Development and validation of a prediction model for estimating one-month mortality of adult COVID-19 patients presenting at emergency department with suspected pneumonia: a multicenter analysis.
Eric H ChouChih-Hung WangFan-Ya ChouChu-Lin TsaiJon WolfshohlJohn GarrettToral BhaktaAndrew SheddDahlia HassaniRobert RischJames d'EtienneGerald O OgolaTsung-Chien LuMatthew Huei-Ming MaPublished in: Internal and emergency medicine (2021)
There are only a few models developed for risk-stratifying COVID-19 patients with suspected pneumonia in the emergency department (ED). We aimed to develop and validate a model, the COVID-19 ED pneumonia mortality index (CoV-ED-PMI), for predicting mortality in this population. We retrospectively included adult COVID-19 patients who visited EDs of five study hospitals in Texas and who were diagnosed with suspected pneumonia between March and November 2020. The primary outcome was 1-month mortality after the index ED visit. In the derivation cohort, multivariable logistic regression was used to develop the CoV-ED-PMI model. In the chronologically split validation cohort, the discriminative performance of the CoV-ED-PMI was assessed by the area under the receiver operating characteristic curve (AUC) and compared with other existing models. A total of 1678 adult ED records were included for analysis. Of them, 180 patients sustained 1-month mortality. There were 1174 and 504 patients in the derivation and validation cohorts, respectively. Age, body mass index, chronic kidney disease, congestive heart failure, hepatitis, history of transplant, neutrophil-to-lymphocyte ratio, lactate dehydrogenase, and national early warning score were included in the CoV-ED-PMI. The model was validated with good discriminative performance (AUC: 0.83, 95% confidence interval [CI]: 0.79-0.87), which was significantly better than the CURB-65 (AUC: 0.74, 95% CI: 0.69-0.79, p-value: < 0.001). The CoV-ED-PMI had a good predictive performance for 1-month mortality in COVID-19 patients with suspected pneumonia presenting at ED. This free tool is accessible online, and could be useful for clinical decision-making in the ED.
Keyphrases
- emergency department
- sars cov
- respiratory syndrome coronavirus
- end stage renal disease
- coronavirus disease
- chronic kidney disease
- heart failure
- cardiovascular events
- body mass index
- newly diagnosed
- ejection fraction
- peritoneal dialysis
- prognostic factors
- type diabetes
- pulmonary embolism
- social media
- patient reported outcomes
- coronary artery disease
- atrial fibrillation
- left ventricular
- case report
- electronic health record
- young adults
- respiratory failure
- acute respiratory distress syndrome
- extracorporeal membrane oxygenation
- data analysis