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Objective: To determine whether surge conditions were associated with increased mortality., Design: Multicenter cohort study., Setting: U.S. ICUs participating in STOP-COVID., Patients: Consecutive adults with COVID-19 admitted to participating ICUs between March 4 and July 1, 2020., Interventions: None., Measurements and Main Results: The main outcome was 28-day in-hospital mortality. To assess the association between admission to an ICU during a surge period and mortality, we used two different strategies: (1) an inverse probability weighted difference-in-differences model limited to appropriately matched surge and non-surge patients and (2) a meta-regression of 50 multivariable difference-in-differences models (each based on sets of randomly matched surge- and non-surge hospitals). In the first analysis, we considered a single surge period for the cohort (March 23 - May 6). In the second, each surge hospital had its own surge period (which was compared to the same time periods in matched non-surge hospitals).Our cohort consisted of 4342 ICU patients (average age 60.8 [sd 14.8], 63.5% men) in 53 U.S. hospitals. Of these, 13 hospitals encountered surge conditions. In analysis 1, the increase in mortality seen during surge was not statistically significant (odds ratio [95% CI]: 1.30 [0.47-3.58], p = .6). In analysis 2, surge was associated with an increased odds of death (odds ratio 1.39 [95% CI, 1.34-1.43], p < .001)., Conclusions: Admission to an ICU with COVID-19 in a hospital that is experiencing surge conditions may be associated with an increased odds of death. Given the high incidence of COVID-19, such increases would translate into substantial excess mortality.

Background: Subphenotypes have been identified in patients with sepsis and ARDS and are associated with different outcomes and responses to therapies., Research Question: Can unique subphenotypes be identified among critically ill patients with COVID-19?, Study Design and Methods: Using data from a multicenter cohort study that enrolled critically ill patients with COVID-19 from 67 hospitals across the United States, we randomly divided centers into discovery and replication cohorts. We used latent class analysis independently in each cohort to identify subphenotypes based on clinical and laboratory variables. We then analyzed the associations of subphenotypes with 28-day mortality., Results: Latent class analysis identified four subphenotypes (SP) with consistent characteristics across the discovery (45 centers; n = 2,188) and replication (22 centers; n = 1,112) cohorts. SP1 was characterized by shock, acidemia, and multiorgan dysfunction, including acute kidney injury treated with renal replacement therapy. SP2 was characterized by high C-reactive protein, early need for mechanical ventilation, and the highest rate of ARDS. SP3 showed the highest burden of chronic diseases, whereas SP4 demonstrated limited chronic disease burden and mild physiologic abnormalities. Twenty-eight-day mortality in the discovery cohort ranged from 20.6% (SP4) to 52.9% (SP1). Mortality across subphenotypes remained different after adjustment for demographics, comorbidities, organ dysfunction and illness severity, regional and hospital factors. Compared with SP4, the relative risks were as follows: SP1, 1.67 (95% CI, 1.36-2.03); SP2, 1.39 (95% CI, 1.17-1.65); and SP3, 1.39 (95% CI, 1.15-1.67). Findings were similar in the replication cohort., Interpretation: We identified four subphenotypes of COVID-19 critical illness with distinct patterns of clinical and laboratory characteristics, comorbidity burden, and mortality., (Copyright © 2021 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.)

