Dataset Information

Delirium Incidence, Duration, and Severity in Critically Ill Patients With Coronavirus Disease 2019.

ABSTRACT: 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.

SUBMITTER: Khan SH

PROVIDER: S-EPMC7690767 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Delirium Incidence, Duration, and Severity in Critically Ill Patients With Coronavirus Disease 2019.

Khan Sikandar H SH Lindroth Heidi H Perkins Anthony J AJ Jamil Yasser Y Wang Sophia S Roberts Scott S Farber Mark M Rahman Omar O Gao Sujuan S Marcantonio Edward R ER Boustani Malaz M Machado Roberto R Khan Babar A BA

Critical care explorations 20201125 12

<h4>Objectives</h4>To determine delirium occurrence rate, duration, and severity in patients admitted to the ICU with coronavirus disease 2019.<h4>Design</h4>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.<h4>Setting</h4>Two large, academic centers serving the state of Indiana.<h4>Patients</h4>Consecutive patients admitted to the ICU with positive severe acute respiratory syndrome coronavirus 2 nasophary ...[more]

PMID: 33251519

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Project description:ObjectivesCoronavirus disease 2019 is caused by severe acute respiratory syndrome-coronavirus-2 infection to which there is no community immunity. Patients admitted to ICUs have high mortality, with only supportive therapies available. Our aim was to profile plasma inflammatory analytes to help understand the host response to coronavirus disease 2019.DesignDaily blood inflammation profiling with immunoassays.SettingTertiary care ICU and academic laboratory.SubjectsAll patients admitted to the ICU suspected of being infected with severe acute respiratory syndrome-coronavirus-2, using standardized hospital screening methodologies, had daily blood samples collected until either testing was confirmed negative on ICU day 3 (coronavirus disease 2019 negative), or until ICU day 7 if the patient was positive (coronavirus disease 2019 positive).InterventionsNone.Measurements and main resultsAge- and sex-matched healthy controls and ICU patients that were either coronavirus disease 2019 positive or coronavirus disease 2019 negative were enrolled. Cohorts were well-balanced with the exception that coronavirus disease 2019 positive patients were more likely than coronavirus disease 2019 negative patients to suffer bilateral pneumonia. Mortality rate for coronavirus disease 2019 positive ICU patients was 40%. We measured 57 inflammatory analytes and then analyzed with both conventional statistics and machine learning. Twenty inflammatory analytes were different between coronavirus disease 2019 positive patients and healthy controls (p < 0.01). Compared with coronavirus disease 2019 negative patients, coronavirus disease 2019 positive patients had 17 elevated inflammatory analytes on one or more of their ICU days 1-3 (p < 0.01), with feature classification identifying the top six analytes between cohorts as tumor necrosis factor, granzyme B, heat shock protein 70, interleukin-18, interferon-gamma-inducible protein 10, and elastase 2. While tumor necrosis factor, granzyme B, heat shock protein 70, and interleukin-18 were elevated for all seven ICU days, interferon-gamma-inducible protein 10 transiently elevated on ICU days 2 and 3 and elastase 2 increased over ICU days 2-7. Inflammation profiling predicted coronavirus disease 2019 status with 98% accuracy, whereas elevated heat shock protein 70 was strongly associated with mortality.ConclusionsWhile many inflammatory analytes were elevated in coronavirus disease 2019 positive ICU patients, relative to healthy controls, the top six analytes distinguishing coronavirus disease 2019 positive ICU patients from coronavirus disease 2019 negative ICU patients were tumor necrosis factor, granzyme B, heat shock protein 70, interleukin-18, interferon-gamma-inducible protein 10, and elastase 2.

Project description:BackgroundSevere acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection causes direct lung damage, overwhelming endothelial activation, and inflammatory reaction, leading to acute respiratory failure and multi-organ dysfunction. Ongoing clinical trials are evaluating targeted therapies to hinder this exaggerated inflammatory response. Critically ill coronavirus disease 2019 (COVID-19) patients have shown heterogeneous severity trajectories, suggesting that response to therapies is likely to vary across patients.Research questionAre critically ill COVID-19 patients biologically and immunologically dissociable based on profiling of currently evaluated therapeutic targets?Study design and methodsWe did a single-center, prospective study in an ICU department in France. Ninety-six critically ill adult patients admitted with a documented SARS-CoV-2 infection were enrolled. We conducted principal components analysis and hierarchical clustering on a vast array of immunologic variables measured on the day of ICU admission.ResultsWe found that patients were distributed in three clusters bearing distinct immunologic features and associated with different ICU outcomes. Cluster 1 had a "humoral immunodeficiency" phenotype with predominant B-lymphocyte defect, relative hypogammaglobulinemia, and moderate inflammation. Cluster 2 had a "hyperinflammatory" phenotype, with high cytokine levels (IL-6, IL-1β, IL-8, tumor necrosis factor-alpha [TNF⍺]) associated with CD4+ and CD8+ T-lymphocyte defects. Cluster 3 had a "complement-dependent" phenotype with terminal complement activation markers (elevated C3 and sC5b-9).InterpretationPatients with severe COVID-19 exhibiting cytokine release marks, complement activation, or B-lymphocyte defects are distinct from each other. Such immunologic variability argues in favor of targeting different mediators in different groups of patients and could serve as a basis for patient identification and clinical trial eligibility.

Project description:BackgroundCardiac injury has been reported in up to 30% of coronavirus disease 2019 (COVID-19) patients. However, cardiac injury is defined mainly by troponin elevation without description of associated structural abnormalities and its time course has not been studied.Research questionWhat are the ECG and echocardiographic abnormalities as well as their time course in critically ill COVID-19 patients?Study design and methodsThe cardiac function of 43 consecutive COVID-19 patients admitted to two ICUs was assessed prospectively and repeatedly, combining ECG, cardiac biomarker, and transthoracic echocardiographic analyses from ICU admission to ICU discharge or death or to a maximum follow-up of 14 days. Cardiac injury was defined by troponin elevation and newly diagnosed ECG or echocardiographic abnormalities, or both.ResultsAt baseline, 49% of patients demonstrated a cardiac injury, and 70% of patients experienced cardiac injury within the first 14 days of ICU stay, with a median time of occurrence of 3 days (range, 0-7 days). The most frequent abnormalities were ECG or echocardiographic signs, or both, of left ventricular (LV) abnormalities (87% of patients with cardiac injury), right ventricular (RV) systolic dysfunction (47%), pericardial effusion (43%), new-onset atrial arrhythmias (33%), LV relaxation impairment (33%), and LV systolic dysfunction (13%). Between baseline and day 14, the incidence of pericardial effusion and of new-onset atrial arrhythmias increased and the incidence of ECG or echocardiographic signs, or both, of LV abnormalities as well as the incidence of LV relaxation impairment remained stable, whereas the incidence of RV and LV systolic dysfunction decreased.InterpretationCardiac injury is common and early in critically ill COVID-19 patients. ECG or echocardiographic signs, or both, of LV abnormalities were the most frequent abnormalities, and patients with cardiac injury experienced more RV than LV systolic dysfunction.

Project description:ObjectivesCritically 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.DesignThis 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.SettingSixty-eight U.S. ICUs.PatientsAdults with coronavirus disease 2019 admitted to 68 ICUs in the United States between March 4, 2020, and June 29, 2020.InterventionsNone.Measurements and main resultsThe 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.ConclusionseXtreme 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.

Dataset Information

Delirium Incidence, Duration, and Severity in Critically Ill Patients With Coronavirus Disease 2019.

Publications

Delirium Incidence, Duration, and Severity in Critically Ill Patients With Coronavirus Disease 2019.

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