title: Mortality in cancer patients with congenital anomalies across different age groups: trend analysis and prognostic risk factors

abstract:
PurposeCongenital anomalies are one of the causes of the high mortality rate in children diagnosed with cancer. However, there is a gap of evidence of the rate of cancer mortality in older patients who had congenital anomalies. The study, therefore, aimed to investigate the epidemiology of cancer mortality in those patients.

MethodsData were retrieved for patients with cancer and died due to congenital causes throughout 43 years from Surveillance, Epidemiology, and End Results program SEER. The age of patients was divided into nine groups each is formed of 10 years interval. Joinpoint analysis was used to calculate the trends of Cancer mortality and Cox proportional hazard ratio to identify the mortality risk factors.

ResultsWe have included 2682 patients with death associated with congenital malformation. The mortality of cancer patients due to congenital anomalies greatly enhanced in the last years with the overall average annual percent was 3.8%. Interestingly, congenital anomalies had less mortality risk than other causes reported in SEER. Moreover, age, sex, radiation, chemotherapy, and behavior of tumor were significantly associated with higher survival in patients with congenital anomalies.

ConclusionsCancer patients with congenital anomalies had less mortality risk than patients with other diseases reported in SEER. The mortality rates decreased recently, with the most mortality in the bone marrow and prostate tumors.

Implications for Cancer SurvivorsCongenital anomalies are considered the least studied diseases in cancer patients. In this study, we studied how congenital anomalies did not increase the risk for cancer. However, our analysis implied the congenital anomalies in the male reproductive system were associated with the highest risk of cancer.

category: oncology


title: Artificial intelligence in the respiratory sounds analysis and computer diagnostics of bronchial asthma

abstract:
Using a database containing audio files of respiratory sound records of asthmatic patients and healthy patients, a method of computer-aided diagnostics based on the machine learning technique - creation of neural networks, has been developed. The database contains 952 records of respiratory sounds of asthma patients at different stages of the disease, aged from several months to 47 years, and 167 records of volunteers. Records were carried out with a quiet breathing at four points: in the oral cavity, above the trachea, on the chest, the second intercostal space on the right side, and at a point on the back.

The developed method of computer-aided diagnostics allows diagnosing bronchial asthma with high reliability: sensitivity of 89.3%, specificity of 86%, accuracy of about 88% and Youdens index of 0.753.

The program learned once makes it possible to diagnose bronchial asthma with high reliability regardless of patients gender and age, a stage of disease, as well as the point of sound recording.

The developed method can be used as an additional screening method for the diagnostics of bronchial asthma and serve as the basis for development of computer control methods, including remote control (telemedicine) of patients condition and the effectiveness of the applied drugs in real time.

category: health informatics


title: Magnetic Resonance Imaging-based Deep Learning Predictive Models of Brain Disorders: A Systematic Review of Modelling Practices, Transparency, and Interpretability

abstract: Brain disorders are characterised by impaired cognition, mood alteration, psychosis, depressive episodes, and neurodegeneration, and comprise several psychiatric and neurological disorders. Clinical diagnoses primarily rely on a combination of life history information and questionnaires, with a distinct lack of discriminative biomarkers in use for psychiatric disorders. Given that symptoms across brain conditions are associated with functional alterations of cognitive and emotional processes, which can correlate with anatomical variation, structural magnetic resonance imaging (MRI) data of the brain are an important focus of research studies, particularly for predictive modelling. With the advent of large MRI data consortiums (such as the Alzheimers Disease Neuroimaging Initiative) facilitating a greater number of MRI-based classification studies, convolutional neural networks (CNNs), which are multi-layer representation-based models particularly well suited to image processing, have become increasingly popular for research into brain conditions. Despite this, modelling practices, the degree of transparency, and considerations of interpretability vary widely across studies, making them difficult to both compare and/or reproduce. Modelling practices here refers to issues surrounding the data splitting procedure, the presence or absence of repeat experiments, the critical appraisal of performance metrics, and the overall reliability of the modelling approach. Transparency refers to how detailed the authors methodological descriptions are, and the availability of code. Finally, interpretability refers to the attempt made by the authors to identify structural brain alterations driving model predictions - this is particularly important as the application of deep learning systems becomes more widespread in clinical settings. Here, we conduct a systematic literature review of 55 studies carrying out CNN-based predictive modelling of brain disorders using MRI data and critique their modelling practices, transparency, and considerations of interpretability; we furthermore propose several practical recommendations aimed at promoting comprehensive, clear, and reproducible research into brain disorders using MRI-based deep learning models.


title: Is it time to use machine learning survival algorithms for survival and risk factors prediction instead of Cox proportional hazard regression? A comparative population-based study

abstract:
PurposeApplying machine learning in medical statistics offers more accurate prediction models. In this paper, we aimed to compare the performance of the Cox Proportional Hazard model (CPH), Classification and Regression Trees (CART), and Random Survival Forest (RSF) in short-, and long-term prediction in glioblastoma patients.

MethodsWe extracted glioblastoma cancer data from the Surveillance, Epidemiology, and End Results database (SEER). We used the CPH, CART, and RSF for the prediction of 1- to 10-year survival probabilities. The Brier Score for each duration was calculated, and the model with the least score was considered the most accurate.

ResultsThe cohort included 26473 glioblastoma patients divided into two groups: training (n = 18538) and validation set (n = 7935). The average survival duration was seven months. For the short- and long-term predictions, RSF was the best algorithm followed by CPH and CART.

ConclusionFor big data, RSF was found to have the highest accuracy and best performance. Using the accurate statistical model for survival prediction and prognostic factors determination will help the care of cancer patients. However, more developments of the R packages are needed to allow more illustrations of the effect of each covariate on the survival probability.


title: Parsing Clinical Trial Eligibility Criteria for Cohort Query by a Multi-Input Multi-Output Sequence Labeling Model

abstract: To enable electronic screening of eligible patients for clinical trials, free-text clinical trial eligibility criteria should be translated to a computable format. Natural language processing (NLP) techniques have the potential to automate this process. In this study, we explored a supervised multi-input multi-output (MIMO) sequence labelling model to parse eligibility criteria into combinations of fact and condition tuples. Our experiments on a small manually annotated training dataset showed that that the performance of the MIMO framework with a BERT-based encoder using all the input sequences achieved an overall lenient-level AUROC of 0.61. Although the per-formance is suboptimal, representing eligibility criteria into logical and semantically clear tuples can potentially make subsequent translation of these tuples into database queries more reliable.


title: Effectiveness of Vaccination Against Reported SARS-CoV-2 Infection in United States Coast Guard Personnel Between May and August 2021: A Time-Series Analysis

abstract:
BackgroundThe United States Coast Guard (CG) began voluntary use of SARS-CoV-2 vaccines under an Emergency Use Authorization on December 16, 2020. Vaccination status is monitored through a service-wide immunization registry. Active Duty and Reserve (military) CG members are required to report any new positive test for COVID-19 to a centralized database.

MethodsBetween May and August 2021, vaccination effectiveness (VE) against any new report of COVID-19 was calculated according to standard formulas, using registry immunization status of cases and monthly mid-point vaccine coverage data. CG members recorded as fully vaccinated with a two-dose vaccine were compared with those with any other vaccine status. Sub-analyses were also conducted according to geographic area (Atlantic vs Pacific), age, and type of vaccine received.

ResultsEffectiveness of full vaccination reached a peak of 89.0% in June, then declined over the rest of the study period to 62.7% in August. In July and August, steeper declines in VE were seen in the Atlantic region. The rate of breakthrough infections remained under 1% in two-dose vaccine recipients, and did not differ between those who received the Moderna or Pfizer vaccines. No hospitalizations or deaths due to COVID-19 disease were recorded in fully vaccinated Coast Guard members.

ConclusionCoincident with the national spread of the Delta variant of SARS-CoV-2, overall vaccine effectiveness among CG personnel decreased during the summer months of 2021, but continued to provide substantial protection, as well as full protection against the most serious outcomes. Policy initiatives and outreach intended to increase vaccine coverage within this and other military populations could extend the disease prevention benefits seen in this study.

category: infectious diseases


title: Protective characteristics of COVID-19 convalescent and post-vaccination IgG antibodies

abstract:
Soon after commencement of the SARS-CoV-2 disease outbreak of 2019 (COVID-19), it became evident that the receptor-binding domain of the viral spike protein is the target of neutralizing antibodies that comprise a critical element of protective immunity to the virus. This study addresses the relative lack of information regarding actual antibody concentrations in convalescent plasma samples from COVID-19 patients and extends these analyses to post-vaccination samples to estimate protective IgG antibody (Ab) levels. Both sample populations were similar and a protective Ab level of 7.5 {micro}g/ml was determined, based on 95% of the normal distribution of the post-vaccination population. The results of this study have implications for future vaccine development, projection of protective efficacy duration, and understanding of the immune response to SARS-CoV-2 infection.

One-Sentence SummaryUsing two quantitative immunoassays, we have found similar IgG antibody responses to the SARS-CoV-2 spike protein in populations of COVID-19 survivors and vaccine recipients that indicate a protective antibody concentration.


title: Hemodynamic profiles by non-invasive monitoring of cardiac index and vascular tone in acute heart failure patients in the emergency department: external validation and clinical outcomes

abstract:
BackgroundNon-invasive finger-cuff monitors measuring cardiac index and vascular tone (SVRI) classify emergency department (ED) patients with acute heart failure (AHF) into three otherwise-indistinguishable subgroups. Our goals were to validate these "hemodynamic profiles" in an external cohort and assess their association with clinical outcomes.

MethodsAHF patients (n=257) from five EDs were prospectively enrolled in the validation cohort (VC). Cardiac index and SVRI were measured with a ClearSight finger-cuff monitor (formerly NexFin, Edwards Lifesciences) as in a previous study (derivation cohort, DC, n=127). A control cohort (CC, n=127) of ED patients with sepsis was drawn from the same study as the DC. K-means cluster analysis previously derived two-dimensional (cardiac index and SVRI) hemodynamic profiles in the DC and CC (k=3 profiles each). The VC was subgrouped de novo into three analogous profiles by unsupervised K-means consensus clustering. PERMANOVA tested whether VC profiles 1-3 differed from profiles 1-3 in the DC and CC, by multivariate group composition of cardiac index and vascular tone.

