Pulmonary arterial hypertension treatment: an individual participant data network meta-analysis.

BACKGROUND AND AIMS: Effective therapies that target three main signalling pathways are approved to treat pulmonary arterial hypertension (PAH). However, there are few large patient-level studies that compare the effectiveness of these pathways. The aim of this analysis was to compare the effectiveness of the treatment pathways in PAH and to assess treatment heterogeneity. METHODS: A network meta-analysis was performed using individual participant data of 6811 PAH patients from 20 Phase III randomized clinical trials of therapy for PAH that were submitted to the US Food and Drug Administration. Individual drugs were grouped by the following treatment pathways: endothelin, nitric oxide, and prostacyclin pathways. RESULTS: The mean (±standard deviation) age of the sample was 49.2 (±15.4) years; 78.4% were female, 59.7% had idiopathic PAH, and 36.5% were on background PAH therapy. After covariate adjustment, targeting the endothelin + nitric oxide pathway {ß: 43.7 m [95% confidence interval (CI): 32.9, 54.4]}, nitric oxide pathway [ß: 29.4 m (95% CI: 22.6, 36.3)], endothelin pathway [ß: 25.3 m (95% CI: 19.8, 30.8)], and prostacyclin pathway [oral/inhaled ß: 19.1 m (95% CI: 14.2, 24.0), intravenous/subcutaneous ß: 24.4 m (95% CI: 15.1, 33.7)] significantly increased 6 min walk distance at 12 or 16 weeks compared with placebo. Treatments also significantly reduced the likelihood of having clinical worsening events. There was significant heterogeneity of treatment effects by age, body mass index, hypertension, diabetes, and coronary artery disease. CONCLUSIONS: Drugs targeting the three traditional treatment pathways significantly improve outcomes in PAH, with significant treatment heterogeneity in patients with some comorbidities. Randomized clinical trials are warranted to identify the most effective treatment strategies in a personalized approach.

Head stabilization apparatus for high-resolution ophthalmic imaging.

Head movement must be stabilized to enable high-quality data collection from optical instrumentation such as eye trackers and ophthalmic imaging devices. Though critically important for imaging, head stabilization is often an afterthought in the design of advanced ophthalmic imaging systems, and experimental devices often adapt used and/or discarded equipment from clinical devices for this purpose. Alternatively, those seeking the most stable solution possible, including many users of adaptive optics ophthalmoscopy systems, utilize bite bars. Bite bars can provide excellent stability but are time consuming to fabricate, decreasing imaging efficiency, and uncomfortable for many patients, especially the elderly and/or those with prosthodontics such as dentures who may refuse participation in a study that requires one. No commercial vendors specifically offer head mount solutions for experimental ophthalmic imaging devices, resulting in nearly every custom device having a different solution for this commonly encountered problem. Parallelizing the head stabilization apparatus across different custom devices may improve standardization of experimental imaging systems for clinical trials and other multicenter investigations. Here we introduce a head mount design for ophthalmic imaging that is modular, adjustable, and customizable to the constraints of different experimental imaging configurations. The three points of head contact in our solution provide excellent stabilization across a range of head sizes and shapes from small children to adults, and the ease of adjustment afforded by our design minimizes the time to get participants stabilized and comfortable.

Minimal Clinically Important Difference in the 6-minute-walk Distance for Patients with Pulmonary Arterial Hypertension.

Rationale: The 6-minute-walk distance (6MWD) is an important clinical and research metric in pulmonary arterial hypertension (PAH); however, there is no consensus about what minimal change in 6MWD is clinically significant. Objectives: We aimed to determine the minimal clinically important difference in the 6MWD. Methods: We performed a meta-analysis using individual participant data from eight randomized clinical trials of therapy for PAH submitted to the U.S. Food and Drug Administration to derive minimal clinically important differences in the 6MWD. The estimates were externally validated using the Pulmonary Hypertension Association Registry. We anchored the change in 6MWD to the change in the Medical Outcomes Survey Short Form physical component score. Measurements and Main Results: The derivation (clinical trial) and validation (Pulmonary Hypertension Association Registry) samples were comprised of 2,404 and 537 adult patients with PAH, respectively. The mean ± standard deviation age of the derivation sample was 50.5 ± 15.2 years, and 1,849 (77%) were female, similar to the validation sample. The minimal clinically important difference in the derivation sample was 33 meters (95% confidence interval, 27-38), which was almost identical to that in the validation sample (36 m [95% confidence interval, 29-43]). The minimal clinically important difference did not differ by age, sex, race, pulmonary hypertension etiology, body mass index, use of background therapy, or World Health Organization functional class. Conclusions: We estimated a 6MWD minimal clinically important difference of approximately 33 meters for adults with PAH. Our findings can be applied to the design of clinical trials of therapies for PAH.

