationship between chronotype and sleep variables.

ResultsRemote working led to delayed bedtime and get-up time. Working modality moderated the chronotype effect on sleep variables, as eveningness was related to worse sleep disturbances and shorter sleep duration only among the office workers. Working modality moderated the mediation of sleep variables between chronotype and depression. The above mediation vanished among remote workers.

ConclusionsRemote working strikingly abolished the vulnerability to sleep problems of evening-type subjects, relieving their predisposition to depressive symptomatology. A working environment complying with individual circadian preferences might ensure an adequate sleep quantity/quality to late chronotypes, promoting their mental health.

Statement of SignificanceThe present study is the first to evaluate the different effect of pandemic-related remote working on sleep health/habits depending on the chronotype. We found longer sleep duration and improved sleep disturbances among evening-type subjects when working from home. This outcome could be ascribable to a better alignment between the endogenous circadian phase and the working schedule, as remote workers reported later bedtimes and get-up times. Moreover, we showed how improved sleep weakened the susceptibility to depressive symptomatology of evening-type people, highlighting an intriguing implication of working remotely on mental health in this category. Morningness-eveningness predisposition should be considered when designing remote working policies, in order to promote sleep and mental health of late chronotypes during the pandemic emergency, as well as in the post-covid era.


title: Coordinated Cortical Thickness Alterations across Psychiatric Conditions: A Transdiagnostic ENIGMA Study

abstract:
IntroductionMental disorders are increasingly conceptualized as overlapping spectra with underlying polygenicity, neurodevelopmental etiology, and clinical comorbidity. They share multi-level neurobiological alterations, including network-like brain structural alterations. However, whether alteration patterns covary across mental disorders in a biologically meaningful way is currently unknown.

MethodsWe accessed summary statistics on cortical thickness alterations from 12,024 patients with six mental disorders and 18,969 controls from the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium. First, we studied cortical thickness co-alteration networks as a form of pathological structural covariance. We identified regions exhibiting high inter-regional covariance across disorders ( hubs), and regions that strongly connect to these hubs facilitating network spreading of disease effects ( epicenters). Next, we applied manifold learning to reveal organizational gradients guiding transdiagnostic patterns of illness effects. Last, we tested whether these gradients capture differential cortical susceptibility with respect to normative cortical thickness covariance, cytoarchitectonic, transcriptomic, and meta-analytical task-based profiles.

ResultsCo-alteration network hubs were linked to normative connectome hubs and anchored to prefrontal and temporal disease epicenters. The principal gradient derived from manifold learning captured maximally different embedding of prefrontal and temporal epicenters within co-alteration networks, followed a normative cortical thickness gradient, and established a transcriptomic link to cortico-cerebello-thalamic circuits. Moreover, gradients segregated functional networks involved in basic sensory, attentional/perceptual, and domain-general cognitive processes, and distinguished between regional cytoarchitectonic profiles.

ConclusionTogether, our findings indicate that disease impact occurs in a synchronized fashion and along multiple levels of hierarchical cortical organization. Such axes can help to disentangle the different neurobiological pathways underlying mental illness.


title: Psychological, endocrine and polygenic predictors of emotional well-being during the COVID-19 pandemic

abstract:
Stress is an established risk factor for somatic and mental disorders. The COVID-19 pandemic and the related countermeasures severely affect the lives of families. Prenatal stress, dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis, and genetic factors might impact the well-being of individuals.

The present work is part of an ongoing birth cohort study and aims to investigate maternal perceived stress, early childhood HPA axis activity and polygenic risk scores (PRSs) as predictors of emotional well-being during the COVID-19 pandemic. All participants are part of the ongoing birth cohort study POSEIDON. Emotional well-being of children (n = 259) and mothers (n = 211) was assessed during the COVID-19 pandemic using the CRISIS questionnaire. Furthermore, associations between previously assessed maternal perceived stress (Perceived Stress Scale), childrens salivary and morning urine cortisol measures at 45 months, PRSs for depression, schizophrenia, loneliness and current emotional well-being were investigated.

A positive association between the childs and the mothers emotional well-being was found. A worse emotional well-being was observed in both children and mothers during the pandemic compared to before. Childrens emotional well-being improved over the course of the pandemic, while mothers well-being worsened. Maternal perceived stress, salivary and morning urine cortisol and PRSs were not significantly associated with the assessed emotional wellbeing.

The present study confirms that emotional well-being of children and mothers is negatively affected by the COVID-19 pandemic, with differences in development over time. Future studies should examine which mechanisms contribute to stress-related associations and at which age they can be identified.


title: Changes to hypothalamic volume and associated subfields during gender-affirming hormone treatment in gender dysphoria

abstract:
1.Sex steroid hormones influence hypothalamic micro- and macrostructure in humans and animal models. Neuroimaging studies have suggested that estrogen and anti-androgen treatment decreases volumes of multiple cortical and subcortical brain areas in transgender individuals, including total hypothalamus volume. Here, we aim to further explore potential effects of gender-affirming hormone treatment (GHT) in transgender individuals on hypothalamic volume by providing additional information on hypothalamic subfields.

38 transgender men (TM) and 15 transgender women (TW), with gender dysphoria (DSM-5), as well as 32 cisgender women (CW) and 21 cisgender men (CM) underwent two magnetic resonance imaging (MRI) measurements with an interval of at least four months (median interval TM= 134.5 days (interquartile range (IQR): 126-152.25); TW= 149 days (IQR: 126-178.5); CW= 147 days (IQR: 139.75-170.5); CM= 146 days (IQR: 132-247)) between both sessions. In transgender individuals GHT, consisting of estrogen and anti-androgen treatment in TW and testosterone treatment in TM, was initiated directly after the first measurement. To assess how GHT interacts with hypothalamic structures, the hypothalamus and its subunits were segmented using FreeSurfer. Subject group x time interaction effects were evaluated using repeated measures ANCOVA models. The Bonferroni method was used to correct for multiple comparisons.

Significant decreases of total hypothalamic volume and associated subunits were detected in TW after estrogen and anti-androgen treatment compared to cisgender groups. Effects were found in the total hypothalamus volume (pcorr= 0.001), the left and right hypothalamus (pcorr= 0.002), the inferior tubular subunit bilaterally (right: pcorr= 0.001; left: pcorr= 0.001), the left superior tubular subunit (pcorr= 0.003) the right anterior inferior subunit (pcorr= 0.002), as well as the right anterior superior subunit (pcorr= 0.0002) of the hypothalamus.

Here, we observed significant volumetric effects on the adult human hypothalamus after an interval of at least four months of estrogen and anti-androgen treatment in TW and added knowledge on associated subfields. Further studies investigating influences of sex steroid hormones on brain structure and functional connections are still needed.


title: Risk factors for severe COVID-19 differ by age: a retrospective study of hospitalized adults

abstract:
BackgroundRisk stratification for hospitalized adults with COVID-19 is essential to inform decisions for individual patients and allocation of potentially scarce resources. So far, risk models for severe COVID outcomes have included age but have not been optimized to best serve the needs of either older or younger adults. Additionally, existing risk models have been limited to either small sample sizes, or modeling mortality over an entire hospital admission. Further, previous models were developed on data from early in the pandemic, before improvements in COVID-19 treatment, the SARS-CoV-2 delta variant, and vaccination. There remains a need for early, accurate identification of patients who may need invasive mechanical ventilation (IMV) or die, considering multiple time horizons.