Rationale: Variation in hospital mortality has been described for coronavirus disease 2019 (COVID-19), but the factors that explain these differences remain unclear., Objective: Our objective was to utilize a large, nationally representative dataset of critically ill adults with COVID-19 to determine which factors explain mortality variability., Methods: In this multicenter cohort study, we examined adults hospitalized in intensive care units with COVID-19 at 70 United States hospitals between March and June 2020. The primary outcome was 28-day mortality. We examined patient-level and hospital-level variables. Mixed-effects logistic regression was used to identify factors associated with interhospital variation. The median odds ratio (OR) was calculated to compare outcomes in higher- vs. lower-mortality hospitals. A gradient boosted machine algorithm was developed for individual-level mortality models., Measurements and Main Results: A total of 4,019 patients were included, 1537 (38%) of whom died by 28 days. Mortality varied considerably across hospitals (0-82%). After adjustment for patient- and hospital-level domains, interhospital variation was attenuated (OR decline from 2.06 [95% CI, 1.73-2.37] to 1.22 [95% CI, 1.00-1.38]), with the greatest changes occurring with adjustment for acute physiology, socioeconomic status, and strain. For individual patients, the relative contribution of each domain to mortality risk was: acute physiology (49%), demographics and comorbidities (20%), socioeconomic status (12%), strain (9%), hospital quality (8%), and treatments (3%)., Conclusion: There is considerable interhospital variation in mortality for critically ill patients with COVID-19, which is mostly explained by hospital-level socioeconomic status, strain, and acute physiologic differences. Individual mortality is driven mostly by patient-level factors. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Objectives: Hypercoagulability may be a key mechanism for acute organ injury and death in patients with severe coronavirus disease 2019, but the relationship between elevated plasma levels of d-dimer, a biomarker of coagulation activation, and mortality has not been rigorously studied. We examined the independent association between d-dimer and death in critically ill patients with coronavirus disease 2019., Design: Multicenter cohort study., Setting: ICUs at 68 hospitals across the United States., Patients: Critically ill adults with coronavirus disease 2019 admitted to ICUs between March 4, 2020, and May 25, 2020, with a measured d-dimer concentration on ICU day 1 or 2., Interventions: None., Measurements and Main Results: The primary exposure was the highest normalized d-dimer level (assessed in four categories: < 2×, 2-3.9×, 4-7.9×, and ≥ 8× the upper limit of normal) on ICU day 1 or 2. The primary endpoint was 28-day mortality. Multivariable logistic regression was used to adjust for confounders. Among 3,418 patients (63.1% male; median age 62 yr [interquartile range, 52-71 yr]), 3,352 (93.6%) had a d-dimer concentration above the upper limit of normal. A total of 1,180 patients (34.5%) died within 28 days. Patients in the highest compared with lowest d-dimer category had a 3.11-fold higher odds of death (95% CI, 2.56-3.77) in univariate analyses, decreasing to a 1.81-fold increased odds of death (95% CI, 1.43-2.28) after multivariable adjustment for demographics, comorbidities, and illness severity. Further adjustment for therapeutic anticoagulation did not meaningfully attenuate this relationship (odds ratio, 1.73; 95% CI, 1.36-2.19)., Conclusions: In a large multicenter cohort study of critically ill patients with coronavirus disease 2019, higher d-dimer levels were independently associated with a greater risk of death., Competing Interests: Dr. Gupta’s institution received funding from the Foundation for the National Institutes of Health (NIH) 5 F32 DC 17342-2; she received funding from GlaxoSmithKline; she is a scientific coordinator for the Anemia Studies in CKD: Erythropoiesis via a Novel Prolyl Hydroxylase Inhibitor Daprodustat (ASCEND) trial (GlaskoSmithKline). Dr. Srivastava received funding from CVS Caremark, AstraZeneca, Horizon Therapeutics, PLC, and Tate & Latham. Dr. Shaefi’s institution received funding from the National Institute on Aging/NIH R03AG060179 and the National Institute of General Medical Sciences/NIH K08GM134220; he received support for article research from the NIH. Dr. Bagchi's institution received funding from the American Heart Association 20IPA35360009. He received funding from Lungpacer Medical, Inc. Dr. Al-Samkari received funding from Agios, Dova, Rigel, Argenx, and Amgen. Dr. Zakai’s institution received funding from the NIH and Centers for Disease Control and Prevention. Dr. Leaf received research support from BioPorto. The remaining authors have disclosed that they do not have any potential conflicts of interest., (Copyright © 2021 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.)