Preoperative Depression Status and 5 Year Metabolic and Bariatric Surgery Outcomes in the PCORnet Bariatric Study Cohort.

OBJECTIVE: To examine whether depression status before metabolic and bariatric surgery (MBS) influenced 5-year weight loss, diabetes, and safety/utilization outcomes in the PCORnet Bariatric Study. SUMMARY OF BACKGROUND DATA: Research on the impact of depression on MBS outcomes is inconsistent with few large, long-term studies. METHODS: Data were extracted from 23 health systems on 36,871 patients who underwent sleeve gastrectomy (SG; n=16,158) or gastric bypass (RYGB; n=20,713) from 2005-2015. Patients with and without a depression diagnosis in the year before MBS were evaluated for % total weight loss (%TWL), diabetes outcomes, and postsurgical safety/utilization (reoperations, revisions, endoscopy, hospitalizations, mortality) at 1, 3, and 5 years after MBS. RESULTS: 27.1% of SG and 33.0% of RYGB patients had preoperative depression, and they had more medical and psychiatric comorbidities than those without depression. At 5 years of follow-up, those with depression, versus those without depression, had slightly less %TWL after RYGB, but not after SG (between group difference = 0.42%TWL, P = 0.04). However, patients with depression had slightly larger HbA1c improvements after RYGB but not after SG (between group difference = - 0.19, P = 0.04). Baseline depression did not moderate diabetes remission or relapse, reoperations, revision, or mortality across operations; however, baseline depression did moderate the risk of endoscopy and repeat hospitalization across RYGB versus SG. CONCLUSIONS: Patients with depression undergoing RYGB and SG had similar weight loss, diabetes, and safety/utilization outcomes to those without depression. The effects of depression were clinically small compared to the choice of operation.

Heterogeneity of treatment effects by risk in pulmonary arterial hypertension.

BACKGROUND: It is currently unknown if disease severity modifies response to therapy in pulmonary arterial hypertension (PAH). We aimed to explore if disease severity, as defined by established risk-prediction algorithms, modified response to therapy in randomised clinical trials in PAH. METHODS: We performed a meta-analysis using individual participant data from 18 randomised clinical trials of therapy for PAH submitted to the United States Food and Drug Administration to determine if predicted risk of 1-year mortality at randomisation modified the treatment effect on three outcomes: change in 6-min walk distance (6MWD), clinical worsening at 12 weeks and time to clinical worsening. RESULTS: Of 6561 patients with a baseline US Registry to Evaluate Early and Long-Term PAH Disease Management (REVEAL 2.0) score, we found that individuals with higher baseline risk had higher probabilities of clinical worsening but no difference in change in 6MWD. We detected a significant interaction of REVEAL 2.0 risk and treatment assignment on change in 6MWD. For every 3-point increase in REVEAL 2.0 score, there was a 12.49 m (95% CI 5.86-19.12 m; p=0.001) greater treatment effect in change in 6MWD. We did not detect a significant risk by treatment interaction on clinical worsening with most of the risk-prediction algorithms. CONCLUSIONS: We found that predicted risk of 1-year mortality in PAH modified treatment effect as measured by 6MWD, but not clinical worsening. Our findings highlight the importance of identifying sources of treatment heterogeneity by predicted risk to tailor studies to patients most likely to have the greatest treatment response.

Informative missingness: What can we learn from patterns in missing laboratory data in the electronic health record?