MethodsThis retrospective study analyzed data from 6,906 hospitalized adults with COVID-19 from a community health system with 51 hospitals and 1085 clinics across five states in the western United States. Risk models were developed to predict mechanical ventilation illness or death across one to 56 days of hospitalization, using clinical data collected available within the first hour after either admission with COVID-19 or a first positive SARS-CoV-2 test. The relative importance of predictive risk factors features for all models was determined using Shapley additive explanations.

FindingsThe percentage of patients who required mechanical ventilation or died within seven days of admission to the hospital due to COVID-19 was 10.82%. For the seven-day interval, models for age [≥] 18 and < 50 years reached AUROC 0.80 (95% CI: 0.70-0.89) and models for age [≥] 50 years reached AUROC 0.83 (95% CI: 0.79-0.88). Models revealed differences in the statistical significance and relative predictive value of risk factors between older and younger patients, including age, BMI, vital signs, and laboratory results. In addition, sex and chronic comorbidities had lower predictive value than vital signs and laboratory results.

InterpretationFor hospitalized adults, baseline data that is readily available within one hour after hospital admission or a first positive inpatient SARS-CoV-2 test can predict critical illness within one day, and up to 56 days later. Further, the relative importance of risk factors differs between older and younger patients.

category: public and global health


title: Idiopathic subglottic stenosis arises at the interface of host and pathogen.

abstract: Idiopathic subglottic stenosis (iSGS) is a rare fibrotic disease of the proximal airway affecting adult Caucasian women nearly exclusively. Life-threatening ventilatory obstruction occurs secondary to pernicious subglottic mucosal scar. Diverse diseases in divergent organ systems are associated with fibrosis, suggesting common biologic mechanisms. One well characterized pathway is chronic inflammation secondary to pathogen. In the present study, we explored the role of the proximal airway microbiome in iSGS pathogenesis. In human samples, abundant bacteria are detectable in iSGS scar as well as in health subglottic controls or patients that developed subglottic stenosis following endotracheal intubation. Interestingly, the community structure of the iSGS proximal airway microbiome does not appear disrupted. Rather, in iSGS defects in the airway epithelial barrier allow displacement of the native microbiome into the immunoprivileged lamina propria and are associated with adaptive immune activation. Animal models of iSGS confirm both bacteria and an adaptive immune response are necessary for pathologic proximal airway fibrosis. Single cell RNA sequencing of the affected airway in iSGS offers an unbiased characterization of the observed epithelial barrier dysfunction. The airway scar in iSGS patients demonstrates basal cell depletion and epithelial acquisition of a mesenchymal phenotype. The epithelial alterations are associated with the observed microbiome displacement, dysregulated immune activation, and localized fibrosis. These results refine our understanding of iSGS and implicate shared pathogenic mechanisms with distal airway fibrotic diseases.

category: respiratory medicine


title: Trend and Weightage of Problem-based Questions in Undergraduate Pharmacology Written Question Papers of Bangladesh

abstract:
BackgroundThe key objective of pharmacology education is to make graduates competent enough to prescribe safely and effectively. There is worldwide speculation of inadequacy of pharmacology education to achieve the expected learning outcomes. Problem-based pharmacotherapy is considered as one of the crucial way to prepare future physicians as rational prescribers. As assessment drives learning priorities, adequate weightage on problem-based questions in undergraduate pharmacology examination might be helpful.

Materials and MethodsThis descriptive cross-sectional study was conducted to analyze the undergraduate pharmacology written question papers (SAQ) of MBBS curriculum of 07 different universities (Bangladesh University of Professionals, University of Dhaka, University of Chittagong, University of Rajshahi, Shahjalal University of Science and Technology, University of Science and Technology, Chittagong and Gono Bishwabidyalay) of Bangladesh in last 10 years (January 2010 to November 2019). Total 131 question papers were collected, and trend and weightage of problem-based questions were evaluated.

ResultsProblem-based questions have been reduced dramatically over the decade and Mean percentage of marks allocated for problem-based questions was 1.2{+/-}1.3 over last years. There was significant difference (<0.00001) of weightage of problem-based questions among different universities of Bangladesh. Highest presence of problem-based question was observed in Gono Bishwabidyalay (GB), followed by Shahjalal University of Science and Technology (SUST), University of Rajshahi (RU) and Bangladesh University of Professionals (BUP) but there was not a single problem-based question in University of Dhaka (DU), University of Chittagong (CU) and University of Science and Technology (USTC) over 10 years period.

ConclusionCurrent study revealed negligible presence of problem-based questions in undergraduate pharmacology written question papers of Bangladesh over 10 years period.

category: medical education


title: Fading of brain network fingerprint in Parkinson's disease predicts motor clinical impairment

abstract: The clinical connectome fingerprint (CCF) was recently introduced as a way to assess brain dynamics and used to predict the cognitive decline in preclinical Alzheimers disease. In this paper we explore the performance of CCF in 47 Parkinsons disease (PD) patients and 47 healthy controls, under the hypothesis that patients would show reduced identifiability as compared to controls, and that such reduction could be used to predict motor impairment. Using source-reconstructed magnetoencephalography signals, we built functional connectomes and observed reduced identifiability in patients compared to healthy individuals in the beta band. Furthermore, we found that the reduction in identifiability was proportional to the motor impairment, assessed through the Unified Parkinsons Disease Rating Scale, and, interestingly, able to predict it (at the subject level). Along with previous evidence, this paper shows that CCF captures disrupted dynamics in neurodegenerative diseases and is particularly effective in predicting motor clinical impairment in PD.


title: Repurposing azacitidine and carboplatin to prime for anti-PDL1 re-challenge of immunotherapy-resistant melanoma

abstract:
Drug repurposing offers the opportunity for approved chemotherapy agents to be used to re-establish sensitivity to immune checkpoint blockade (ICB) therapy. Here we investigated the clinical and translational aspects of an early phase II study of azacitidine and carboplatin priming for anti-PDL1 immunotherapy (Avelumab) in patients with advanced ICB-resistant melanoma. 20 participants with ICB resistant metastatic melanoma received 2 x 4-week cycles of azacitidine and carboplatin followed by ICB re-challenge with anti-PD-L1 avelumab. The overall response rate (ORR) determined after 2 x 4-week cycles of azacitidine and carboplatin priming was 10% (2/20) with 2 partial responses (PR). The ORR determined after priming followed by 6 cycles of avelumab (week 22) was 10%, with 2/20 participants achieving iPR. The clinical benefit rate (CBR) for azacitidine and carboplatin priming was 65% (13/20) and after priming followed by 6 cycles of avelumab CBR was 35% (n = 7/20). The median PFS was 18.0 weeks (95% CI: 14.87 - 21.13 weeks) and the median OS was 47.86 weeks (95% CI: 9.67 - 86.06 weeks). Translational correlation analysis of tumour biopsies at baseline, after priming and after 6 cycles of avelmuab confirmed HLA-A generally increased after priming with azacitidine and carboplatin, particularly if it was absent at the start of treatment. Average methylation of CpGs across the HLA-A locus showed a consistent decrease in methylation after priming and T-cells, in particular CD8+, showed the greatest increase in infiltration. Priming with azacitidine and carboplatin can induce disease stabilization and re-sensitisation to ICB for metastatic melanoma.

