Predictors of Mortality in Hospitalized COVID-19 Patients Complicated With Hypotension and Hypoxemia: A Retrospective Cohort Study
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SUBMITTER: Sun B
PROVIDER: S-EPMC8581201 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundFirst reported case of Severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) in Kazakhstan was identified in March 2020. Many specialized tertiary hospitals in Kazakhstan including National Research Cardiac Surgery Center (NRCSC) were re-organized to accept coronavirus disease 2019 (COVID-19) infected patients during summer months of 2020. Although many studies from worldwide reported their experience in treating patients with COVID-19, there are limited data available from the Central Asia countries. The aim of this study is to identify predictors of mortality associated with COVID-19 in NRCSC tertiary hospital in Nur-Sultan, Kazakhstan.MethodsThis is a retrospective cohort study of patients admitted to the NRCSC between June 1st-August 31st 2020 with COVID-19. Demographic, clinical and laboratory data were collected from electronic records. In-hospital mortality was assessed as an outcome. Patients were followed-up until in-hospital death or discharge from the hospital. Descriptive statistics and factors associated with mortality were assessed using univariate and multivariate logistic regression models.ResultsTwo hundred thirty-nine admissions were recorded during the follow-up period. Mean age was 57 years and 61% were males. Median duration of stay at the hospital was 8 days and 34 (14%) patients died during the hospitalization. Non-survivors were more likely to be admitted later from the disease onset, with higher fever, lower oxygen saturation and increased respiratory rate compared to survivors. Leukocytosis, lymphopenia, anemia, elevated liver and kidney function tests, hypoproteinemia, elevated inflammatory markers (C-reactive protein (CRP), ferritin, and lactate dehydrogenase (LDH)) and coagulation tests (fibrinogen, D-dimer, international normalized ratio (INR), and activated partial thromboplastin time (aPTT)) at admission were associated with mortality. Age (OR 1.2, CI:1.01-1.43), respiratory rate (OR 1.38, CI: 1.07-1.77), and CRP (OR 1.39, CI: 1.04-1.87) were determined to be independent predictors of mortality.ConclusionThis study describes 14% mortality rate from COVID-19 in the tertiary hospital. Many abnormal clinical and laboratory variables at admission were associated with poor outcome. Age, respiratory rate and CRP were found to be independent predictors of mortality. Our finding would help healthcare providers to predict the risk factors associated with high risk of mortality. Further investigations involving large cohorts should be provided to support our findings.
| S-EPMC8694457 | biostudies-literature
Project description:Hypoxemia is a hallmark of coronavirus disease 2019 (COVID-19) severity. We sought to determine predictors of hypoxemia and related adverse outcomes among patients hospitalized with COVID-19 in the two largest hospitals in Jerusalem, Israel, from 9 March through 16 July 2020. Patients were categorized as those who developed reduced (<94%) vs. preserved (≥94%) arterial oxygen saturation (SpO2) within the first 48 h after arrival to the emergency department. Overall, 492 hospitalized patients with COVID-19 were retrospectively analyzed. Patients with reduced SpO2 were significantly older, had more comorbidities, higher body surface area (BSA) and body mass index (BMI), lower lymphocyte counts, impaired renal function, and elevated liver enzymes, c-reactive protein (CRP), and D-dimer levels as compared to those with preserved SpO2. In the multivariable regression analysis, older age (odds ratio (OR) 1.02 per year, p < 0.001), higher BSA (OR 1.16 per 0.10 m2, p = 0.003) or BMI (OR 1.05 per 1 kg/m2, p = 0.011), lower lymphocyte counts (OR 1.72 per 1 × 103/μL decrease, p = 0.002), and elevated CRP (1.11 per 1 mg/dL increase, p < 0.001) were found to be independent predictors of low SpO2. Severe hypoxemia requiring ventilatory support, older age, and pre-existing comorbidities, including underlying renal dysfunction and heart failure, were found to be significantly associated with in-hospital mortality. These findings suggest that assessment of predictors of hypoxemia early at the time of hospitalization with COVID-19 may be helpful in risk stratification and management.