BACKGROUND: In electronic health records, patterns of missing laboratory test results could capture patients' course of disease as well as ​​reflect clinician's concerns or worries for possible conditions. These patterns are often understudied and overlooked. This study aims to identify informative patterns of missingness among laboratory data collected across 15 healthcare system sites in three countries for COVID-19 inpatients. METHODS: We collected and analyzed demographic, diagnosis, and laboratory data for 69,939 patients with positive COVID-19 PCR tests across three countries from 1 January 2020 through 30 September 2021. We analyzed missing laboratory measurements across sites, missingness stratification by demographic variables, temporal trends of missingness, correlations between labs based on missingness indicators over time, and clustering of groups of labs based on their missingness/ordering pattern. RESULTS: With these analyses, we identified mapping issues faced in seven out of 15 sites. We also identified nuances in data collection and variable definition for the various sites. Temporal trend analyses may support the use of laboratory test result missingness patterns in identifying severe COVID-19 patients. Lastly, using missingness patterns, we determined relationships between various labs that reflect clinical behaviors. CONCLUSION: In this work, we use computational approaches to relate missingness patterns to hospital treatment capacity and highlight the heterogeneity of looking at COVID-19 over time and at multiple sites, where there might be different phases, policies, etc. Changes in missingness could suggest a change in a patient's condition, and patterns of missingness among laboratory measurements could potentially identify clinical outcomes. This allows sites to consider missing data as informative to analyses and help researchers identify which sites are better poised to study particular questions.

Trends in Public Awareness and Knowledge of Drinking Guidelines: a Representative Population Survey in England, 2016-2022.

AIM: To examine trends in public awareness and knowledge of drinking guidelines in the UK since their revision in 2016, which had moved from a daily to a weekly guideline, made the guideline the same for men and women, and reduced the guideline for men by around one-third. METHOD: Data were from a representative, repeat cross-sectional survey. We analysed changes in awareness and knowledge of drinking guidelines among 8168 adult drinkers between 2016 and 2022 and associations with sociodemographic characteristics, smoking status and level of alcohol consumption. RESULTS: The proportion of drinkers aware of guidelines declined from 86.0% (95%CI 84.0-88.0%) in 2016 to 81.7% (79.5-84.0%) in 2019, then increased during the COVID-19 pandemic, peaking at 91.6% (90.1-93.1%) in 2020. The proportion who correctly identified the guideline as a maximum of exactly 14 units/week remained at around a quarter from 2016 (25.0%, 22.4-27.5%) to 2018 (25.8%, 23.2-28.3%), whereas the proportion who gave a figure of 14 units or fewer rose from 52.1 (49.2-55.0%) to 57.4% (54.6-60.3%). However, by 2022, guideline knowledge had worsened significantly, with these figures falling to 19.7 (17.4-21.9%) and 46.5% (43.6-49.4%), respectively. Changes over time were similar across subgroups. Odds of guideline awareness and knowledge were higher among drinkers who were aged ≥35, female, more educated and from more advantaged social grades. CONCLUSIONS: The majority of adult drinkers in the UK are aware of low-risk drinking guidelines. However, 6 years since their announcement, knowledge of the revised drinking guidelines remains poor. Less than a quarter know the recommended weekly limit and only around half think it is 14 units or less. Inequalities have persisted over time, such that disadvantaged groups remain less likely to know the guidelines.

Young people's explanations for the decline in youth drinking in England.

BACKGROUND: Youth alcohol consumption has fallen markedly over the last twenty years in England. This paper explores the drivers of the decline from the perspectives of young people. METHODS: The study used two methods in a convergent triangulation design. We undertook 38 individual or group qualitative interviews with 96 participants in various educational contexts in England. An online survey of 547 young people in England, was also conducted. Participants were aged between 12-19 years. For both data sources, participants were asked why they thought youth alcohol drinking might be in decline. Analysis of interview data was both deductive and inductive, guided by a thematic approach. Content analysis of survey responses further refined these themes and indicated their prevalence within a larger sample. RESULTS: The research identified eight key themes that young people used to explain the decline in youth drinking: The potential for alcohol-related harm; Contemporary youth cultures and places of socialisation; The affordability of alcohol; Displacement of alcohol by other substances; Access and the regulatory environment; Disputing the decline; Future Orientations; and Parenting and the home environment. Heterogeneity in the experiences and perspectives of different groups of young people was evident, particularly in relation to age, gender, and socio-economic position. CONCLUSIONS: Young people's explanations for the decline in youth drinking in England aligned well with those generated by researchers and commentators in prior literature. Our findings suggest that changing practices of socialisation, decreased alcohol affordability and changed attitudes toward risk and self-governance may be key explanations.

A 2.8 Å Structure of Zoliflodacin in a DNA Cleavage Complex with Staphylococcus aureus DNA Gyrase.

