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IMPORTANCEThe efficacy of antiplatelet therapy in critically ill patients with COVID-19 is uncertain.OBJECTIVE To determine whether antiplatelet therapy improves outcomes for critically ill adults with COVID-19. DESIGN, SETTING, AND PARTICIPANTSIn an ongoing adaptive platform trial (REMAP-CAP) testing multiple interventions within multiple therapeutic domains, 1557 critically ill adult patients with COVID-19 were enrolled between October 30, 2020, and June 23, 2021, from 105 sites in 8 countries and followed up for 90 days (final follow-up date: July 26, 2021).INTERVENTIONS Patients were randomized to receive either open-label aspirin (n = 565), a P2Y12 inhibitor (n = 455), or no antiplatelet therapy (control; n = 529). Interventions were continued in the hospital for a maximum of 14 days and were in addition to anticoagulation thromboprophylaxis. MAIN OUTCOMES AND MEASURESThe primary end point was organ support-free days (days alive and free of intensive care unit-based respiratory or cardiovascular organ support) within 21 days, ranging from −1 for any death in hospital (censored at 90 days) to 22 for survivors with no organ support. There were 13 secondary outcomes, including survival to discharge and major bleeding to 14 days. The primary analysis was a bayesian cumulative logistic model. An odds ratio (OR) greater than 1 represented improved survival, more organ support-free days, or both. Efficacy was defined as greater than 99% posterior probability of an OR greater than 1. Futility was defined as greater than 95% posterior probability of an OR less than 1.2 vs control. Intervention equivalence was defined as greater than 90% probability that the OR (compared with each other) was between 1/1.2 and 1.2 for 2 noncontrol interventions. RESULTSThe aspirin and P2Y12 inhibitor groups met the predefined criteria for equivalence at an adaptive analysis and were statistically pooled for further analysis. Enrollment was discontinued after the prespecified criterion for futility was met for the pooled antiplatelet group compared with control. Among the 1557 critically ill patients randomized, 8 patients withdrew consent and 1549 completed the trial (median age, 57 years; 521 [33.6%] female). The median for organ support-free days was 7 (IQR, −1 to 16) in both the antiplatelet and control groups (median-adjusted OR, 1.02 [95% credible interval {CrI}, 0.86-1.23]; 95.7% posterior probability of futility). The proportions of patients surviving to hospital discharge were 71.5% (723/1011) and 67.9% (354/521) in the antiplatelet and control groups, respectively (median-adjusted OR, 1.27 [95% CrI, 0.99-1.62]; adjusted absolute difference, 5% [95% CrI, −0.2% to 9.5%]; 97% posterior probability of efficacy). Among survivors, the median for organ support-free days was 14 in both groups. Major bleeding occurred in 2.1% and 0.4% of patients in the antiplatelet and control groups (adjusted OR, 2.97 [95% CrI,; adjusted absolute risk increase, 0.8% [95% CrI, 0.1%-2.7%]; 99.4% probability of harm).CONCLUSIONS AND RELEVANCE Among crit...

To study the efficacy of lopinavir-ritonavir and hydroxychloroquine in critically ill patients with coronavirus disease 2019 .Methods: Critically ill adults with COVID-19 were randomized to receive lopinavir-ritonavir, hydroxychloroquine, combination therapy of lopinavir-ritonavir and hydroxychloroquine or no antiviral therapy (control). The primary endpoint was an ordinal scale of organ support-free days. Analyses used a Bayesian cumulative logistic model and expressed treatment effects as an adjusted odds ratio (OR) where an OR > 1 is favorable. Results:We randomized 694 patients to receive lopinavir-ritonavir (n = 255), hydroxychloroquine (n = 50), combination therapy (n = 27) or control (n = 362). The median organ support-free days among patients in lopinavir-ritonavir, hydroxychloroquine, and combination therapy groups was 4 (-1 to 15), 0 (-1 to 9) and-1 (-1 to 7), respectively,

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Background The Coronavirus disease 2019 (COVID-19) pandemic has underlined the urgent need for reliable, multicenter, and full-admission intensive care data to advance our understanding of the course of the disease and investigate potential treatment strategies. In this study, we present the Dutch Data Warehouse (DDW), the first multicenter electronic health record (EHR) database with full-admission data from critically ill COVID-19 patients. Methods A nation-wide data sharing collaboration was launched at the beginning of the pandemic in March 2020. All hospitals in the Netherlands were asked to participate and share pseudonymized EHR data from adult critically ill COVID-19 patients. Data included patient demographics, clinical observations, administered medication, laboratory determinations, and data from vital sign monitors and life support devices. Data sharing agreements were signed with participating hospitals before any data transfers took place. Data were extracted from the local EHRs with prespecified queries and combined into a staging dataset through an extract–transform–load (ETL) pipeline. In the consecutive processing pipeline, data were mapped to a common concept vocabulary and enriched with derived concepts. Data validation was a continuous process throughout the project. All participating hospitals have access to the DDW. Within legal and ethical boundaries, data are available to clinicians and researchers. Results Out of the 81 intensive care units in the Netherlands, 66 participated in the collaboration, 47 have signed the data sharing agreement, and 35 have shared their data. Data from 25 hospitals have passed through the ETL and processing pipeline. Currently, 3464 patients are included in the DDW, both from wave 1 and wave 2 in the Netherlands. More than 200 million clinical data points are available. Overall ICU mortality was 24.4%. Respiratory and hemodynamic parameters were most frequently measured throughout a patient's stay. For each patient, all administered medication and their daily fluid balance were available. Missing data are reported for each descriptive. Conclusions In this study, we show that EHR data from critically ill COVID-19 patients may be lawfully collected and can be combined into a data warehouse. These initiatives are indispensable to advance medical data science in the field of intensive care medicine.