Profiles in the VC were compared by a primary outcome of 90-day mortality and a 30-day ranked composite secondary outcome (death, mechanical cardiac support, intubation, new/emergent dialysis, coronary intervention/surgery) as time-to-event (survival analysis) and binary events (odds ratio, OR). Descriptive statistics were used to compare profiles by two validated risk scores for the primary outcome, and one validated score for the secondary outcome.

ResultsThe VC had median age 60 years (interquartile range {49-67}), and was 45% (n=116) female. Multivariate profile composition by cardiac index and vascular tone differed significantly between VC profiles 1-3 and CC profiles 1-3 (p=0.001, R2=0.159). A difference was not detected between profiles in the VC vs. the DC (p=0.59, R2=0.016).

VC profile 3 had worse 90-day survival than profiles 1 or 2 (HR = 4.8, 95%CI 1.4-17.1). The ranked secondary outcome was more likely in profile 1 (OR = 10.0, 1.2-81.2) and profile 3 (12.8, 1.7-97.9) compared to profile 2. Diabetes prevalence and blood urea nitrogen were lower in the high-risk profile 3 (p<0.05). No significant differences between profiles were observed for other clinical variables or the 3 clinical risk scores.

ConclusionsHemodynamic profiles in ED patients with AHF, by non-invasive finger-cuff monitoring of cardiac index and vascular tone, were replicated de novo in an external cohort. Profiles showed significantly different risks of clinically-important adverse patient outcomes.

category: emergency medicine


title: Efficacy of vasopressin, steroid, and epinephrine protocol for in-hospital cardiac arrest resuscitation: A systematic review and meta-analysis of randomized controlled trials with trial sequential analysis

abstract:
AimTo assess the effect of vasopressin, steroid and epinephrine (VSE) combination therapy on return of spontaneous circulation (ROSC) after in-hospital cardiac arrest (IHCA), and test the conclusiveness of evidence using trial sequential analysis (TSA).

MethodsThe systematic search included PubMed, EMBASE, Scopus, and Cochrane Central Register of Controlled Trials. Randomized controlled trials that included adult patients with in-hospital cardiac arrest, with at least one group receiving combined vasopressin, epinephrine and steroid therapy were selected. Data was extracted independently by two reviewers. The main outcome of interest was ROSC. Other outcomes included survival to hospital discharge with good neurological outcomes and survival to 30 and 90 days with good neurological outcomes.

ResultsWe included a total of three randomized controlled trials (n=869 patients). Results showed that Vasopressin, steroid and epinephrine combination therapy increased return of spontaneous circulation (risk ratio, 1.32; 95% CI, 1.18-1.47) as compared to placebo. Trial sequential analysis demonstrated that the existing evidence is conclusive. This was also validated by the alpha-spending adjusted relative risk (1.32 [1.16, 1.49], p<0.0001). Other outcomes could not be meta-analysed due to differences in timeframe in the included studies.

ConclusionsVSE combination therapy administered in cardiopulmonary resuscitation led to improved rates of return of spontaneous circulation. Future trials of vasopressin, steroid and epinephrine combination therapy should evaluate survival to hospital discharge, neurological function and long-term survival.


title: Epidemiological and microbiological investigation of the large increase of vibriosis in northern Europe in 2018

abstract:
Northern European countries and countries bordering the Baltic Sea have witnessed an increase of vibriosis cases during recent heatwaves. Here, we described the epidemiology of vibriosis cases and the genetic diversity of Vibrio isolates from Norway, Sweden, Denmark, Finland, Poland, Estonia, and Latvia in 2018, a year with an exceptionally warm summer. We conducted a retrospective study and analysed demographics, geographic distribution, seasonality, causative species, and severity of non-travel related vibriosis cases in 2018. Data sources included surveillance systems, national laboratory notification databases and/or nationwide surveys to public health microbiology laboratories. Moreover, we performed whole genome sequencing and multilocus sequence typing of available isolates from 2014-2018 to map their genetic diversity.

In 2018, we identified 445 non-travel related vibriosis cases in the study countries, which was considerably higher than the median of 126 cases between 2014-2017 (range: 87-272). The main reported mode of transmission was exposure to seawater. We observed a species-specific geographic disparity of vibriosis cases across the Nordic-Baltic region. Developing severe vibriosis was associated with infections of Vibrio vulnificus (adjOR: 17.2; 95% CI: 3.3-90.5) or Vibrio parahaemolyticus (adjOR: 2.1; 95% CI: 1.0-4.5), being [≥]65 years of age (65-79 years, adjOR: 3.9; 95% CI: 1.7-8.7; 80+ years, adjOR: 15.5; 95% CI: 4.4-54.3) or acquiring infections during summer (adjOR: 5.1; 95% CI: 2.4-10.9). Although phylogenetic analysis revealed diversity between Vibrio isolates, two V. vulnificus clusters (<10 SNPs) were identified. A share sentinel surveillance system for vibriosis during summer months might be highly valuable to monitor this emerging public health issue.

category: epidemiology


title: Failure of Concentric Regulatory Zones to Halt the Spread of COVID-19 in South Brooklyn, New York: October-November 2020

abstract: We relied on reports of confirmed case incidence and test positivity, along with data on the movements of devices with location-tracking software, to evaluate a novel scheme of three concentric regulatory zones introduced by then New York Governor Cuomo to address an outbreak of COVID-19 in South Brooklyn in the fall of 2020. The regulatory scheme imposed differential controls on access to eating places, schools, houses of worship, large gatherings and other businesses within the three zones, but without restrictions on mobility. Within the central red zone, COVID-19 incidence temporarily declined from 131.2 per 100,000 population during the week ending October 3 to 62.5 per 100,000 by the week ending October 31, but then rebounded to 153.6 per 100,000 by the week ending November 28. Within the intermediate orange and peripheral yellow zones combined, incidence steadily rose from 28.8 per 100,000 during the week ending October 3 to 109.9 per 100,000 by the week ending November 28. Data on device visits to pairs of eating establishments straddling the red-orange boundary confirmed compliance with access controls. More general analysis of device movements showed stable patterns of mobility between and beyond zones unaffected by the Governors orders. A geospatial regression model of COVID-19 incidence in relation to device movements across zip code tabulation areas identified a cluster of five high-mobility ZCTAs with estimated reproduction number 1.91 (95% confidence interval, 1.27-2.55). In the highly populous area of South Brooklyn, controls on access alone, without restrictions on mobility, were inadequate to halt an advancing COVID-19 outbreak.


title: Modelling of time-to-events in an ambispective study: illustration with the analysis of ABO blood groups on venous thrombosis recurrence

abstract:
In studies of time-to-events, it is common to collect information about events that occurred before the inclusion in a prospective cohort. In an ambispective design, when the risk factors studied are independent of time, including both pre- and post-inclusion events in the analyses increases the statistical power but may lead to a selection bias. To avoid such a bias, we propose a survival analysis weighted by the inverse of the survival probability at the time of data collection about the events.

This method is applied to the study of the association of ABO blood groups with the risk of venous thromboembolism (VT) recurrence in the MARTHA and MEGA cohorts. The former relying on an ambispective design and the latter on a standard prospective one. In the combined sample totalling 2,752 patients including 993 recurrences, compared with the O1 group, A1 has an increased risk (Hazard Ratio (HR) of 1.18, p=4.2x10-3), homogeneously in MARTHA and in MEGA. The same trend (HR=1.19, p=0.06) was observed for the less frequent A2 group.

In conclusion, this work clarified the association of ABO blood groups with the risk of VT recurrence. Besides, the methodology proposed here to analyse time-independent risk factors of events in an ambispective design has an immediate field of application in the context of genome wide association studies.


title: SeroTracker-ROB: reproducible decision rules for risk of bias assessment of seroprevalence studies

abstract:
BackgroundEvaluating seroprevalence study risk of bias (RoB) is crucial for robust infection surveillance, but can be a time-consuming and subjective process. We aimed to develop decision rules for reproducible RoB assessment and an automated tool to implement these decision rules.

MethodsWe developed the SeroTracker-RoB approach to RoB assessment. To do so, we created objective criteria for items on the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Prevalence Studies and developed decision rules for RoB based on these items. The criteria and decision rules were based on published guidance for assessing RoB for prevalence studies and expert opinion. Decision rules were validated against the SeroTracker database of seroprevalence studies, which included consensus manual RoB judgements from two independent reviewers. We measured efficiency by calculating paired-samples t-test for time to judge RoB using the automated tool versus manually for 25 randomly selected articles from the SeroTracker database, coverage as the proportion of database studies where the decision rules could evaluate RoB, and reliability by calculating intraclass correlations between automated and manual RoB assessments.

ResultsWe established objective criteria for seven of nine JBI items. We developed a set of decision rules with 61 branches. The SeroTracker-RoB tool was significantly faster than manual assessment with a mean time of 0.80 vs. 2.93 minutes per article (p<0.001), classified 100% (n = 2,070) of studies, and had good reliability compared to manual review (intraclass correlation 0.77, 95% confidence interval 0.74 to 0.80). The SeroTracker-RoB Excel Tool embeds this approach in a simple data extraction sheet for use by other researchers.

ConclusionsThe SeroTracker-RoB approach was faster than manual assessment, with complete coverage and good reliability compared to two independent human reviewers. This approach and tool enable rapid, transparent, and reproducible evidence synthesis of infection prevalence studies, and may support public health efforts during future outbreaks and pandemics.

O_TEXTBOXWhat is new?

O_LIWhat is already known: Risk of bias assessments are a core element of evidence synthesis but can be time consuming and subjective. As such, there is a need for validated and transparent tools to automate such assessments, particularly during disease outbreaks and pandemics to inform public health decision making. However, there are currently no automated tools for risk of bias assessment of prevalence studies.
C_LIO_LIWhat is new: We developed a reproducible approach to risk of bias assessment for SARS-CoV-2 seroprevalence studies. The automated approach was five times faster than manual human assessment, successfully categorized all 2,070 studies that it was tested on, and had good agreement with manual review. We built a simple Excel tool so that other researchers can use this automated approach.
C_LIO_LIPotential impact: The SeroTracker-RoB approach and tool enables rapid, transparent, and reproducible risk of bias assessments for SARS-CoV-2 seroprevalence studies, and could be readily adapted for other types of disease prevalence studies. This process may also be applicable to automation of critical appraisal and risk of bias assessment for other types of studies and in other scientific disciplines.
C_LI

C_TEXTBOX


title: SeroTracker-RoB: an approach to automating reproducible risk of bias assessment of seroprevalence studies


title: Very high relative seroprevalence of anti-SARS-CoV-2 antibodies among communities in Bangui, Central African Republic

abstract:
BackgroundLarge-scale population-based seroprevalence studies of SARS-CoV-2 are essential to characterize the cumulative incidence of SARS-CoV-2 infection and to extrapolate the prevalence of presumptive immunity at the population level.