One Sentence SummarySequential azacitidine and carboplatin stabilises disease burden and re-establishes sensitivity to checkpoint immune blockade immunotherapy.

category: oncology


title: Global and local ancestry modulate APOE association with Alzheimer's neuropathology and cognitive outcomes in an admixed sample

abstract: Dementia is more prevalent in Blacks than in Whites, likely due to a combination of environmental and biological factors. Paradoxically, clinical studies suggest an attenuation of APOE {varepsilon}4 risk of dementia in African ancestry (AFR), but lack of neuropathological data preclude the interpretation of the biological factors underlying these findings, including the association between APOE {varepsilon}4 risk and Alzheimers disease (AD) pathology, the most frequent cause of dementia. We investigated the interaction between African ancestry, AD-related neuropathology, APOE genotype, and functional cognition in a postmortem sample of 400 individuals with a range of AD pathology severity and lack of comorbid neuropathology from a cohort of community-dwelling, admixed Brazilians. Increasing proportions of African ancestry (AFR) correlated with a lower burden of neuritic plaques (NP). However, for individuals with high levels of NP and neurofibrillary tangles (NFT), AFR proportion was associated with worse Clinical Dementia Rating sum of boxes (CDR-SOB). Among APOE {varepsilon}4 carriers, the association between AFR proportion and CDR-SOB disappeared. APOE local ancestry inference of a subset of 309 individuals revealed that, in APOE {varepsilon}4 noncarriers, non-European APOE background associated with lower NP burden, but with worst cognitive outcomes compared to European APOE when adjusting by the similar NP burden. Finally, APOE {varepsilon}4 was associated with worse AD neuropathological burden only in a European APOE background. APOE genotype and its association with AD neuropathology and clinical pattern are highly influenced by ancestry, with AFR associated with lower NP burden and attenuated APOE4 risk compared to European ancestry.

category: genetic and genomic medicine


title: Developing and validating a multivariable prediction model for predicting costs of Colorectal Surgery

abstract:
Hospitals are faced with a burden to predict and therefore to calculate and also to manage various cost factors in regard to the patients and their treatments. Especially the increased costs which occur if a patient suffers from an anastomotic insufficiency. This can lead to an unavoidable deficit in the final revenue of these medical centers.

This study aims to determine whether machine learning (ML) algorithms can predict the cost factors based on patients with and without colon anastomosis after colorectal surgery. For the forecasting, multiple predictors will be taken into the model to provide a tool which can be helpful for hospitals to manage their costs which can end up in operating more cost effectively. This proof of principle will lay the groundwork for an efficient ML-based prediction tool based on multicenter data from a range of international centers in the subsequent phases of the study.

With a % MAPE result of 18 to 25.6 the prediction if our model showed decent results in order to forecast the costs in regard to various diagnosed factors and surgery approaches. There is an urgent need for further studies on predicting cost factors, especially for cases with and without anastomotic leakage to minimize unnecessary costs for the hospitals.

category: health economics


title: A Utility-Based Machine Learning-Driven Personalized Lifestyle Recommendation for Cardiovascular Disease Prevention

abstract: In recent decades, cardiovascular disease (CVD) has become the leading cause of death in most countries of the world. Since many types of CVD are preventable by modifying lifestyle behaviors, the objective of this paper is to develop an effective personalized lifestyle recommendation algorithm for reducing the risk of common types of CVD. However, in practice, the underlying relationships between the risk factors (e.g., lifestyles, blood pressure, etc.) and disease onset is highly complex. It is also challenging to identify the effective modification recommendations for different individuals due to the uncertainties in individuals preference to change and disease progression. Therefore, to address these challenges, this study developed a novel data-driven approach for personalized lifestyle behaviors recommendation based on machine learning and a personalized exponential utility function model. The contributions of this work can be summarized into three aspects: (1) a classification-based prediction model is implemented to accurately predict the CVD risk based on the condition of risk factors; (2) the generative adversarial network (GAN) is incorporated to learn the underlying relationship between risk factors, as well as quantifying the uncertainty of disease progression under lifestyle modifications; and (3) a novel personalized exponential utility function model is proposed to evaluate the modifications utilities with respect to CVD risk reduction, individuals preference to change and disease progression uncertainty, and identify the optimal modification for each individual. The effectiveness of the proposed method is validated through an open-access CVD dataset. The results demonstrate that the personalized lifestyle modification recommended by the proposed methodology can significantly reduce the potential CVD risk. Thus, it is very promising to be further applied to real-world cases for CVD prevention.


title: Clinical manifestations and disease severity of SARS-CoV-2 infection among infants in Canada

abstract:
ImportanceThere are limited data on outcomes of SARS-CoV-2 infection among infants (<1 year of age). In the absence of approved vaccines for infants, understanding characteristics associated with hospitalization and severe disease from COVID-19 in this age group will help inform clinical management and public health interventions.

ObjectiveThe objective of this study was to describe the clinical manifestations, disease severity, and characteristics associated with hospitalization among infants infected with the initial strains of SARS-CoV-2.

DesignProspective study of infants with SARS-CoV-2 from April 8th 2020 to May 31st 2021.

SettingNational study using the infrastructure of the Canadian Paediatric Surveillance Program, reporting inpatients and outpatients seen in clinics and emergency departments.

ParticipantsInfants <1 year of age with microbiologically confirmed SARS-CoV-2 infection.

ExposureInfant-level characteristics associated with hospitalization for COVID-19.

Main outcomes and MeasuresCases were classified as either: 1) Non-hospitalized patient with SARS-CoV-2 infection; 2) COVID-19-related hospitalization; or 3) non-COVID-19-related hospitalization (e.g., incidentally detected SARS-CoV-2). Case severity was defined as asymptomatic, outpatient care, mild (inpatient care), moderate or severe disease. Multivariable logistic regression was performed to identify characteristics associated with hospitalization.

ResultsA total of 531 cases were reported, including 332 (62.5%) non-hospitalized and 199 (37.5%) hospitalized infants. Among hospitalized infants, 141 of 199 infants (70.9%) were admitted because of COVID-19-related illness, and 58 (29.1%) were admitted for reasons other than acute COVID-19. Amongst all cases with SARS-CoV-2 infection, the most common presenting symptoms included fever (66.5%), coryza (47.1%), cough (37.3%) and decreased oral intake (25.0%). In our main analysis, infants with a comorbid condition had higher odds of hospitalization compared to infants with no comorbid conditions (aOR=4.53, 2.06-9.97), and infants <1 month had higher odds of hospitalization then infants aged 1-3 months (aOR=3.78, 1.97-7.26). In total, 20 infants (3.8%) met criteria for severe disease.

Conclusions and RelevanceWe describe one of the largest cohorts of infants with SARS-CoV-2 infection. Overall, severe COVID-19 in this age group is uncommon with most infants having mild disease. Comorbid conditions and younger age were associated with COVID-19-related hospitalization amongst infants.

