Machine Learning Prediction of Death in Critically Ill Patients With Coronavirus Disease 2019.
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ABSTRACT: Objectives
Critically ill patients with coronavirus disease 2019 have variable mortality. Risk scores could improve care and be used for prognostic enrichment in trials. We aimed to compare machine learning algorithms and develop a simple tool for predicting 28-day mortality in ICU patients with coronavirus disease 2019.Design
This was an observational study of adult patients with coronavirus disease 2019. The primary outcome was 28-day inhospital mortality. Machine learning models and a simple tool were derived using variables from the first 48 hours of ICU admission and validated externally in independent sites and temporally with more recent admissions. Models were compared with a modified Sequential Organ Failure Assessment score, National Early Warning Score, and CURB-65 using the area under the receiver operating characteristic curve and calibration.Setting
Sixty-eight U.S. ICUs.Patients
Adults with coronavirus disease 2019 admitted to 68 ICUs in the United States between March 4, 2020, and June 29, 2020.Interventions
None.Measurements and main results
The study included 5,075 patients, 1,846 (36.4%) of whom died by day 28. eXtreme Gradient Boosting had the highest area under the receiver operating characteristic curve in external validation (0.81) and was well-calibrated, while k-nearest neighbors were the lowest performing machine learning algorithm (area under the receiver operating characteristic curve 0.69). Findings were similar with temporal validation. The simple tool, which was created using the most important features from the eXtreme Gradient Boosting model, had a significantly higher area under the receiver operating characteristic curve in external validation (0.78) than the Sequential Organ Failure Assessment score (0.69), National Early Warning Score (0.60), and CURB-65 (0.65; p < 0.05 for all comparisons). Age, number of ICU beds, creatinine, lactate, arterial pH, and Pao2/Fio2 ratio were the most important predictors in the eXtreme Gradient Boosting model.Conclusions
eXtreme Gradient Boosting had the highest discrimination overall, and our simple tool had higher discrimination than a modified Sequential Organ Failure Assessment score, National Early Warning Score, and CURB-65 on external validation. These models could be used to improve triage decisions and clinical trial enrichment.
SUBMITTER: Churpek MM
PROVIDER: S-EPMC8378790 | biostudies-literature |
REPOSITORIES: biostudies-literature
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| S-EPMC7314329 | biostudies-literature
Project description:ImportanceThe 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.ObjectivesTo assess factors associated with death and to examine interhospital variation in treatment and outcomes for patients with COVID-19.Design, setting, and participantsThis 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.ExposuresPatient-level data, including demographics, comorbidities, and organ dysfunction, and hospital characteristics, including number of ICU beds.Main outcomes and measuresThe 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.ResultsA 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 relevanceThis 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.
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Project description:Objectives:To determine delirium occurrence rate, duration, and severity in patients admitted to the ICU with coronavirus disease 2019. Design:Retrospective data extraction study from March 1, 2020, to June 7, 2020. Delirium outcomes were assessed for up to the first 14 days in ICU. Setting:Two large, academic centers serving the state of Indiana. Patients:Consecutive patients admitted to the ICU with positive severe acute respiratory syndrome coronavirus 2 nasopharyngeal swab polymerase chain reaction test from March 1, 2020, to June 7, 2020, were included. Individuals younger than 18 years of age, without any delirium assessments, or without discharge disposition were excluded. Measurements and Main Results:Primary outcomes were delirium rates and duration, and the secondary outcome was delirium severity. Two-hundred sixty-eight consecutive patients were included in the analysis with a mean age of 58.4 years (sd, 15.6 yr), 40.3% were female, 44.4% African American, 20.7% Hispanic, and a median Acute Physiology and Chronic Health Evaluation II score of 18 (interquartile range, 13-25). Delirium without coma occurred in 29.1% of patients, delirium prior to coma in 27.9%, and delirium after coma in 23.1%. The first Confusion Assessment Method for the ICU assessment was positive for delirium in 61.9%. Hypoactive delirium was the most common subtype (87.4%). By day 14, the median number of delirium/coma-free were 5 days (interquartile range, 4-11 d), and median Confusion Assessment Method for the ICU-7 score was 6.5 (interquartile range, 5-7) indicating severe delirium. Benzodiazepines were ordered for 78.4% of patients in the cohort. Mechanical ventilation was associated with greater odds of developing delirium (odds ratio, 5.0; 95% CI, 1.1-22.2; p = 0.033) even after adjusting for sedative medications. There were no between-group differences in mortality. Conclusions:Delirium without coma occurred in 29.1% of patients admitted to the ICU. Delirium persisted for a median of 5 days and was severe. Mechanical ventilation was significantly associated with odds of delirium even after adjustment for sedatives. Clinical attention to manage delirium duration and severity, and deeper understanding of the virus' neurologic effects is needed for patients with coronavirus disease 2019.