| S-EPMC8397029 | biostudies-literature
Project description:In patients hospitalized with COVID-19 pneumonia, both tocilizumab and baricitinib have been shown to have clinical benefit compared with placebo. To date, there are few data comparing the two treatments, and their relative benefits and harms are unknown. This study aims to evaluate the effectiveness of tocilizumab versus baricitinib in patients hospitalized with COVID-19 pneumonia and hypoxemia.DesignRetrospective cohort study.SettingSeven inpatient acute-care hospitals in Wisconsin.ParticipantsPatients hospitalized with COVID-19, hypoxemia, and Pao2-to-Fio2 ratio less than or equal to 300 mm Hg, who received either tocilizumab or baricitinib.InterventionsElectronic chart review.Measurements and main resultsPatients were divided into tocilizumab and baricitinib cohorts based on actual medication received. The primary outcome was hospital discharge alive and free from mechanical ventilation within 60 days, assessed by logistic regression. Three hundred eighty-two patients were included: 194 in the tocilizumab cohort and 188 in the baricitinib cohort. Most baseline characteristics in the two cohorts were similar. All patients received dexamethasone. Two patients were lost to follow-up. In the remaining 380 patients, probability of successful discharge in the two cohorts was quantitatively similar in unadjusted, multivariate-adjusted, and propensity score-matched analyses. Hospital length of stay, rates of thromboembolic events, and rates of hospital-acquired infections were all similar in the two cohorts.ConclusionsIn patients hospitalized with COVID-19 pneumonia and hypoxemia who receive dexamethasone, treatment with tocilizumab or baricitinib appears to result in similar outcomes.
| S-EPMC9243240 | biostudies-literature
Project description:BackgroundThe novel coronavirus SARS-CoV-2 and its associated disease, COVID-19, have caused worldwide disruption, leading countries to take drastic measures to address the progression of the disease. As SARS-CoV-2 continues to spread, hospitals are struggling to allocate resources to patients who are most at risk. In this context, it has become important to develop models that can accurately predict the severity of infection of hospitalized patients to help guide triage, planning, and resource allocation.ObjectiveThe aim of this study was to develop accurate models to predict the mortality of hospitalized patients with COVID-19 using basic demographics and easily obtainable laboratory data.MethodsWe performed a retrospective study of 375 hospitalized patients with COVID-19 in Wuhan, China. The patients were randomly split into derivation and validation cohorts. Regularized logistic regression and support vector machine classifiers were trained on the derivation cohort, and accuracy metrics (F1 scores) were computed on the validation cohort. Two types of models were developed: the first type used laboratory findings from the entire length of the patient's hospital stay, and the second type used laboratory findings that were obtained no later than 12 hours after admission. The models were further validated on a multicenter external cohort of 542 patients.ResultsOf the 375 patients with COVID-19, 174 (46.4%) died of the infection. The study cohort was composed of 224/375 men (59.7%) and 151/375 women (40.3%), with a mean age of 58.83 years (SD 16.46). The models developed using data from throughout the patients' length of stay demonstrated accuracies as high as 97%, whereas the models with admission laboratory variables possessed accuracies of up to 93%. The latter models predicted patient outcomes an average of 11.5 days in advance. Key variables such as lactate dehydrogenase, high-sensitivity C-reactive protein, and percentage of lymphocytes in the blood were indicated by the models. In line with previous studies, age was also found to be an important variable in predicting mortality. In particular, the mean age of patients who survived COVID-19 infection (50.23 years, SD 15.02) was significantly lower than the mean age of patients who died of the infection (68.75 years, SD 11.83; P<.001).ConclusionsMachine learning models can be successfully employed to accurately predict outcomes of patients with COVID-19. Our models achieved high accuracies and could predict outcomes more than one week in advance; this promising result suggests that these models can be highly useful for resource allocation in hospitals.
| S-EPMC7572117 | biostudies-literature
Project description:Clinical features and natural history of coronavirus disease 2019 (COVID-19) differ widely among different countries and during different phases of the pandemia. Here, we aimed to evaluate the case fatality rate (CFR) and to identify predictors of mortality in a cohort of COVID-19 patients admitted to three hospitals of Northern Italy between March 1 and April 28, 2020. All these patients had a confirmed diagnosis of SARS-CoV-2 infection by molecular methods. During the study period 504/1697 patients died; thus, overall CFR was 29.7%. We looked for predictors of mortality in a subgroup of 486 patients (239 males, 59%; median age 71 years) for whom sufficient clinical data were available at data cut-off. Among the demographic and clinical variables considered, age, a diagnosis of cancer, obesity and current smoking independently predicted mortality. When laboratory data were added to the model in a further subgroup of patients, age, the diagnosis of cancer, and the baseline PaO2/FiO2 ratio were identified as independent predictors of mortality. In conclusion, the CFR of hospitalized patients in Northern Italy during the ascending phase of the COVID-19 pandemic approached 30%. The identification of mortality predictors might contribute to better stratification of individual patient risk.