Key PointsO_ST_ABSQuestionC_ST_ABSWhat are the spectrum of illness, disease severity, and characteristics associated with hospitalization in infants with SARS-CoV-2 infection?

FindingsA total of 531 cases were reported to the Canadian Paediatric Surveillance Program, including 332 (62.5%) non-hospitalized and 199 (37.5%) hospitalized infants. In total, 20 infants met criteria for severe disease (3.8%). Infants characteristics associated with admission included age of less than one month and comorbid conditions.

MeaningThis study provides data on the spectrum of disease, severity, and characteristics associated with admission due to COVID-19 in infants, which informs clinical management and public health interventions in this specific population.


title: Optimal Deployment of Automated External Defibrillators in a Long and Narrow Environment

abstract:
Aim of the studyPublic access to automated external defibrillators (AEDs) plays a key role in increasing survival outcomes for patients with out-of-hospital cardiac arrest. Based on the concept of maximizing "rescue benefit" of AEDs, we aimed to develop strategies for optimal deployment of AEDs for long and narrow spaces.

MethodsWe classified the effective coverage of an AED in hot, warm, and cold zones. The AEDs were categorized, according to their accessibility, as fixed, summonable, or patrolling types. The overall rescue benefit of the AEDs were evaluated by the weighted size of their collective hot zones. The optimal strategies for the deployment of AEDs were derived mathematically and numerically verified by computer programs.

ResultsTo maximize the overall rescue benefit of the AEDs, the AEDs should avoid overlapping with each others coverage as much as possible. Specific rules for optimally deploying one, two, or multiple AEDs, and various types of AEDs are summarized and presented.

ConclusionA methodology for assessing the rescue benefit of deployed AEDs was proposed, and deployment strategies for maximizing the rescue benefit of AEDs along a long, narrow, corridor-like, finite space were derived. The strategies are simple and readily implementable. Our methodology can be easily generalized to search for optimal deployment of AEDs in planar areas or three-dimensional spaces.


title: Humoral Antibody Kinetics with ChAdOx1-nCOV (CovishieldTM) and BBV-152 (CovaxinTM) Vaccine among Indian Healthcare workers: A 6-month Longitudinal Cross-sectional Coronavirus Vaccine-induced Antibody Titre (COVAT) Study

abstract:
Background and AimsThere is limited data available on longitudinal humoral antibody dynamics following two doses of ChAdOx1-nCOV (CovishieldTM) and BBV-152 (CovaxinTM) vaccine against SARS-CoV-2 among Indians.

MethodsWe conducted a 6-month longitudinal study in vaccinated healthcare workers by serially measuring quantitative anti-spike antibody at 3-weeks, 3-months and 6- months after the completion of second dose. Geometric mean titer (GMT) and linear mixed models were used to assess the dynamics of antibody levels at 6 months.

ResultsOf the 481 participants, GMT of anti-spike antibody decreased by 56% at 6- months regardless of demographics and comorbidities in 360 SARS-CoV-2 naive individuals, significantly in hypertensives. Participants with past infection had significantly higher GMT at all time points compared to naive individuals. Among SARS-CoV-2 naive cohorts, a significantly higher GMT was noted amongst the Covishield recipients at all time points, but there was a 44% decline in GMT at 6- month compared to peak titer period. Decline in GMT was insignificant (8%) in Covaxin recipients at 6-month despite a lower GMT at all time points vs. Covishield. There was 5.6-fold decrease in seropositivity rate at 6-month with both vaccines. Participants with type 2 diabetes mellitus have a lower seropositivity rate at all the time points. While seropositivity rate was significantly higher with Covishield vs. Covaxin at all time points except at 6-month where Covaxin recipients had a higher seropositivity, although no difference in seropositivity was noted in propensity-matched analysis.

ConclusionsThere is waning humoral antibody response following two doses of either vaccine at six months.

HighlightsO_LIWe assessed humoral antibody dynamics following two doses of the two vaccines used in India until 6 months.
C_LIO_LIOur study of 481 health care workers showed a significant decrease in the anti-spike antibody at 6-months.
C_LIO_LIReduction in antibody was regardless of demographics, comorbidities and the vaccine type.
C_LIO_LIT2DM cohorts had lowest seropositivity, while hypertensive had significant antibody decline at 6-month.
C_LI


title: Accessing Medical Care for Infertility: A Study of Women in Mexico

abstract:
BackgroundInvestigating the burden of access to infertility treatment has primarily been conducted in high-income countries, with little known for low- and middle-income countries, which comprise 80% of the worlds population. The objective of this study was to investigate access to infertility care in Mexico.

MethodsThis was a cross-sectional analysis in the Mexican Teachers Cohort (MTC), a prospective cohort study of 115,307 Mexican female public school teachers from 12 states in Mexico. Log-binomial models, adjusted for age, hormonal contraceptive use, teaching in a rural school, and speaking an indigenous language, were used to estimate the prevalence ratio (PR) and 95% confidence intervals (95% CI) of accessing medical care for infertility among women reporting a history of infertility.

Results19,580 (17%) participants reported a history of infertility. Of those who experienced infertility, 12,470 (63.7%) reported seeking medical care for infertility, among whom 8,467 (67.9%) reported undergoing fertility treatments. Among women who reported a history of infertility, women who taught in a rural school (PR:0.95;0.92-0.97), spoke an indigenous language (PR:0.88; 0.84-0.92), or had less than a university degree (PR:0.93; 0.90-0.97) were less likely to access medical care for fertility. Women who had ever had a mammogram (PR:1.07; 1.05-1.10), had a pap-smear in the past year (PR:1.08;1.06-1.10), or who had utilized private healthcare regularly or in times of illness were more likely to access medical care for fertility.

ConclusionUtilization of infertility care varied by demographic and access characteristics, including speaking an indigenous language, teaching in a rural school, and having a private healthcare provider.

category: obstetrics and gynecology


title: MatchMiner: An open source platform for cancer precision medicine

abstract: The systematic deployment of next generation sequencing means patient tumors can be genomically profiled and specific genetic alterations can be targeted with precision medicine (PM) drugs. More therapeutic clinical trials are needed to test new PM drugs to advance precision medicine, however, the availability of comprehensive patient sequencing data coupled with complex clinical trial eligibility has made it challenging to match patients to PM trials. To facilitate enrollment onto PM trials, we developed MatchMiner. MatchMiner is an open-source platform to computationally match genomically profiled cancer patients to PM trials. Here, we describe MatchMiners capabilities, outline its deployment at Dana-Farber Cancer Institute (DFCI), and characterize its impact on PM trial enrollment. MatchMiners two primary goals are to (1) facilitate PM trial options for all patients, and (2) accelerate trial enrollment onto PM trials. MatchMiner has 3 main modes of use: (1) patient-centric, where a clinician looks up trial options for an individual patient, (2) trial-centric, where a trial team identifies candidate patients for their trial by setting up a filter, and (3) trial search, where a clinician can find trial options for patients that have external genomic reports. From the time MatchMiner was first deployed at DFCI in March 2016 through March 2021, we curated 354 PM trials containing a broad range of genomic and clinical eligibility criteria and MatchMiner facilitated 166 trial consents (MatchMiner consents, MMC) for 159 patients. To quantify MatchMiners impact on trial consent, we retrospectively measured time from genomic sequencing report date to trial consent date for the 166 MMC compared to trial consents not facilitated by MatchMiner (non-MMC). We found MMC consented to trials 55 days (22%) earlier than non-MMC. MatchMiner has enabled our clinicians to match patients to PM trials and accelerated the trial enrollment decision making process.