Since 2000, some thirteen quinolones and fluoroquinolones have been developed and have come to market. The quinolones, one of the most successful classes of antibacterial drugs, stabilize DNA cleavage complexes with DNA gyrase and topoisomerase IV (topo IV), the two bacterial type IIA topoisomerases. The dual targeting of gyrase and topo IV helps decrease the likelihood of resistance developing. Here, we report on a 2.8 Å X-ray crystal structure, which shows that zoliflodacin, a spiropyrimidinetrione antibiotic, binds in the same DNA cleavage site(s) as quinolones, sterically blocking DNA religation. The structure shows that zoliflodacin interacts with highly conserved residues on GyrB (and does not use the quinolone water-metal ion bridge to GyrA), suggesting it may be more difficult for bacteria to develop target mediated resistance. We show that zoliflodacin has an MIC of 4 µg/mL against Acinetobacter baumannii (A. baumannii), an improvement of four-fold over its progenitor QPT-1. The current phase III clinical trial of zoliflodacin for gonorrhea is due to be read out in 2023. Zoliflodacin, together with the unrelated novel bacterial topoisomerase inhibitor gepotidacin, is likely to become the first entirely novel chemical entities approved against Gram-negative bacteria in the 21st century. Zoliflodacin may also become the progenitor of a new safer class of antibacterial drugs against other problematic Gram-negative bacteria.

A Revised Moral Appraisal of Early Induction of Labor in Cases of Anencephaly.

The central concern of this article is whether early induction of labor for an anencephalic fetus can ever be morally justified, particularly by a Catholic healthcare ethics committee. By revisiting and refining arguments in articles by Drane (1992) and Bole (1992) published in this journal, a revised argument - consistent with the Catholic moral tradition - can seemingly be constructed that a Catholic healthcare ethics committee might use to justify early induction of labor in some pregnancies involving an anencephalic fetus. Such a revised argument depends upon two central claims; first, that the anencephalic fetus in question is necessarily in the process of dying when early induction of labor occurs, and second, that the fetus is judged to be undergoing extraordinary or disproportionate means of preserving their life as a result of receiving ongoing maternal support of a mother's womb. The revised argument developed in this article aims to utilize the doctrine of double effect in conjunction with these two central claims to justify early induction of labor for anencephalic fetal persons in some circumstances. Unfortunately, the revised argument - if successful - would be at odds with a stance taken in the United States Conference of Catholic Bishops (USCCB) 1996 statement "Moral Principles Concerning Infants with Anencephaly." However, there is reason to believe the revised argument offered in this article is well aligned with other guidance from the USCCB, contained in the publication Ethical and Religious Directives for Catholic Healthcare Services (2018). This article concludes by noting some important limitations of the argument and offering hope that consideration of the argument ultimately helps to strengthen the Catholic moral tradition.

SurvMaximin: Robust federated approach to transporting survival risk prediction models.

OBJECTIVE: For multi-center heterogeneous Real-World Data (RWD) with time-to-event outcomes and high-dimensional features, we propose the SurvMaximin algorithm to estimate Cox model feature coefficients for a target population by borrowing summary information from a set of health care centers without sharing patient-level information. MATERIALS AND METHODS: For each of the centers from which we want to borrow information to improve the prediction performance for the target population, a penalized Cox model is fitted to estimate feature coefficients for the center. Using estimated feature coefficients and the covariance matrix of the target population, we then obtain a SurvMaximin estimated set of feature coefficients for the target population. The target population can be an entire cohort comprised of all centers, corresponding to federated learning, or a single center, corresponding to transfer learning. RESULTS: Simulation studies and a real-world international electronic health records application study, with 15 participating health care centers across three countries (France, Germany, and the U.S.), show that the proposed SurvMaximin algorithm achieves comparable or higher accuracy compared with the estimator using only the information of the target site and other existing methods. The SurvMaximin estimator is robust to variations in sample sizes and estimated feature coefficients between centers, which amounts to significantly improved estimates for target sites with fewer observations. CONCLUSIONS: The SurvMaximin method is well suited for both federated and transfer learning in the high-dimensional survival analysis setting. SurvMaximin only requires a one-time summary information exchange from participating centers. Estimated regression vectors can be very heterogeneous. SurvMaximin provides robust Cox feature coefficient estimates without outcome information in the target population and is privacy-preserving.

Are changes in attitudes towards school associated with declining youth drinking? A multi-level analysis of 37 countries.