| S-EPMC7692524 | biostudies-literature
Project description:BackgroundThe global coronavirus disease 2019 (COVID-19) pandemic offers the opportunity to assess how hospitals manage the care of hospitalized patients with varying demographics and clinical presentations. The goal of this study was to demonstrate the impact of densely populated residential areas on hospitalization and to identify predictors of length of stay and mortality in hospitalized patients with COVID-19 in one of the hardest hit counties internationally.MethodsThis was a single-center cohort study of 1325 sequentially hospitalized patients with COVID-19 in New York between March 2, 2020, to May 11, 2020. Geospatial distribution of study patients' residences relative to population density in the region were mapped, and data analysis included hospital length of stay, need and duration of invasive mechanical ventilation (IMV), and mortality. Logistic regression models were constructed to predict discharge dispositions in the remaining active study patients.ResultsThe median age of the study cohort (interquartile range [IQR]) was 62 (49-75) years, and more than half were male (57%) with history of hypertension (60%), obesity (41%), and diabetes (42%). Geographic residence of the study patients was disproportionately associated with areas of higher population density (r s = 0.235; P = .004), with noted "hot spots" in the region. Study patients were predominantly hypertensive (MAP > 90 mmHg; 670, 51%) on presentation with lymphopenia (590, 55%), hyponatremia (411, 31%), and kidney dysfunction (estimated glomerular filtration rate < 60 mL/min/1.73 m2; 381, 29%). Of the patients with a disposition (1188/1325), 15% (182/1188) required IMV and 21% (250/1188) developed acute kidney injury. In patients on IMV, the median (IQR) hospital length of stay in survivors (22 [16.5-29.5] days) was significantly longer than that of nonsurvivors (15 [10-23.75] days), but this was not due to prolonged time on the ventilator. The overall mortality in all hospitalized patients was 15%, and in patients receiving IMV it was 48%, which is predicted to minimally rise from 48% to 49% based on logistic regression models constructed to project disposition in the remaining patients on ventilators. Acute kidney injury during hospitalization (odds ratioE, 3.23) was the strongest predictor of mortality in patients requiring IMV.ConclusionsThis is the first study to collectively utilize the demographics, clinical characteristics, and hospital course of COVID-19 patients to identify predictors of poor outcomes that can be used for resource allocation in future waves of the pandemic.
| S-EPMC7543608 | biostudies-literature
Project description:BackgroundThe waves of COVID-19 infections in Ontario, Canada, were marked by differences in patient characteristics and treatment. Our objectives were to (i) describe patient characteristics, treatment, and outcomes of hospitalized older adults with COVID-19 between waves 1, 2, and 3, (ii) determine if there was an improvement in in-hospital mortality in waves 2 and 3 after adjusting for covariates.MethodsThis retrospective cohort study was done in five acute care hospitals in Toronto, Ontario. Consecutive hospitalized older adults aged ≥65 years with confirmed COVID-19 infection were included. Wave 1 extended from March 11 to July 31, 2020, wave 2 from August 1, 2020 to February 20, 2021, and wave 3 from February 21 to June 30, 2021. Patient characteristics and outcomes were abstracted from charts. A logistic regression model was used to determine the association between COVID-19 and in-hospital mortality in waves 2 and 3 compared with wave 1.ResultsOf the 1671 patients admitted to acute care, 297 (17.8%) were admitted in wave 1, 751 (44.9%) in wave 2, and 623 (37.3%) in wave 3. The median age of our cohort was 77.0 years (interquartile range: 71.0-85.0) and 775 (46.4%) were female. The prevalence of frailty declined in progressive waves. The use of dexamethasone, remdesivir, and tocilizumab was significantly higher in waves 2 and 3 compared with wave 1. In the unadjusted analysis, in-hospital mortality was unchanged between waves 1 and 2, but it was lower in wave 3 (18.3% vs. 27.4% in wave 1). After adjustment, in-hospital mortality was unchanged in waves 2 and 3 compared with wave 1.ConclusionIn-hospital mortality in hospitalized older adults with COVID-19 was similar between waves 1 and 3. Further research should be done to determine if COVID-19 therapies have similar benefits for older adults compared with younger adults.
| S-EPMC9059224 | biostudies-literature
Project description:BackgroundTo analyze the clinical characteristics and predictors for mortality of adult younger than 60 years old with severe coronavirus disease 2019 (COVID-19).MethodsWe retrospectively retrieved data for 152 severe inpatients with COVID-19 including 60 young patients in the Eastern Campus of Wuhan University affiliated Renmin Hospital in Wuhan, China, from January 31, 2020 to February 20, 2020. We recorded and analyzed patients' demographic, clinical, laboratory, and chest CT findings, treatment and outcomes data.ResultsOf those 60 severe young patients, 15 (25%) were died. Male was more predominant in deceased young patients (12, 80%) than that in recovered young patients (22, 49%). Hypertension was more common among deceased young patients (8, 53%) than that in recovered young patients (7, 16%). Compared with the recovered young patients, more deceased young patients presented with sputum (11, 73%), dyspnea (12, 80%) and fatigue (13, 87%). Only sputum, PSI and neutrophil counts were remained as independent predictors of death in a multivariate logistic regression model. Among ARDS patients, the recovered were administrated with corticosteroid earlier and anticoagulation. The addition of neutrophil counts >6.3×109/L to the SMART-COP score resulted in improved area under the curves.ConclusionsSevere acute respiratory syndrome coronavirus 2 (SARS-Cov-2) infection in young deceased patients appears to cause exuberant inflammatory responses, leading to compromised oxygen exchange, coagulation and multi-organ dysfunction. In addition, young patients with ARDS could benefit from adjuvant early corticosteroid and anticoagulation therapy. The expanded SMART-COP could predict the fatal outcomes with optimal efficiency.
