Bictegravir/emtricitabine/tenofovir alafenamide as first-line treatment in naïve HIV patients in a rapid-initiation model of care: BIC-NOW clinical trial

OBJECTIVE

Multiple strategies have been utilized to reduce the incidence of HIV, including PrEP and rapid antiretroviral therapy initiation. The study objectives were to evaluate the efficacy, safety, satisfaction, treatment adherence, and system retention obtained with rapid initiation of bictegravir/emtricitabine/tenofovir alafenamide (BIC/FTC/TAF) in naïve patients.

METHODS

This phase IV, multicenter, open-label, single-arm, 48-week clinical trial enrolled patients between January 2020 and June 2022. Adherence to treatment was evaluated with the SMAQ questionnaire and patient satisfaction with the EQ-5D.

RESULTS

208 participants were enrolled with mean age of 35.6 years; 87.6% were males; mean CD4 count was 393.5 cells/uL (<200 cells/uL in 22.1%); viral load log was 5.6 (VL>100,000 cop/mL in 43.3%); 22.6% had AIDS, and 4.3% were coinfected with HBV. BIC/FTC/TAF was initiated on the day of their first visit to the HIV specialist in 98.6% of participants, and 9.6% were lost to follow-up. The efficacy at week 48 was 84.1 % by intention-to- treat (ITT), 94.6% by modified ITT, and 98.3% by per protocol analysis. The regimen was discontinued in two subjects (0.9%) during week 1 for grade 3 adverse events. Treatment adherence [weeks 4 (90%, IQR: 80-99%) vs. 48 (90%, IQR: 80-95%; p=0.49)] and patient satisfaction [weeks 4 (90%, IQR: 80-99%) vs. 48 (90%, IQR: 80-95 p=0.49) rates were very high over the 48- week study period.

CONCLUSIONS

BIC/FTC/TAF is an appropriate option for rapid ART initiation in naïve HIV patients, offering high efficacy, safety, durability, treatment adherence, retention in the healthcare system, and patient satisfaction. Number Clinical Trial registration: NCT06177574.

A randomized double-blinded trial to assess recurrence of systemic allergic reactions following COVID-19 mRNA vaccination

BACKGROUND

Systemic allergic reactions (sARs) following coronavirus disease 2019 (COVID-19) mRNA vaccines were initially reported at a higher rate than after traditional vaccines.

OBJECTIVE

We aimed to evaluate the safety of revaccination in these individuals and to interrogate mechanisms underlying these reactions.

METHODS

In this randomized, double-blinded, phase 2 trial, participants aged 16 to 69 years who previously reported a convincing sAR to their first dose of COVID-19 mRNA vaccine were randomly assigned to receive a second dose of BNT162b2 (Comirnaty) vaccine and placebo on consecutive days in a blinded, 1:1 crossover fashion at the National Institutes of Health. An open-label BNT162b2 booster was offered 5 months later if the second dose did not result in severe sAR. None of the participants received the mRNA-1273 (Spikevax) vaccine during the study. The primary end point was recurrence of sAR following second dose and booster vaccination; exploratory end points included biomarker measurements.

RESULTS

Of 111 screened participants, 18 were randomly assigned to receive study interventions. Eight received BNT162b2 second dose followed by placebo; 8 received placebo followed by BNT162b2 second dose; 2 withdrew before receiving any study intervention. All 16 participants received the booster dose. Following second dose and booster vaccination, sARs recurred in 2 participants (12.5%; 95% CI, 1.6 to 38.3). No sAR occurred after placebo. An anaphylaxis mimic, immunization stress-related response (ISRR), occurred more commonly than sARs following both vaccine and placebo and was associated with higher predose anxiety scores, paresthesias, and distinct vital sign and biomarker changes.

CONCLUSIONS

Our findings support revaccination of individuals who report sARs to COVID-19 mRNA vaccines. Distinct clinical and laboratory features may distinguish sARs from ISRRs.

Response-guided neoadjuvant sacituzumab govitecan for localized triple-negative breast cancer: results from the NeoSTAR trial

BACKGROUND

Sacituzumab govitecan (SG), a novel antibody-drug conjugate (ADC) targeting TROP2, is approved for pre-treated metastatic triple-negative breast cancer (mTNBC). We conducted an investigator-initiated clinical trial evaluating neoadjuvant (NA) SG (NCT04230109), and report primary results.

PATIENTS AND METHODS

Participants with early-stage TNBC received NA SG for four cycles. The primary objective was to assess pathological complete response (pCR) rate in breast and lymph nodes (ypT0/isN0) to SG. Secondary objectives included overall response rate (ORR), safety, event-free survival (EFS), and predictive biomarkers. A response-guided approach was utilized, and subsequent systemic therapy decisions were at the discretion of the treating physician.

RESULTS

From July 2020 to August 2021, 50 participants were enrolled (median age = 48.5 years; 13 clinical stage I disease, 26 stage II, 11 stage III). Forty-nine (98%) completed four cycles of SG. Overall, the pCR rate with SG alone was 30% [n = 15, 95% confidence interval (CI) 18% to 45%]. The ORR per RECIST V1.1 after SG alone was 64% (n = 32/50, 95% CI 77% to 98%). Higher Ki-67 and tumor-infiltrating lymphocytes (TILs) were predictive of pCR to SG (P = 0.007 for Ki-67 and 0.002 for TILs), while baseline TROP2 expression was not (P = 0.440). Common adverse events were nausea (82%), fatigue (76%), alopecia (76%), neutropenia (44%), and rash (48%). With a median follow-up time of 18.9 months (95% CI 16.3-21.9 months), the 2-year EFS for all participants was 95%. Among participants with a pCR with SG (n = 15), the 2-year EFS was 100%.

CONCLUSIONS

In the first NA trial with an ADC in localized TNBC, SG demonstrated single-agent efficacy and feasibility of response-guided escalation/de-escalation. Further research on optimal duration of SG as well as NA combination strategies, including immunotherapy, are needed.

OHDSI Standardized Vocabularies-a large-scale centralized reference ontology for international data harmonization

IMPORTANCE

The Observational Health Data Sciences and Informatics (OHDSI) is the largest distributed data network in the world encompassing more than 331 data sources with 2.1 billion patient records across 34 countries. It enables large-scale observational research through standardizing the data into a common data model (CDM) (Observational Medical Outcomes Partnership [OMOP] CDM) and requires a comprehensive, efficient, and reliable ontology system to support data harmonization.

MATERIALS AND METHODS

We created the OHDSI Standardized Vocabularies-a common reference ontology mandatory to all data sites in the network. It comprises imported and de novo-generated ontologies containing concepts and relationships between them, and the praxis of converting the source data to the OMOP CDM based on these. It enables harmonization through assigned domains according to clinical categories, comprehensive coverage of entities within each domain, support for commonly used international coding schemes, and standardization of semantically equivalent concepts.

RESULTS

The OHDSI Standardized Vocabularies comprise over 10 million concepts from 136 vocabularies. They are used by hundreds of groups and several large data networks. More than 8600 users have performed 50 000 downloads of the system. This open-source resource has proven to address an impediment of large-scale observational research-the dependence on the context of source data representation. With that, it has enabled efficient phenotyping, covariate construction, patient-level prediction, population-level estimation, and standard reporting.

DISCUSSION AND CONCLUSION

OHDSI has made available a comprehensive, open vocabulary system that is unmatched in its ability to support global observational research. We encourage researchers to exploit it and contribute their use cases to this dynamic resource.

On-site testing and treatment of sexually transmitted infections among female sex workers using molecular point-of-care testing integrated into harm reduction services in Madrid, Spain

INTRODUCTION

This study aimed to evaluate the feasibility of molecular point-of-care testing for STIs, the prevalence of STIs and associated factors, and testing and treatment uptake among street-based female sex workers (FSWs) attending a mobile harm reduction unit in Madrid, Spain.

METHODS

This was a prospective, longitudinal study. From August 15th to December 6th, 2022, participants were screened for Chlamydia trachomatis, Neisseria gonorrhoeae, and Trichomonas vaginalis using molecular testing (Xpert) on self-collected urine samples at a mobile harm reduction unit. Additionally, rapid tests were used to screen participants for HIV, hepatitis C virus (HCV), and syphilis. On-site same-day results and treatment for those infected were offered.

RESULTS

Among 77 FSWs included the median age was 40 (range, 33-48), 64 % were homeless, and 84 % reported drug use in the past six months. Four participants self-reported having HIV, of whom all were on antiretroviral therapy, and 14 (18 %) had HCV antibodies, including three with current infection. The prevalence of at least one STI was 66 %. When categorized by type of STI, the prevalences were as follows: 15 % for CT, 15 % for NG, 51 % for TV, and 21 % for syphilis. Notably, the prevalence of STIs was higher among FSW with recent drug use, with no cases of CT or NG detected among FSWs who did not recently use drugs. In adjusted analysis, drug use was associated an increased odds of having an STI (adjusted odds ratio, 10.47; 95 % CI: 1.67-65.42). All participants consented to screening, and all but one received on-site result-based linkage to treatment.