BACKGROUND: Changes in adolescents' attitudes towards school are a potential explanation for recent declines in young people's alcohol consumption. However, this has not been tested using multi-national survey data, which would permit stronger causal inferences by ruling out other country-specific explanations. This study, therefore, uses an international survey of schoolchildren to examine the associations between changing attitudes towards school and adolescent alcohol consumption. METHODS: We used data from 247 325 15-year-olds across 37 countries participating in four waves of the Health Behaviour in School-aged Children study (2001/02-2013/14). Attitudes towards school were assessed using two measures-self-reported pressure from schoolwork and whether respondents like school. Outcome measures were weekly alcohol consumption and having been drunk twice in one's lifetime. We used whole population and gender-specific hierarchical linear probability models to assess the relationship between attitudes and alcohol outcomes within countries over time. RESULTS: Country-level changes over time in liking school were not associated with changes in alcohol consumption. However, a 10% increase in feeling pressured by schoolwork was associated with a 1.8% decline in drunkenness [95% confidence interval (CI): -3.2% to -0.3%] and weakly associated with a 1.7% decline in weekly drinking (95% CI: -3.6% to 0.2%). Among girls only, increases in feeling pressured by schoolwork were associated with a 2.1% decline in weekly drinking (95% CI: -3.7% to -0.6%) and a 2.4% decline in drunkenness (95% CI: -3.8% to -1.1%). CONCLUSION: Changes in attitudes towards school may have played a minor role in the decline in alcohol consumption among adolescent girls only.

Distinguishing Admissions Specifically for COVID-19 From Incidental SARS-CoV-2 Admissions: National Retrospective Electronic Health Record Study.

BACKGROUND: Admissions are generally classified as COVID-19 hospitalizations if the patient has a positive SARS-CoV-2 polymerase chain reaction (PCR) test. However, because 35% of SARS-CoV-2 infections are asymptomatic, patients admitted for unrelated indications with an incidentally positive test could be misclassified as a COVID-19 hospitalization. Electronic health record (EHR)-based studies have been unable to distinguish between a hospitalization specifically for COVID-19 versus an incidental SARS-CoV-2 hospitalization. Although the need to improve classification of COVID-19 versus incidental SARS-CoV-2 is well understood, the magnitude of the problems has only been characterized in small, single-center studies. Furthermore, there have been no peer-reviewed studies evaluating methods for improving classification. OBJECTIVE: The aims of this study are to, first, quantify the frequency of incidental hospitalizations over the first 15 months of the pandemic in multiple hospital systems in the United States and, second, to apply electronic phenotyping techniques to automatically improve COVID-19 hospitalization classification. METHODS: From a retrospective EHR-based cohort in 4 US health care systems in Massachusetts, Pennsylvania, and Illinois, a random sample of 1123 SARS-CoV-2 PCR-positive patients hospitalized from March 2020 to August 2021 was manually chart-reviewed and classified as "admitted with COVID-19" (incidental) versus specifically admitted for COVID-19 ("for COVID-19"). EHR-based phenotyping was used to find feature sets to filter out incidental admissions. RESULTS: EHR-based phenotyped feature sets filtered out incidental admissions, which occurred in an average of 26% of hospitalizations (although this varied widely over time, from 0% to 75%). The top site-specific feature sets had 79%-99% specificity with 62%-75% sensitivity, while the best-performing across-site feature sets had 71%-94% specificity with 69%-81% sensitivity. CONCLUSIONS: A large proportion of SARS-CoV-2 PCR-positive admissions were incidental. Straightforward EHR-based phenotypes differentiated admissions, which is important to assure accurate public health reporting and research.

Unsupervised modeling and genome-wide association identify novel features of allergic march trajectories.

BACKGROUND: The allergic march refers to the natural history of allergic conditions during infancy and childhood. However, population-level disease incidence patterns do not necessarily reflect the development of allergic disease in individuals. A better understanding of the factors that predispose to different allergic trajectories is needed. OBJECTIVE: Our aim was to determine the demographic and genetic features that are associated with the major allergic march trajectories. METHODS: Presence or absence of common allergic conditions (atopic dermatitis [AD], IgE-mediated food allergy [IgE-FA], asthma, and allergic rhinitis [AR]) was ascertained in a pediatric primary care birth cohort of 158,510 subjects. Hierarchic clustering and decision tree modeling were used to associate demographic features with allergic outcomes. Genome-wide association study was used to test for risk loci associated with specific allergic trajectories. RESULTS: We found an association between self-identified black race and progression from AD to asthma. Conversely, Asian or Pacific Islander race was associated with progression from AD to IgE-mediated food allergy, and white race was associated with progression from AD to AR. Genome-wide association study of trajectory groups identified risk loci associated with progression from AD to asthma (rs60242841) and from AD to AR (rs9565267, rs151041509, and rs78171803). Consistent with our epidemiologic associations, rs60242841 was more common in individuals of African ancestry than in individuals of European ancestry, whereas rs9565267 and rs151041509 were more common in individuals of European ancestry than in individuals of African ancestry. CONCLUSION: We have identified novel associations between race and progression along distinct allergic trajectories. Ancestral genetic differences may contribute to these associations. These results uncover important health disparities, refine the concept of the allergic march, and represent a step toward developing individualized medical approaches for these conditions.