| S-EPMC8264719 | biostudies-literature
Project description:The impact of the coronavirus disease 2019 (COVID-19) pandemic among patients with chronic liver disease is unknown. Given the high prevalence of nonalcoholic fatty liver disease (NAFLD), we determined the predictors of mortality and hospital resource use among patients with NAFLD admitted with COVID-19 by using electronic medical records data for adult patients with COVID-19 hospitalized in a multihospital health system who were discharged between March and December 2020. NAFLD was diagnosed by imaging or liver biopsy without other liver diseases. Charlson's comorbidity index (CCI) and Elixhauser comorbidity index (ECI) scores were calculated. In the study sample, among the 4,835 patients hospitalized for COVID-19, 553 had NAFLD (age: 55 ± 16 years, 51% male, 17% White, 11% Black, 58% Hispanic, 8% Asian, 5% from congregated living, 58% obese, 15% morbid obesity [body mass index ≥ 40], 51% type 2 diabetes, 63% hypertension, mean [SD] baseline CCI of 3.9 [3.2], and baseline ECI of 13.4 [11.3]). On admission, patients with NAFLD had more respiratory symptoms, higher body temperature and heart rate, higher alanine aminotransferase and aspartate aminotransferase than non-NAFLD controls (n = 2,736; P < 0.05). Of the patients with NAFLD infected with COVID-19, 3.9% experienced acute liver injury. The NAFLD group had significantly longer length of stay, intensive care unit use, and mechanical ventilation, with a crude inpatient mortality rate of 11%. In multivariate analysis, independent predictors of inpatient mortality among patients with NAFLD infected with COVID-19 were older age, morbid obesity, ECI score ≥ 11, higher Fibrosis-4 Index (FIB-4) score, and oxygen saturation <90% (all P < 0.05), but not sex, race/ethnicity, or any individual comorbidity (all P > 0.05). Conclusion: Patients with NAFLD infected with COVID-19 tend to be sicker on admission and require more hospital resource use. Independent predictors of mortality included higher FIB-4 and multimorbidity scores, morbid obesity, older age, and hypoxemia on admission.
| S-EPMC8426701 | biostudies-literature
Project description:BackgroundWe aimed to identify the prevalence and predictors of venous thromboembolism (VTE) or mortality in hospitalized coronavirus disease 2019 (COVID-19) patients.MethodsA retrospective cohort study of hospitalized adult patients admitted to an integrated health care network in the New York metropolitan region between March 1, 2020 and April 27, 2020. The final analysis included 9,407 patients with an overall VTE rate of 2.9% (2.4% in the medical ward and 4.9% in the intensive care unit [ICU]) and a VTE or mortality rate of 26.1%. Most patients received prophylactic-dose thromboprophylaxis. Multivariable analysis showed significantly reduced VTE or mortality with Black race, history of hypertension, angiotensin converting enzyme/angiotensin receptor blocker use, and initial prophylactic anticoagulation. It also showed significantly increased VTE or mortality with age 60 years or greater, Charlson Comorbidity Index (CCI) of 3 or greater, patients on Medicare, history of heart failure, history of cerebrovascular disease, body mass index greater than 35, steroid use, antirheumatologic medication use, hydroxychloroquine use, maximum D-dimer four times or greater than the upper limit of normal (ULN), ICU level of care, increasing creatinine, and decreasing platelet counts.ConclusionIn our large cohort of hospitalized COVID-19 patients, the overall in-hospital VTE rate was 2.9% (4.9% in the ICU) and a VTE or mortality rate of 26.1%. Key predictors of VTE or mortality included advanced age, increasing CCI, history of cardiovascular disease, ICU level of care, and elevated maximum D-dimer with a cutoff at least four times the ULN. Use of prophylactic-dose anticoagulation but not treatment-dose anticoagulation was associated with reduced VTE or mortality.
| S-EPMC9044533 | biostudies-literature