title: Single Cell Characterization of Myeloma and its Precursor Conditions Reveals Transcriptional Signatures of Early Tumorigenesis

abstract: Multiple myeloma is a plasma cell malignancy almost always preceded by precursor conditions, but low tumor burden of these early stages has hindered the study of their molecular programs through bulk sequencing technologies. Here, we generated and analyzed single cell RNA-sequencing of plasma cells from 26 patients at varying disease stages and 9 healthy donors. In silico dissection and comparison of normal and transformed plasma cells from the same bone marrow biopsy enabled discovery of novel, patient-specific transcriptional changes. Using Bayesian Non-Negative Matrix Factorization, we discovered 15 gene expression signatures which represent transcriptional modules relevant to myeloma biology, and identified a signature that is uniformly lost in neoplastic cells across disease stages. Finally, we demonstrated that tumors contain heterogeneous subpopulations expressing distinct transcriptional patterns. Our findings characterize transcriptomic alterations present at the earliest stages of myeloma, paving the way for exploration of personalized treatment approaches prior to malignant disease.


title: Reduction in postoperative opioid requirement associated with use of the NSS-2(R) Bridge device, a disposable auriculo-nerve field stimulator, and factors affecting the response in cancer patients undergoing abdominal surgical procedures

abstract:
ObjectiveDetermine the effect on opioid use after surgery with use of the NSS-2(R) Bridge device (NBD(R)) as a field nerve stimulator of the nerves innervating the ear for 5 days.

MethodsThis was a prospective, randomized, double-blind, placebo-controlled trial investigating the effectiveness of the NBD(R) in reducing opioid (expressed as oral morphine equivalent; OME, mg) requirement in subjects undergoing abdominal surgery for cancer. A total of 53 subjects randomly assigned to either an active NBD(R) group or placebo group were included in the analysis. Secondary endpoints included pain using a verbal analogue scale (VAS, 0 = no pain to 10 = worst possible pain), time to ambulation, oral intake, first bowel movement, discharge from the hospital, and tolerability of the NBD(R). Lastly, functional recovery rated using the 12-item Short Form Survey (SF12) assessed at three months.

ResultsUse of the NBD(R) resulted in a 26% overall reduction in OME with no difference in pain level expressed as the area under the curve between postoperative day 1 to 5. respectively). This overall reduction accounts for a 6% reduction in OME in the patients undergoing laparoscopic surgery and a 39% reduction in OME and 25% reduction in pain in patients undergoing open surgery. The tolerability of the device was reported as excellent.

ConclusionsCancer patients have been identified as a population at risk of developing opioid use disorders. This prospective, randomized, double-blind, placebo-controlled study, demonstrated that NBD(R) may be an effective alternative to the use of opioid postoperatively in patients undergoing abdominal surgery for cancer, especially in especially in patients undergoing open surgery and in elderly.

category: pain medicine


title: Single-cell genomics improves the discovery of risk variants and genes of cardiac traits

abstract: Genome-wide association studies (GWAS) have linked hundreds of loci to cardiac diseases. However, in most loci the causal variants and their target genes remain unknown. We developed a combined experimental and analytical approach that integrates single cell epigenomics with GWAS to prioritize risk variants and genes. We profiled accessible chromatin in single cells obtained from human hearts and leveraged the data to study genetics of Atrial Fibrillation (AF), the most common cardiac arrhythmia. Enrichment analysis of AF risk variants using cell-type-resolved open chromatin regions (OCRs) implicated cardiomyocytes as the main mediator of AF risk. We then performed statistical fine-mapping, leveraging the information in OCRs, and identified putative causal variants in 122 AF-associated loci. Taking advantage of the fine-mapping results, our novel statistical procedure for gene discovery prioritized 45 high-confidence risk genes, highlighting transcription factors and signal transduction pathways important for heart development. We further leveraged our single-cell data to study genetics of gene expression. An unexpected finding from earlier studies is that expression QTLs (eQTLs) are often shared across tissues even though most regulatory elements are cell-type specific. We found that this sharing is largely driven by the limited power of eQTL studies using bulk tissues to detect cell-type-specific regulatory variants. This finding points to an important limitation of using eQTLs to interpret GWAS of complex traits. In summary, our analysis provides a comprehensive map of AF risk variants and genes, and a general framework to integrate single-cell genomics with genetic studies of complex traits.


title: Intrinsic Capacity of Rural Elderly in Thar Desert using WHO ICOPE (Integrated Care for Older Persons) Screening Tool: A Pilot Study

abstract:
IntroductionICOPE (Integrated Care for Older Persons) screening tool helps to address declines in physical and mental capacities in older people. In India majority of the older population resides in rural areas and there is a paucity of studies that demonstrates the utility of the ICOPE screening tool in India. Thus, this study was conducted to demonstrate the feasibility of using WHO ICOPE screening tool in a rural population.

MethodsA cross-sectional study was conducted in the two villages of Jodhpur. WHO ICOPE screening was done for a comprehensive geriatric assessment of intrinsic capacity by determining cognitive decline, the decline in mobility, malnutrition, sensory loss, depressive symptoms, health risks, social care, and support. Additionally, demographic details and information about health conditions were gathered.

ResultA total 451 participants (Male=54.5% and Female= 45.5%) surveyed. The mean age was 68.36 (SD=7.73) years and the majority of participants (68.3%) were illiterate. Most of the elderly have good families and lived with their children. Cognitive decline was found to be prevalent in 31.5% (n=142) of the participants, while mobility was diminished in 52.1% (n=235) participants. Eye problems were observed in 49.4% (n=223) participants, while 68.3% (n=308) were observed to be suffering from hearing loss. Limitation in mobility observed with the chair rise test and feeling of pain was found to be significantly associated with gender difference, with more limitation in females than males (p = 0.005; {chi}2 = 7.95) and more pain felt by females than males (p = 0.001; {chi}2 = 15.64).

ConclusionThis tool seems suitable in identifying the intrinsic capacity of the rural elderly.

category: geriatric medicine


title: SARS-CoV-2 and influenza co-infection throughout the COVID-19 pandemic: An assessment of co-infection rates and cohort characterization

abstract:
BackgroundCase reports of patients infected with COVID-19 and influenza virus ("flurona") have raised questions around the prevalence and clinical significance of these reports.

MethodsEpidemiological data from the HHS Protect Public Data Hub was analyzed to show trends in SARS-CoV-2 and influenza co-infection-related hospitalizations in the United States in relation to SARS-CoV-2 and influenza strain data from NCBI Virus and FluView. In addition, we retrospectively analyzed all cases of PCR-confirmed SARS-CoV-2 across the Mayo Clinic Enterprise from January 2020 to January 2022 and identified cases of influenza co-infections within two weeks of PCR-positive diagnosis date. Using a cohort from the Mayo Clinic with joint PCR testing data, we estimated the expected number of co-infection cases given the background prevalences of COVID-19 and influenza during the Wuhan (Original), Alpha, Delta, and Omicron waves of the pandemic.