ObjectiveThe objective of our survey was to estimate the cumulative population immunity for COVID-19 and to identify individual characteristics associated with a positive serostatus.

MethodThis was a clustered cross-sectional study conducted from July 12 to August 20, 2021, in households in the city of Bangui, the capital of the Central African Republic. Information regarding demographic characteristics (age, gender, and place of residence), comorbidities (chronic diseases) was collected. A venous blood sample was obtained for each participant to determine the level of total anti-SARS-CoV-2 antibodies using a WANTAI SARS-CoV-2 Ab ELISA kit.

ResultsAll up, 799 participants were surveyed. The average age was 27 years, and 45{middle dot}8% of the respondents were male (sex ratio: 0.8). The overall proportion of respondents with a positive serostatus was 74{middle dot}1%. Participants over 20 years of age were twice as likely to have a positive serostatus, with an OR of 2.{middle dot} {middle dot}2 (95% CI: [1{middle dot}6, 3{middle dot}1]).

InterpretationThe results of this survey revealed a high cumulative level of immunity in Bangui, thus indicating a significant degree of spread of SARS-CoV-2 in the population. The public health implications of this high level of immunity to SARS-CoV-2, particularly on its variants burden, remain to be determined.

FundingThis study was funded by the French Ministry for Europe and Foreign Affairs through the REPAIR COVID-19-Africa project coordinated by the Pasteur International Network association.


title: Managing electromyogram contamination in scalp recordings: an approach identifying reliable beta and gamma EEG features of psychoses or other disorders

abstract:
ObjectiveIn publications on the electroencephalographic (EEG) features of psychoses and other disorders, various methods are utilised to diminish electromyogram (EMG) contamination. The extent of residual EMG contamination using these methods has not been recognised. Here, we seek to emphasise the extent of residual EMG contamination of EEG.

MethodsWe compared scalp electrical recordings after applying different EMG-pruning methods with recordings of EMG-free data from 6 fully-paralysed healthy subjects. We calculated the ratio of the power of pruned, normal scalp electrical recordings in the 6 subjects, to the power of unpruned recordings in the same subjects when paralysed. We produced "contamination graphs" for different pruning methods.

ResultsEMG contamination exceeds EEG signals progressively more as frequencies exceed 25 Hz and with distance from the vertex. In contrast, Laplacian signals are spared in central scalp areas, even to 100 Hz.

ConclusionGiven probable EMG contamination of EEG in psychiatric and other studies, few findings on beta- or gamma-frequency power can be relied upon. Based on the effectiveness of current methods of EEG de-contamination, investigators should be able to re-analyse recorded data, re-evaluate conclusions from high frequency EEG data and be aware of limitations of the methods.

category: psychiatry and clinical psychology


title: Race-Specific, U.S. State-Specific COVID-19 Vaccination Rates Adjusted for Age

abstract: We provide the first age-standardized race/ethnicity-specific, state-specific vaccination rates for the United States, encompassing all states reporting race/ethnicity-specific vaccinations. The data reflect vaccinations through mid-October 2021. We use indirect age standardization to compare racial/ethnic state vaccination rates to national age-specific vaccination patterns. Results show that white and Black state median vaccination rates are, respectively, 89% and 76% of what would be predicted based on age; Hispanic and Native rates are almost identical to what would be predicted; and Asian-American/Pacific Islander rates are 110% of what would be predicted. We also find that racial/ethnic group vaccination rates are associated with state politics, as proxied by 2020 Trump vote share: for each percentage point increase in 2020 Trump vote share, vaccination rates decline by 1.08 percent of what would be predicted based on age. This decline is sharpest for Native American populations, although Native vaccinations are reported for relatively few states.

category: public and global health


title: Child marriage and adverse reproductive outcomes among young Afghan women: implication for policy and practice in Afghanistan

abstract:
BackgroundChild marriage is defined as marriage before the age of 18 years and it has been linked to several adverse health and social outcomes. This study aimed to explore the prevalence and determinants of child marriage and its association with adverse reproductive outcomes among a nationally representative sample of young Afghan women.

MethodsThis was a secondary analysis of the 2015 Afghanistan Demographic and Health Survey (DHS) data. Based on the UN recommendation on child marriage study, only women aged 20-24 years old were included. Descriptive statistics and binary logistic regression were employed to determine the distribution of respondents characteristics and prevalence and determinants of child marriage. Multivariate logistic models examined the association between child marriage and adverse reproductive outcomes accounting for the sociodemographic factors.

ResultsAn estimated 52% of the Afghan women aged 20-24 married at ages less than 18 years. Poor illiterate women were more likely to marry at early ages (<18). There was a significant negative relationship between child marriage and history of rapid repeat childbirth, delivery by skilled personnel, and institutional delivery. In both adjusted and unadjusted models, women married at age [≤]14 were more likely to experience terminated or unintended pregnancy (AOR = 1.89, 95% CI: 1.31-2.75 and AOR = 2.20. 95% CI: 1.24-3.91, respectively), inadequate ANC (AOR = 1.71, 95% CI: 1.01-2.90), unmet need for family planning (AOR = 1.44, 95% CI: 1.05-1.98), fistula (AOR = 2.36, 95% CI: 1.22-4.57); While, for those married at age 15-17 years, only terminated or unintended pregnancy remained significant.

ConclusionThe younger age of marriage was associated with a higher prevalence of adverse reproductive outcomes among Afghan women. Moreover, poverty and illiteracy proved to be important predictors of child marriage in Afghan women. Strict international law enforcement and advocacy are a need in the current situation of Afghanistan to increase young womens education, promote their civil rights, and improve their autonomy and role in decision-making concerning their health.


title: Short-Term Effects of Strengthening Exercises of Lower Limb Rehabilitation Protocol on Pain, Stiffness, Physical Function and Body Mass Index among Knee Osteoarthritis Participants Who Were Overweight or Obese: A Clinical Trial

abstract:
BackgroundOsteoarthritis (OA) of the knee is defined as a progressive disease of the synovial joints and is characterized by wear and tear of cartilage and underlying bone. This study aimed to determine the short-term effects of the lower limb rehabilitation protocol (LLRP) on pain, stiffness, physical function, and body mass index (BMI) among knee OA participants who were overweight or obese.

MethodologySingle blinded randomized controlled trial of one-month duration was conducted at Rehmatul-Lil-Alameen Postgraduate Institute, Lahore, Pakistan. Fifty overweight or obese participants with knee OA were randomly divided into two groups by a computer-generated number. Participants in the Rehabilitation Protocol Group (RPG) were provided with leaflets explaining the strengthening exercises of the LLRP and instruction of daily care (IDC), while the participants in the Control Group (CG) were provided with leaflets explaining IDC only for a duration of four weeks. The primary outcome measures were the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores for pain, stiffness, and physical function. The secondary outcome measures were BMI, exercise adherence, and patients satisfaction by the numeric rating scale ranging from 0 to 10. Paired Samples t-test was used to analyze the differences within groups from baseline to post-test evaluations. The analysis of variance 2 x 2 factor was used to analyze the difference of BMI, knee pain, stiffness, and physical function between the groups.

ResultsParticipants in the RPG and CG reported a statistically significant reduction in knee pain, and stiffness (p [≤] 0.05) within group. The reduction in the scores of knee pain was higher in participants of the RPG than the CG (p = 0.001). Additionally, participants in the RPG reported greater satisfaction (p = 0.001), higher self-reported exercise adherence (p = 0.010) and coordinator-reported exercise adherence (p = 0.046) compared to the participants in the CG.

ConclusionShort-term effects of the LLRP appear to reduce knee pain and stiffness only, but not physical function and BMI.

TRIAL REGISTRATIONName: Iranian Registry of Clinical Trials

Number: IRCT20191221045846N2

Date of registration: June 28, 2020

Registration timing: prospective

category: rehabilitation medicine and physical therapy


title: Meta-topologies define distinct anatomical classes of brain tumors linked to histology and survival

abstract:
BackgroundThe current WHO classification integrates histological and molecular features of brain tumors. The aim of this study was to identify generalizable topological patterns with the potential to add an anatomical dimension to the classification of brain tumors.

MethodsWe applied non-negative matrix factorization as an unsupervised pattern discovery strategy to the fine-grained topographic tumor profiles of 936 patients with primary and secondary brain tumors. From the anatomical features alone, this machine learning algorithm enabled the extraction of latent topological tumor patterns, termed meta-topologies. The optimal parts-based representation was automatically determined in 10,000 split-half iterations. We further characterized each meta-topologys unique histopathologic profile and survival probability, thus linking important biological and clinical information to the underlying anatomical patterns

ResultsIn primary brain tumors, six meta-topologies were extracted, each detailing a transpallial pattern with distinct parenchymal and ventricular compositions. We identified one infratentorial, one allopallial, three neopallial (parieto-occipital, frontal, temporal) and one unisegmental meta-topology. Each meta-topology mapped to distinct histopathologic and molecular profiles. The unisegmental meta-topology showed the strongest anatomical-clinical link demonstrating a survival advantage in histologically identical tumors. Brain metastases separated to an infra- and supratentorial meta-topology with anatomical patterns highlighting their affinity to the cortico-subcortical boundary of arterial watershed areas.

ConclusionsUsing a novel data-driven approach, we identified generalizable topological patterns in both primary and secondary brain tumors Differences in the histopathologic profiles and prognosis of these anatomical tumor classes provide insights into the heterogeneity of tumor biology and might add to personalized clinical decision making.

category: neurology


title: Patient experience with healthcare: Feedback for a Post COVID-19 clinic at a tertiary care center in rural area

abstract:
PurposePost-acute sequelae of SARS-CoV-2 (PASC) is a complex condition with multisystem involvement. We assessed patients perspectives and experience with a PASC clinic established at University of Iowa in June 2020.