Rationale & Objective: Underlying kidney disease is an emerging risk factor for more severe coronavirus disease 2019 (COVID-19) illness. We examined the clinical courses of critically ill COVID-19 patients with and without pre-existing chronic kidney disease (CKD) and investigated the association between the degree of underlying kidney disease and in-hospital outcomes., Study Design: Retrospective cohort study., Settings & Participants: 4,264 critically ill patients with COVID-19 (143 patients with pre-existing kidney failure receiving maintenance dialysis; 521 patients with pre-existing non-dialysis-dependent CKD; and 3,600 patients without pre-existing CKD) admitted to intensive care units (ICUs) at 68 hospitals across the United States., Predictor(s): Presence (vs absence) of pre-existing kidney disease., Outcome(s): In-hospital mortality (primary); respiratory failure, shock, ventricular arrhythmia/cardiac arrest, thromboembolic events, major bleeds, and acute liver injury (secondary)., Analytical Approach: We used standardized differences to compare patient characteristics (values>0.10 indicate a meaningful difference between groups) and multivariable-adjusted Fine and Gray survival models to examine outcome associations., Results: Dialysis patients had a shorter time from symptom onset to ICU admission compared to other groups (median of 4 [IQR, 2-9] days for maintenance dialysis patients; 7 [IQR, 3-10] days for non-dialysis-dependent CKD patients; and 7 [IQR, 4-10] days for patients without pre-existing CKD). More dialysis patients (25%) reported altered mental status than those with non-dialysis-dependent CKD (20%; standardized difference=0.12) and those without pre-existing CKD (12%; standardized difference=0.36). Half of dialysis and non-dialysis-dependent CKD patients died within 28 days of ICU admission versus 35% of patients without pre-existing CKD. Compared to patients without pre-existing CKD, dialysis patients had higher risk for 28-day in-hospital death (adjusted HR, 1.41 [95% CI, 1.09-1.81]), while patients with non-dialysis-dependent CKD had an intermediate risk (adjusted HR, 1.25 [95% CI, 1.08-1.44])., Limitations: Potential residual confounding., Conclusions: Findings highlight the high mortality of individuals with underlying kidney disease and severe COVID-19, underscoring the importance of identifying safe and effective COVID-19 therapies in this vulnerable population., (Copyright © 2020 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.)

National data on patient characteristics, treatment, and outcomes of critically ill coronavirus disease 2019 (COVID-19) solid organ transplant (SOT) patients are limited. We analyzed data from a multicenter cohort study of adults with laboratory-confirmed COVID-19 admitted to intensive care units (ICUs) at 68 hospitals across the United States from March 4 to May 8, 2020. From 4153 patients, we created a propensity score matched cohort of 386 patients, including 98 SOT patients and 288 non-SOT patients. We used a binomial generalized linear model (log-binomial model) to examine the association of SOT status with death and other clinical outcomes. Among the 386 patients, the median age was 60 years, 72% were male, and 41% were black. Death within 28 days of ICU admission was similar in SOT and non-SOT patients (40% and 43%, respectively; relative risk [RR] 0.92; 95% confidence interval [CI]: 0.70-1.22). Other outcomes and requirement for organ support including receipt of mechanical ventilation, development of acute respiratory distress syndrome, and receipt of vasopressors were also similar between groups. There was a trend toward higher risk of acute kidney injury requiring renal replacement therapy in SOT vs. non-SOT patients (37% vs. 27%; RR [95% CI]: 1.34 [0.97-1.85]). Death and organ support requirement were similar between SOT and non-SOT critically ill patients with COVID-19., (© 2020 The American Society of Transplantation and the American Society of Transplant Surgeons.)