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Project description:To describe the epidemiology of superinfections (occurring > 48 hr after hospital admission) and their impact on the ICU and 28-day mortality in patients with coronavirus disease 2019 with acute respiratory distress syndrome, requiring mechanical ventilation.DesignRetrospective analysis of prospectively collected observational data.SettingUniversity-affiliated adult ICU.PatientsNinety-two coronavirus disease 2019 patients admitted to the ICU from February 21, 2020, to May 6, 2020.InterventionsNone.Measurements and main resultsThe prevalence of superinfection at ICU admission was 21.7%, and 53 patients (57.6%) had at least one superinfection during ICU stay, with a total of 75 (82%) ventilator-associated pneumonia and 57 (62%) systemic infections. The most common pathogens responsible for ventilator-associated pneumonia were Pseudomonas aeruginosa (n = 26, 34.7%) and Stenotrophomonas maltophilia (n = 14, 18.7%). Bloodstream infection occurred in 16 cases, including methicillin-resistant Staphylococcus epidermidis (n = 8, 14.0%), Enterococcus species (n = 6, 10.5%), and Streptococcus species (n = 2, 3.5%). Fungal infections occurred in 41 cases, including 36 probable (30 by Candida albicans, six by C. nonalbicans) and five proven invasive candidiasis (three C. albicans, two C. nonalbicans). Presence of bacterial infections (odds ratio, 10.53; 95% CI, 2.31-63.42; p = 0.005), age (odds ratio, 1.17; 95% CI, 1.07-1.31; p = 0.001), and the highest Sequential Organ Failure Assessment score (odds ratio, 1.27; 95% CI, 1.06-1.63; p = 0.032) were independently associated with ICU or 28-day mortality.ConclusionsPrevalence of superinfections in coronavirus disease 2019 patients requiring mechanical ventilation was high in this series, and bacterial superinfections were independently associated with ICU or 28-day mortality (whichever comes first).
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Project description:ObjectivesCoronavirus disease 2019 is associated with high mortality rates and multiple organ damage. There is increasing evidence that these patients are at risk for various cardiovascular insults; however, there are currently no guidelines for the diagnosis and management of such cardiovascular complications in patients with coronavirus disease 2019. We share data and recommendations from a multidisciplinary team to highlight our institution's clinical experiences and guidelines for managing cardiovascular complications of coronavirus disease 2019.Design setting and patientsThis was a retrospective cohort study of patients admitted to one of six ICUs dedicated to the care of patients with coronavirus disease 2019 located in three hospitals within one academic medical center in Atlanta, Georgia.Measurements/interventionsChart review was conducted for sociodemographic, laboratory, and clinical data. Rates of specific cardiovascular complications were assessed, and data were analyzed using a chi-square or Wilcoxon rank-sum test for categorical and continuous variables. Additionally, certain cases are presented to demonstrate the sub committee's recommendations.Main resultsTwo-hundred eighty-eight patients were admitted to the ICU with coronavirus disease 2019. Of these, 86 died (29.9%), 242 (84.03%) had troponin elevation, 70 (24.31%) had dysrhythmias, four (1.39%) had ST-elevation myocardial infarction, eight (2.78%) developed cor pulmonale, and 190 (65.97%) with shock. There was increased mortality risk in patients with greater degrees of troponin elevation (p < 0.001) and with the development of arrhythmias (p < 0.001), cor pulmonale (p < 0.001), and shock (p < 0.001).ConclusionsWhile there are guidelines for the diagnosis and management of pulmonary complications of coronavirus disease 2019, there needs to be more information regarding the management of cardiovascular complications as well. These recommendations garnered from the coronavirus disease 2019 cardiology subcommittee from our institution will add to the existing knowledge of these potential cardiovascular insults as well as highlight suggestions for the diagnosis and management of the range of cardiovascular complications of coronavirus disease 2019. Additionally, with the spread of coronavirus disease 2019, our case-based recommendations provide a bedside resource for providers newly caring for patients with coronavirus disease 2019.
| S-EPMC7717747 | biostudies-literature
Project description:ObjectivesCritical illness is characterized by increased serum cortisol concentrations and bioavailability resulting from the activation of the hypothalamic-pituitary-adrenal axis, which constitutes an essential part of the stress response. The actions of glucocorticoids are mediated by a ubiquitous intracellular receptor protein, the glucocorticoid receptor. So far, data on coronavirus disease 2019 and glucocorticoid receptor alpha expression are lacking.DesignProspective observational study.SettingOne academic multidisciplinary ICU.SubjectsTwenty-six adult coronavirus disease 2019 patients; 33 adult noncoronavirus disease 2019 patients, matched for age, sex, and disease severity, constituted the control group. All patients were steroid-free.InterventionsNone.Measurements and main resultsGlucocorticoid receptor alpha, glucocorticoid-inducible leucine zipper expression, and serum cortisol were measured on ICU admission. In coronavirus disease 2019 patients, glucocorticoid receptor alpha and glucocorticoid-inducible leucine zipper messenger RNA expression were upregulated (4.7-fold, p < 0.01 and 14-fold, p < 0.0001, respectively), and cortisol was higher (20.3 vs 14.3 μg/dL, p < 0.01) compared with the control group.ConclusionsICU coronavirus disease 2019 patients showed upregulated glucocorticoid receptor alpha and glucocorticoid-inducible leucine zipper expression, along with cortisol levels, compared with ICU noncoronavirus disease 2019 patients. Thus, on ICU admission, critical coronavirus disease 2019 appears to be associated with hypercortisolemia, and increased synthesis of glucocorticoid receptor alpha and induced proteins.
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