Characterization of Long COVID Definitions and Clinical Coding Practices (preprint)

Background: Long COVID characterized as post-acute sequelae of SARS-CoV-2 (PASC) has no universal clinical case definition. Recent efforts have focused on understanding long COVID symptoms and electronic health records (EHR) data provides a unique resource for understanding this condition. The introduction of the International Classification of Diseases (ICD)-10 code U09.9 for - Post COVID-19 condition, unspecified to identify patients with long COVID has provided a method of evaluating this condition in EHRs, however, the accuracy of this code is unclear. Objective: Our study aimed to characterize the utility and accuracy of the U09.9 code across three healthcare systems - The Veterans Health Administration (VHA), Beth Israel Deaconess Medical Center (BIDMC) and The University of Pittsburgh Medical Center (UPMC) against patients identified with long COVID via a chart review by operationalizing the World Health Organization (WHO) and Centers for Disease Control (CDC) definitions. Methods: COVID positive patients with either a U07.1 ICD code or positive polymerase chain reaction (PCR) test within these healthcare systems were identified for chart review. Among this cohort we sampled patients based on two approaches i) with a U09.9 code and ii) without a U09.9 code but with a new onset PASC related ICD code, which allows us to assess the sensitivity of the U09.9 code. To operationalize the long COVID definition based on health agency guidelines, we grouped symptoms into a core cluster of 11 commonly reported symptoms among long COVID patients and an extended cluster, that captured all other symptoms by disease domain. Patients having at least 2 symptoms persisting for >=60 days that were new onset after their COVID infection, with at least one symptom in the core cluster, were labeled as having long COVID per chart review. We compared the performance of the code across three health systems and across different time periods of the pandemic. Results: A total of 900 patient charts were reviewed across 3 healthcare systems. The prevalence of long COVID among the cohort with the U09.9 ICD code, based on the operationalized WHO definition was between 23.2%-62.4% across these healthcare systems. We also evaluated a less stringent version of the WHO definition and the Centers for Disease Control (CDC) definition and observed an increase in the prevalence of long COVID at all three healthcare systems. Conclusions: This is one of the first studies to evaluate the U09.9 code against a clinical case definition for long COVID, as well as the first to apply this definition to EHR data using a chart review approach on a nationwide cohort across multiple healthcare systems. This chart review approach can be implemented at other EHR systems to further evaluate the utility and performance of the U09.9 code.

The impact of the COVID-19 pandemic on clinical guidance, risk assessment and support for UK obstetric sonographers

UK obstetric sonographers adapted their working practices during the COVID-19 pandemic in response to new guidance issued by professional organisations, and requirements for on-going departmental risk assessments. This study aimed to provide an insight into the implementation of this guidance, completion of risk assessments and perception of support within UK obstetric ultrasound departments during the pandemic period. Obstetric sonographers working in the UK (n=138) used the Qualtrics XMTM platform to complete an anonymous, online, cross-sectional survey about their working experiences during the pandemic. Participants responded to closed questions about national guidance, risk assessments and their perception of support whilst providing fetal ultrasound screening services. Respondents provided additional detail about their experiences in these areas via free-text boxes. Over 90% of respondents were aware of, or had read guidance issued by professional organisations, although sonographers rated the overall usefulness of new guidelines at an average of 5.2/10 (where 0 = not useful at all, and 10 = extremely useful). Challenges for the implementation of guidance in departments were also identified, mostly related to the clinical working environment, including limitations of physical space (76.3%), time constraints (67.5%) and ventilation (61.3%). Most sonographers (77.2%) were aware that a departmental risk assessment had been undertaken, with waiting areas, scan rooms and clinically vulnerable staff highlighted as the most concerning factors. Sonographers felt most supported by their ultrasound colleagues (83.5%) and line managers (41.2%). They felt least supported by senior management and leadership personnel (60.8%), other antenatal colleagues (51.5%) and professional organisations (41.2%). Whilst most sonographers were aware of published COVID-19 guidance, challenges for its implementation in clinical departments were identified. Local risk mitigation strategies often did not prioritise the scan room environment, despite it being highlighted as a concern. Support from the wider, senior service team and professional organisations will be essential to facilitate post-pandemic recovery of the workforce.