ImportanceThe longer-term effects of therapies for the treatment of critically ill patients with COVID-19 are unknown.ObjectiveTo determine the effect of multiple interventions for critically ill adults with COVID-19 on longer-term outcomes.Design, Setting, and ParticipantsPrespecified secondary analysis of an ongoing adaptive platform trial (REMAP-CAP) testing interventions within multiple therapeutic domains in which 4869 critically ill adult patients with COVID-19 were enrolled between March 9, 2020, and June 22, 2021, from 197 sites in 14 countries. The final 180-day follow-up was completed on March 2, 2022.InterventionsPatients were randomized to receive 1 or more interventions within 6 treatment domains: immune modulators (n = 2274), convalescent plasma (n = 2011), antiplatelet therapy (n = 1557), anticoagulation (n = 1033), antivirals (n = 726), and corticosteroids (n = 401).Main Outcomes and MeasuresThe main outcome was survival through day 180, analyzed using a bayesian piecewise exponential model. A hazard ratio (HR) less than 1 represented improved survival (superiority), while an HR greater than 1 represented worsened survival (harm); futility was represented by a relative improvement less than 20% in outcome, shown by an HR greater than 0.83.ResultsAmong 4869 randomized patients (mean age, 59.3 years; 1537 [32.1%] women), 4107 (84.3%) had known vital status and 2590 (63.1%) were alive at day 180. IL-6 receptor antagonists had a greater than 99.9% probability of improving 6-month survival (adjusted HR, 0.74 [95% credible interval {CrI}, 0.61-0.90]) and antiplatelet agents had a 95% probability of improving 6-month survival (adjusted HR, 0.85 [95% CrI, 0.71-1.03]) compared with the control, while the probability of trial-defined statistical futility (HR >0.83) was high for therapeutic anticoagulation (99.9%; HR, 1.13 [95% CrI, 0.93-1.42]), convalescent plasma (99.2%; HR, 0.99 [95% CrI, 0.86-1.14]), and lopinavir-ritonavir (96.6%; HR, 1.06 [95% CrI, 0.82-1.38]) and the probabilities of harm from hydroxychloroquine (96.9%; HR, 1.51 [95% CrI, 0.98-2.29]) and the combination of lopinavir-ritonavir and hydroxychloroquine (96.8%; HR, 1.61 [95% CrI, 0.97-2.67]) were high. The corticosteroid domain was stopped early prior to reaching a predefined statistical trigger; there was a 57.1% to 61.6% probability of improving 6-month survival across varying hydrocortisone dosing strategies.Conclusions and RelevanceAmong critically ill patients with COVID-19 randomized to receive 1 or more therapeutic interventions, treatment with an IL-6 receptor antagonist had a greater than 99.9% probability of improved 180-day mortality compared with patients randomized to the control, and treatment with an antiplatelet had a 95.0% probability of improved 180-day mortality compared with patients randomized to the control. Overall, when considered with previously reported short-term results, the findings indicate that initial in-hospital treatment effects were consistent for most therapies through 6 months.

IMPORTANCEOveractivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19.ObjectiveTo determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19.DESIGN, SETTING, AND PARTICIPANTSIn an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022).INTERVENTIONSPatients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days.MAIN OUTCOMES AND MEASURESThe primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes.RESULTSOn February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively).CONCLUSIONS AND RELEVANCEIn this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes.TRIAL REGISTRATIONClinicalTrials.gov Identifier: NCT02735707

Introduction Determining the optimal timing for extubation can be challenging in the intensive care. In this study, we aim to identify predictors for extubation failure in critically ill patients with COVID-19. Methods We used highly granular data from 3464 adult critically ill COVID patients in the multicenter Dutch Data Warehouse, including demographics, clinical observations, medications, fluid balance, laboratory values, vital signs, and data from life support devices. All intubated patients with at least one extubation attempt were eligible for analysis. Transferred patients, patients admitted for less than 24 h, and patients still admitted at the time of data extraction were excluded. Potential predictors were selected by a team of intensive care physicians. The primary and secondary outcomes were extubation without reintubation or death within the next 7 days and within 48 h, respectively. We trained and validated multiple machine learning algorithms using fivefold nested cross-validation. Predictor importance was estimated using Shapley additive explanations, while cutoff values for the relative probability of failed extubation were estimated through partial dependence plots. Results A total of 883 patients were included in the model derivation. The reintubation rate was 13.4% within 48 h and 18.9% at day 7, with a mortality rate of 0.6% and 1.0% respectively. The grandient-boost model performed best (area under the curve of 0.70) and was used to calculate predictor importance. Ventilatory characteristics and settings were the most important predictors. More specifically, a controlled mode duration longer than 4 days, a last fraction of inspired oxygen higher than 35%, a mean tidal volume per kg ideal body weight above 8 ml/kg in the day before extubation, and a shorter duration in assisted mode (< 2 days) compared to their median values. Additionally, a higher C-reactive protein and leukocyte count, a lower thrombocyte count, a lower Glasgow coma scale and a lower body mass index compared to their medians were associated with extubation failure. Conclusion The most important predictors for extubation failure in critically ill COVID-19 patients include ventilatory settings, inflammatory parameters, neurological status, and body mass index. These predictors should therefore be routinely captured in electronic health records.