Importance: The US is currently an epicenter of the coronavirus disease 2019 (COVID-19) pandemic, yet few national data are available on patient characteristics, treatment, and outcomes of critical illness from COVID-19., Objectives: To assess factors associated with death and to examine interhospital variation in treatment and outcomes for patients with COVID-19., Design, Setting, and Participants: This multicenter cohort study assessed 2215 adults with laboratory-confirmed COVID-19 who were admitted to intensive care units (ICUs) at 65 hospitals across the US from March 4 to April 4, 2020., Exposures: Patient-level data, including demographics, comorbidities, and organ dysfunction, and hospital characteristics, including number of ICU beds., Main Outcomes and Measures: The primary outcome was 28-day in-hospital mortality. Multilevel logistic regression was used to evaluate factors associated with death and to examine interhospital variation in treatment and outcomes., Results: A total of 2215 patients (mean [SD] age, 60.5 [14.5] years; 1436 [64.8%] male; 1738 [78.5%] with at least 1 chronic comorbidity) were included in the study. At 28 days after ICU admission, 784 patients (35.4%) had died, 824 (37.2%) were discharged, and 607 (27.4%) remained hospitalized. At the end of study follow-up (median, 16 days; interquartile range, 8-28 days), 875 patients (39.5%) had died, 1203 (54.3%) were discharged, and 137 (6.2%) remained hospitalized. Factors independently associated with death included older age (≥80 vs <40 years of age: odds ratio [OR], 11.15; 95% CI, 6.19-20.06), male sex (OR, 1.50; 95% CI, 1.19-1.90), higher body mass index (≥40 vs <25: OR, 1.51; 95% CI, 1.01-2.25), coronary artery disease (OR, 1.47; 95% CI, 1.07-2.02), active cancer (OR, 2.15; 95% CI, 1.35-3.43), and the presence of hypoxemia (Pao2:Fio2<100 vs ≥300 mm Hg: OR, 2.94; 95% CI, 2.11-4.08), liver dysfunction (liver Sequential Organ Failure Assessment score of 2-4 vs 0: OR, 2.61; 95% CI, 1.30-5.25), and kidney dysfunction (renal Sequential Organ Failure Assessment score of 4 vs 0: OR, 2.43; 95% CI, 1.46-4.05) at ICU admission. Patients admitted to hospitals with fewer ICU beds had a higher risk of death (<50 vs ≥100 ICU beds: OR, 3.28; 95% CI, 2.16-4.99). Hospitals varied considerably in the risk-adjusted proportion of patients who died (range, 6.6%-80.8%) and in the percentage of patients who received hydroxychloroquine, tocilizumab, and other treatments and supportive therapies., Conclusions and Relevance: This study identified demographic, clinical, and hospital-level risk factors that may be associated with death in critically ill patients with COVID-19 and can facilitate the identification of medications and supportive therapies to improve outcomes.

Background and Objectives: Dysregulated mineral metabolism is a common and potentially maladaptive feature of critical illness, especially in patients with AKI, but its association with death has not been comprehensively investigated. We sought to determine whether elevated plasma levels of the osteocyte-derived, vitamin D-regulating hormone, fibroblast growth factor 23 (FGF23), are prospectively associated with death in critically ill patients with AKI requiring RRT, and in a general cohort of critically ill patients with and without AKI., Design, Setting, Participants, & Measurements: We measured plasma FGF23 and other mineral metabolite levels in two cohorts of critically ill patients ( n =1527). We included 817 patients with AKI requiring RRT who enrolled in the ARF Trial Network (ATN) study, and 710 patients with and without AKI who enrolled in the Validating Acute Lung Injury biomarkers for Diagnosis (VALID) study. We hypothesized that higher FGF23 levels at enrollment are independently associated with higher 60-day mortality., Results: In the ATN study, patients in the highest compared with lowest quartiles of C-terminal (cFGF23) and intact FGF23 (iFGF23) had 3.84 (95% confidence interval, 2.31 to 6.41) and 2.08 (95% confidence interval, 1.03 to 4.21) fold higher odds of death, respectively, after adjustment for demographics, comorbidities, and severity of illness. In contrast, plasma/serum levels of parathyroid hormone, vitamin D metabolites, calcium, and phosphate were not associated with 60-day mortality. In the VALID study, patients in the highest compared with lowest quartiles of cFGF23 and iFGF23 had 3.52 (95% confidence interval, 1.96 to 6.33) and 1.93 (95% confidence interval, 1.12 to 3.33) fold higher adjusted odds of death., Conclusions: Higher FGF23 levels are independently associated with greater mortality in critically ill patients., (Copyright © 2018 by the American Society of Nephrology.)