"It has been the most difficult time in my career": A qualitative exploration of UK obstetric sonographers' experiences during the COVID-19 pandemic.

INTRODUCTION: Substantial changes were made to the provision of pregnancy ultrasound services during the COVID-19 pandemic with the intention of minimising virus transmission and maintaining service continuity. Published literature describing the impact of the pandemic on obstetric sonographers is predominantly quantitative in nature, however statistics cannot fully convey sonographers' voices. This study aimed to gain a deeper understanding of the lived experiences of UK obstetric sonographers performing pregnancy ultrasound scans during the pandemic. METHODS: A UK-wide, online, anonymous cross-sectional survey on Qualtrics XM™ was open to responses between 9th March and 6th May 2021. Whilst this survey contained some quantitative elements, open questions were included to capture additional qualitative detail from respondents about their perceptions and experiences of scanning during the pandemic. Key themes were generated from free text responses using thematic analysis. RESULTS: Written responses were received from 111/138 sonographers participating in the survey. Five themes were generated, depicting the impact of the pandemic on obstetric sonographers: 1) continuity in a crisis; 2) decisions about me, without me; 3) battle scars - the lasting damage of COVID-19; 4) what people think I do vs. what I really do; and 5) the human touch. A cross-cutting theme was sonographers' feelings of disconnection from senior figures and expectant parents which created a sense of abandonment and distrust. CONCLUSION: Survey respondents' self-reported experiences of ineffective leadership and management, and perceived lack of understanding of the complexity of the sonographer role are potential contributory factors in the high levels of moral injury and occupational burnout reported within the workforce during the pandemic.

Differential impacts of perceived social support on alcohol and cannabis use in young adults: lessons from the COVID-19 pandemic

Coronavirus (COVID-19) lockdowns provided a unique opportunity to examine how changes in the social environment impact mental health and wellbeing. We addressed this issue by assessing how perceived social support across COVID-19 restrictions alters alcohol and cannabis use in emerging adults, a population vulnerable to adverse outcomes of substance use. Four hundred sixty-three young adults in Canada and the United States completed online questionnaires for three retrospective time points: Pre-Covid, Lockdown and Eased Restrictions. Sociodemographic factors, perceived social support, and substance use were assessed. Overall, alcohol use decreased while cannabis use increased during Lockdown. Interestingly, social support negatively predicted alcohol use and positively predicted cannabis use during Lockdown. These findings suggest a difference in motives underlying alcohol and cannabis use in emerging adults. Importantly, these changes were not sustained when restrictions eased, suggesting that emerging adults exhibit resiliency to the impacts of COVID-19 restrictions on substance use. © 2023, University of Toronto. All rights reserved.

Data-Driven Real-Time Strategic Placement of Mobile Vaccine Distribution Sites

The deployment of vaccines across the US provides significant defense against serious illness and death from COVID-19. Over 70% of vaccine-eligible Americans are at least partially vaccinated, but there are pockets of the population that are under-vaccinated, such as in rural areas and some demographic groups (e.g. age, race, ethnicity). These pockets are extremely susceptible to the Delta variant, exacerbating the healthcare crisis and increasing the risk of new variants. In this paper, we describe a data-driven model that provides real-time support to Virginia public health officials by recommending mobile vaccination site placement in order to target under-vaccinated populations. Our strategy uses fine-grained mobility data, along with US Census and vaccination uptake data, to identify locations that are most likely to be visited by unvaccinated individuals. We further extend our model to choose locations that maximize vaccine uptake among hesitant groups. We show that the top recommended sites vary substantially across some demographics, demonstrating the value of developing customized recommendation models that integrate fine-grained, heterogeneous data sources. We also validate our recommendations by analyzing the success rates of deployed vaccine sites, and show that sites placed closer to our recommended areas administered higher numbers of doses. Our model is the first of its kind to consider evolving mobility patterns in real-time for suggesting placement strategies customized for different targeted demographic groups.