Combinations of Drinking Occasion Characteristics Associated with Units of Alcohol Consumed among British Adults: An Event-Level Decision Tree Modeling Study.

BACKGROUND: Alcohol consumption is influenced by the characteristics of drinking occasions, for example, location, timing, or the composition of the drinking group. However, the relative importance of occasion characteristics is not yet well understood. This study aims to identify which characteristics, and combinations of characteristics, are associated with units consumed within drinking occasions. It also tests whether accounting for occasion characteristics improves the prediction of consumption compared to using demographic information only. METHODS: The data come from a cross-sectional, nationally representative, online market research survey. Our sample includes 18,409 British drinkers aged 18 + who recorded the characteristics of 46,072 drinking occasions using 7-day retrospective drinking diaries in 2018. We used decision tree modeling and nested linear regression to predict units consumed in occasions using information on drinking location/venue, occasion timing, company, occasion type (e.g., a quiet night in), occasion motivation, drink type and packaging, food eaten and entertainment/ other activities during the occasion. We estimated models separately for 6 age-sex groups and controlled for usual drinking frequency, and social grade in nested linear regression models. Open Science Framework preregistration: https://osf.io/42epd. RESULTS: Our 6 final models accounted for between 55% and 71% of the variance in drinking occasion alcohol consumption. Beyond demographic characteristics (1 to 9%) and occasion duration (24 to 60%), further occasion characteristics and combinations of characteristics accounted for 31 to 70% of the total explained variance. The characteristics most strongly associated with heavy alcohol consumption were long occasion duration, drinking spirits as doubles, and drinking wine. Spirits were also consumed in light occasions, but as singles. This suggests that the serving size is an important differentiator of light and heavy occasions. CONCLUSIONS: Combinations of occasion duration and drink type are strongly predictive of alcohol consumption in adults' drinking occasions. Accounting for characteristics of drinking occasions, both individually and in combination, substantially improves the prediction of alcohol consumption.

Clustering of health-related behaviours within children aged 11-16: a systematic review.

OBJECTIVE: We aimed to systematically review and synthesise evidence on the clustering of a broad range of health-related behaviours amongst 11-16 year olds. METHOD: A literature search was conducted in September 2019. Studies were included if they used cluster analysis, latent class analysis, prevalence odds ratios, principal component analysis or factor analysis, and considered at least three health-related behaviours of interest among 11-16 year olds in high-income countries. Health-related behaviours of interest were substance use (alcohol, cigarettes and other drug use) and other behavioural risk indicators (diet, physical activity, gambling and sexual activity). RESULTS: The review identified 41 studies, which reported 198 clusters of health-related behaviours of interest. The behaviours of interest reported within clusters were used to define eight behavioural archetypes. Some included studies only explored substance use, while others considered substance use and/or other health-related behaviours. Consequently, three archetypes were comprised by clusters reporting substance use behaviours alone. The archetypes were: (1) Poly-Substance Users, (2) Single Substance Users, (3) Substance Abstainers, (4) Substance Users with No/Low Behavioural Risk Indicators, (5) Substance Abstainers with Behavioural Risk Indicators, (6) Complex Configurations, (7) Overall Unhealthy and (8) Overall Healthy. CONCLUSION: Studies of youth health behavioural clustering typically find both a 'healthy' cluster and an 'unhealthy' cluster. Unhealthy clusters are often characterised by poly-substance use. Our approach to synthesising cluster analyses may offer a means of navigating the heterogeneity of method, measures and behaviours of interest in this literature.

What Every Reader Should Know About Studies Using Electronic Health Record Data but May Be Afraid to Ask.