MethodsWe conducted a mixed-method survey in June 2021 to ask PASC clinic patients about 1) PASC symptoms and their impact on physical and mental health, and cognition using the PROMIS Global Health and Cognitive Function abilities items, and 2) satisfaction with clinic services and referrals, barriers to care, and recommended support resources.

FindingsNinety-seven patients (97/277, 35% response rate) completed the survey. Most were women (67%, n=65/97), Caucasian (93%, n=90/97) and received outpatient care during acute COVID-19 illness (79%). Fifty percent reported wait time of 1-3 months and 40% traveled >1 hour for appointment. The most common symptoms >3 months from initial infection were fatigue (77%), "brain fog" (73%), exercise intolerance (73%), anxiety (63%), sleep difficulties (56%) and depression (44%). Qualitative analysis of open-ended answers added valuable context to quantitative results. A minority of patients reported significantly reduced functioning ([≥]1.5 SD below mean) of their physical health (22.5%), mental health (15.9%) and cognitive abilities (17.6%). Satisfaction with clinical services was high though participants identified barriers to care including scheduling delays and financial concerns. Respondents suggested potential strategies for optimizing recovery including continuity of care, a co-located multispecialty clinic and being provided with timely information from emerging research.

ConclusionOur study reports high PASC symptom burden, its impact on health and patient experience with healthcare. It is important that primary healthcare professionals listen to patients with empathy and support them during recovery. Healthcare systems and policymakers should focus on accessible, comprehensive, and patient-centered integrated care.

category: health systems and quality improvement


title: Antibody titers before and after booster doses of SARS-CoV-2 mRNA vaccines in healthy adults

abstract: Two-dose messenger RNA vaccines (BNT162b2/Pfizer and mRNA-1273/Moderna) against SARS-CoV-2 were rolled out in the US in December 2020, and provide protection against hospitalization and death from COVID-19 for at least six months. Breakthrough infections have increased with waning immunity and the spread of the B.1.617.2 (Delta) variant in summer 2021, prompting approval of boosters for all adults over 18. We measured anti-receptor binding domain (RBD) IgG and surrogate virus neutralization of the interaction between SARS-CoV-2 spike protein and the human angiotensin-converting enzyme (ACE2) receptor, before and after boosters in N=33 healthy adults. We document large antibody responses 6-10 days after booster, with antibody levels that exceed levels documented after natural infection with COVID-19, after two doses of vaccine, or after both natural infection and vaccination. Surrogate neutralization of B.1.617.2 is high but reduced in comparison with wild-type SARS-CoV-2. These data support the use of boosters to prevent breakthrough infections and suggest that antibody-mediated immunity may last longer than after the second vaccine dose.


title: DNA Methylation scores augment 10-year risk prediction of diabetes

abstract:
Type 2 diabetes mellitus (T2D) is one of the most prevalent diseases in the world and presents a major health and economic burden, a notable proportion of which could be alleviated with improved early prediction and intervention. While standard risk factors including age, obesity, and hypertension have shown good predictive performance, we show that the use of CpG DNA methylation information leads to a significant improvement in the prediction of 10-year T2D incidence risk.

Whilst previous studies have been largely constrained by linear assumptions and the use of CpGs one-at-the-time, we have adopted a more flexible approach based on a range of linear and tree-ensemble models for classification and time-to-event prediction. Using the Generation Scotland cohort (n=9,537) our best performing model (Area Under the Curve (AUC)=0.880, Precision Recall AUC (PRAUC)=0.539, McFaddens R2=0.316) used a LASSO Cox proportional-hazards predictor and showed notable improvement in onset prediction, above and beyond standard risk factors (AUC=0.860, PRAUC=0.444 R2=0.261). Replication of the main finding was observed in an external test dataset (the German-based KORA study, p=3.7x10-4). Tree-ensemble methods provided comparable performance and future improvements to these models are discussed.

Finally, we introduce MethylPipeR, an R package with accompanying user interface, for systematic and reproducible development of complex trait and incident disease predictors. While MethylPipeR was applied to incident T2D prediction with DNA methylation in our experiments, the package is designed for generalised development of predictive models and is applicable to a wide range of omics data and target traits.

category: genetic and genomic medicine


title: ROLE OF BODY MASS AND PHYSICAL ACTIVITY IN AUTONOMIC FUNCTION MODULATION ON POST-COVID-19 CONDITION: AN OBSERVATIONAL SUBANALYSIS OF FIT-COVID STUDY

abstract:
The harmful effects of coronavirus disease 2019 (COVID-19) can reach the autonomic nervous system (ANS) and endothelial function. Therefore, the detrimental multiorgan effects of COVID-19 could be induced by deregulations in ANS that may persist after the acute SARS-CoV-2 infection. Additionally, investigating the differences in ANS response in overweight/obese, and physically inactive participants who had COVID-19 compared to those who did not have the disease is necessary. The aim of the study was to analyze the autonomic function of young adults after mild-to-moderate infection with COVID-19 and to assess whether body mass index (BMI) and levels of physical activity modulates autonomic function in participants with and without COVID-19. Patients previously infected with COVID-19 and healthy controls were recruited for this cross-sectional observational study. A general anamnesis was taken and BMI and physical activity levels were assessed. The ANS was evaluated through heart rate variability. A total of 57 subjects were evaluated. Sympathetic nervous system activity in post-COVID-19 group was increased (stress index; p=0.0273). They also presented lower values of parasympathetic activity (p<0.05). Overweight/obese subjects in the post-COVID-19 group presented significantly lower parasympathetic activity and reduced global variability compared to non-obese in control group (p<0.05). Physically inactive subjects in post-COVID-19 group presented significantly higher sympathetic activity than active subjects in control group. Parasympathetic activity was significantly increased in physically active subjects in control group compared to the physically inactive post-COVID-19 group (p<0.05). COVID-19 promotes changes in the ANS of young adults, and these changes are modulated by Overweight/obesity and physical activity levels.

Key Points- Our main finding is that even in mild and moderate infections, young adults who had COVID-19 had greater sympathetic activity, less parasympathetic activity, and global variability when compared to uninfected individuals.
- In participants who were overweight and obese and/or physically inactive, cardiac autonomic modulation showed worse indices.
- Our study provides new insights regarding the role of body mass index and physical activity status on post-COVID-19 infection autonomic deregulation that may contribute to the understand of pathophysiology and treatment of of post-acute sequelae SARS-CoV-2 infection.

category: cardiovascular medicine


title: Patterns of brain neurodegeneration in early-stage relapsing-remitting multiple sclerosis

abstract:
Recurrent neuroinflammation in relapsing-remitting MS (RRMS) is thought to lead to neurodegeneration, resulting in progressive disability. Repeated magnetic resonance imaging (MRI) of the brain provides non-invasive measures of atrophy over time, a key marker of neurodegeneration. This study investigates regional neurodegeneration of the brain in early-stage RRMS using volumetry and voxel-based morphometry (VBM).

RRMS patients (N=354) underwent 3T structural MRI at diagnosis and 1-year follow-up, as part of the Scottish multicentre  FutureMS study. MRI data were processed using FreeSurfer to derive volumetrics, and FSL for VBM (grey matter (GM) only), to establish patterns of change in GM and normal-appearing white matter (NAWM) over time throughout the cerebrum, cerebellum and brainstem.

Volumetric analyses showed a decrease over time (q<0.05) in bilateral cortical GM and NAWM, multiple subcortical structures, cerebellar GM and the brainstem. Additionally, NAWM and GM volume decreased respectively in the following cortical regions, frontal: 14 out of 28 regions and 17/28; temporal: 18/18 and 15/18; parietal: 14/14 and 11/14; occipital: 7/8 and 8/8. Left GM and NAWM asymmetry was observed in the frontal lobe. GM VBM analysis showed three major clusters of decrease over time: 1) temporal lobe and subcortical areas, 2) cerebellum, 3) anterior cingulum and supplementary motor cortex; and four smaller clusters within the occipital lobe.

Widespread neurodegeneration was observed in early-stage RRMS; particularly in the brainstem, cerebellar GM, and subcortical and occipital-temporal regions. Volumetric and VBM results emphasise different as well as overlapping patterns of longitudinal change, and provide potential response markers for existing therapies and trials of neuroprotective agents.

category: radiology and imaging


title: Patterns of brain degeneration in early-stage relapsing-remitting multiple sclerosis


title: Clinical Outcome of Neurological patients with COVID-19: the impact of Healthcare organization improvement between waves.

abstract:
ObjectiveThe aim of this study is to evaluate the differences of clinical presentations and the impact of healthcare organization on outcomes of neurological COVID-19 patients admitted during the first and second pandemic waves.

MethodsIn this single center cohort study, we included all patients with SARS-CoV-2 infection admitted to a Neuro-COVID Unit. Demographic, clinical and laboratory data were compared between patients admitted during the first and second waves of COVID-19 pandemic.

Results223 patients were included, of whom 112 and 111 hospitalized during the first and second pandemic waves, respectively. Patients admitted during the second wave were younger and exhibited pulmonary COVID-19 severity, resulting in less oxygen support (n=41, 36.9% vs n=79, 70.5%, p<0.001) and lower mortality rates (14.4% vs 31.3%, p=0.004). The different healthcare strategies and early steroid treatment emerged as significant predictors of mortality independently from age, premorbid conditions and COVID-19 severity in cox regression analyses.