Antidepressant use and risk of intubation or death in hospitalized patients with COVID-19: A retrospective cohort study of clinical effectiveness.

Initial controlled trials of the serotonergic antidepressant fluvoxamine showed promise for treatment of mild to moderate COVID-19 in outpatients, although more recent outpatient data have been less encouraging. Turning to studies of hospitalized patients, a retrospective cohort study by Hoertel and associates in 2021 found a markedly reduced risk of intubation or death among patients hospitalized with COVID-19 who were receiving serotonergic antidepressants at the time of admission vs. those not receiving antidepressants. In an attempt to replicate these latter findings, we performed a similarly designed study of 500 individuals hospitalized with COVID-19 in a large academic hospital system who were taking a serotonergic antidepressant at the time of admission compared with two groups (N = 573 and N = 593) not receiving an antidepressant. In analyses controlling for demographic and clinical variables, we found no significant difference in effect between the antidepressant group and either of the two comparison groups [hazard ratios (95% CI) for intubation or death 1.1 (0.83-1.5) and 1.1 (0.86-1.5); and for death alone 1.3 (0.93-1.8) and 1.1 (0.85-1.7)]. Examining the results of our study, along with those of Hoertel et al. and three additional retrospective cohort studies in inpatients published in the interim, the data permit only very limited conclusions, with the findings on the effect of serotonergic antidepressants ranging from a strongly protective effect to no effect. Although there are numerous threats to validity that might account for this wide range of findings, we could not identify any principal factor or set of factors that could clearly explain the differences.

Characterizing the use of the ICD-10 Code for Long COVID in 3 US Healthcare Systems (preprint)

The International Classification of Diseases (ICD)-10 code (U09.9) for post-acute sequelae of COVID-19 (PASC) was introduced in October of 2021. As researchers seek to leverage this billing code for research purposes in large scale real-world studies of PASC, it is of utmost importance to understand the functional use of the code by healthcare providers and the clinical characteristics of patients who have been assigned this code. To this end, we operationalized clinical case definitions of PASC using World Health Organization and Centers for Disease Control guidelines. We then chart reviewed 300 patients with COVID-19 from three participating healthcare systems of the 4CE Consortium who were assigned the U09.9 code. Chart review results showed the average positive predictive value (PPV) of the U09.9 code ranged from 40.2% to 65.4% depending on which definition of PASC was used in the evaluation. The PPV of the U09.9 code also fluctuated significantly between calendar time periods. We demonstrated the potential utility of textual data extracted from natural language processing techniques to more comprehensively capture symptoms associated with PASC from electronic health records data. Finally, we investigated the utilization of long COVID clinics in the cohort of patients. We observed that only an average of 24.0% of patients with the U09.9 code visited a long COVID clinic. Among patients who met the WHO PASC definition, only an average of 35.6% visited a long COVID clinic.

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.

Acute respiratory distress syndrome after SARS-CoV-2 infection on young adult population: International observational federated study based on electronic health records through the 4CE consortium.

PURPOSE: In young adults (18 to 49 years old), investigation of the acute respiratory distress syndrome (ARDS) after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been limited. We evaluated the risk factors and outcomes of ARDS following infection with SARS-CoV-2 in a young adult population. METHODS: A retrospective cohort study was conducted between January 1st, 2020 and February 28th, 2021 using patient-level electronic health records (EHR), across 241 United States hospitals and 43 European hospitals participating in the Consortium for Clinical Characterization of COVID-19 by EHR (4CE). To identify the risk factors associated with ARDS, we compared young patients with and without ARDS through a federated analysis. We further compared the outcomes between young and old patients with ARDS. RESULTS: Among the 75,377 hospitalized patients with positive SARS-CoV-2 PCR, 1001 young adults presented with ARDS (7.8% of young hospitalized adults). Their mortality rate at 90 days was 16.2% and they presented with a similar complication rate for infection than older adults with ARDS. Peptic ulcer disease, paralysis, obesity, congestive heart failure, valvular disease, diabetes, chronic pulmonary disease and liver disease were associated with a higher risk of ARDS. We described a high prevalence of obesity (53%), hypertension (38%- although not significantly associated with ARDS), and diabetes (32%). CONCLUSION: Trough an innovative method, a large international cohort study of young adults developing ARDS after SARS-CoV-2 infection has been gather. It demonstrated the poor outcomes of this population and associated risk factor.