CONCLUSIONS

This study demonstrates the feasibility, high STI prevalence, and high linkage to testing and treatment following point-of-care molecular testing among street-based FSWs who have recently used drugs in Madrid, Spain.

Development of an undergraduate certificate in clinical and translational science: improving competence of the clinical research workforce

Introduction: Academic research centers often struggle to recruit and retain a well-trained and diverse clinical and translational science (CTS) workforce. In particular, the clinical research professional (CRP) career pathway is not well known to undergraduate students and other individuals outside of academic medicine despite being a potential career route. To address these workforce challenges, the CRP Task Force at the University of Cincinnati (UC) aims to train a competent and diverse CRP workforce through targeted educational programming in the UC undergraduate population. Methods: Using a six-step curriculum development process that included: 1) performing a needs assessment, 2) determining content, 3) writing goals and objectives, 4) selecting the educational strategies, 5) implementing the curriculum, and 6) evaluating the curriculum, we designed an undergraduate certificate program in CTS. Results: The needs assessment included both internal and external data gathering to inform curriculum development and program decisions. Content was determined using the Core Competency Framework for the Clinical Research Professional Version 3.1., and program learning outcomes were written with both the competency framework and local workforce needs in mind. Educational strategies were selected based on optimization of available resources and local expertise with an emphasis on interactive didactics complemented by experiential learning. Implementation is underway and evaluation will follow once students begin enrolling. Discussion: By educating an undergraduate student population about CTS methods and career opportunities, we anticipate increased numbers of well-qualified, diverse applicants who pursue CRP careers locally and regionally.

Social-environmental phenotypes of rapid cystic fibrosis lung disease progression in adolescents and young adults living in the United States

Background

Cystic fibrosis (CF) is a genetic disease but is greatly impacted by non-genetic (social/environmental and stochastic) influences. Some people with CF experience rapid decline, a precipitous drop in lung function relative to patient- and/or center-level norms. Those who experience rapid decline in early adulthood, compared to adolescence, typically exhibit less severe clinical disease but greater loss of lung function. The extent to which timing and degree of rapid decline are informed by social and environmental determinants of health (geomarkers) is unknown.

Methods

A longitudinal cohort study was performed (24,228 patients, aged 6-21 years) using the U.S. CF Foundation Patient Registry. Geomarkers at the ZIP Code Tabulation Area level measured air pollution/respiratory hazards, greenspace, crime, and socioeconomic deprivation. A composite score quantifying social-environmental adversity was created and used in covariate-adjusted functional principal component analysis, which was applied to cluster longitudinal lung function trajectories.

Results

Social-environmental phenotyping yielded three primary phenotypes that corresponded to early, middle, and late timing of peak decline in lung function over age. Geographic differences were related to distinct cultural and socioeconomic regions. Extent of peak decline, estimated as forced expiratory volume in 1 s of % predicted/year, ranged from 2.8 to 4.1 % predicted/year depending on social-environmental adversity. Middle decliners with increased social-environmental adversity experienced rapid decline 14.2 months earlier than their counterparts with lower social-environmental adversity, while timing was similar within other phenotypes. Early and middle decliners experienced mortality peaks during early adolescence and adulthood, respectively.

Conclusion

While early decliners had the most severe CF lung disease, middle and late decliners lost more lung function. Higher social-environmental adversity associated with increased risk of rapid decline and mortality during young adulthood among middle decliners. This sub-phenotype may benefit from enhanced lung-function monitoring and personalized secondary environmental health interventions to mitigate chemical and non-chemical stressors.

Supporting Pharmacovigilance Signal Validation and Prioritization with Analyses of Routinely Collected Health Data: Lessons Learned from an EHDEN Network Study

INTRODUCTION

Individual case reports are the main asset in pharmacovigilance signal management. Signal validation is the first stage after signal detection and aims to determine if there is sufficient evidence to justify further assessment. Throughout signal management, a prioritization of signals is continually made. Routinely collected health data can provide relevant contextual information but are primarily used at a later stage in pharmacoepidemiological studies to assess communicated signals.

OBJECTIVE

The aim of this study was to examine the feasibility and utility of analysing routine health data from a multinational distributed network to support signal validation and prioritization and to reflect on key user requirements for these analyses to become an integral part of this process.

METHODS

Statistical signal detection was performed in VigiBase, the WHO global database of individual case safety reports, targeting generic manufacturer drugs and 16 prespecified adverse events. During a 5-day study-a-thon, signal validation and prioritization were performed using information from VigiBase, regulatory documents and the scientific literature alongside descriptive analyses of routine health data from 10 partners of the European Health Data and Evidence Network (EHDEN). Databases included in the study were from the UK, Spain, Norway, the Netherlands and Serbia, capturing records from primary care and/or hospitals.

RESULTS

Ninety-five statistical signals were subjected to signal validation, of which eight were considered for descriptive analyses in the routine health data. Design, execution and interpretation of results from these analyses took up to a few hours for each signal (of which 15-60 minutes were for execution) and informed decisions for five out of eight signals. The impact of insights from the routine health data varied and included possible alternative explanations, potential public health and clinical impact and feasibility of follow-up pharmacoepidemiological studies. Three signals were selected for signal assessment, two of these decisions were supported by insights from the routine health data. Standardization of analytical code, availability of adverse event phenotypes including bridges between different source vocabularies, and governance around the access and use of routine health data were identified as important aspects for future development.

CONCLUSIONS

Analyses of routine health data from a distributed network to support signal validation and prioritization are feasible in the given time limits and can inform decision making. The cost-benefit of integrating these analyses at this stage of signal management requires further research.

Validation of the Spanish ASQ translation: Screening pediatric patients for suicide-risk in Argentina

BACKGROUND

The high frequency of suicide risk in adolescents necessitates the development and validation of specific tools for systematic screening. To date, there are translated, but not validated suicide risk screening tools in Spanish.

OBJECTIVE

To validate the Spanish version of the Ask Suicide-Screening Questions (ASQ) for suicide risk screening in pediatric patients in Argentina.

METHOD

Using a cross-sectional multicenter design, a convenience sample of pediatric patients aged 10 to 18 years old were recruited from outpatient/inpatient medical settings and private psychiatric clinics. The Spanish version of the Suicidal Ideation Questionnaire (SIQ) assessment tool was used as a standard criterion to validate the ASQ.

RESULTS

A total of 301/380 pediatric patients were screened for suicide risk. Twentyeight percent of the entire sample (83/301) of youth screened positive on the ASQ, and 21% (62/301) screened positive on the SIQ/SIQ-JR and were considered "at risk" for suicide. Compared with the SIQ, the Spanish ASQ yielded a sensitivity of 96.8% (95% Confidence Interval [CI]: 88.8-99.6%), specificity of 90.4% (95% CI: 85.9-93.8%), positive predictive value of 72.3% (95 CI: 61.4-81.6%), and negative predictive value of 99.1% (95% CI: 96.7-99.9%). The positive Likelihood Ratio (LR) was 10.1 (95% CI: 6.1-14.0), and the negative LR was 0.03 (95% CI: -0.01-0.09). Kappa was 0.77 (95% CI: 0.69-0.86), and the Area Under the Curve was 0.94 (95% CI: 0.91-0.97).

CONCLUSION

The Spanish language ASQ demonstrated strong psychometric properties, providing initial evidence that it is a valid tool for identifying Spanish-speaking youth at risk for suicide.

Large-scale characterization of gender differences in diagnosis prevalence and time to diagnosis

We carry out an analysis of gender differences in patterns of disease diagnosis across four large observational health datasets and find that women are routinely older when first assigned most diagnoses. Among 112 acute and chronic diseases, women experience longer lengths of time between symptom onset and disease diagnosis than men for most diseases regardless of metric used, even when only symptoms common to both genders are considered. These findings are consistent for patients with private as well as government insurance. Our analysis highlights systematic gender differences in patterns of disease diagnosis and suggests that symptoms of disease are measured or weighed differently for women and men. Data and code leverage the open-source common data model and analytic code and results are publicly available.

Padé approximant meets federated learning: A nearly lossless, one-shot algorithm for evidence synthesis in distributed research networks with rare outcomes

OBJECTIVE

We developed and evaluated a novel one-shot distributed algorithm for evidence synthesis in distributed research networks with rare outcomes.

MATERIALS AND METHODS

Fed-Padé, motivated by a classic mathematical tool, Padé approximants, reconstructs the multi-site data likelihood via Padé approximant whose key parameters can be computed distributively. Thanks to the simplicity of [2,2] Padé approximant, Fed-Padé requests an extremely simple task and low communication cost for data partners. Specifically, each data partner only needs to compute and share the log-likelihood and its first 4 gradients evaluated at an initial estimator. We evaluated the performance of our algorithm with extensive simulation studies and four observational healthcare databases.