ConclusionsDifferences in healthcare strategies during the second phase of COVID-19 pandemic probably explain the differences in clinical outcomes independently of disease severity, underlying the importance of standardized early management of neurological patients with SARS-CoV-2 infection.


title: KBG Syndrome: Prospective Videoconferencing and Use of AI-driven Facial Phenotyping in 25 New Patients

abstract: Genetic variants in the gene Ankyrin Repeat Domain 11 (ANKRD11) and deletions in 16q24.3 are known to cause KBG syndrome, a rare syndrome associated with craniofacial, intellectual, and neurobehavioral anomalies. We report 25 unpublished individuals from 22 families, all with molecularly confirmed diagnoses of KBG syndrome. Twenty-one individuals have de novo variants, three have inherited variants, and one is inherited from a parent exhibiting low-level mosaicism. Of the variants, 20 are truncating (frameshift or nonsense), and the remaining five individuals have missense variants (with one of these in three family members). One of the missense variants has been found in at least two other affected individuals. We created a novel protocol for collection and reporting of data, including prospectively interviewing these individuals and their families throughout eight countries via videoconferencing by a single clinician. Participants medical records, including imaging, were reviewed, and data was uploaded to the Human Disease Gene website using Human Phenotype Ontology (HPO) terms. Photos of the participants were submitted to GestaltMatcher and Face2Gene (FDNA Inc, USA) for facial analysis, and we found similar facial phenotypes among the participants. Within our cohort, common traits included short stature, macrodontia, anteverted nares, wide nasal bridge, wide nasal base, thick eyebrows, synophrys and hypertelorism. Seventy-two percent of participants had gastrointestinal complaints and 80% had hearing loss. Three participants were started on growth hormone with positive results. Behavioral issues and global developmental delays were found in most participants. Neurologic abnormalities including seizures and/or EEG abnormalities were also very common (44%), suggesting that early detection and seizure prophylaxis could be an important point of intervention. Twenty-four percent were diagnosed with attention deficit hyperactivity disorder (ADHD) and 28% were diagnosed with autism spectrum disorder (ASD). Additionally, we have identified minimally reported symptoms, including recurrent sinus infections (16%) and previously unreported migraines (20%). Based on the videoconferencing and these data, we provide a set of recommendations regarding diagnostic and treatment approaches for KBG syndrome.


title: Efficacy and safety of a novel antiviral preparation in ICU-admitted patients with COVID-19: a phase III randomized controlled trial

abstract:
IntroductionDespite an increasing number of studies, there is as yet no efficient antiviral treatment developed for the disease. In this clinical trial, we examined the efficacy of a novel herbal antiviral preparation comprising Zataria multiflora Boiss, Glycyrrhiza glabra, Cinnamomum Vermont, Allium sativuml, and Syzygium aromaticum in critically ill patients with COVID-19 patients.

MethodsA total number of 120 ICU-admitted patients requiring pulmonary support with a diagnosis of COVID-19 pneumonia were recruited to the trial. Participants were equally randomized to receive either the novel antiviral preparation sublingually, for up to two consecutive weeks or till discharge, or normal saline as the matching placebo. Clinical and laboratory parameters as well as survival rates were compared between the two groups at the study end.

ResultsThe cumulative incidence of death throughout the study period was 8.33% in the medication group and 60% in the placebo group (risk ratio: 0.14; 95% confidence interval [CI], 0.05 to 0.32; P<0.001). Survival rates were significantly higher in the treatment group. Additionally, on day 7, several laboratory factors including white blood cells (WBCs) count, C-reactive protein (CRP), and SpO2 were improved in patients treated with the novel antiviral preparation compared with the placebo group.

ConclusionThe novel antiviral preparation tested in this trial significantly improved the survival rate and reduced mortality in critically ill patients with COVID-19. Thus, this preparation might be suggested as a potentially promising COVID-19 treatment.

Funded by Shimi Teb Salamat Co., Shiraz, Iran, and registered on the Iranian registry of clinical trials (registration No. IRCT20200509047373N2).

category: intensive care and critical care medicine


title: Responsivity of the striatal dopamine system to methylphenidate - a within-subject I-123-β-CIT-SPECT study in children and adolescents with Attention-Deficit/Hyperactivity Disorder

abstract:
BackgroundMethylphenidate (MPH) is the first-line pharmacological treatment of attention-deficit/hyperactivity disorder (ADHD). MPH binds to the dopamine (DA) transporter (DAT), which has high density in the striatum. Assessments of the striatal dopamine transporter by single positron emission computed tomography (SPECT) in childhood and adolescent patients are rare but can provide insight in how effects of MPH affect DAT availability. The aim of our within-subject study was to investigate the effect of MPH on DAT availability and how responsivity to MPH in DAT availability is linked to clinical symptoms and cognitive functioning.

MethodsThirteen adolescent male patients (9-16 years) with diagnosis of ADHD according to DSM-IV and long-term stimulant medication (for at least 6 months) with MPH were assessed twice within 7 days using SPECT after application of I-123-{beta}-CIT to examine DAT binding potential (DAT BP). SPECT measures took place in on and off-MPH status balanced for order across participants. A virtual-reality continuous-performance test was performed at each time point. Further clinical symptoms were assessed for baseline off-MPH.

ResultsOn-MPH status was associated with a highly significant decrease (-27,6%) of striatal DAT BP as compared to off-MPH (t=4.93, p<0.001). More pronounced decrease in striatal DAT BP was associated with higher off-MPH attentional and externalizing symptom ratings (Pearson r=0.68, p=0.01). Striatal DAT BP off-MPH, but not on-MPH, was associated with higher symptom ratings off-MPH (Pearson r=0.56, p=0.04). In further exploratory analysis in left vs. right striatal sub-regions, stronger decrease in DAT BP in the right caudate nucleus was weakly associated with improved performance in the continuous-performance test (Pearson r= - 0.54, p=0.07).

ConclusionOur findings corroborate previous reports from mainly adult samples that MPH reduces striatal DAT BP availability and suggest higher off-MPH DAT BP, likely reflecting low baseline DA levels, as a marker of symptom severity. More speculatively, regional specific responsivity of DAT BP to MPH may reflect treatment response with respect to cognitive functioning. However, implications from this small patient sample should be treated with caution and warrant replication.


title: Gender dysphoria and sexual euphoria - A Bayesian perspective on the influence of gender-affirming hormone therapy on sexual arousal

abstract: While the concept of sexual orientation is more clearly defined in cisgender, this is less so in transgender individuals. Both experienced gender and sex hormones have a relation to sexual preferences, arousal in response to erotic stimuli, and thus sexual orientation. In transgender individuals sexual orientation occasionally changes before or during transition, which may involve gender-affirming hormone therapy. Using functional magnetic resonance imaging, we investigated whether the neuronal and behavioral patterns of sexual arousal in transgender individuals moved from the given (before) to their chosen gender after 4.5 months of hormone therapy. To this aim, trans women and men as well as age-matched cisgender controls rated visual stimuli showing heterosexual, lesbian or gay intercourse for subjective sexual arousal. Utilizing a Bayesian framework allowed us to incorporate behavioral findings in cisgender individuals of different sexual orientations. The hypothesized changes in response patterns could indeed be observed in the behavioral responses to the single but not the differentiation between stimulus categories with the strongest results for trans men and lesbian scenes. Activation of the ventral striatum supported our hypothesis only for lesbian scenes in trans women. This prominent role of lesbian stimuli might be explained by their differential responses in cis women and men. We show that correlates of sexual arousal in transgender individuals might change in direction of the chosen gender. Future investigations longer into transition might resolve the discrepancy on behavioral and neuronal levels.


title: COVID-19 vaccination and menstrual cycle changes: A United Kingdom (UK) retrospective case-control study

abstract:
BackgroundThere has been increasing public concern that COVID-19 vaccines cause menstrual cycle disturbances, yet there is currently limited data to evaluate the impact of vaccination on menstrual health. Our objectives were (1) to evaluate the prevalence of menstrual changes following vaccination against COVID-19, (2) to test potential risk factors for any such changes, and (3) to identify patterns of symptoms in participants written accounts.

MethodsWe performed a secondary analysis of a retrospective online survey titled "The Covid-19 Pandemic and Womens Reproductive Health", conducted in March 2021 in the UK before widespread media attention regarding potential impacts of SARS-CoV-2 vaccination on menstruation. Participants were recruited via a Facebook ad campaign in the UK and eligibility criteria for survey completion were age greater than 18 years, having ever menstruated and currently living in the UK. In total, 26,710 people gave consent and completed the survey. For this analysis we selected 4,989 participants who were pre-menopausal and vaccinated. These participants were aged 28 to 43, predominantly from England (81%), of white background (95%) and not using hormonal contraception (58%).

FindingsAmong pre-menopausal vaccinated individuals (n=4,989), 80% did not report any menstrual cycle changes up to 4 months after their first COVID-19 vaccine injection. Current use of combined oral contraceptives was associated with lower odds of reporting any changes by 48% (OR = 0.52, 95CI = [0.34 to 0.78], P<0.001). Odds of reporting any menstrual changes were increased by 44% for current smokers (OR = 1.44, 95CI = [1.07 to 1.94], P<0.01) and by more than 50% for individuals with a positive COVID status [Long Covid (OR = 1.61, 95CI = [1.28 to 2.02], P<0.001), acute COVID (OR = 1.54, 95CI = [1.27 to 1.86], P<0.001)]. The effects remain after adjusting for self-reported magnitude of menstrual cycle changes over the year preceding the survey. Written accounts report diverse symptoms; the most common words include "cramps", "late", "early", "spotting", "heavy" and "irregular", with a low level of clustering among them.

ConclusionsFollowing vaccination for COVID-19, menstrual disturbance occurred in 20% of individuals in a UK sample. Out of 33 variables investigated, smoking and a previous history of SARS-CoV-2 infection were found to be risk factors while using oestradiol-containing contraceptives was found to be a protective factor. Diverse experiences were reported, from menstrual bleeding cessation to heavy menstrual bleeding.


title: Space-time Classification Index for Assessing COVID-19 Hotspots

abstract:
ObjectivesTo develop new methods to address problems associated with use of traditional measures of disease surveillance, including prevalence and positivity rates.

MethodsWe use data from the public New York Times Github repository to develop a space-time classification index of COVID-19 hotspots. The Local Indicator of Spatial Association (LISA) statistic is applied to identify daily clusters of COVID-19 cases, from July 4th to July 19th.

ResultsThe classification index is a spatial and temporal assessment tool that seeks to incorporate temporal trends of the clusters that are "high-high" and "high-low". Two classifications support the index: severity and temporal duration. We define severity as the number of times a county is statistically significant and temporal duration captures the number of consecutive days a county is a hotspot.

ConclusionsThe space-time classification index provides a statistically robust measure of the spatial patterns of COVID-19 hotspots. Spatial information is not captured through measures like the positivity rate, which merely divides the number of cases by tests conducted. The index proposed in this paper can guide intervention efforts by classifying counties with six-levels of importance.


title: Pausing methotrexate improves immunogenicity of COVID-19 vaccination in patients with rheumatic diseases

abstract:
ObjectiveTo study the effect of methotrexate (MTX) and its discontinuation on the humoral immune response after COVID-19 vaccination in patients with autoimmune rheumatic diseases (AIRD).

