COVID-19 interventional trials: Analysis of data sharing intentions during a time of pandemic.

BACKGROUND: This survey of COVID-19 interventional studies encompasses, and expands upon, a previous publication [1] examining individual participant level data (IPD) sharing intentions for COVID-related trials and publications prior to June 30, 2020. METHODS: Replicating our inclusion criteria from the original survey, we evaluated a larger dataset of 2759 trials and 281 publications in this follow-up survey for willingness to share IPD and studied if sharing sentiment has evolved since the beginning of the pandemic. RESULTS: We found that 18 months into the pandemic, data sharing intentions remained static at 15% for trials registered through ClinicalTrials.gov (ClinicalTrials.gov is a digital registry of information about publicly and privately funded clinical studies in which human volunteers participate in interventional or observational scientific research) prior to September 19, 2021 compared to our initial survey. However, a comparison of declared intentions to share IPD at the time of publication revealed a noticeable shift: affirmative intentions grew from 21.4% (6/28) in our original publications survey to 57% (160/281) in this survey. Within the subset of studies published within journals affiliated with the International Committee of Medical Journal Editors (ICMJE), positive sharing intentions are even higher (65%). CONCLUSIONS: Although intent to share data at the time of registration has not changed from our prior study in June 2020, there is growing commitment to sharing data reflected in the increasing number of affirmative declarations at the time of publication. Actual sharing of data will accelerate new insights into COVID-19 through secondary re-use of data.

Estimating risk of mechanical ventilation and in-hospital mortality among adult COVID-19 patients admitted to Mass General Brigham: The VICE and DICE scores.

BACKGROUND: Risk stratification of COVID-19 patients upon hospital admission is key for their successful treatment and efficient utilization of hospital resources. We sought to evaluate the risk factors on admission (including comorbidities, vital signs, and initial laboratory assessment) associated with ventilation need and in-hospital mortality in COVID-19. METHODS: We established a retrospective cohort of COVID-19 patients from Mass General Brigham hospitals. Demographic, clinical, and admission laboratory data were obtained from electronic medical records of patients admitted to the hospital with laboratory-confirmed COVID-19 before May 19, 2020. Multivariable logistic regression analyses were used to construct and validate the Ventilation in COVID Estimator (VICE) and Death in COVID Estimator (DICE) risk scores. FINDINGS: The entire cohort included 1042 patients (median age, 64 years; 56.8% male). The derivation and validation cohorts for the risk scores included 578 and 464 patients, respectively. We found four factors to be independently predictive for mechanical ventilation requirement (diabetes mellitus, SpO2:FiO2 ratio, C-reactive protein, and lactate dehydrogenase), and 10 factors to be predictors of in-hospital mortality (age, male sex, coronary artery disease, diabetes mellitus, chronic statin use, SpO2:FiO2 ratio, body mass index, neutrophil to lymphocyte ratio, platelet count, and procalcitonin). Using these factors, we constructed the VICE and DICE risk scores, which performed with C-statistics of 0.84 and 0.91, respectively. Importantly, the chronic use of a statin was associated with protection against death due to COVID-19. The VICE and DICE score calculators have been placed on an interactive website freely available to healthcare providers and researchers (https://covid-calculator.com/). INTERPRETATION: The risk scores developed in this study may help clinicians more appropriately determine which COVID-19 patients will need to be managed with greater intensity. FUNDING: COVID-19 Fast Grant (fastgrants.org).

COVID-19 trials: declarations of data sharing intentions at trial registration and at publication.

BACKGROUND: The sharing of individual participant-level data from COVID-19 trials would allow re-use and secondary analysis that can help accelerate the identification of effective treatments. The sharing of trial data is not the norm, but the unprecedented pandemic caused by SARS-CoV-2 may serve as an impetus for greater data sharing. We sought to assess the data sharing intentions of interventional COVID-19 trials as declared in trial registrations and publications. METHODS: We searched ClinicalTrials.gov and PubMed for COVID-19 interventional trials. We analyzed responses to ClinicalTrials.gov fields regarding intent to share individual participant level data and analyzed the data sharing statements in eligible publications. RESULTS: Nine hundred twenty-four trial registrations were analyzed. 15.7% were willing to share, of which 38.6% were willing to share immediately upon publication of results. 47.6% declared they were not willing to share. Twenty-eight publications were analyzed representing 26 unique COVID-19 trials. Only seven publications contained data sharing statements; six indicated a willingness to share data whereas one indicated that data was not available for sharing. CONCLUSIONS: At a time of pressing need for researchers to work together to combat a global pandemic, intent to share individual participant-level data from COVID-19 interventional trials is limited.

