A Novel Severity Score to Predict Inpatient Mortality in COVID-19 patients

Abstract

IntroductionCOVID-19 is commonly mild and self-limiting, but in a considerable portion of patients the disease is severe and fatal. Determining which patients are at high risk of severe illness or mortality is essential for appropriate clinical decision making. We propose a novel severity score specifically for COVID-19 to help predict disease severity and mortality.Methods4,711 patients with confirmed SARS-CoV-2 infection were included. We derived a risk model using the first half of the cohort (n=2,355 patients) by logistic regression and bootstrapping methods. The discriminative power of the risk model was assessed by calculating the area under the receiver operating characteristic curves (AUC). The severity score was validated in a second half of 2,356 patients.ResultsMortality incidence was 26.4% in the derivation cohort and 22.4% in the validation cohort. A COVID-19 severity score ranging from 0 to 10, consisting of age, oxygen saturation, mean arterial pressure, blood urea nitrogen, C-Reactive protein, and the international normalized ratio was developed. A ROC curve analysis was performed in the derivation cohort achieved an AUC of 0.824 (95% CI 0.814-0.851) and an AUC of 0.798 (95% CI 0.789-0.818) in the validation cohort. Furthermore, based on the risk categorization the probability of mortality was 11.8%, 39% and 78% for patient with low (0-3), moderate (4-6) and high (7-10) COVID-19 severity score.ConclusionThis developed and validated novel COVID-19 severity score will aid physicians in predicting mortality during surge periods.

Ondansetron use is associated with lower COVID-19 mortality in a Real-World Data network-based analysis

“…Looking at interactions between other covariates, we found that the CRP and BUN dyad, laboratory biomarkers that are found in prognostic models for COVID-19 mortality, are also associated with mortality in our cohort [36,37]. Similarly, the previously observed mortality link of interacting factors ferritin and age [38] as well as higher D-dimer levels in males were also confirmed by our analyses [39].…”

Predicting mortality in SARS-COV-2 (COVID-19) positive patients in the inpatient setting using a Novel Deep Neural Network

“…Hematological labs that were associated with mortality (previously presented in the results) were also seen in other studies (27). Biochemical laboratory abnormalities like creatinine, blood urea nitrogen (28), INR and PT (29) were also associated with mortality. Patients managed with invasive ventilation (30) and non-invasive ventilation (31) which actually signifies that the patients that were not able to maintain normal respiratory physiology had worse outcomes.…”

Age-adjusted quick Sequential Organ Failure Assessment score for predicting mortality and disease severity in children with infection: a systematic review and meta-analysis

“…As described in previous studies [39][40][41] , we assessed the discriminative power of the prediction score (ageadjusted qSOFA) for identifying at-risk pediatric patients by calculating AUC. An AUC above 0.7 was considered to be acceptable and useful 34,40 .…”

“…As described in previous studies [39][40][41] , we assessed the discriminative power of the prediction score (ageadjusted qSOFA) for identifying at-risk pediatric patients by calculating AUC. An AUC above 0.7 was considered to be acceptable and useful 34,40 . In our results, aged-adjusted qSOFA achieved an AUC of 0.733, indicating a useful discrimination for pediatric patients at risk who need close monitoring and intensive treatment.…”