MethodsNeutralising SARS-CoV-2 antibodies were measured after second vaccination in 64 rheumatic patients on methotrexate therapy, 31 of whom temporarily paused medication without a fixed regimen. The control group consisted of 21 AIRD patients without immunosuppressive medication.

ResultsMTX patients showed a significantly lower median antibody response compared to AIRD patients without immunosuppressive therapy (p< 0.001). Young age (<60 years) and MTX-hold after vaccination were found to be the main factors influencing antibody response after vaccination, while BMI or MTX dose demonstrated no effect. For patients taking MTX, age correlated negatively with immune response (r=-0.49; p<0.001) and all patients with antibody levels (14 %) below the cut-off were older than 60 years. Patients who held MTX during at least one vaccination showed significantly higher median neutralising antibody levels after second vaccination, compared to patients who continued MTX therapy during both vaccinations (68.82 %, 92.73 %, p=<0.001). This effect was particularly pronounced in patients older than 60 years (p=0.0016). The impact of the time period after vaccination was greater than of the time before vaccination with the critical cut-off being 10 days.

ConclusionMTX reduces the immunogenicity of SARS-CoV-2 vaccination in an age-dependent manner. Our data further suggest that holding MTX for at least 10 days after vaccination significantly improves the antibody response in patients over 60 years of age.

category: rheumatology


title: Pausing methotrexate improves immunogenicity of COVID-19 vaccination in elderly patients with rheumatic diseases


title: Intracranial approach for sub-second monitoring of neurotransmitters during DBS electrode implantation does not increase infection rate

abstract:
IntroductionCurrently, sub-second monitoring of neurotransmitter release in humans can only be performed during standard of care invasive procedures like DBS electrode implantation. The procedure requires acute insertion of a research probe and additional time in surgery, which may increase infection risk. We sought to determine the impact of our research procedure, particularly the extended time in surgery, on infection risk.

MethodsWe screened 607 DBS electrode implantation procedures performed at Wake Forest Baptist Medical Center between January 2011 through October 2020 using International Classification of Diseases (ICD) codes for infection. During this period, 116 cases included an IRB approved 30-minute research protocol, during the DBS electrode implantation surgery, to monitor sub-second neurotransmitter release. We used Fishers Exact test (FET) to determine if there was a significant change in the infection rate following DBS electrode implantation procedures that included, versus those that did not include, the neurotransmitter monitoring research protocol.

ResultsWithin 30-days following DBS electrode implantation, infection was observed in 7 (1.43%) out of 491 procedures that did not include the research procedure and 2 (1.72%) of the 116 procedures that did include the research procedure. Total infection rates (i.e., not constrained by 30-day time window) for all non-research cases was 28/491 (5.70%) and only 4/116 (3.45%) for research inclusive cases. Notably, all types of infection observed were typical of those expected for DBS electrode implantation.

ConclusionTotal infection rates are not statistically different in patients who performed the research procedure (3.45% vs. 5.70%; p = 0.4872, FET) and not statistically different across research and non-research groups within 30-days following the research procedure (1.72% vs. 1.43%; p = 0.684, FET). Our results demonstrate that the research procedures used for sub-second monitoring of neurotransmitter release in humans can be performed without increasing the rate of infection.

category: surgery


title: Is Footedness Driving Right Lower Extremity Arthroplasty Becoming Commoner Than Left Lower Extremity Arthroplasty?

abstract: The question arises whether footedness transforms into asymmetrical incidence of wear and tear within lower extremity joints. After obtaining institutional review board approval for exempt research, the author manually counted the number of patients who underwent right or left or bilateral, hip or knee, primary or revision arthroplasty over a five-year period (2016-2020) at a university-affiliated hospital in the United States. Overall, right lower extremity arthroplasty was significantly commoner than left lower extremity arthroplasty (P=0.002). Individually, only right primary hip arthroplasty (P=0.033) and right revision knee arthroplasty (P=0.041) were significantly commoner procedures than their left counterparts. These results should set up the stage for future investigations into footedness retrospectively and prospectively to rule out if commoner right footedness in itself is driving this asymmetrical incidence of lower extremity arthroplasty or whether automatic transmission vehicular driving is independently contributing to this asymmetrical incidence.

category: occupational and environmental health


title: A comparison of health care use after severe COVID-19, respiratory syncytial virus, and influenza in children

abstract:
BackgroundWe aimed to explore whether children in hospital care with COVID-19 have increased post-discharge health care use when compared to children in hospital care with 1) RSV infection, and 2) other RTIs.

MethodsIn 34,214 children aged 1 month to 5 years who were registered with one or more hospital contacts with COVID-19 (N=128), RSV infection (N=4,009) or other RTIs (upper- and lower unspecified RTI as well as influenza) (N=34,457) (January 1st, 2017 to September 20th, 2021), we used a pre-post study design to investigate the individual all-cause primary and specialist health care use from 12 weeks prior to hospital admission, to 12 weeks after hospital discharge, stratified on infants (1-12 months) and toddlers (1-5 years).

FindingsWe found a slight increase in primary health care use in the first four weeks after discharge for children aged 1-12 months with COVID-19 when compared to children with RSV infection (0.064 percentage points, 95% CI 0.02-0.126, 0.52% relative increase). For children aged 1-5 years, COVID-19 discharge was associated with a 1-4 weeks increase in primary health care use when compared to children with RSV infection (0.068 percentage points, 95% CI 0.022-0.144, 0.53% relative increase) and other RTI (0.046 percentage points, 95% CI 0.002-0.091, 0.45% relative increase). For children aged 1-12 months in hospital care with COVID-19, we found a similar-magnitude-increase in post-discharge inpatient specialist care use, which lasted for 12 weeks.

InterpretationOur findings imply no severe impact on health care use after hospitalization with COVID-19 compared to hospitalization with RSV infection or other RTIs. The etiological mechanisms for potentially worse post-hospitalization complaints or health-seeking behavior for COVID-19 than for other RTIs in children should be further explored.

category: health economics


title: Identifying high-risk comorbidities of short and long-term opioid prescription use

abstract:
BackgroundElectronic health records (EHR) are useful tools for understanding complex medical phenotypes, but they have been underutilized for opioid use disorders (OUD). Patterns of prescription opioid use might provide an objective measure of OUD risk.

MethodsWe extracted data for over 2.6 million patients across three health registries (Vanderbilt University Medical Center, Mass General Brigham, Geisinger) between 2005 and 2018. We defined three groups based on levels of opioid exposure: No Prescription, Minimal Exposure (2 prescriptions within 90 days at least once, but never 3 prescriptions <90 days apart), and Chronic Exposure ([≥]10 opioid prescriptions in a year), and compared them to the full registries and to patients with OUD diagnostic codes. We extracted demographic and clinical characteristics known to co-occur with OUD, including psychiatric and substance use disorders, pain-related diagnoses, HIV, and hepatitis C.

ResultsThe prevalence of substance (alcohol, tobacco, cannabis) use disorders was higher in patients with OUD and Chronic Exposure than those with No Prescription or Minimal Exposure. Patients in the OUD and Chronic Exposure groups had more psychiatric (anxiety, depression, schizophrenia, bipolar disorder) and medical comorbidities (pain, hepatitis C, HIV) than those in the Minimal Exposure group. Notably, patients in the Minimal Exposure group had different comorbidity profiles (higher rates of substance use and psychiatric disorders, more pain conditions) than those in the Unscreened or No Prescription groups, highlighting the value of including opioid exposure in studies of OUD.

ConclusionsLong-term opioid prescription use may serve as an additional tool to characterize OUD risk.

category: addiction medicine


title: Intersecting single-cell transcriptomics and genome-wide association studies identifies crucial cell populations and candidate genes for atherosclerosis.

abstract:
BackgroundGenome-wide association studies have discovered hundreds of common genetic variants for atherosclerotic disease and cardiovascular risk factors. The translation of susceptibility loci into biological mechanisms and targets for drug discovery remains challenging. Intersecting genetic and gene expression data has led to the identification of candidate genes. However, previously studied tissues are often non-diseased and heterogeneous in cell composition, hindering accurate candidate prioritization. Therefore, we analyzed single-cell transcriptomics from atherosclerotic plaques for cell-type-specific expression to identify atherosclerosis-associated candidate gene-cell pairs.

Methods and ResultsTo identify disease-associated genes, we applied gene-based analyses using GWAS summary statistics from 46 atherosclerotic and cardiovascular disease, risk factors, and other traits. We then intersected these candidates with scRNA-seq data to identify genes specific for individual cell (sub)populations in atherosclerotic plaques. The coronary artery disease loci demonstrated a prominent signal in plaque smooth muscle cells (SKI, KANK2, SORT1) p-adj. = 0.0012, and endothelial cells (SLC44A1, ATP2B1) p-adj. = 0.0011. Further sub clustering revealed genes in risk loci for coronary calcification specifically enriched in a synthetic smooth muscle cell population. Finally, we used liver-derived scRNA-seq data and showed hepatocyte-specific enrichment of genes involved in serum lipid levels.

ConclusionWe discovered novel gene-cell pairs, on top of known pairs, pointing to new biological mechanisms of atherosclerotic disease. We highlight that loci associated with coronary artery disease reveal prominent association levels in mainly plaque smooth muscle and endothelial cell populations. We present an intuitive single-cell transcriptomics-driven workflow rooted in human large-scale genetic studies to identify putative candidate genes and affected cells associated with cardiovascular traits. Collectively, our workflow allows for the identification of cell-specific targets relevant for atherosclerosis and can be universally applied to other complex genetic diseases and traits.

Translational perspectiveGWAS identified a large number of genomic loci associated with atherosclerotic disease. The translation of these results into drug development and faster diagnostics remains challenging. With our approach, we cross-reference the GWAS findings for atherosclerotic disease with scRNA-seq data of disease-relevant tissue and bring the GWAS findings closer to the functional and mechanistic studies.

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title: Social Class, Race/Ethnicity, and COVID-19 Mortality Among Working Age Adults in the United States

abstract:
ImportanceSubstantial racial/ethnic disparities in COVID-19 mortality have been documented. Social class is a likely explanation of mortality disparities across and within racial/ethnic groups. This is the first U.S. study of social class and COVID-19 mortality in working age adults.