Long-term kidney function recovery and mortality after COVID-19-associated acute kidney injury: An international multi-centre observational cohort study.

Background: While acute kidney injury (AKI) is a common complication in COVID-19, data on post-AKI kidney function recovery and the clinical factors associated with poor kidney function recovery is lacking. Methods: A retrospective multi-centre observational cohort study comprising 12,891 hospitalized patients aged 18 years or older with a diagnosis of SARS-CoV-2 infection confirmed by polymerase chain reaction from 1 January 2020 to 10 September 2020, and with at least one serum creatinine value 1-365 days prior to admission. Mortality and serum creatinine values were obtained up to 10 September 2021. Findings: Advanced age (HR 2.77, 95%CI 2.53-3.04, p < 0.0001), severe COVID-19 (HR 2.91, 95%CI 2.03-4.17, p < 0.0001), severe AKI (KDIGO stage 3: HR 4.22, 95%CI 3.55-5.00, p < 0.0001), and ischemic heart disease (HR 1.26, 95%CI 1.14-1.39, p < 0.0001) were associated with worse mortality outcomes. AKI severity (KDIGO stage 3: HR 0.41, 95%CI 0.37-0.46, p < 0.0001) was associated with worse kidney function recovery, whereas remdesivir use (HR 1.34, 95%CI 1.17-1.54, p < 0.0001) was associated with better kidney function recovery. In a subset of patients without chronic kidney disease, advanced age (HR 1.38, 95%CI 1.20-1.58, p < 0.0001), male sex (HR 1.67, 95%CI 1.45-1.93, p < 0.0001), severe AKI (KDIGO stage 3: HR 11.68, 95%CI 9.80-13.91, p < 0.0001), and hypertension (HR 1.22, 95%CI 1.10-1.36, p = 0.0002) were associated with post-AKI kidney function impairment. Furthermore, patients with COVID-19-associated AKI had significant and persistent elevations of baseline serum creatinine 125% or more at 180 days (RR 1.49, 95%CI 1.32-1.67) and 365 days (RR 1.54, 95%CI 1.21-1.96) compared to COVID-19 patients with no AKI. Interpretation: COVID-19-associated AKI was associated with higher mortality, and severe COVID-19-associated AKI was associated with worse long-term post-AKI kidney function recovery. Funding: Authors are supported by various funders, with full details stated in the acknowledgement section.

Antidepressant use and risk of intubation or death in hospitalized patients with COVID-19: A retrospective cohort study of clinical effectiveness

Initial controlled trials of the serotonergic antidepressant fluvoxamine showed promise for treatment of mild to moderate COVID-19 in outpatients, although more recent outpatient data have been less encouraging. Turning to studies of hospitalized patients, a retrospective cohort study by Hoertel and associates in 2021 found a markedly reduced risk of intubation or death among patients hospitalized with COVID-19 who were receiving serotonergic antidepressants at the time of admission vs. those not receiving antidepressants. In an attempt to replicate these latter findings, we performed a similarly designed study of 500 individuals hospitalized with COVID-19 in a large academic hospital system who were taking a serotonergic antidepressant at the time of admission compared with two groups (N = 573 and N = 593) not receiving an antidepressant. In analyses controlling for demographic and clinical variables, we found no significant difference in effect between the antidepressant group and either of the two comparison groups [hazard ratios (95% CI) for intubation or death 1.1 (0.83–1.5) and 1.1 (0.86–1.5);and for death alone 1.3 (0.93–1.8) and 1.1 (0.85–1.7)]. Examining the results of our study, along with those of Hoertel et al. and three additional retrospective cohort studies in inpatients published in the interim, the data permit only very limited conclusions, with the findings on the effect of serotonergic antidepressants ranging from a strongly protective effect to no effect. Although there are numerous threats to validity that might account for this wide range of findings, we could not identify any principal factor or set of factors that could clearly explain the differences.