Acute kidney injury (AKI) is a complex systemic syndrome associated with high morbidity and mortality. Among critically ill patients admitted to intensive care units (ICUs), the incidence of AKI is as high as 50% and is associated with dismal outcomes. Thus, the development and validation of clinical risk prediction tools that accurately identify patients at high risk for AKI in the ICU is of paramount importance. We provide a comprehensive review of 3 clinical risk prediction tools that have been developed for incident AKI occurring in the first few hours or days following admission to the ICU. We found substantial heterogeneity among the clinical variables that were examined and included as significant predictors of AKI in the final models. The area under the receiver operating characteristic curves was ∼0.8 for all 3 models, indicating satisfactory model performance, though positive predictive values ranged from only 23 to 38%. Hence, further research is needed to develop more accurate and reproducible clinical risk prediction tools. Strategies for improved assessment of AKI susceptibility in the ICU include the incorporation of dynamic (time-varying) clinical parameters, as well as biomarker, functional, imaging, and genomic data., (© 2018 S. Karger AG, Basel.)

Rationale: Acute kidney injury is a common and severe complication of critical illness and cardiac surgery. Despite significant attempts at developing treatments, therapeutic advances to attenuate acute kidney injury and expedite recovery have largely failed., Objectives: Identifying genetic loci associated with increased risk of acute kidney injury may reveal novel pathways for therapeutic development., Methods: We conducted an exploratory genome-wide association study to identify single-nucleotide polymorphisms associated with genetic susceptibility to in-hospital acute kidney injury., Measurements and Main Results: We genotyped 609,508 single-nucleotide polymorphisms and performed genotype imputation in 760 acute kidney injury cases and 669 controls. We then evaluated polymorphisms that showed the strongest association with acute kidney injury in a replication patient population containing 206 cases with 1,406 controls. We observed an association between acute kidney injury and four single-nucleotide polymorphisms at two independent loci on metaanalysis of discovery and replication populations. These include rs62341639 (metaanalysis P = 2.48 × 10 -7 ; odds ratio [OR], 0.64; 95% confidence interval [CI], 0.55-0.76) and rs62341657 (P = 3.26 × 10 -7 ; OR, 0.65; 95% CI, 0.55-0.76) on chromosome 4 near APOL1-regulator IRF2, and rs9617814 (metaanalysis P = 3.81 × 10 -6 ; OR, 0.70; 95% CI, 0.60-0.81) and rs10854554 (P = 6.53 × 10 -7 ; OR, 0.67; 95% CI, 0.57-0.79) on chromosome 22 near acute kidney injury-related gene TBX1., Conclusions: Our findings reveal two genetic loci that are associated with acute kidney injury. Additional studies should be conducted to functionally evaluate these loci and to identify other common genetic variants contributing to acute kidney injury.

Introduction: Decreased production of cathelicidin antimicrobial protein-18 (hCAP18) has been proposed to be a key mechanism linking decreased 25-hydroxyvitamin D (25D) levels with adverse outcomes among critically ill patients. However, few studies in humans have directly assessed plasma hCAP18 levels, and no study has evaluated the association between hCAP18 levels and adverse outcomes among critically ill patients., Methods: We performed a single-center, prospective cohort study among 121 critically ill patients admitted to intensive care units (ICUs) between 2008 and 2012. We measured plasma hCAP18, 25D, D-binding protein, and parathyroid hormone levels on ICU day 1. The primary endpoint was 90-day mortality. Secondary endpoints included hospital mortality, sepsis, acute kidney injury, duration of mechanical ventilation, and hospital length of stay., Results: ICU day 1 hCAP18 levels were directly correlated with 25D levels (Spearman's rho (rs) = 0.30, P = 0.001). In multivariate analyses adjusted for age and Acute Physiology and Chronic Health Evaluation II (APACHE II) score, patients with hCAP18 levels in the lowest compared to highest tertile on ICU day 1 had a 4.49 (1.08 to 18.67) greater odds of 90-day mortality, and also had greater odds of sepsis. ICU day 1 levels of other analytes were not associated with 90-day mortality., Conclusions: Lower 25D levels on ICU day 1 are associated with lower hCAP18 levels, which are in turn associated with a greater risk of 90-day mortality. These findings provide a potential mechanistic basis for the frequently observed association between low 25D levels and poor outcomes in critically ill patients.