FindingsConsidering data from all states of the United States using HHS Protect Public Data Hub, hospitalizations due to influenza co-infection with SARS-CoV-2 were seen to be highest in January 2022 compared to all previous months during the COVID-19 pandemic. Among 171,639 SARS-CoV-2-positive cases analyzed at Mayo Clinic between January 2020 and January 2022, only 73 cases of influenza co-infection were observed. Identified coinfected patients were relatively young (mean age: 28.4 years), predominantly male, and had few comorbidities. During the Delta era (June 16, 2021 to December 13, 2021), there were 9 lab-confirmed co-infection cases observed compared to 13.9 expected cases (95% CI: [12.7, 15.2]), and during the Omicron era (December 14, 2021 to January 17, 2022), there were 54 lab-confirmed co-infection cases compared to 80.9 expected cases (95% CI: [76.6, 85.1]).

ConclusionsReported co-infections of SARS-CoV-2 and influenza are rare. These co-infections have occurred throughout the COVID-19 pandemic and their prevalence can be explained by background rates of COVID-19 and influenza infection. Preliminary assessment of longitudinal EHR data suggests that most co-infections so far have been observed among relatively young and healthy patients. Further analysis is needed to assess the outcomes of "flurona" among subpopulations with risk factors for severe COVID-19 such as older age, obesity, and immunocompromised status.

Significance StatementReports of COVID-19 and influenza co-infections ("flurona") have raised concern in recent months as both COVID-19 and influenza cases have increased to significant levels in the US. Here, we analyze trends in co-infection cases over the course of the pandemic to show that these co-infection cases are expected given the background prevalences of COVID-19 and influenza independently. In addition, from an initial analysis of these co-infection cases which have been observed at the Mayo Clinic, we find that these co-infection cases are extremely rare and have mostly been observed in relatively young, healthy patients.


title: Chronic fatigue associated with post-COVID syndrome versus transient fatigue caused by high intensity exercise: are they comparable in terms of vascular effects?

abstract:
PurposeThe pathophysiology of chronic fatigue associated with post-COVID syndrome is not well recognized. It is assumed that this condition is partly due to vascular dysfunction developed during an acute phase of infection. There is great demand for a diagnostic tool that is able to clinically assess post-COVID syndrome and monitor the rehabilitation process.

Patients and MethodsThe Flow Mediated Skin Fluorescence (FMSF) technique appears uniquely suitable for the analysis of basal microcirculatory oscillations and reactive hyperemia induced by transient ischemia. The FMSF was used to measure vascular circulation in 45 patients with post-COVID syndrome. The results were compared with those for a group of 26 amateur runners before and after high intensity exercise, as well as for a control group of 32 healthy age-matched individuals.

ResultsBased on the NOI and RHR parameters measured with the FMSF technique, it was found that chronic fatigue associated with post-COVID syndrome is comparable with transient fatigue caused by high-intensity exercise in terms of vascular effects. Both chronic fatigue associated with post-COVID syndrome and transient fatigue caused by high-intensity exercise are associated with vascular stress in the macrocirculation and microcirculation.

ConclusionThe NOI and RHR parameters measured with the FMSF technique can be used for non-invasive clinical assessment of post-COVID syndrome, as well as for monitoring the rehabilitation process.


title: LGE-MRI for diagnosis of left atrial cardiomyopathy as identified in high-definition endocardial voltage and conduction velocity mapping

abstract:
BackgroundElectro-anatomical voltage, conduction velocity (CV) mapping and late-gadolinium-enhancement-magnetic-resonance-imaging (LGE-MRI) are different diagnostic modalities for atrial cardiomyopathy (ACM). However, discordances remain in the location and extent of detected ACM.

Objectives(1) Comparison of ACM extent and location between current modalities. (2) Development of new estimated optimised image-intensity-thresholds (EOIIT) for LGE-MRI identifying patients with ACM.

MethodsThirty-six ablation-naive persistent AF patients underwent LGE-MRI and high-definition electro-anatomical mapping in sinus rhythm. Significant ACM was defined as low-voltage-substrate (LVS) extent[≥]5% of the left atrium (LA) surface at <0.5 mV. LGE areas were classified using the Utah, image-intensity-ratio (IIR>1.20) and new EOIIT method for comparison to LVS and slow-conductionareas <0.2 m/s. ROC-analysis determined the LGE-extent enabling accurate diagnosis of ACM.

ResultsThe degree and distribution of detected pathological substrate varied significantly (p<0.001) across the mapping modalities: 3% (IQR 0-12%) of the LA displayed LVS<0.5 mV vs. 14% (3-25%) slow-conduction-areas<0.2 m/s vs. 16% (6-32%) LGE with Utah method vs. 17%(11-24%) using IIR>1.20, with enhanced discrepancies on posterior LA. A linear correlation was found between the OIIT and each patients mean blood pool intensity (R2=0.89, p<0.001). LGE-MRI-based ACM-diagnosis improved with the novel EOIIT (83% sensitivity, 88% specificity, AUC:0.94) in comparison to the Utah method (60% sensitivity, 75% specificity, AUC:0.76), and IIR>1.20 (58% sensitivity, 75% specificity, AUC:0.71)

ConclusionImportant discordances in distribution of pathological substrate exist between LA-LVS, CV and LGE-MRI, irrespective of the LGE-detection protocol that is used. However, the new EOIIT method improves LGE-MRI-based ACM-diagnosis in ablation-naive AF-patients.


title: The relationship of maternal gestational mass spectrometry-derived metabolites with offspring congenital heart disease: results from multivariable and Mendelian randomization analyses

abstract:
BackgroundIt is plausible that maternal pregnancy metabolism influences risk of offspring congenital heart disease (CHD). We sought to explore this through a systematic approach using different methods and data.

MethodsWe undertook multivariable logistic regression of the odds of CHD for 923 Mass Spectrometry (MS)-derived metabolites in a sub-sample of a UK birth cohort (Born in Bradford (BiB); N = 2,605, 46 CHD cases). We considered metabolites reaching a p-value threshold <0.05 to be suggestively associated with CHD. We sought validation of our findings, by repeating the multivariable regression analysis within the BiB cohort for any metabolite that was measured by nuclear magnetic resonance (NMR) or clinical chemistry (N = 7,296, 87 CHD cases), and by using genetic risk scores (GRS: weighted genetic risk scores of single nucleotide polymorphisms (SNPs) that were associated with each metabolite) in Mendelian randomization (MR) analyses. MR analyses were performed in BiB and two additional European birth cohorts (N = 38,662, 319 CHD cases).

ResultsIn the main multivariable analyses, we identified 44 metabolites suggestively associated with CHD, including those from the following super pathways: amino acids, lipids, co-factors and vitamins, xenobiotics, nucleotides, energy, and several unknown molecules. Of these 44, isoleucine and leucine were available in the larger BiB cohort (NMR), and for these the results were validated. MR analyses were possible for 27/44 metabolites and for 11 there was consistency with multivariable regression results.