Coincident with the tsunami of COVID-19-related publications, there has been a surge of studies using real-world data, including those obtained from the electronic health record (EHR). Unfortunately, several of these high-profile publications were retracted because of concerns regarding the soundness and quality of the studies and the EHR data they purported to analyze. These retractions highlight that although a small community of EHR informatics experts can readily identify strengths and flaws in EHR-derived studies, many medical editorial teams and otherwise sophisticated medical readers lack the framework to fully critically appraise these studies. In addition, conventional statistical analyses cannot overcome the need for an understanding of the opportunities and limitations of EHR-derived studies. We distill here from the broader informatics literature six key considerations that are crucial for appraising studies utilizing EHR data: data completeness, data collection and handling (eg, transformation), data type (ie, codified, textual), robustness of methods against EHR variability (within and across institutions, countries, and time), transparency of data and analytic code, and the multidisciplinary approach. These considerations will inform researchers, clinicians, and other stakeholders as to the recommended best practices in reviewing manuscripts, grants, and other outputs from EHR-data derived studies, and thereby promote and foster rigor, quality, and reliability of this rapidly growing field.

International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6 Countries: Retrospective Cohort Study.

BACKGROUND: Many countries have experienced 2 predominant waves of COVID-19-related hospitalizations. Comparing the clinical trajectories of patients hospitalized in separate waves of the pandemic enables further understanding of the evolving epidemiology, pathophysiology, and health care dynamics of the COVID-19 pandemic. OBJECTIVE: In this retrospective cohort study, we analyzed electronic health record (EHR) data from patients with SARS-CoV-2 infections hospitalized in participating health care systems representing 315 hospitals across 6 countries. We compared hospitalization rates, severe COVID-19 risk, and mean laboratory values between patients hospitalized during the first and second waves of the pandemic. METHODS: Using a federated approach, each participating health care system extracted patient-level clinical data on their first and second wave cohorts and submitted aggregated data to the central site. Data quality control steps were adopted at the central site to correct for implausible values and harmonize units. Statistical analyses were performed by computing individual health care system effect sizes and synthesizing these using random effect meta-analyses to account for heterogeneity. We focused the laboratory analysis on C-reactive protein (CRP), ferritin, fibrinogen, procalcitonin, D-dimer, and creatinine based on their reported associations with severe COVID-19. RESULTS: Data were available for 79,613 patients, of which 32,467 were hospitalized in the first wave and 47,146 in the second wave. The prevalence of male patients and patients aged 50 to 69 years decreased significantly between the first and second waves. Patients hospitalized in the second wave had a 9.9% reduction in the risk of severe COVID-19 compared to patients hospitalized in the first wave (95% CI 8.5%-11.3%). Demographic subgroup analyses indicated that patients aged 26 to 49 years and 50 to 69 years; male and female patients; and black patients had significantly lower risk for severe disease in the second wave than in the first wave. At admission, the mean values of CRP were significantly lower in the second wave than in the first wave. On the seventh hospital day, the mean values of CRP, ferritin, fibrinogen, and procalcitonin were significantly lower in the second wave than in the first wave. In general, countries exhibited variable changes in laboratory testing rates from the first to the second wave. At admission, there was a significantly higher testing rate for D-dimer in France, Germany, and Spain. CONCLUSIONS: Patients hospitalized in the second wave were at significantly lower risk for severe COVID-19. This corresponded to mean laboratory values in the second wave that were more likely to be in typical physiological ranges on the seventh hospital day compared to the first wave. Our federated approach demonstrated the feasibility and power of harmonizing heterogeneous EHR data from multiple international health care systems to rapidly conduct large-scale studies to characterize how COVID-19 clinical trajectories evolve.

Authorship Correction: International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6 Countries: Retrospective Cohort Study.

[This corrects the article DOI: 10.2196/31400.].

Summary statistic analyses can mistake confounding bias for heritability.

Linkage disequilibrium SCore regression (LDSC) has become a popular approach to estimate confounding bias, heritability, and genetic correlation using only genome-wide association study (GWAS) test statistics. SumHer is a newly introduced alternative with similar aims. We show using theory and simulations that both approaches fail to adequately account for confounding bias, even when the assumed heritability model is correct. Consequently, these methods may estimate heritability poorly if there was an inadequate adjustment for confounding in the original GWAS analysis. We also show that the choice of a summary statistic for use in LDSC or SumHer can have a large impact on resulting inferences. Further, covariate adjustments in the original GWAS can alter the target of heritability estimation, which can be problematic for test statistics from a meta-analysis of GWAS with different covariate adjustments.