RESULTS

Our simulation studies revealed that a [2,2]-Padé approximant can well reconstruct the multi-site likelihood so that Fed-Padé produces nearly identical estimates to the pooled analysis. Across all simulation scenarios considered, the median of relative bias and rate of instability of our Fed-Padé are both <0.1%, whereas meta-analysis estimates have bias up to 50% and instability up to 75%. Furthermore, the confidence intervals derived from the Fed-Padé algorithm showed better coverage of the truth than confidence intervals based on the meta-analysis. In real data analysis, the Fed-Padé has a relative bias of <1% for all three comparisons for risks of acute liver injury and decreased libido, whereas the meta-analysis estimates have a substantially higher bias (around 10%).

CONCLUSION

The Fed-Padé algorithm is nearly lossless, stable, communication-efficient, and easy to implement for models with rare outcomes. It provides an extremely suitable and convenient approach for synthesizing evidence in distributed research networks with rare outcomes.

The Lived Experiences of Female Relatives of Child Sexual Abuse Material (CSAM) Offenders in Ireland and the United Kingdom

There is a limited understanding about how an association with those that download Child Sexual Abuse Material (CSAM), a highly stigmatized crime, impacts the lives of their innocent family members. Non-offending family members are often considered a valuable protective resource for offender desistance and in safeguarding children from abuse. Therefore, the present study aimed to explore the lived experiences of female family members of CSAM offenders in Ireland and the United Kingdom to both identify and target areas for intervention thus ameliorating their ability to protect. A qualitative research design was adopted, and data analyzed via reflexive thematic analysis. Fifteen individuals self-selected for participation and interviews resulted in the identification of three key themes: Shattered Worldview, The Injured Self; Contamination by Association. The analysis highlighted how non-offending family members experienced considerable shame, trauma, and stigma with consequences that reached into every aspect of their lives. The findings are discussed in the context of the limited available literature along with research implications and recommendations for both policy and practice.

High Resolution and Spatiotemporal Place-Based Computable Exposures at Scale

Place-based exposures, termed "geomarkers", are powerful determinants of health but are often understudied because of a lack of open data and integration tools. Existing DeGAUSS (Decentralized Geomarker Assessment for Multisite Studies) software has been successfully implemented in multi-site studies, ensuring reproducibility and protection of health information. However, DeGAUSS relies on transporting geomarker data, which is not feasible for high-resolution spatiotemporal data too large to store locally or download over the internet. We expanded the DeGAUSS framework for high-resolution spatiotemporal geomarkers. Our approach stores data subsets based on coarsened location and year in an online repository, and appropriate subsets are downloaded to complete exposure assessment locally using exact date and location. We created and validated two free and open-source DeGAUSS containers for estimation of high-resolution, daily ambient air pollutant exposures, transforming published exposure assessment models into computable exposures for geomarker assessment at scale.

Representing and utilizing clinical textual data for real world studies: An OHDSI approach

Clinical documentation in electronic health records contains crucial narratives and details about patients and their care. Natural language processing (NLP) can unlock the information conveyed in clinical notes and reports, and thus plays a critical role in real-world studies. The NLP Working Group at the Observational Health Data Sciences and Informatics (OHDSI) consortium was established to develop methods and tools to promote the use of textual data and NLP in real-world observational studies. In this paper, we describe a framework for representing and utilizing textual data in real-world evidence generation, including representations of information from clinical text in the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM), the workflow and tools that were developed to extract, transform and load (ETL) data from clinical notes into tables in OMOP CDM, as well as current applications and specific use cases of the proposed OHDSI NLP solution at large consortia and individual institutions with English textual data. Challenges faced and lessons learned during the process are also discussed to provide valuable insights for researchers who are planning to implement NLP solutions in real-world studies.

Built environment factors predictive of early rapid lung function decline in cystic fibrosis

BACKGROUND

The extent to which environmental exposures and community characteristics of the built environment collectively predict rapid lung function decline, during adolescence and early adulthood in cystic fibrosis (CF), has not been examined.

OBJECTIVE

To identify built environment characteristics predictive of rapid CF lung function decline.

METHODS

We performed a retrospective, single-center, longitudinal cohort study (n = 173 individuals with CF aged 6-20 years, 2012-2017). We used a stochastic model to predict lung function, measured as forced expiratory volume in 1 s (FEV1 ) of % predicted. Traditional demographic/clinical characteristics were evaluated as predictors. Built environmental predictors included exposure to elemental carbon attributable to traffic sources (ECAT), neighborhood material deprivation (poverty, education, housing, and healthcare access), greenspace near the home, and residential drivetime to the CF center.

MEASUREMENTS AND MAIN RESULTS

The final model, which included ECAT, material deprivation index, and greenspace, alongside traditional demographic/clinical predictors, significantly improved fit and prediction, compared with only demographic/clinical predictors (Likelihood Ratio Test statistic: 26.78, p < 0.0001; the difference in Akaike Information Criterion: 15). An increase of 0.1 μg/m3 of ECAT was associated with 0.104% predicted/yr (95% confidence interval: 0.024, 0.183) more rapid decline. Although not statistically significant, material deprivation was similarly associated (0.1-unit increase corresponded to additional decline of 0.103% predicted/year [-0.113, 0.319]). High-risk regional areas of rapid decline and age-related heterogeneity were identified from prediction mapping.

CONCLUSION

Traffic-related air pollution exposure is an important predictor of rapid pulmonary decline that, coupled with community-level material deprivation and routinely collected demographic/clinical characteristics, enhance CF prognostication and enable personalized environmental health interventions.

Cochlear nerve dysplasia in unilateral severe to profound congenital sensorineural hearing loss - Prevalence in Australian children and the impact of socioeconomic disadvantage on its management

INTRODUCTION

Congenital unilateral sensorineural hearing loss (cuSNHL) carries potentially significant social, educational, and developmental consequences. Early diagnosis enables investigation, and consideration of options for management and early intervention, helping to mitigate the effects of hearing loss. Cochlear nerve dysplasia (CND) is a prominent cause of cuSNHL and may affect candidacy for cochlear implantation. Socioeconomic disadvantage may impact on a patient's family's capacity to participate in necessary intervention and follow-up.

METHODS

Infants with severe-profound cuSNHL referred to a large Australian quaternary pediatric center between October 2004 and December 2020 were retrospectively included. Audiometric and clinical data, and the presence of hearing loss risk factors were obtained from a prospectively collated database. In Australia MRI scans are provided free-of-charge to citizens and residents. MRI scans were reviewed to determine the status of the nerves within the internal acoustic meatus (IAM grade) along with attendance rates. Travel distance to the hospital was also calculated. Reasons for non-attendance at MRI were obtained from patient medical records and correspondence. Socioeconomic, educational, and occupational indices, and travel distances were obtained using patient residential postcodes with reference to Australian Bureau of Statistics data.

RESULTS

A total of 98 patients were reviewed, 64.3% (n = 63) of whom underwent MRI. The median age at diagnosis was 40 days (IQR 27). The prevalence of CND was 75% (n = 47). Importantly, there was no significant difference in the degree of hearing loss between IAM grades (F(4,57) = 1.029, p = 0.405). Socioeconomic indices were significantly lower in patients not attending MRI investigations compared with patients who did attend. Travel distance was not significantly different between the two groups.

CONCLUSION

CND is a prominent cause of cuSNHL in Australian infants. MRI at a young age allows parent education regarding management options and timely intervention where indicated. Socioeconomic disadvantage significantly impacts on participation in further routine assessment of cuSNHL, potentially limiting management options for these children long term.

Racial Fairness in Precision Medicine: Pediatric Asthma Prediction Algorithms

PURPOSE

Quantify and examine the racial fairness of two widely used childhood asthma predictive precision medicine algorithms: the asthma predictive index (API) and the pediatric asthma risk score (PARS).

DESIGN

Apply the API and PARS and evaluate model performance overall and when stratified by race.

SETTING

Cincinnati, OH, USA.

SUBJECTS

A prospective birth cohort of 590 children with clinically measured asthma diagnosis by age seven.

MEASURES

Model diagnostic criteria included sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

ANALYSIS

Significant differences in model performance between Black and white children were considered to be present if the P-value associated with a t-test based on 100 bootstrap replications was less than .05.

RESULTS

Compared to predictions for white children, predictions for Black children using the PARS had a higher sensitivity (.88 vs .57), lower specificity (.55 vs .83), higher PPV (.42 vs .33), but a similar NPV (.93 vs .93). Within the API and compared to predictions for white children, predictions for Black children had a higher sensitivity (.63 vs .53), similar specificity (.81 vs .80), higher PPV (.54 vs .28), and lower NPV (.86 vs .92).

