Abstract
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+0.02492age − 0.6503albumin+0.81926creat+0.00388CRP+0.00143LDH)/1+e(−2.4475+ 0.02492age − 0.6503albumin+0.81926creat+0.00388CRP+0.00143LDH). 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.
Highlights
From March to May 2020, New York City experienced a severe crisis of COVID-19 cases that resulted in a surge of patients who required hospital-level care
E primary combined endpoint included either intubation, stage 3 acute kidney injury (AKI) defined by Kidney Disease Improving Global Outcomes (KDIGO) criteria [13], or death during hospitalization. We chose these endpoints because we considered the presence of any of these endpoints representative of a serious deterioration of COVID-19 especially during the surge in New York City at that time
A total of 2545 patients were admitted to the hospital with COVID-19. 537 patients (21.1%) died, 309 patients (12.1%)
Summary
From March to May 2020, New York City experienced a severe crisis of COVID-19 cases that resulted in a surge of patients who required hospital-level care. Many patients recovered quickly, some progressed to develop severe COVID-19 resulting in significant morbidity and potentially death. E 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. Laboratory tests available on admission in at least 70% of patients (and age) were included for univariate analysis. E aim of this study was to develop and validate a model for COVID19 severity based on biomarkers. Our study demonstrated that poor outcome in COVID19 patients can be predicted with good sensitivity and specificity using a few laboratory tests. Our study demonstrated that poor outcome in COVID19 patients can be predicted with good sensitivity and specificity using a few laboratory tests. is is useful for identifying patients at risk during admission
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