Development and operation of the defence COVID-19 lab as a SARS-CoV-2 diagnostic screening capability for UK military personnel.

BACKGROUND: In the face of the COVID-19 pandemic, the Defence Science and Technology Laboratory (Dstl) and Defence Pathology combined to form the Defence Clinical Lab (DCL), an accredited (ISO/IEC 17025:2017) high-throughput SARS-CoV-2 PCR screening capability for military personnel. LABORATORY STRUCTURE AND RESOURCE: The DCL was modular in organisation, with laboratory modules and supporting functions combining to provide the accredited SARS-CoV-2 (envelope (E)-gene) PCR assay. The DCL was resourced by Dstl scientists and military clinicians and biomedical scientists. LABORATORY RESULTS: Over 12 months of operation, the DCL was open on 289 days and tested over 72 000 samples. Six hundred military SARS-CoV-2-positive results were reported with a median E-gene quantitation cycle (Cq) value of 30.44. The lowest Cq value for a positive result observed was 11.20. Only 64 samples (0.09%) were voided due to assay inhibition after processing started. CONCLUSIONS: Through a sustained effort and despite various operational issues, the collaboration between Dstl scientific expertise and Defence Pathology clinical expertise provided the UK military with an accredited high-throughput SARS-CoV-2 PCR test capability at the height of the COVID-19 pandemic. The DCL helped facilitate military training and operational deployments contributing to the maintenance of UK military capability. In offering a bespoke capability, including features such as testing samples in unit batches and oversight by military consultant microbiologists, the DCL provided additional benefits to the UK Ministry of Defence that were potentially not available from other SARS-CoV-2 PCR laboratories. The links between Dstl and Defence Pathology have also been strengthened, benefitting future research activities and operational responses.

International electronic health record-derived post-acute sequelae profiles of COVID-19 patients.

The risk profiles of post-acute sequelae of COVID-19 (PASC) have not been well characterized in multi-national settings with appropriate controls. We leveraged electronic health record (EHR) data from 277 international hospitals representing 414,602 patients with COVID-19, 2.3 million control patients without COVID-19 in the inpatient and outpatient settings, and over 221 million diagnosis codes to systematically identify new-onset conditions enriched among patients with COVID-19 during the post-acute period. Compared to inpatient controls, inpatient COVID-19 cases were at significant risk for angina pectoris (RR 1.30, 95% CI 1.09-1.55), heart failure (RR 1.22, 95% CI 1.10-1.35), cognitive dysfunctions (RR 1.18, 95% CI 1.07-1.31), and fatigue (RR 1.18, 95% CI 1.07-1.30). Relative to outpatient controls, outpatient COVID-19 cases were at risk for pulmonary embolism (RR 2.10, 95% CI 1.58-2.76), venous embolism (RR 1.34, 95% CI 1.17-1.54), atrial fibrillation (RR 1.30, 95% CI 1.13-1.50), type 2 diabetes (RR 1.26, 95% CI 1.16-1.36) and vitamin D deficiency (RR 1.19, 95% CI 1.09-1.30). Outpatient COVID-19 cases were also at risk for loss of smell and taste (RR 2.42, 95% CI 1.90-3.06), inflammatory neuropathy (RR 1.66, 95% CI 1.21-2.27), and cognitive dysfunction (RR 1.18, 95% CI 1.04-1.33). The incidence of post-acute cardiovascular and pulmonary conditions decreased across time among inpatient cases while the incidence of cardiovascular, digestive, and metabolic conditions increased among outpatient cases. Our study, based on a federated international network, systematically identified robust conditions associated with PASC compared to control groups, underscoring the multifaceted cardiovascular and neurological phenotype profiles of PASC.

