key: cord-0748277-34s3ddwb authors: Bhargava, Ashish; Sharma, Mamta; Akagi, Elisa; Szpunar, Susanna M.; Saravolatz, Louis title: Predictors for in-hospital mortality from coronavirus disease 2019 (COVID-19) infection among adults aged 18–65 years date: 2020-12-16 journal: Infection control and hospital epidemiology DOI: 10.1017/ice.2020.1390 sha: 4fdd330753fc7379a174dafe7d7f162cd507c190 doc_id: 748277 cord_uid: 34s3ddwb nan We conducted a retrospective study at a 776-bed, tertiary-care center. The study was approved by the Ascension St John Hospital Institutional Review Board. We included adult patients with confirmed COVID-19 by positive real-time reverse-transcriptase-polymerase chain reaction (RT-PCR) assay of a nasopharyngeal swab for severe acute respiratory coronavirus virus 2 (SARS-CoV-2) from March 8 to June 14, 2020. Patient demographics, comorbid conditions, presenting symptoms, initial vital signs, admission laboratory and radiological findings, and outcome variables were extracted from the electronic medical records. Statistical analyses were performed using SPSS version 27.0 software (IBM, Armonk, NY). Univariable analyses were conducted using the Student t test, the Mann-Whitney U test, and χ 2 analysis. Variables that were significant or near-significant predictors of mortality (P < .09) were entered into a multivariable logistic regression model using a forward likelihood ratio algorithm. For comorbidities, the Charlson weighted index of comorbidity (CWIC) score was used instead of individual comorbid conditions. 3 Results from the regression are reported as odds ratios with 95% confidence intervals. All reported P values are 2-sided. In total, 265 hospitalized patients, ages 18-65 years, were included in this study. The mean age of the cohort was 50.4 years (SD, 10.7), 140 (52.8%) were male, and 226 (85.3%) were black/African-American. The mean body mass index of the cohort was 35.8 kg/m 2 (SD, 9.3) . The mean duration of symptoms prior to hospitalization was 5.8 days (SD, 3.8). Severe pneumonia was diagnosed in 49 patients (18.5%). Mechanical ventilation was required for 66 patients (24.9%). Overall, 214 patients (80.8%) improved clinically and survived to discharge. The in-hospital case fatality rate (CFR) was 19.2% (51 of 265). Patients who died were significantly older (mean age, 53.4 years [SD, 9.4] vs 49.7 years [SD, 10.8]) than patients who survived (P = .03). Patients who died were significantly more likely to have hypertension, diabetes with chronic complications, hemiplegia, preexisting renal disease, liver disease, and a diagnosis of malignancy (Table 1 ). The prevalence of lymphocytopenia and thrombocytopenia were higher among patients who died than those who survived. The Quick Sequential Organ Failure Assessment (qSOFA) score (0-3) is composed of 3 clinical parameters with 1 point allotted to each of these parameters: systolic blood pressure ≤100 mm Hg, respiratory rate ≥22 breaths per minute, and altered mental status. For patients with qSOFA scores of 0, 1, 2, and 3 at the time of hospital admission, the mortality rates were 9.7%, 21.1%, 41.7%, and 60%, respectively (P < .0001). The final multivariable logistic regression model included 4 variables that predicted increased odds of death in patients with COVID-19 infection: Charlson score, presence of hypertension, qSOFA, and thrombocytopenia at the time of hospital admission ( Table 2 ). In our study, the CFR among patients aged ≤65 years was 19.2%, which is similar to previous US studies, in which mortality ranged from 8.3 % to 22.7%. 4 The qSOFA score was introduced by the Sepsis-3 task force as a tool to assist in the early identification of patients at risk of sepsis. Patients with a qSOFA score of 2 or higher had a mortality rate of 24% compared to 3% among patients with a qSOFA score of <2. 5 In our study, a qSOFA score of 2 was associated with a mortality rate of 41.7%. Thrombocytopenia in critically ill patients usually suggests serious organ malfunction or physiologic decompensation, often evolving toward disseminated intravascular coagulation. In a meta-analysis, a lower platelet count was encountered in nonsurviving COVID-19 patients. 6 In our study, 37.3% of nonsurvivors had thrombocytopenia on presentation compared to 13.6% of survivors. Similar to clinical studies, we found that a higher Charlson score was an independent predictor of mortality. [7] [8] [9] In terms of individual comorbidities, hypertension, diabetes with chronic complications, hemiplegia, renal disease, malignancy, and liver disease, were associated with mortality. Previous studies from China have reported mortality in patients with comorbidities of 10.5% for cardiovascular disease, 7.3% for diabetes, 6.3% for chronic respiratory disease, 6% for hypertension, and 5.6% for cancer. 7 Previously, we reported that acute or pre-existing renal disease was an independent predictor for severe COVID-19 infection. 9 A study of adults aged 18-34 years identified significantly higher mortality among patients with hypertension. 10 This study has several limitations. It was limited by the sample size. This study was a single institution study of admitted patients which makes generalization difficult. Because of the retrospective design, certain laboratory results were sometimes unavailable on admission, including lactate dehydrogenase, D-dimer, and serum ferritin. Patients with chronic lung disease and conditions associated with immunosuppression were only a small percentage among hospitalized patients. Therefore, the role of some of these variables in predicting mortality from COVID-19 could have been underestimated. In conclusion, calculation of the qSOFA score bedside at the time of admission can predict mortality among COVID-19 patients aged Note. OR, odds ratio; CI, confidence interval; CWIC, Charlson weighted index of comorbidity; qSOFA, quick sepsis-related organ-failure assessment. qSOFA 1 has a score of 1, qSOFA 2 has a score of 2, and qSOFA 3 has a score of 3. a Compared to a qSOFA score of zero. ≤65 years. These findings can be applied globally, including resource-limited countries. Subsequent research involving multiple study sites and with a larger database can further validate the findings of our study. 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This research did not receive any specific grants from funding agencies in the public, commercial, or not-for-profit sectors.Conflicts of interest. All authors have no association that might pose a conflict of interest.