CONCLUSIONS

Overall, racial disparities in model diagnostic criteria were greatest for sensitivity and specificity in the PARS, but racial disparities existed in three of the four criteria for both the PARS and the API.

Characteristics and outcomes of COVID-19 patients with COPD from the United States, South Korea, and Europe

Background: Characterization studies of COVID-19 patients with chronic obstructive pulmonary disease (COPD) are limited in size and scope. The aim of the study is to provide a large-scale characterization of COVID-19 patients with COPD. Methods: We included thirteen databases contributing data from January-June 2020 from North America (US), Europe and Asia. We defined two cohorts of patients with COVID-19 namely a 'diagnosed' and 'hospitalized' cohort. We followed patients from COVID-19 index date to 30 days or death. We performed descriptive analysis and reported the frequency of characteristics and outcomes among COPD patients with COVID-19. Results: The study included 934,778 patients in the diagnosed COVID-19 cohort and 177,201 in the hospitalized COVID-19 cohort. Observed COPD prevalence in the diagnosed cohort ranged from 3.8% (95%CI 3.5-4.1%) in French data to 22.7% (95%CI 22.4-23.0) in US data, and from 1.9% (95%CI 1.6-2.2) in South Korean to 44.0% (95%CI 43.1-45.0) in US data, in the hospitalized cohorts. COPD patients in the hospitalized cohort had greater comorbidity than those in the diagnosed cohort, including hypertension, heart disease, diabetes and obesity. Mortality was higher in COPD patients in the hospitalized cohort and ranged from 7.6% (95%CI 6.9-8.4) to 32.2% (95%CI 28.0-36.7) across databases. ARDS, acute renal failure, cardiac arrhythmia and sepsis were the most common outcomes among hospitalized COPD patients.   Conclusion: COPD patients with COVID-19 have high levels of COVID-19-associated comorbidities and poor COVID-19 outcomes. Further research is required to identify patients with COPD at high risk of worse outcomes.

Characteristics and outcomes of COVID-19 patients with and without asthma from the United States, South Korea, and Europe

Objective: Large international comparisons describing the clinical characteristics of patients with COVID-19 are limited. The aim of the study was to perform a large-scale descriptive characterization of COVID-19 patients with asthma.Methods: We included nine databases contributing data from January to June 2020 from the US, South Korea (KR), Spain, UK and the Netherlands. We defined two cohorts of COVID-19 patients ('diagnosed' and 'hospitalized') based on COVID-19 disease codes. We followed patients from COVID-19 index date to 30 days or death. We performed descriptive analysis and reported the frequency of characteristics and outcomes in people with asthma defined by codes and prescriptions.Results: The diagnosed and hospitalized cohorts contained 666,933 and 159,552 COVID-19 patients respectively. Exacerbation in people with asthma was recorded in 1.6-8.6% of patients at presentation. Asthma prevalence ranged from 6.2% (95% CI 5.7-6.8) to 18.5% (95% CI 18.2-18.8) in the diagnosed cohort and 5.2% (95% CI 4.0-6.8) to 20.5% (95% CI 18.6-22.6) in the hospitalized cohort. Asthma patients with COVID-19 had high prevalence of comorbidity including hypertension, heart disease, diabetes and obesity. Mortality ranged from 2.1% (95% CI 1.8-2.4) to 16.9% (95% CI 13.8-20.5) and similar or lower compared to COVID-19 patients without asthma. Acute respiratory distress syndrome occurred in 15-30% of hospitalized COVID-19 asthma patients.Conclusion: The prevalence of asthma among COVID-19 patients varies internationally. Asthma patients with COVID-19 have high comorbidity. The prevalence of asthma exacerbation at presentation was low. Whilst mortality was similar among COVID-19 patients with and without asthma, this could be confounded by differences in clinical characteristics. Further research could help identify high-risk asthma patients.[Box: see text]Supplemental data for this article is available online at https://doi.org/10.1080/02770903.2021.2025392 .

Evaluating a novel approach to stimulate open science collaborations: a case series of "study-a-thon" events within the OHDSI and European IMI communities

OBJECTIVE

We introduce and review the concept of a study-a-thon as a catalyst for open science in medicine, utilizing harmonized real world, observation health data, tools, skills, and methods to conduct network studies, generating insights for those wishing to use study-a-thons for future research.

MATERIALS AND METHODS

A series of historical study-a-thons since 2017 to present were reviewed for thematic insights as to the opportunity to accelerate the research method to conduct studies across therapeutic areas. Review of publications and experience of the authors generated insights to illustrate the conduct of study-a-thons, key learning, and direction for those wishing to conduct future such study-a-thons.

RESULTS

A review of six study-a-thons have provided insights into their scientific impact, and 13 areas of insights for those wishing to conduct future study-a-thons. Defining aspects of the study-a-thon method for rapid, collaborative research through network studies reinforce the need to clear scientific rationale, tools, skills, and methods being collaboratively to conduct a focused study. Well-characterized preparatory, execution and postevent phases, coalescing skills, experience, data, clinical input (ensuring representative clinical context to the research query), and well-defined, logical steps in conducting research via the study-a-thon method are critical.

CONCLUSIONS

A study-a-thon is a focused multiday research event generating reliable evidence on a specific medical topic across different countries and health systems. In a study-a-thon, a multidisciplinary team collaborate to create an accelerated contribution to scientific evidence and clinical practice. It critically accelerates the research process, without inhibiting the quality of the research output and evidence generation, through a reproducible process.

Air pollution, depressive and anxiety disorders, and brain effects: A systematic review

Accumulating data suggest that air pollution increases the risk of internalizing psychopathology, including anxiety and depressive disorders. Moreover, the link between air pollution and poor mental health may relate to neurostructural and neurofunctional changes. We systematically reviewed the MEDLINE database in September 2021 for original articles reporting effects of air pollution on 1) internalizing symptoms and behaviors (anxiety or depression) and 2) frontolimbic brain regions (i.e., hippocampus, amygdala, prefrontal cortex). One hundred and eleven articles on mental health (76% human, 24% animals) and 92 on brain structure and function (11% human, 86% animals) were identified. For literature search 1, the most common pollutants examined were PM2.5 (64.9%), NO2 (37.8%), and PM10 (33.3%). For literature search 2, the most common pollutants examined were PM2.5 (32.6%), O3 (26.1%) and Diesel Exhaust Particles (DEP) (26.1%). The majority of studies (73%) reported higher internalizing symptoms and behaviors with higher air pollution exposure. Air pollution was consistently associated (95% of articles reported significant findings) with neurostructural and neurofunctional effects (e.g., increased inflammation and oxidative stress, changes to neurotransmitters and neuromodulators and their metabolites) within multiple brain regions (24% of articles), or within the hippocampus (66%), PFC (7%), and amygdala (1%). For both literature searches, the most studied exposure time frames were adulthood (48% and 59% for literature searches 1 and 2, respectively) and the prenatal period (26% and 27% for literature searches 1 and 2, respectively). Forty-three percent and 29% of studies assessed more than one exposure window in literature search 1 and 2, respectively. The extant literature suggests that air pollution is associated with increased depressive and anxiety symptoms and behaviors, and alterations in brain regions implicated in risk of psychopathology. However, there are several gaps in the literature, including: limited studies examining the neural consequences of air pollution in humans. Further, a comprehensive developmental approach is needed to examine windows of susceptibility to exposure and track the emergence of psychopathology following air pollution exposure.

Corrigendum: Vaccine safety surveillance using routinely collected healthcare data-An empirical evaluation of epidemiological designs

[This corrects the article DOI: 10.3389/fphar.2022.893484.].

Adaptation and validation of a coding algorithm for the Charlson Comorbidity Index in administrative claims data using the SNOMED CT standardized vocabulary

Objectives

The Charlson comorbidity index (CCI), the most ubiquitous comorbid risk score, predicts one-year mortality among hospitalized patients and provides a single aggregate measure of patient comorbidity. The Quan adaptation of the CCI revised the CCI coding algorithm for applications to administrative claims data using the International Classification of Diseases (ICD). The purpose of the current study is to adapt and validate a coding algorithm for the CCI using the SNOMED CT standardized vocabulary, one of the most commonly used vocabularies for data collection in healthcare databases in the U.S.

Methods

The SNOMED CT coding algorithm for the CCI was adapted through the direct translation of the Quan coding algorithms followed by manual curation by clinical experts. The performance of the SNOMED CT and Quan coding algorithms were compared in the context of a retrospective cohort study of inpatient visits occurring during the calendar years of 2013 and 2018 contained in two U.S. administrative claims databases. Differences in the CCI or frequency of individual comorbid conditions were assessed using standardized mean differences (SMD). Performance in predicting one-year mortality among hospitalized patients was measured based on the c-statistic of logistic regression models.