Predictors of mortality in hospitalized COVID-19 patients: A systematic review and meta-analysis.

Mortality rates of coronavirus disease-2019 (COVID-19) continue to rise across the world. Information regarding the predictors of mortality in patients with COVID-19 remains scarce. Herein, we performed a systematic review of published articles, from 1 January to 24 April 2020, to evaluate the risk factors associated with mortality in COVID-19. Two investigators independently searched the articles and collected the data, in accordance with PRISMA guidelines. We looked for associations between mortality and patient characteristics, comorbidities, and laboratory abnormalities. A total of 14 studies documenting the outcomes of 4659 patients were included. The presence of comorbidities such as hypertension (odds ratio [OR], 2.5; 95% confidence interval [CI], 2.1-3.1; P < .00001), coronary heart disease (OR, 3.8; 95% CI, 2.1-6.9; P < .00001), and diabetes (OR, 2.0; 95% CI, 1.7-2.3; P < .00001) were associated with significantly higher risk of death amongst patients with COVID-19. Those who died, compared with those who survived, differed on multiple biomarkers on admission including elevated levels of cardiac troponin (+44.2 ng/L, 95% CI, 19.0-69.4; P = .0006); C-reactive protein (+66.3 µg/mL, 95% CI, 46.7-85.9; P < .00001); interleukin-6 (+4.6 ng/mL, 95% CI, 3.6-5.6; P < .00001); D-dimer (+4.6 µg/mL, 95% CI, 2.8-6.4; P < .00001); creatinine (+15.3 µmol/L, 95% CI, 6.2-24.3; P = .001); and alanine transaminase (+5.7 U/L, 95% CI, 2.6-8.8; P = .0003); as well as decreased levels of albumin (-3.7 g/L, 95% CI, -5.3 to -2.1; P < .00001). Individuals with underlying cardiometabolic disease and that present with evidence for acute inflammation and end-organ damage are at higher risk of mortality due to COVID-19 infection and should be managed with greater intensity.

Timely access to trial data in the context of a pandemic: the time is now.

OBJECTIVE: Clinical trial data sharing has the potential to accelerate scientific progress, answer new lines of scientific inquiry, support reproducibility and prevent redundancy. Vivli, a non-profit organisation, operates a global platform for sharing of individual participant-level trial data and associated documents. Sharing of these data collected from each trial participant enables combining of these data to drive new scientific insights or assess reproducibility-not possible with the aggregate or summary data tables historically made available. We report on our initial experience including key metrics, lessons learned and how we see our role in the data sharing ecosystem. We also describe how Vivli is addressing the needs of the COVID-19 challenge through a new dedicated portal that provides a direct search function for COVID-19 studies, availability for fast-tracked request review and data sharing. DATA SUMMARY: The Vivli platform was established in 2018 and has partnered with 28 diverse members from industry, academic institutions, government platforms and non-profit foundations. Currently, 5400 trials representing 3.6 million participants are shared on the platform. From July 2018 to September 2020, Vivli received 201 requests. To date, 106 of 201 requests received approval, 5 have been declined, 27 withdrew and 27 are in the revision stage. CONCLUSIONS: The pandemic has only magnified the necessity for data sharing. If most data are shared and in a manner that allows interoperability, then we have hope of moving towards a cohesive scientific understanding more quickly not only for COVID-19 but also for all diseases. Conversely, if only isolated pockets of data are shared then society loses the opportunity to close vital gaps in our understanding of this rapidly evolving epidemic. This current challenge serves to highlight the value of data sharing platforms-critical enablers that help researchers build on prior knowledge.