ObjectivesTo determine the joint effects of social class, race/ethnicity, and gender on the burden of COVID-19 mortality. A secondary objective was to determine whether differences in opportunities for remote work were correlated with COVID-19 death rates for sociodemographic groups.

DesignAnnual mortality study which used a special government tabulation of 2020 COVID-19 related deaths stratified by decedents social class (educational attainment) and race/ethnicity.

SettingUnited States in 2020.

ParticipantsCOVID-19 decedents aged 25 to 64 years old (n=69,001).

ExposuresSocial class (working class, some college, college graduate), race/ethnicity (Hispanic, Black, Asian, Indigenous, multiracial, and non-Hispanic white), and gender (women, men). Detailed census data on occupations held by adults in 2020 in each of the 36 sociodemographic groups studied were used to quantify the possibility of remote work for each group.

Main Outcomes and MeasuresAge-adjusted COVID-19 death rates for 36 sociodemographic groups defined by social class, race/ethnicity, and gender. Disparities were quantified by relative risks and 95% confidence intervals. College graduates were the (low risk) referent group for all relative risk calculations.

ResultsA higher proportion of Hispanics, Blacks, and Indigenous people were working class in 2020. COVID-19 mortality was five times higher in the working class vs. college graduates (72.2 vs. 14.6 deaths per 100,000, RR=4.94, 95% CI 4.82-5.05). The joint detriments of lower socioeconomic position, Hispanic ethnicity, and male gender resulted in a COVID-19 death rate which was over 27 times higher (178.0 vs. 6.5 deaths/100,000, RR=27.4, 95%CI 25.9-28.9) for working class Hispanic men vs. college graduate white women. In regression modeling, percent employed in never remote jobs explained 72% of the variance in COVID-19 death rates.

Conclusions and RelevanceSARS-CoV-2 infection control efforts should prioritize the working class (i.e. those with no college education), particularly those employed in "never remote" jobs with inflexible and unsafe working conditions (i.e. blue collar, service, and retail sales workers).

KEY POINTSO_ST_ABSQuestionC_ST_ABSDid COVID-19 mortality rates among non-elderly adults vary significantly by social class, race/ethnicity, and gender in 2020?

FindingsAmong 69,001 COVID-19 decedents, age-adjusted COVID-19 deaths rates were 5 times higher in working class vs. college graduate adults 25-64 years old. Working class Hispanic, Black, and Indigenous men suffered the highest burden of COVID-19 mortality, while college graduate white women experienced the lowest death rate.

MeaningCOVID-19 mitigation efforts should prioritize the working class (i.e. those with no college education), particularly blue collar, service, and retail sales workers.


title: The Population-based Microbiome Research Core: a longitudinal infrastructure for assessment of household microbiome and human health research

abstract:
PurposeThe Population-based Microbiome Research Core (PMRC) is an expandable and longitudinal research core infrastructure to support the study of the human microbiome within the context of environmental, sociodemographic, and health factors. Broadly, the purpose of this infrastructure is to provide new insights into how human-environment interactions affect health through its influence on the composition and function of the microbiome. The PMRC was established as an ancillary study of the Survey of Health of Wisconsin (SHOW) and serves as a platform for ancillary studies, ongoing follow-up of the cohort, and expansion of the microbiome biorepository.

ParticipantsThe study recruited adult participants who had previously participated in SHOWs Wisconsin Microbiome Study (WMS). Over 59% of the eligible WMS participants agreed to provide a repeat stool sample and household samples including dust, high touch surface swabs and outside soil.

Findings to datePMRC includes 323 individuals; the majority (96%) were over the age of eighteen, white (84%), urban (75%), and lived in their homes for over one year (92%). Overall, 97% of participants completed the questionnaire and household high-touch surface swab collection, and 93% and 94% completed dust and stool collection, respectively. Soil samples were collected for 86% of all participant homes.

Future plansSample protocols developed for the PMRC offer a unique framework for future household-based microbiome research. This infrastructure can support the generation of new knowledge on the role of the home environment in relation to the human microbiome and identify new opportunities for intervention research.


title: Behaviour, booster vaccines and waning vaccine protection: modelling the medium-term dynamics of SARS-CoV-2 transmission in England

abstract: England has experienced a heavy burden of COVID-19, with high infection levels observed throughout the summer months of 2021. Alongside the emergence of evidence suggesting that COVID-19 vaccine protection wanes over time, booster vaccinations began for individuals aged 50 and above in September 2021. Using a model fitted to 18 months of epidemiological data, we project potential dynamics of SARS-CoV-2 transmission in England to September 2022. We consider key uncertainties including behavioural change, waning vaccine protection, strategies for vaccination, and the reintroduction of public health and social measures. We project the current wave of transmission will peak in Autumn 2021, with low levels of transmission in early 2022. The extent to which SARS-CoV-2 transmission resurges in 2022 depends largely on assumptions around waning vaccine protection and booster vaccinations. Widespread booster vaccinations or the reimposition of mild public health and social measures such as work-from-home policies could largely mitigate the wave of COVID-19 transmission projected to occur in England in Spring/Summer 2022.


title: Distinct Adaptive Immunophenotype in duodenal mucosa but not peripheral blood of patients with functional dyspepsia

abstract:
Background and aimsFunctional dyspepsia is characterised by chronic symptoms of post- prandial distress or epigastric pain not associated with defined structural pathology. Increased peripheral gut-homing T cell have been previously identified in patients. To date, it is unknown if these T cells were antigen-experienced, or if a specific immunophenotype was associated with FD. This study aimed to characterise immune populations in the blood and duodenal mucosa of FD patients that may be implicated in disease pathophysiology.

MethodsWe identified duodenal T cell populations from 23 controls and 49 Rome III FD patients by flow cytometry. We also analysed duodenal eosinophils and T cell populations in peripheral blood from 37 controls and 49 patients and investigated if subtyping patients based on reported symptoms or co-morbidity identified specific immunophenoptypes.

ResultsIn addition to increased duodenal mucosal CD4+ effector cells, FD patients demonstrated a shift in the T helper cell balance compared to controls. Patients had increased duodenal mucosal Th2 populations in the effector (13.03{+/-}16.11, 19.84{+/-}15.51, p=0.038), central memory (23.75{+/-}18.97, 37.52{+/-}17.51, p=0.007) and effector memory (9.80{+/-}10.50 vs 20.53{+/-}14.15, p=0.001) populations. Th17 populations were also increased in the effector (31.74{+/-}24.73 vs 45.57{+/-}23.75, p=0.03) and effector memory (11.95{+/-}8.42 vs 18.44{+/-}15.63, p=0.027) subsets.

ConclusionOur findings confirm the involvement of adaptive responses in the aetiopathogenesis of FD, specifically a Th2 and Th17 signature in the duodenal mucosa. The presence of effector and memory cells suggest that the microinflammation in FD is antigen driven.

category: gastroenterology


title: Sustained negative mental health outcomes among healthcare workers over the first year of the COVID-19 pandemic: a prospective cohort study

abstract:
ObjectiveTo characterize the evolution of healthcare workers mental health status over the 1-year period following the initial COVID-19 pandemic outbreak and to examine baseline characteristics associated with resolution or persistence of mental health problems over time.

MethodsWe conducted an 8-month follow-up cohort study. Eligible participants were healthcare workers working in Spain. Baseline data were collected during the initial pandemic outbreak. Survey-based self-reported measures included COVID-19-related exposures, sociodemographic characteristics, and three mental health outcomes (psychological distress, depression symptoms, and posttraumatic stress disorder symptoms). We examined three longitudinal trajectories in mental health outcomes between baseline and follow-up assessments (namely asymptomatic/stable, recovering, and persistently symptomatic/worsening).

ResultsWe recruited 1,807 participants. Between baseline and follow-up assessments, the proportion of respondents screening positive for psychological distress and probable depression decreased, respectively, from 74% to 56% and from 28% to 21%. Two-thirds remained asymptomatic/stable in terms of depression symptoms and 56% remained symptomatic or worsened over time in terms of psychological distress.

ConclusionsPoor mental health outcomes among healthcare workers persisted over time. Occupational programs and mental health strategies should be put in place.


title: Predictors of Treatment Response, Remission, Relapse and Rehospitalization in First-Episode Psychosis Patients in Medellin, Colombia

abstract:
BackgroundMost studies with first episode psychosis patients have been conducted in high-income countries. On the other hand, very few first episode studies have been conducted in Latin-America. Therefore, the goal of our study is to determine predictors of treatment response, remission, relapse and rehospitalization in a first episode psychosis population from Medellin, Colombia.

MethodsData was obtained from electronic health records from first episode patients with a diagnosis of schizophrenia-spectrum disorder diagnoses who were evaluated between January 2014 and December 2016 at two psychiatric institutions in Medellin, Colombia. Survival and Cox proportional hazard models were used for the analysis.

ResultsDuration of untreated psychosis and hospitalization at the time of presentation was associated with both response and remission. Response was also predicted by less first-order symptoms and more years of education. Remission was predicted by older age of onset. Relapse and rehospitalization were predicted by use of substances and poor adherence to pharmacologic treatment. Less years of education and hospitalization at the time of presentation were also associated with rehospitalization.