ConclusionsIn summary, we have used complimentary data sources and statistical techniques to construct layers of evidence. We found that amino acid metabolism during pregnancy, several lipids (more specifically androgenic steroids), and levels of succinylcarnitine could be important contributing factors for CHD.

category: epidemiology


title: Increase in coercive measures in psychiatric hospitals in Germany during the COVID-19 Pandemic

abstract:
ObjectiveTo examine whether the pandemic in 2020 caused changes in psychiatric hospital cases, the percentage of patients exposed to coercive interventions, and aggressive incidents.

MethodsWe used the case registry for coercive measures of the State of Baden-Wuerttemberg, comprising case-related data on mechanical restraint, seclusion, physical restraint, and forced medication in each of the States 31 licensed hospitals treating adults, to compare data from 2019 and 2020.

ResultsThe number of cases in adult psychiatry decreased by 7.6% from 105,782 to 97,761. The percentage of involuntary cases increased from 12.3 to 14.1%, and the absolute number of coercive measures increased by 4.7% from 26,269 to 27,514. The percentage of cases exposed to any kind of coercive measure increased by 24.6% from 6.5 to 8.1%, and the median cumulative duration per affected case increased by 13.1% from 12.2 to 13.8 hrs, where seclusion increased more than mechanical restraint. The percentage of patients with aggressive incidents, collected in 10 hospitals, remained unchanged.

ConclusionsWhile voluntary cases decreased considerably during the pandemic, involuntary cases increased slightly. However, the increased percentage of patients exposed to coercion is not only due to a decreased percentage of voluntary patients, as the duration of coercive measures per case also increased. The changes that indicate a deterioration in treatment quality were probably caused by the multitude of measures to manage the pandemic. The focus of attention has shifted from prevention of coercion to prevention of infection.


title: Measles incidence in South Africa: a six-year review, 2015 - 2020

abstract:
In 2012 the World Health Organization (WHO) aimed to eliminate measles in five regions by 2020. This retrospective descriptive study reviewed measles surveillance data in South Africa for the period 2015 - 2020 to document the epidemiology of measles and the progress made towards meeting the 2020 measles elimination goal.

A total of 22,578 specimens were tested over the period 2015 - 2020 yielding 401 (1.8%) confirmed measles cases, 321 (1.4%) compatible and 21,856 (96.8%) discarded cases. The most affected age group was 0-4 year olds. At the provincial level, South Africa achieved adequate surveillance, defined as more than two cases of febrile rash notified annually per 100 000 popoulation, except for KwaZulu-Natal and Limpopo in 2020, probably due to COVID-19 lockdown restrictions. Of confirmed cases, only 26% were vaccinated, 3% were too young to receive vaccines, 5% were not vaccinated, and 65% had vaccination status unknown. Measles vaccine effectiveness amongst 1-4 year olds was 80%. Using the standard case definition, South Africa achieved the measles elimination target of less than one case per one million nationally in years 2015, 2016 and 2020. The years 2017 to 2019 had incidence rates exceeded one per million nationally. Using a narrow case definition, that excluded positive rubella cases, improved the indicators with only the year 2017 having an incidence rate of more than one per million.

South Africa displays intermittent measles outbreaks approximately six-yearly interspersed by inter-epidemic periods in which the country meets measles elimination targets. Intense effort is needed to increase the vaccine coverage to avoid periodic outbreaks. Enhanced molecular testing of each case will be required as measles incidence declines regionally.


title: An evaluation of metabolic, dietetic, and nutritional status reveals impaired outcomes in breast cancer patients undergoing chemotherapy compared with a matched control group.

abstract:
PurposeNutritional status changes in breast cancer patients during treatment are prevalent. However, the metabolic implications of those alterations are poorly understood. We aimed to characterize body composition, lipids, glucose levels, and indices that express cardiovascular risk in breast cancer patients after completion of chemotherapy and then to compare those results with a matched control group.

MethodsA cross-sectional study was performed. Women who completed their chemotherapy were recruited (BC group) and compared with a group of non-malignant age- and body mass index-matched (MC group), as well as a group of healthy, non-malignant women (HC group). Body composition by bioelectrical impedance analysis, handgrip strength, and blood sample were collected. Visceral adiposity, triglyceride glucose and lipid accumulation product indices were calculated. Food consumption was assessed.

Results88 women were included (BC=36, MC=36, HC=16). BC patients demonstrated worse values of phase angle, nutritional risk index, extracellular body water to total body water ratio and lower handgrip strength. Additionally, those women had impairments in lipids, worst glucose levels, visceral fat dysfunction and consequently higher cardiovascular risk, presenting important unhealthy dietary patterns with higher carbohydrate and caloric intake and insufficient protein and fiber ingestion. No differences were observed between MC and HC.

ConclusionBreast cancer patients present unhealthy metabolic, nutritional, and dietetic features when compared to a group of age- and BMI-matched non-malignant females. Also, breast cancer patients had higher levels of cardiovascular risk. Further investigations are required to examine the underlying mechanisms and the potential longitudinal changes during surveillance time.

category: nutrition


title: The accuracy of machine learning models using ultrasound images in prostate cancer diagnosis: A systematic review

abstract: Prostate Cancer (PCa) is the third most commonly diagnosed cancer worldwide, and its diagnosis requires many medical examinations, including imaging. Ultrasound offers a practical and cost-effective method for prostate imaging due to its real-time availability at the bedside. Nowadays, various Artificial Intelligence (AI) models, including Machine learning (ML) with neural networks, have been developed to make an accurate diagnosis. In PCa diagnosis, there have been many developed models of ML and the model algorithm using ultrasound images shows good accuracy. This study aims to analyse the accuracy of neural network machine learning models in prostate cancer diagnosis using ultrasound images. The protocol was registered with PROSPERO registration number CRD42021277309. Three reviewers independently conduct a literature search in five online databases (MEDLINE, EBSCO, Proquest, Sciencedirect, and Scopus). We screened a total of 132 titles and abstracts that meet our inclusion and exclusion criteria. We included articles published in English, using human subjects, using neural networks machine learning models, and using prostate biopsy as a standard diagnosis. Non relevant studies and review articles were excluded. After screening, we found six articles relevant to our study. Risk of bias analysis was conducted using QUADAS-2 tool. Of the six articles, four articles used Artificial Neural Network (ANN), one article used Recurrent Neural Network (RNN), and one article used Deep Learning (DL). All articles suggest a positive result of ultrasound in the diagnosis of prostate cancer with a varied ROC curve of 0.76-0.98. Several factors affect AI accuracy, including the model of AI, mode and type of transrectal sonography, Gleason grading, and PSA level. Although there was only limited and low-moderate quality evidence, we managed to analyse the predominant findings comprehensively. In conclusion, machine learning with neural network models is a potential technology in prostate cancer diagnosis that could provide instant information for further workup with relatively high accuracy above 70% of sensitivity/specificity and above 0.5 of ROC-AUC value. Image-based machine learning models would be helpful for doctors to decide whether or not to perform a prostate biopsy.

category: urology


title: Vitamin D and acute respiratory infection: secondary analysis of a previous randomised controlled trial and updated meta-analyses

abstract:
BackgroundRecent meta-analyses concluded that vitamin D supplementation can prevent acute respiratory infection (ARI). However, the findings were heavily influenced by results from two arms of a six-arm cluster-randomised trial that were analysed without accounting for the cluster trial design. We have used publicly available data to provide results from the remaining four unpublished trial arms and to reanalyse the meta-analyses, accounting for the cluster trial design.