Results

For each database and calendar year combination, no significant differences in the CCI or frequency of individual comorbid conditions were observed between vocabularies (SMD ≤ 0.10). Specifically, the difference in CCI measured using the SNOMED CT vs. Quan coding algorithms was highest in MDCD in 2013 (3.75 vs. 3.6; SMD = 0.03) and lowest in DOD in 2018 (3.93 vs. 3.86; SMD = 0.02). Similarly, as indicated by the c-statistic, there was no evidence of a difference in the performance between coding algorithms in predicting one-year mortality (SNOMED CT vs. Quan coding algorithms, range: 0.725–0.789 vs. 0.723–0.787, respectively). A total of 700 of 5,348 (13.1%) ICD code mappings were inconsistent between coding algorithms. The most common cause of discrepant codes was multiple ICD codes mapping to a SNOMED CT code (n = 560) of which 213 were deemed clinically relevant thereby leading to information gain.

Conclusion

The current study repurposed an important tool for conducting observational research to use the SNOMED CT standardized vocabulary.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-022-02006-1.

Development and external validation of prediction models for adverse health outcomes in rheumatoid arthritis: A multinational real-world cohort analysis

BACKGROUND

Identification of rheumatoid arthritis (RA) patients at high risk of adverse health outcomes remains a major challenge. We aimed to develop and validate prediction models for a variety of adverse health outcomes in RA patients initiating first-line methotrexate (MTX) monotherapy.

METHODS

Data from 15 claims and electronic health record databases across 9 countries were used. Models were developed and internally validated on Optum® De-identified Clinformatics® Data Mart Database using L1-regularized logistic regression to estimate the risk of adverse health outcomes within 3 months (leukopenia, pancytopenia, infection), 2 years (myocardial infarction (MI) and stroke), and 5 years (cancers [colorectal, breast, uterine] after treatment initiation. Candidate predictors included demographic variables and past medical history. Models were externally validated on all other databases. Performance was assessed using the area under the receiver operator characteristic curve (AUC) and calibration plots.

FINDINGS

Models were developed and internally validated on 21,547 RA patients and externally validated on 131,928 RA patients. Models for serious infection (AUC: internal 0.74, external ranging from 0.62 to 0.83), MI (AUC: internal 0.76, external ranging from 0.56 to 0.82), and stroke (AUC: internal 0.77, external ranging from 0.63 to 0.95), showed good discrimination and adequate calibration. Models for the other outcomes showed modest internal discrimination (AUC < 0.65) and were not externally validated.

INTERPRETATION

We developed and validated prediction models for a variety of adverse health outcomes in RA patients initiating first-line MTX monotherapy. Final models for serious infection, MI, and stroke demonstrated good performance across multiple databases and can be studied for clinical use.

FUNDING

This activity under the European Health Data & Evidence Network (EHDEN) has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 806968. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA.

Mid‐term outcomes of concomitant Cox‐Maze IV: Results from a multicenter prospective registry

Background

Benefits of concomitant atrial fibrillation (AF) surgical treatment are well established. Cardiac societies support treating AF during cardiac surgery with a class I recommendation. Despite these guidelines, adoption has been inconsistent. We report results of routine performance of concomitant Cox‐Maze IV (CMIV) from participating centers using a standardized, prospective registry.

Methods

Nine surgeons at four cardiac surgery programs enrolled 807 patients undergoing concomitant CMIV surgery over 12 years. Lesions were created using bipolar radiofrequency clamps and cryoablation probes. Follow‐up occurred at 3‐ and 6‐months, then annually for 3 years. Freedom from AF was defined as no episode >30 s of atrial arrhythmia.

Results

Sixty‐four percent of patients were male, mean age 69 years, mean left atrial size 4.6 cm, mean preoperative AF duration 4.0 years, mean EuroSCORE 6.4, and mean CHADS₂ score 3.1. Thirty‐day postoperative mortality and neurologic event rates were 3.3% and 1.3%, respectively. New pacemaker implant rate was 6.3%. Freedom from AF rates at 1‐ and 3‐years stratified by preoperative AF type were: paroxysmal 94.6% and 87.5%, persistent 82.1% and 81.9%, and longstanding persistent 84.1% and 78.1%. At 3‐year follow up, 84% of patients were off antiarrhythmic drugs and 74% of sinus rhythm patients were off oral anticoagulants.

Conclusions

Routine CMIV is safe and effective. Acceptable outcomes can be achieved across multiple centers and multiple operators even in a moderate risk patient population undergoing more complex procedures. Surgeons and institutions should be encouraged by all cardiac societies to adopt the CMIV procedure to maximize patient benefit.

Vaccine Safety Surveillance Using Routinely Collected Healthcare Data-An Empirical Evaluation of Epidemiological Designs

Background: Routinely collected healthcare data such as administrative claims and electronic health records (EHR) can complement clinical trials and spontaneous reports to detect previously unknown risks of vaccines, but uncertainty remains about the behavior of alternative epidemiologic designs to detect and declare a true risk early. Methods: Using three claims and one EHR database, we evaluate several variants of the case-control, comparative cohort, historical comparator, and self-controlled designs against historical vaccinations using real negative control outcomes (outcomes with no evidence to suggest that they could be caused by the vaccines) and simulated positive control outcomes. Results: Most methods show large type 1 error, often identifying false positive signals. The cohort method appears either positively or negatively biased, depending on the choice of comparator index date. Empirical calibration using effect-size estimates for negative control outcomes can bring type 1 error closer to nominal, often at the cost of increasing type 2 error. After calibration, the self-controlled case series (SCCS) design most rapidly detects small true effect sizes, while the historical comparator performs well for strong effects. Conclusion: When applying any method for vaccine safety surveillance we recommend considering the potential for systematic error, especially due to confounding, which for many designs appears to be substantial. Adjusting for age and sex alone is likely not sufficient to address differences between vaccinated and unvaccinated, and for the cohort method the choice of index date is important for the comparability of the groups. Analysis of negative control outcomes allows both quantification of the systematic error and, if desired, subsequent empirical calibration to restore type 1 error to its nominal value. In order to detect weaker signals, one may have to accept a higher type 1 error.

Popular interventions to enhance sustained attention in children and adolescents: A critical systematic review

There are a myriad of interventions promoting activities designed to help enhance sustained attention in children and adolescents. In this systematic review, we critically evaluate the evidence behind three popular sustained attention training approaches - cognitive attention training, meditation, and physical activity. Seven databases were searched in addition to secondary searches. Cognitive attention training, meditation training or physical activity intervention studies aimed at improving sustained attention (randomised-controlled or non-randomised-controlled designs) in samples of children and adolescents (3-18 years) were included. We screened 3437 unique articles. Thirty-seven studies satisfied inclusion criteria. In general, cognitive attention training (n = 14) did not reliably improve sustained attention. Physical activity (n = 15) and meditation interventions (n = 8) demonstrated somewhat more potential in enhancing sustained attention, but these effects should be considered preliminary and need to be replicated with greater methodological rigour. Cognitive attention training demonstrated very limited transfer to other aspects of attention. Notably, mindfulness training had rather consistent positive effects on selective attention. Across all three intervention types, there was very weak evidence for transfer to other aspects of cognition, behaviour, and academic achievement. The paper concludes with methodological recommendations for future studies to strengthen the evidence base.

Differential anchoring effects of vaccination comparator selection: characterizing a potential bias due to healthcare utilization in COVID-19 versus influenza

Background

Observational data enables large-scale vaccine safety surveillance but requires careful evaluation of the potential sources of bias. One potential source of bias is the index date selection procedure for the unvaccinated cohort or unvaccinated comparison time (“anchoring”).

Objective

Here, we evaluated the different index date selection procedures for 2 vaccinations: COVID-19 and influenza.

Methods

For each vaccine, we extracted patient baseline characteristics on the index date and up to 450 days prior and then compared them to the characteristics of the unvaccinated patients indexed on (1) an arbitrary date or (2) a date of a visit. Additionally, we compared vaccinated patients indexed on the date of vaccination and the same patients indexed on a prior date or visit.

Results

COVID-19 vaccination and influenza vaccination differ drastically from each other in terms of the populations vaccinated and their status on the day of vaccination. When compared to indexing on a visit in the unvaccinated population, influenza vaccination had markedly higher covariate proportions, and COVID-19 vaccination had lower proportions of most covariates on the index date. In contrast, COVID-19 vaccination had similar covariate proportions when compared to an arbitrary date. These effects attenuated, but were still present, with a longer lookback period. The effect of day 0 was present even when the patients served as their own controls.

Conclusions

Patient baseline characteristics are sensitive to the choice of the index date. In vaccine safety studies, unexposed index event should represent vaccination settings. Study designs previously used to assess influenza vaccination must be reassessed for COVID-19 to account for a potentially healthier population and lack of medical activity on the day of vaccination.