ConclusionPredictors of treatment response, remission, relapse and rehospitalization in first-episode patients are similar in Colombia compared to other high-income regions such as the United States and Europe.


title: Whole Genome Sequencing Illuminates the Developmental Signatures of Human Language Ability

abstract: 1Language is the foundation of human social interaction, education, commerce, and mental health. The heritability underlying language is well-established, but our understanding of its genetic basis -- and how it compares to that of more general cognitive functioning-- remains unclear. To illuminate the language-specific contributions of rare and common variation, we performed whole genome sequencing in N=350 individuals who were characterized with seven latent language phenotypes. We conducted region, gene, and gene set-based analyses to identify patterns of genetic burden that disproportionately explained these language factors compared to nonverbal IQ. These analyses identified language-specific associations with NDST4 and GRIN2A, with common variant replication of NDST4 in an independent sample. Rare variant burden analyses revealed three distinct functional profiles of genes that make contributions to language: a prenatally-expressed profile with enrichment for chromatin modifiers and broad neuropsychiatric risk, a postnatal cortex-expressed profile with enrichment for ion channels and cognitive/neuropsychiatric associations, and a postnatal, subcortically-expressed profile with enrichment of cilium-related proteins. Compared to a profile strongly associated with nonverbal IQ, these language-related profiles showed less intolerance to damaging variation, suggesting that the selection patterns acting on language differ from patterns linked to intellectual disability. Furthermore, we found evidence that rare potential reversions to an ancestral state are associated with poorer overall specific language ability. The breadth of these variant, gene, and profile associations suggest that while human-specific selection patterns do contribute to language, these are distributed broadly across numerous key mechanisms and developmental periods, and not in one or a few "language genes".


title: SARS-CoV-2 genome-based severity predictions correspond to lower qPCR values and higher viral load

abstract: The 2019 coronavirus disease (COVID-19) pandemic has demonstrated the importance of predicting, identifying, and tracking mutations throughout a pandemic event. As the COVID-19 global pandemic surpassed one year, several variants had emerged resulting in increased severity and transmissibility. In order to reduce the impact on human life, it is critical to rapidly identify which genetic variants result in increased virulence or transmission. To address the former, we evaluated if a genome-based predictive algorithm designed to predict clinical severity could predict polymerase chain reaction (PCR) results, as a surrogate for viral load and severity. Using a previously published algorithm, we compared the viral genome-based severity predictions to clinically-derived PCR-based viral load of 716 viral genomes. For those samples predicted to be "severe" (predicted severity score > 0.5), we observed an average cycle threshold (Ct) of 18.3, whereas those in in the "mild" category (severity prediction < 0.5) had an average Ct of 20.4 (P = 0.0017). We found a non-trivial correlation between predicted severity probability and cycle threshold (r = -0.199). Additionally, when divided into quartiles by prediction severity probability, the most probable quartile ([≥]75% probability) had a Ct of 16.6 (n=10) as compared to those least probable to be severe (<25%) of 21.4 (n=350) (P = 0.0045). Taken together, our results suggest that the severity predicted by a genome-based algorithm can be related to the metrics from the clinical diagnostic test, and that relative severity may be inferred from diagnostic values.


title: Is any job better than no job? A systematic review

abstract:
ObjectivesThis systematic review addresses the question "Is any job better than no job?" Specifically, it compares health and well-being outcomes in those who are unemployed with those who are in jobs that could be considered poor or low quality and the impact of any movement between them.

MethodWe conducted a systematic review following a PROSPERO-registered protocol (CRD42020182794). Medline, Embase, PsycINFO, HMIC, ASSIA, TRIP, Google Scholar and 10 websites were searched in April 2020 and again in May 2021 without date limits. Two reviewers working independently screened search results against the inclusion/exclusion criteria. A checklist for quantitative studies reporting correlations was used to critically appraise articles included at full text. We undertook synthesis without meta-analysis (narrative synthesis) and explored a range of variables (for example, study design and quality, type of outcome measure) that we considered might have an impact on the association between exposure and outcome.

ResultsWe included 25 studies reported in 30 journal articles. All 25 studies involved secondary analysis of data from national cohorts, including six from the UK. The most frequent outcomes reported were measures of mental well-being. There was considerable heterogeneity across included studies in terms of design, population, definition of poor/bad or low quality job and outcome types and measures. Overall the quality of the included studies was moderate. The evidence base is inconsistent. There are studies that suggested either labour market position might be preferable, but a number of studies found no statistically significant difference. Cohort and case- control studies looking at mental well-being outcomes showed some support for a poor job being better than unemployment. However, we did not find sufficient numbers of well-designed studies showing a strong association to support a causal relationship. Most included study designs were unable to distinguish whether changes in employment status occurred before a change in outcome. Three studies looking at employment transitions found that moving to a poor job from unemployment was not associated with improved mental health, but moving from a poor job to unemployment was associated with a deterioration.

ConclusionEvidence that better health and well-being outcomes are more likely to be associated with a poor/bad or low quality job than with unemployment is inconsistent. Studies conducted in the UK suggest that a poor job is not significantly associated with better health and well-being outcomes than unemployment. The studies we identified do not allow us to distinguish whether this lack of association is the result of a state welfare regime preventing some of the worst ills associated with unemployment, or a reflection of job quality. The evidence base has significant limitations in study design and conduct. In summary, the evidence we found suggests it is not safe to assume that, in the UK, any job will lead to better health and well-being outcomes than unemployment.


title: Impact of the Liberian National Community Health Assistant Program on Childhood Illness Treatment in Grand Bassa County, Liberia: A Difference-in-Differences Analysis of Population-Based Data

abstract:
Liberia launched its National Community Health Assistant Program in 2016, which seeks to ensure that all people living 5 kilometers or farther from a health facility have access to trained, supplied, supervised, and paid community health workers (CHWs). This study aims to evaluate the impact of the national program following implementation in Grand Bassa County in 2018 using data from population-based surveys.

We measured before-to-after changes in childhood treatment from qualified providers in a portion of the county that implemented in a first phase compared to those which had not yet implemented. We also assessed changes in whether children received oral rehydration therapy for diarrhea and malaria rapid diagnostic tests if they had a fever by a qualified provider (facility based or CHW). For these analyses, we used a difference-in-differences approach and adjusted for potential confounding using inverse probability of treatment weighting. We also assessed changes in the source from which care was received and examined changes by key dimensions of equity (distance from health facilities, maternal education, and household wealth).

We found that treatment of childhood illness by a qualified provider increased by 60.3 percentage points (95%CI 44.7-76.0) more in intervention than comparison areas. Difference-in-differences for oral rehydration therapy and malaria rapid diagnostic tests were 37.6 (95%CI 19.5-55.8) and 38.5 (95%CI 19.9-57.0) percentage points, respectively.

In intervention areas, treatment by a CHW increased from 0 to 81.6% and care from unqualified providers dropped. Increases in treatment by a qualified provider did not vary significantly by household wealth, remoteness, or maternal education.

This evaluation found evidence that the Liberian National Community Health Assistant Program has increased access to effective treatment in rural Grand Bassa County. Improvements were approximately equal across three measured dimensions of marginalization.


title: Distribution of confirmed with COVID-19 by age and gender in Mexico

abstract: Social, economic, and cultural factors can influence the likelihood of exposure to the virus of each person in sanitary emergencies like those of COVID-19. In this sense, parallel to the biological vulnerability to infection with SARS-CoV-2, said factors determine a complementary vulnerability to infection. Hence, they can influence in gender and age distributions of those confirmed, which is not entirely comprehended yet. The effect that age and gender can have on total vulnerability in Mexico thus far is not understood. A better understanding of such dependence can help policy optimization and decision-making to future similar emergencies. We aim to study the age and gender distributions of those confirmed with COVID-19 in Mexico. We also investigate the vulnerability to the infection with SARS-CoV-2 depending on such features. Two different samples of the Mexican population are analyzed in this non-experimental study to compare each other and evaluate the association of the result of the COVID-19 test with gender and age. Data up until the beginning of the vaccination are considered. The percentage of confirmed males is higher than females in both samples, and most tested and confirmed are working-age. Age distributions are positively skewed, with the peak in [30,39] years, which disagrees with the distribution of the Mexican population. The data suggest that the vulnerability to infection weakly depends on gender and age. Males were identified as the most vulnerable gender, and the age group [70,79] showed a higher vulnerability to infection.


title: Spatiotemporal mapping of major trauma in Victoria, Australia

abstract:
BackgroundSpatiotemporal modelling techniques allow one to predict injury across time and space. However, such methods have been underutilised in injury studies. This study demonstrates the use of statistical spatiotemporal modelling in identifying areas of significantly high injury risk, and areas witnessing significantly increasing risk over time.

MethodsWe performed a retrospective review of hospitalised major trauma patients from the Victorian State Trauma Registry, Australia, between 2007 and 2019. Geographical locations of injury events were mapped to the 79 local government areas (LGAs) in the state. We employed Bayesian spatiotemporal models to quantify spatial and temporal patterns, and analysed the results across a range of geographical remoteness and socioeconomic levels.

ResultsThere were 31,317 major trauma patients included. For major trauma overall, we observed substantial spatial variation in injury incidence and a significant 2.1% increase in injury incidence per year. Area-specific risk of injury by motor vehicle collision was higher in regional areas relative to metropolitan areas, while risk of injury by low fall was higher in metropolitan areas. Significant temporal increases were observed in injury by low fall, and the greatest increases were observed in the most disadvantaged LGAs.

ConclusionsThese findings can be used to inform injury prevention initiatives, which could be designed to target areas with relatively high injury risk and with significantly increasing injury risk over time. Our finding that the greatest year-on-year increases in injury incidence were observed in the most disadvantaged areas highlights the need for a greater emphasis on reducing inequities in injury.


title: Hospital admissions for respiratory tract infections in children aged 0-5 years for 2017/2023

abstract:
AimTo compare hospital admissions across common respiratory tract infections (RTI) in 2017-21, and project possible hospital admissions for the RTIs among children aged 0-12 months and 1-5 years in 2022 and 2023.

MethodsIn 644 885 children aged 0-12 months and 1-5 years, we plotted the observed monthly number of RTI admissions (upper- and lower RTI, influenza, respiratory syncytial virus (RSV), and COVID-19) from January 1st, 2017 until October 31st, 2021. We also plotted the number of RTI admissions with a need for respiratory support. We used the observed data to project four different scenarios of RTI admissions for the rest of 2021 until 2023, with different impacts on hospital wards: 1) "Business as usual", 2) "Continuous lockdown", 3) "Childrens immunity debt", and 4) "Maternal and child immunity debt".

ResultsBy October 31st, 2021, the number of simultaneous RTI admissions had exceeded the numbers usually observed at the typical season peak in January, i.e. [~]900. Based on our observed data and assuming that children and their mothers (who transfer antibodies to the very youngest) have not been exposed to RTI over the last one and a half years, our scenarios suggest that hospitals should be prepared to handle two to three times as many RTI admissions, and two to three times as many RTI admissions requiring respiratory support among 0-5-year-olds as normal, from November 2021 to April 2022.

ConclusionScenarios with immunity debt suggest that pediatric hospital wards and policy makers should plan for extended capacity.

category: respiratory medicine