Predicting Poor Outcome of COVID-19 Patients on the Day of Admission with the COVID-19 Score
| Autor: | Mitchell F. Berman, Luke Tseng, Yuqi Miao, Katerina Elisman, Desmond Jordan, Shuang Wang, Erin Hittesdorf, Katherine A Eiseman, Nina Yoh, Gebhard Wagener |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Multivariate statistics
medicine.medical_specialty Univariate analysis Article Subject RC86-88.9 business.industry Medical emergencies. Critical care. Intensive care. First aid Retrospective cohort study 030204 cardiovascular system & hematology Critical Care and Intensive Care Medicine Logistic regression Triage 03 medical and health sciences 0302 clinical medicine Internal medicine Cohort Clinical endpoint Medicine 030212 general & internal medicine Stage (cooking) business Research Article |
| Zdroj: | Critical Care Research and Practice Critical Care Research and Practice, Vol 2021 (2021) |
| ISSN: | 2090-1305 |
| Popis: | Background. COVID-19 may result in multiorgan failure and death. Early detection of patients at risk may allow triage and more intense monitoring. The aim of this study was to develop a simple, objective admission score, based on laboratory tests, that identifies patients who are likely going to deteriorate. Methods. This is a retrospective cohort study of all COVID-19 patients admitted to a tertiary academic medical center in New York City during the COVID-19 crisis in spring 2020. The primary combined endpoint included intubation, stage 3 acute kidney injury (AKI), or death. Laboratory tests available on admission in at least 70% of patients (and age) were included for univariate analysis. Tests that were statistically or clinically significant were then included in a multivariate binary logistic regression model using stepwise exclusion. 70% of all patients were used to train the model, and 30% were used as an internal validation cohort. The aim of this study was to develop and validate a model for COVID-19 severity based on biomarkers. Results. Out of 2545 patients, 833 (32.7%) experienced the primary endpoint. 53 laboratory tests were analyzed, and of these, 47 tests (and age) were significantly different between patients with and without the endpoint. The final multivariate model included age, albumin, creatinine, C-reactive protein, and lactate dehydrogenase. The area under the ROC curve was 0.850 (CI [95%]: 0.813, 0.889), with a sensitivity of 0.800 and specificity of 0.761. The probability of experiencing the primary endpoint can be calculated as p = e − 2.4475 + 0.02492 age − 0.6503 albumin + 0.81926 creat + 0.00388 CRP + 0.00143 LDH / 1 + e − 2.4475 + 0.02492 age − 0.6503 albumin + 0.81926 creat + 0.00388 CRP + 0.00143 LDH . Conclusions. Our study demonstrated that poor outcome in COVID-19 patients can be predicted with good sensitivity and specificity using a few laboratory tests. This is useful for identifying patients at risk during admission. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Plný text