Changes in laboratory value improvement and mortality rates over the course of the pandemic: an international retrospective cohort study of hospitalised patients infected with SARS-CoV-2.

OBJECTIVE: To assess changes in international mortality rates and laboratory recovery rates during hospitalisation for patients hospitalised with SARS-CoV-2 between the first wave (1 March to 30 June 2020) and the second wave (1 July 2020 to 31 January 2021) of the COVID-19 pandemic. DESIGN, SETTING AND PARTICIPANTS: This is a retrospective cohort study of 83 178 hospitalised patients admitted between 7 days before or 14 days after PCR-confirmed SARS-CoV-2 infection within the Consortium for Clinical Characterization of COVID-19 by Electronic Health Record, an international multihealthcare system collaborative of 288 hospitals in the USA and Europe. The laboratory recovery rates and mortality rates over time were compared between the two waves of the pandemic. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was all-cause mortality rate within 28 days after hospitalisation stratified by predicted low, medium and high mortality risk at baseline. The secondary outcome was the average rate of change in laboratory values during the first week of hospitalisation. RESULTS: Baseline Charlson Comorbidity Index and laboratory values at admission were not significantly different between the first and second waves. The improvement in laboratory values over time was faster in the second wave compared with the first. The average C reactive protein rate of change was -4.72 mg/dL vs -4.14 mg/dL per day (p=0.05). The mortality rates within each risk category significantly decreased over time, with the most substantial decrease in the high-risk group (42.3% in March-April 2020 vs 30.8% in November 2020 to January 2021, p<0.001) and a moderate decrease in the intermediate-risk group (21.5% in March-April 2020 vs 14.3% in November 2020 to January 2021, p<0.001). CONCLUSIONS: Admission profiles of patients hospitalised with SARS-CoV-2 infection did not differ greatly between the first and second waves of the pandemic, but there were notable differences in laboratory improvement rates during hospitalisation. Mortality risks among patients with similar risk profiles decreased over the course of the pandemic. The improvement in laboratory values and mortality risk was consistent across multiple countries.

Acute respiratory distress syndrome after SARS-CoV-2 infection on young adult population: international observational federated study based on electronic health records through the 4CE consortium ARDS after SARS-CoV-2 infection on young adult (preprint)

Purpose : In young adults (18 to 49 years old), investigation of the acute respiratory distress syndrome (ARDS) after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been limited. We evaluated the risk factors and outcomes of ARDS following infection with SARS-CoV-2 in a young adult population. Methods : A retrospective cohort study was conducted between January 1st, 2020 and February 28th, 2021 using patient-level electronic health records (EHR), across 241 United States hospitals and 43 European hospitals participating in the Consortium for Clinical Characterization of COVID-19 by EHR (4CE). To identify the risk factors associated with ARDS, we compared young patients with and without ARDS through a federated analysis. We further compared the outcomes between young and old patients with ARDS. Results : Among the 75,377 hospitalized patients with positive SARS-CoV-2 PCR, 1001 young adults presented with ARDS ( 7.8% of young hospitalized adults). Their mortality rate at 90 days was 16.2% and they presented with a similar complication rate for infection than older adults with ARDS. Peptic ulcer disease, paralysis, obesity, congestive heart failure, valvular disease, diabetes, chronic pulmonary disease and liver disease were associated with a higher risk of ARDS. We described a high prevalence of obesity (53%), hypertension (38%- although not significantly associated with ARDS), and diabetes (32%). Conclusion : Trough an innovative method, a large international cohort study of young adults developing ARDS after SARS-CoV-2 infection has been gather. It demonstrated the poor outcomes of this population and associated risk factor.

SurvMaximin: Robust Federated Approach to Transporting Survival Risk Prediction Models (preprint)

ObjectiveFor 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 MethodsFor 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 can be a single center, corresponding to transfer learning. ResultsSimulation 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. ConclusionsThe 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.

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.].

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.