P104 Comparative risk of infection for first-line csDMARD therapy in rheumatoid arthritis: a multinational cohort analysis of real world data

Background/Aims

Infections on conventional synthetic disease modifying anti-rheumatic drugs (csDMARDs) are an important concern for rheumatoid arthritis (RA) patients, especially during the COVID-19 pandemic. However comparative safety data between csDMARDs have been conflicting and limited in power. The objective was to assess the comparative safety of serious, opportunistic and all infections (including non-serious) of first-line csDMARDs in RA through a large multinational observational study.

Methods

We evaluated first-line new users of methotrexate (MTX), hydroxychloroquine (HCQ), sulfasalazine (SZ) and leflunomide (LEF) monotherapy. Data was obtained from four US databases (IQVIA US Ambulatory EMR (AMBER), Optum® De-identified Clinformatics® Datamart (Optum), IBM MarketScan® Medicare Supplemental Database (MDCR), and IBM MarketScan Commercial Database (CCAE)), one from Germany (IQVIA Disease Analyser Germany EMR (Germany)), and another from the UK (IQVIA UK The Health Improvement Network). Patients included were ≥18 years with a RA diagnosis between 2005-2019, without prior inflammatory arthritis, cancer or infection (in the preceding 30 days). Serious infections were defined as those requiring hospitalisation or resulting in death within 30 days; opportunistic infections were defined as per published EULAR consensus. Patients were followed from 1-day following treatment initiation to the earliest of treatment discontinuation, switching, or add-on plus 14 days, or loss to follow-up. Cox proportional-hazards models for MTX against each csDMARD with large-scale propensity score stratification were performed. A large set of negative control outcomes were used to calibrate hazard ratios (cHR) to account for potential residual confounding. Estimates were pooled where homogeneity across sources was adequate (I2&lt;0.4).

Results

A total of 247,511 patients were included (MTX: 141,647; HCQ: 73,286, SSZ: 16,521, LEF: 16,057), with pooled incidence rates of serious, opportunistic and all infections across sources for MTX users of 33.7, 20.1 and 311.8 per 1,000 pyrs, respectively. With MTX as the referent, for all infections, the pooled cHR (with 95% Confidence Intervals) for SSZ was 0.73 (0.62, 0.86); HCQ, 0.96 (0.89, 1.04); and LEF, 0.74 (0.50, 1.08). The serious infection pooled cHR for SSZ was 0.75 (0.58, 0.97) and for LEF, 0.93 (0.61, 1.40). For opportunistic infections, pooled cHR for HCQ was 1.04 (0.92, 1.19).

Conclusion

SSZ, LEF and less consistently HCQ had a lower risk of all (including non-serious) infections, compared to MTX. SSZ and LEF were associated with a 25% reduction in the expected risk of all infections. SSZ was associated with a 25% lower risk of serious infections relative to MTX. In the first large scale observational network study assessing comparative risk of infection with csDMARDs there were differences between drugs in risk for all infections, with potential implications for clinical care.

Disclosure

M. Jani: None. E. Burn: None. J. Weaver: Corporate appointments; Janssen. L. Carmona: None. K. Chatzidionysiou: None. B. Illigen: None. D. Vizcaya: Corporate appointments; Bayer. T. Duarte-Salles: None. P. Ryan: Corporate appointments; Janssen. D. Prieto-Alhambra: None.

Current Approaches to Vaccine Safety Using Observational Data: A Rationale for the EUMAEUS (Evaluating Use of Methods for Adverse Events Under Surveillance-for Vaccines) Study Design

Post-marketing vaccine safety surveillance aims to detect adverse events following immunization in a population. Whether certain methods of surveillance are more precise and unbiased in generating safety signals is unclear. Here, we synthesized information from existing literature to provide an overview of the strengths, weaknesses, and clinical applications of epidemiologic and analytical methods used in vaccine monitoring, focusing on cohort, case-control and self-controlled designs. These designs are proposed to be evaluated in the EUMAEUS (Evaluating Use of Methods for Adverse Event Under Surveillance-for vaccines) study because of their widespread use and potential utility. Over the past decades, there have been an increasing number of epidemiological study designs used for vaccine safety surveillance. While traditional cohort and case-control study designs remain widely used, newer, novel designs such as the self-controlled case series and self-controlled risk intervals have been developed. Each study design comes with its strengths and limitations, and the most appropriate study design will depend on availability of resources, access to records, number and distribution of cases, and availability of population coverage data. Several assumptions have to be made while using the various study designs, and while the goal is to mitigate any biases, violations of these assumptions are often still present to varying degrees. In our review, we discussed some of the potential biases (i.e., selection bias, misclassification bias and confounding bias), and ways to mitigate them. While the types of epidemiological study designs are well established, a comprehensive comparison of the analytical aspects (including method evaluation and performance metrics) of these study designs are relatively less well studied. We summarized the literature, reporting on two simulation studies, which compared the detection time, empirical power, error rate and risk estimate bias across the above-mentioned study designs. While these simulation studies provided insights on the analytic performance of each of the study designs, its applicability to real-world data remains unclear. To bridge that gap, we provided the rationale of the EUMAEUS study, with a brief description of the study design; and how the use of real-world multi-database networks can provide insights into better methods evaluation and vaccine safety surveillance.

Characteristics and outcomes of COVID-19 patients with COPD from the United States, South Korea, and Europe

Background: Characterization studies of COVID-19 patients with chronic obstructive pulmonary disease (COPD) are limited in size and scope. The aim of the study is to provide a large-scale characterization of COVID-19 patients with COPD. Methods: We included thirteen databases contributing data from January-June 2020 from North America (US), Europe and Asia. We defined two cohorts of patients with COVID-19 namely a 'diagnosed' and 'hospitalized' cohort. We followed patients from COVID-19 index date to 30 days or death. We performed descriptive analysis and reported the frequency of characteristics and outcomes among COPD patients with COVID-19. Results: The study included 934,778 patients in the diagnosed COVID-19 cohort and 177,201 in the hospitalized COVID-19 cohort. Observed COPD prevalence in the diagnosed cohort ranged from 3.8% (95%CI 3.5-4.1%) in French data to 22.7% (95%CI 22.4-23.0) in US data, and from 1.9% (95%CI 1.6-2.2) in South Korean to 44.0% (95%CI 43.1-45.0) in US data, in the hospitalized cohorts. COPD patients in the hospitalized cohort had greater comorbidity than those in the diagnosed cohort, including hypertension, heart disease, diabetes and obesity. Mortality was higher in COPD patients in the hospitalized cohort and ranged from 7.6% (95%CI 6.9-8.4) to 32.2% (95%CI 28.0-36.7) across databases. ARDS, acute renal failure, cardiac arrhythmia and sepsis were the most common outcomes among hospitalized COPD patients.   Conclusion: COPD patients with COVID-19 have high levels of COVID-19-associated comorbidities and poor COVID-19 outcomes. Further research is required to identify patients with COPD at high risk of worse outcomes.

Residential bacteria and fungi identified by high-throughput sequencing and childhood respiratory health

The objective of this study was to examine and compare environmental microbiota from dust and children's respiratory health outcomes at ages seven and twelve. At age seven, in-home visits were conducted for children enrolled in the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS). Floor dust was collected and analyzed for bacterial (16 S rRNA gene) and fungal (internal transcribed spacer region) microbiota. Respiratory outcomes, including physician-diagnosed asthma, wheeze, rhinitis, and aeroallergen sensitivity were assessed by physical examination and caregiver-report at ages seven and twelve. The associations between dust microbiota and respiratory outcomes were evaluated using Permanova, DESeq, and weighted quantile sum (WQS) regression models. Four types of WQS regression models were run to identify mixtures of fungi or bacteria that were associated with the absence or presence of health outcomes. For alpha or beta diversity of fungi and bacteria, no significant associations were found with respiratory health outcomes. DESeq identified specific bacterial and fungal indicator taxa that were higher or lower with the presence of different health outcomes. Most individual indicator fungal species were lower with asthma and wheeze and higher with aeroallergen positivity and rhinitis, whereas bacterial data was less consistent. WQS regression models demonstrated that a combination of species might influence health outcomes. Several heavily weighted species had a strong influence on the models, and therefore, created a microbial community that was associated with the absence or presence of asthma, wheeze, rhinitis, and aeroallergen+. Weights for specific species within WQS regression models supported indicator taxa findings. Health outcomes might be more influenced by the composition of a complex mixture of bacterial and fungal species in the indoor environment than by the absence or presence of individual species. This study demonstrates that WQS is a useful tool in evaluating mixtures in relation to potential health effects.

Risk of Surgical Site Infections in OTA/AO Type C Tibial Plateau and Tibial Plafond Fractures: A Systematic Review and Meta-Analysis

OBJECTIVES

To analyze the current incidence of postoperative infection for OTA/AO type C fractures of the tibial plateau and tibial plafond.

DATA SOURCES

Three medical databases: PubMed/MEDLINE, ScienceDirect, and the Cochrane Library, were used in our systematic literature search. Search results were restricted to articles transcribed in English/Spanish and publication date after January 1, 2000, to present day.