MethodsThe intracluster correlation co-efficient (ICC) and design effect were estimated. We then calculated the risk reduction (RR) of ARI from summary statistics, adjusting for the design effect, individually for the five different vitamin D treatment groups (four previously unpublished) and for all the vitamin D groups pooled. For this trial, individual patient data were used to estimate the effect of vitamin D on ARI risk and number of ARIs, adjusting for the cluster trial design, using random-effects models. Finally, we reanalysed the most recent trial-level meta-analysis, including the trial data generated by the correct analysis of the cluster randomized trial.

ResultsThere were 744 trial participants (6 treatment groups, 21 clusters, mean cluster size 35.4). The ICC was 0.08 (95% CI 0.02-0.14) and design effect 3.75. In analyses based on summary statistics, there was no statistically significant effect of vitamin D on ARI risk in any individual treatment group, or when groups were pooled (RR 0.75, 95%CI 0.50-1.13). In individual patient data analyses, there was also no statistically significant effect of vitamin D on the ARI risk or number of ARIs in any treatment group, or when pooled: odds ratio 0.58 (0.26-1.29), rate ratio 0.70 (0.44-1.12), respectively. Update of the previous meta-analysis showed no effect of vitamin D on ARI either when data from the two arms of the trial, or when all trial arms were incorporated (RR 0.98, 0.96-1.00, P=0.10 both analyses).

ConclusionsOverall, vitamin D supplementation had no effect on the risk of an ARI or on the number of ARIs in this trial or in a re-analysis of the most recent meta-analysis. The results of the updated meta-analysis do not suggest that vitamin D supplementation would reduce the risk of Covid 19.

category: endocrinology


title: Determinants of Thyroid Dysfunction among Type 2 Diabetes Patients Attending Private Hospitals in Dire Dawa, Eastern Ethiopia

abstract:
PurposeThe purpose of this study is to capture the determinants of thyroid dysfunction in type 2 diabetes mellitus at private hospitals in Dire-Dawa, Eastern Ethiopia. Various studies found that thyroid dysfunction is common in type 2 diabetes and it is associated with poor blood glucose control and chronic diabetic complications responsible for morbidity and mortality. However, only limited studies have assessed determinants of thyroid dysfunctions among type 2 diabetes in Ethiopia.

MethodsUnmatched case-control study conducted in two private hospitals found in Dire Dawa town, between May - November 2021. A total of 92 type 2 diabetic patients with thyroid dysfunction as Cases and 183 type 2 diabetes patients with normal thyroid function as controls selected by purposive and systematic random sampling, respectively. Data collected by interview and using checklist, entered into SPSS version 22, and analyzed. Bivariate and multivariate logistic regression analysis employed to identify determinants of thyroid dysfunction with AOR and 95%CI. Independent t-test computed to observe significant mean difference of continuous variables. Variables with P-value < 0.05 declared as significant.

ResultFemale gender predominate 65.9% of participants (p= 0.02). The mean glycated hemoglobin level among cases was 10.32 ({+/-} 2.4 SD) and 9.249 ({+/-} 2.3 SD) among controls, with significant difference (p=0.001). Similarly, the mean LDL cholesterol among cases 116.92 {+/-}45.9 SD and control 102.34 {+/-}43.97SD showed significant difference (p=0.016). Diabetic retinopathy and neuropathy, and ACEI/ARB also significantly associated with thyroid dysfunction (p< 0.05).

ConclusionFemale gender, lower educational level, and duration of diabetes associated with thyroid dysfunction. Most patients in both groups had unacceptably elevated HgA1c which need to be addressed. Thus, screening for thyroid dysfunction, especially the female gender, needs to be done.


title: A large outbreak of COVID-19 in a UK prison, October 2020 to April 2021

abstract:
IntroductionPrisons are susceptible to outbreaks. Control measures focusing on isolation and cohorting negatively affect wellbeing. We present an outbreak of COVID-19 in a large male prison in Wales, UK, October 2020 to April 2021, and discuss control measures.

MethodsWe gathered case-information, including demographics, staff-residence postcode, resident cell number, work areas/dates, test results, staff interview dates/notes and resident prison-transfer dates. Epidemiological curves were mapped by prison location. Control measures included isolation (exclusion from work or cell-isolation), cohorting (new admissions and work-area groups), asymptomatic testing (case-finding), removal of communal dining and movement restrictions. Facemask use and enhanced hygiene were already in place. Whole genome sequencing (WGS) and interviews determined genetic relationship between cases plausibility of transmission.

ResultsOf 453 cases, 53% (n=242) were staff, most aged 25-34 years (11.5% females, 27.15% males) and symptomatic (64%). Crude attack-rate was higher in staff (29%, 95%CI: 26-64%) than in residents (12%, 95%CI: 9-15%).

ConclusionsWhole genome sequencing can help differentiate multiple introductions from person-to-person transmission in prisons. It should be introduced alongside asymptomatic testing as soon as possible to control prison outbreaks. Timely epidemiological investigation, including data visualisation, allowed dynamic risk assessment and proportionate control measures, minimising reduction in resident welfare.


title: Recovery Time and Its Predictors among Women Admitted with Obstetric Fistula in Jimma University Medical Center Southwest, Ethiopia: A Retrospective Cohort Study

abstract:
BackgroundObstetric fistula is one of the most shocking medical disabilities that women face as a result of problems caused by a lack of surgical intervention.

MethodsFrom January 2011 to February 2017, a retrospective analysis was undertaken on obstetric fistula participants who received undergone surgical repair at the Jimma University Medical Center.

Results81.4% of fistula patients were reported to have recovered. The results of lognormal inverse-Gaussian frailty model revealed that weight [≥]50kg ([FE]= 0.86, 95% CI: 0.747, 0.99), divorced ([FE]=1.2, 95% CI: 1.028, 1.413), urban residence ([FE]= 1.56, 95% CI: 01.046, 2.317), urine incontinence >3 months ([FE]=1.2, 95% CI: 1.056, 1.371), no antenatal care ([FE]=1.189, 95% CI:1.023, 1.382), duration of labor <2days ([FE]= 0.86, 95% CI: 0.758, 0.986), health center delivery ([FE]= 0.76, 95% CI: 0.576, 0.989), vaginal delivery ([FE]= 1.5, 95% CI: 1.125, 1.996), and partially damaged urethra ([FE]=1.59, 95% CI: 1.168, 2.166) and recto-vaginal fistula([FE]= 0.735, 95%CI: 0.6045, 0.894) were associated with the recovery time.

ConclusionPatients with a weight < 50 kg, delivery at a health center, labor lasting <2 days, urinary incontinence lasting <3 months, antenatal care follow-up, cesarean section delivery, urethra status not damaged, and recto-vaginal fistula had a faster recovery period.