STUDY SELECTION

Inclusion criteria were studies reporting postoperative infection data for OTA/AO type 41C, 43C, or equivalent fractures of skeletally mature individuals. A minimum of 6 total fractures of interest and a frequency of 75% overall were required. Studies reporting on pathologic fractures, stress fractures, or low-energy fracture types were excluded.

DATA EXTRACTION

Two authors independently screened abstracts, evaluated full-text manuscripts, and extracted relevant data from included studies. Any instances of discrepancy were resolved within the study committee by consensus.

DATA SYNTHESIS

Outcomes were expressed using direct proportions (PR) with a 95% confidence interval. The effects of comorbidities on infection rates were reported using odds ratios with a 95% confidence interval. All analyses used a DerSimonian-Laird estimate with a random-effects model based on heterogeneity. The presence of publication bias was evaluated using funnel plots and Egger's tests.

CONCLUSIONS

Patients with these specific fractures develop infections at a notable frequency. The rates of deep infections were approximately 6% in tibial plateau fractures and 9% in tibial plafond fractures. These results may be useful as a reference for patient counseling and other future studies aimed at minimizing postoperative infection for these injuries.

LEVEL OF EVIDENCE

Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Characteristics and outcomes of COVID-19 patients with COPD from the United States, South Korea, and Europe

Background: Characterization studies of COVID-19 patients with chronic obstructive pulmonary disease (COPD) are limited in size and scope. The aim of the study is to provide a large-scale characterization of COVID-19 patients with COPD. Methods: We included thirteen databases contributing data from January-June 2020 from North America (US), Europe and Asia. We defined two cohorts of patients with COVID-19 namely a 'diagnosed' and 'hospitalized' cohort. We followed patients from COVID-19 index date to 30 days or death. We performed descriptive analysis and reported the frequency of characteristics and outcomes among COPD patients with COVID-19. Results: The study included 934,778 patients in the diagnosed COVID-19 cohort and 177,201 in the hospitalized COVID-19 cohort. Observed COPD prevalence in the diagnosed cohort ranged from 3.8% (95%CI 3.5-4.1%) in French data to 22.7% (95%CI 22.4-23.0) in US data, and from 1.9% (95%CI 1.6-2.2) in South Korean to 44.0% (95%CI 43.1-45.0) in US data, in the hospitalized cohorts. COPD patients in the hospitalized cohort had greater comorbidity than those in the diagnosed cohort, including hypertension, heart disease, diabetes and obesity. Mortality was higher in COPD patients in the hospitalized cohort and ranged from 7.6% (95%CI 6.9-8.4) to 32.2% (95%CI 28.0-36.7) across databases. ARDS, acute renal failure, cardiac arrhythmia and sepsis were the most common outcomes among hospitalized COPD patients.   Conclusion: COPD patients with COVID-19 have high levels of COVID-19-associated comorbidities and poor COVID-19 outcomes. Further research is required to identify patients with COPD at high risk of worse outcomes.

Unique and overlapping contributions of sustained attention and working memory to parent and teacher ratings of inattentive behavior

Sustained attention and working memory are two closely intertwined executive functions that may underlie inattentive behavior. However, little research has teased apart their precise contributions in a single study. This study examines the extent to which ratings of children's inattentive behavior are associated with these executive functions. Specifically, we investigated the unique and overlapping statistical contributions of sustained attention capacity and working memory capacity to parent and teacher ratings of inattentive behavior (operationalized as scores on both the Inattentive and Hyperactive/Impulsive scales of the Conners' Rating Scale), while controlling for IQ. Children aged 8-11 years completed measures of sustained attention capacity, working memory capacity and IQ. Parents and teachers completed Conners-3 Parent and Teacher Short Forms, as a measure of inattentive behavior. We found that the unique statistical contribution of sustained attention capacity emerged as the most important factor in both parent and teacher ratings of inattentive behavior, with effects of moderate magnitude. In contrast, working memory capacity accounted for a small amount of variance. The overlap between sustained attention and working memory explained a small but substantive amount of variance in inattentive behavior. These findings support the idea that sustained attention and working memory are distinct executive functions that may contribute to goal-directed behavior both uniquely and through their interactions.

Towards a broader concept of wellbeing in evaluating paediatric quality of life

Paediatric health-care professionals have a primary duty to promote the best interests of their patients. This is reiterated in article 3 of the United Nations Convention on the Rights of the Child and is predicated on promoting children's health and wellbeing. However, there is ambiguity over what standard applies when evaluating whether a paediatric health-care decision supports good outcomes. Values like 'best interests', 'doing no harm' or 'quality of life' may be indeterminate or vague and clinicians may have difficulty in conceptualising what exactly constitutes 'a good life' for children. This uncertainty leads to the question: how do we best evaluate paediatric health decisions and outcomes? Patient-reported outcome measures (PROMs) are questionnaires that aim to achieve this by attaining data on a patient's quality of life and wellbeing. While PROMs originated with adult cohorts, they have since been applied to paediatric populations. Children are vulnerable due to their interdependency; and this raises ethical tensions regarding the potential benefits of such data, respect for autonomy and assent/consent of the individual child in clinical settings. These inherent tensions should be balanced by realising a collective good for children. PROMs should be a robust data collection source that facilitates substantive justice, both procedurally and in distributing limited health resources via accurate quality-adjusted life-years generation. This article aims to (i) overview the traditional and emerging paediatric PROMs; (ii) outline the tensions of using PROMS for children in a clinical setting and (iii) analyse the ability of traditional and emerging PROMs to promote justice in paediatric resource allocation.

Phenotyping in distributed data networks: selecting the right codes for the right patients

Observational data can be used to conduct drug surveillance and effectiveness studies, investigate treatment pathways, and predict patient outcomes. Such studies require developing executable algorithms to find patients of interest or phenotype algorithms. Creating reliable and comprehensive phenotype algorithms in data networks is especially hard as differences in patient representation and data heterogeneity must be considered. In this paper, we discuss a process for creating a comprehensive concept set and a recommender system we built to facilitate it. PHenotype Observed Entity Baseline Endorsements (PHOEBE) uses the data on code utilization across 22 electronic health record and claims datasets mapped to the Observational Health Data Sciences and Informatics (OHDSI) Common Data Model from the 6 countries to recommend semantically and lexically similar codes. Coupled with Cohort Diagnostics, it is now used in major network OHDSI studies. When used to create patient cohorts, PHOEBE identifies more patients and captures them earlier in the course of the disease.

Investigating the impact of development and internal validation design when training prognostic models using a retrospective cohort in big US observational healthcare data

OBJECTIVE

The internal validation of prediction models aims to quantify the generalisability of a model. We aim to determine the impact, if any, that the choice of development and internal validation design has on the internal performance bias and model generalisability in big data (n~500 000).

DESIGN

Retrospective cohort.

SETTING

Primary and secondary care; three US claims databases.

PARTICIPANTS

1 200 769 patients pharmaceutically treated for their first occurrence of depression.

METHODS

We investigated the impact of the development/validation design across 21 real-world prediction questions. Model discrimination and calibration were assessed. We trained LASSO logistic regression models using US claims data and internally validated the models using eight different designs: 'no test/validation set', 'test/validation set' and cross validation with 3-fold, 5-fold or 10-fold with and without a test set. We then externally validated each model in two new US claims databases. We estimated the internal validation bias per design by empirically comparing the differences between the estimated internal performance and external performance.

RESULTS

The differences between the models' internal estimated performances and external performances were largest for the 'no test/validation set' design. This indicates even with large data the 'no test/validation set' design causes models to overfit. The seven alternative designs included some validation process to select the hyperparameters and a fair testing process to estimate internal performance. These designs had similar internal performance estimates and performed similarly when externally validated in the two external databases.

CONCLUSIONS

Even with big data, it is important to use some validation process to select the optimal hyperparameters and fairly assess internal validation using a test set or cross-validation.

Characteristics and outcomes of patients with COVID-19 with and without prevalent hypertension: a multinational cohort study

OBJECTIVE

To characterise patients with and without prevalent hypertension and COVID-19 and to assess adverse outcomes in both inpatients and outpatients.

DESIGN AND SETTING

This is a retrospective cohort study using 15 healthcare databases (primary and secondary electronic healthcare records, insurance and national claims data) from the USA, Europe and South Korea, standardised to the Observational Medical Outcomes Partnership common data model. Data were gathered from 1 March to 31 October 2020.

PARTICIPANTS

Two non-mutually exclusive cohorts were defined: (1) individuals diagnosed with COVID-19 (diagnosed cohort) and (2) individuals hospitalised with COVID-19 (hospitalised cohort), and stratified by hypertension status. Follow-up was from COVID-19 diagnosis/hospitalisation to death, end of the study period or 30 days.

OUTCOMES

Demographics, comorbidities and 30-day outcomes (hospitalisation and death for the 'diagnosed' cohort and adverse events and death for the 'hospitalised' cohort) were reported.

RESULTS

We identified 2 851 035 diagnosed and 563 708 hospitalised patients with COVID-19. Hypertension was more prevalent in the latter (ranging across databases from 17.4% (95% CI 17.2 to 17.6) to 61.4% (95% CI 61.0 to 61.8) and from 25.6% (95% CI 24.6 to 26.6) to 85.9% (95% CI 85.2 to 86.6)). Patients in both cohorts with hypertension were predominantly >50 years old and female. Patients with hypertension were frequently diagnosed with obesity, heart disease, dyslipidaemia and diabetes. Compared with patients without hypertension, patients with hypertension in the COVID-19 diagnosed cohort had more hospitalisations (ranging from 1.3% (95% CI 0.4 to 2.2) to 41.1% (95% CI 39.5 to 42.7) vs from 1.4% (95% CI 0.9 to 1.9) to 15.9% (95% CI 14.9 to 16.9)) and increased mortality (ranging from 0.3% (95% CI 0.1 to 0.5) to 18.5% (95% CI 15.7 to 21.3) vs from 0.2% (95% CI 0.2 to 0.2) to 11.8% (95% CI 10.8 to 12.8)). Patients in the COVID-19 hospitalised cohort with hypertension were more likely to have acute respiratory distress syndrome (ranging from 0.1% (95% CI 0.0 to 0.2) to 65.6% (95% CI 62.5 to 68.7) vs from 0.1% (95% CI 0.0 to 0.2) to 54.7% (95% CI 50.5 to 58.9)), arrhythmia (ranging from 0.5% (95% CI 0.3 to 0.7) to 45.8% (95% CI 42.6 to 49.0) vs from 0.4% (95% CI 0.3 to 0.5) to 36.8% (95% CI 32.7 to 40.9)) and increased mortality (ranging from 1.8% (95% CI 0.4 to 3.2) to 25.1% (95% CI 23.0 to 27.2) vs from 0.7% (95% CI 0.5 to 0.9) to 10.9% (95% CI 10.4 to 11.4)) than patients without hypertension.

CONCLUSIONS

COVID-19 patients with hypertension were more likely to suffer severe outcomes, hospitalisations and deaths compared with those without hypertension.

An Evidence-Based Protocol for Manual Prone Positioning of Patients With ARDS

BACKGROUND

Manual prone positioning has been shown to reduce mortality among patients with moderate to severe acute respiratory distress syndrome, but it is associated with a high incidence of pressure injuries and unplanned extubations. This study investigated the feasibility of safely implementing a manual prone positioning protocol that uses a dedicated device.

REVIEW OF EVIDENCE

A search of CINAHL and Medline identified multiple randomized controlled trials and meta-analyses that demonstrated both the reduction of mortality when prone positioning is used for more than 12 hours per day in patients with acute respiratory distress syndrome and the most common complications of this treatment.

IMPLEMENTATION

An existing safe patient-handling device was modified to enable staff to safely perform manual prone positioning with few complications for patients receiving mechanical ventilation. All staff received training on the protocol and use of the device before implementation.

EVALUATION

This study included 36 consecutive patients who were admitted to the medical intensive care unit at a large academic medical center because of hypoxemic respiratory failure/acute respiratory distress syndrome and received mechanical ventilation and prone positioning. Data were collected on clinical presentation, interventions, and complications.

SUSTAINABILITY

Using the robust protocol and the low-cost device, staff can safely perform a low-volume, high-risk maneuver. This method provides cost savings compared with other prone positioning methods.

CONCLUSIONS

Implementing a prone positioning protocol with a dedicated device is feasible, with fewer complications and lower costs than anticipated.

Assessing and Augmenting Predictive Models for Hospital Readmissions With Novel Variables in an Urban Safety-net Population

BACKGROUND

The performance of existing predictive models of readmissions, such as the LACE, LACE+, and Epic models, is not established in urban safety-net populations. We assessed previously validated predictive models of readmission performance in a socially complex, urban safety-net population, and if augmentation with additional variables such as the Area Deprivation Index, mental health diagnoses, and housing access improves prediction. Through the addition of new variables, we introduce the LACE-social determinants of health (SDH) model.

METHODS

This retrospective cohort study included adult admissions from July 1, 2016, to June 30, 2018, at a single urban safety-net health system, assessing the performance of the LACE, LACE+, and Epic models in predicting 30-day, unplanned rehospitalization. The LACE-SDH development is presented through logistic regression. Predictive model performance was compared using C-statistics.

RESULTS

A total of 16,540 patients met the inclusion criteria. Within the validation cohort (n=8314), the Epic model performed the best (C-statistic=0.71, P<0.05), compared with LACE-SDH (0.67), LACE (0.65), and LACE+ (0.61). The variables most associated with readmissions were (odds ratio, 95% confidence interval) against medical advice discharge (3.19, 2.28-4.45), mental health diagnosis (2.06, 1.72-2.47), and health care utilization (1.94, 1.47-2.55).

CONCLUSIONS

The Epic model performed the best in our sample but requires the use of the Epic Electronic Health Record. The LACE-SDH performed significantly better than the LACE and LACE+ models when applied to a safety-net population, demonstrating the importance of accounting for socioeconomic stressors, mental health, and health care utilization in assessing readmission risk in urban safety-net patients.

233 BISPHOSPHONATES: ANOTHER COMPLEX DRUG TO PRESCRIBE

Background

Bisphosphonates provide effective treatment for osteoporosis. They accumulate a bone reservoir lasting for 3 years and beyond. The 2021 NICE guidelines recommend a medication review and a ‘drug holiday’ after 5 years of oral bisphosphonate therapy for low-fracture risk patients. Continuing treatment for high risk individuals is advised: age=/&gt;75, previous hip or vertebral fracture, one or more fractures during treatment, recent DEXA scan with T score =/&lt;−2.5, and/or current treatment with oral glucocorticoids. This retrospective audit aimed to assess compliance with NICE guidelines in a primary care setting.

Methods

Data were collected using the Health One online medical record system in an urban general practice. Inclusion criteria: all patients =/&gt; 65 years old, prescribed oral bisphosphonate therapy for osteoporosis for &gt;5 years. Exclusion criteria: deceased, did not attend clinic &gt;1 year, patients on bisphosphonate treatment for conditions other than osteoporosis.

Results

137 patients with a history of bisphosphonate therapy were identified. 76 patients were on bisphosphonate treatment for greater than 5 years. Of the 76 patients, 33 were classified as low-fracture risk and appropriately commenced a drug holiday, while 22 correctly remained on bisphosphonates due to a high fracture risk. The remaining 21 patients inappropriately continued therapy without receiving a medication review, repeat DEXA or fracture-risk assessment.

Conclusion

One third of patients on bisphosphonates beyond 5 years were not assessed for a drug holiday. The aim of a bisphosphonate ‘drug holiday’ is to reduce poly-pharmacy and prevent rare but serious long-term adverse events (such as atypical fractures, osteonecrosis of the jaw, gastric cancer and atrial fibrillation). Factors which had an impact on inappropriate prescribing should be assessed. Incorporating computer-based prescribing alerts could support safe prescribing practices.

Personal exposure to average weekly ultrafine particles, lung function, and respiratory symptoms in asthmatic and non-asthmatic adolescents

An increasing amount of evidence suggests ultrafine particles (UFPs) are linked to adverse health effects, especially in those with chronic conditions such as asthma, due to their small size and physicochemical characteristics. Toxicological and experimental studies have demonstrated these properties, and the mechanisms by which they deposit and translocate in the body result in increased toxicity in comparison to other air pollutants. However, current epidemiological literature is limited due to exposure misclassification and thus identifying health outcomes associated with UFPs. The objective of this study was to investigate the association between weekly personal UFP exposure with lung function and respiratory symptoms in 117 asthmatic and non-asthmatic adolescents between 13 and 17 years of age in the Cincinnati area. Between 2017 and 2019, participants collected weekly UFP concentrations by sampling for 3 h a day in their home, school, and during transit. In addition, pulmonary function was evaluated at the end of the sampling week, and respiratory symptoms were logged on a mobile phone application. Multivariable linear regression and zero-inflated Poisson (ZIP) models were used to estimate the association between personal UFP and respiratory outcomes. The average median weekly UFP exposure of all participants was 4340 particles/cm3 (p/cc). Results of fully adjusted regression models revealed a negative association between UFPs and percent predicted forced expiratory volume/forced vital capacity ratio (%FEV1/FVC) (β:-0.03, 95% CI [-0.07, 0.02]). Prediction models estimated an association between UFPs and respiratory symptoms, which was greater in asthmatics compared to non-asthmatics. Our results indicate an interaction between asthma status and the likelihood of experiencing respiratory symptoms when exposed to UFPs, indicating an exacerbation of this chronic condition. More research is needed to determine the magnitude of the role UFPs play on respiratory health.