Personalized Prediction of Hospital Mortality in COVID-19-Positive Patients.
Mayo Clin Proc Innov Qual Outcomes
; 5(4): 795-801, 2021 Aug.
Article
in English
| MEDLINE | ID: covidwho-1225334
ABSTRACT
OBJECTIVE:
To develop predictive models for in-hospital mortality and length of stay (LOS) for coronavirus disease 2019 (COVID-19)-positive patients. PATIENTS ANDMETHODS:
We performed a multicenter retrospective cohort study of hospitalized COVID-19-positive patients. A total of 764 patients admitted to 14 different hospitals within the Cleveland Clinic from March 9, 2020, to May 20, 2020, who had reverse transcriptase-polymerase chain reaction-proven coronavirus infection were included. We used LightGBM, a machine learning algorithm, to predict in-hospital mortality at different time points (after 7, 14, and 30 days of hospitalization) and in-hospital LOS. Our final cohort was composed of 764 patients admitted to 14 different hospitals within our system.RESULTS:
The median LOS was 5 (range, 1-44) days for patients admitted to the regular nursing floor and 10 (range, 1-38) days for patients admitted to the intensive care unit. Patients who died during hospitalization were older, initially admitted to the intensive care unit, and more likely to be white and have worse organ dysfunction compared with patients who survived their hospitalization. Using the 10 most important variables only, the final model's area under the receiver operating characteristics curve was 0.86 for 7-day, 0.88 for 14-day, and 0.85 for 30-day mortality in the validation cohort.CONCLUSION:
We developed a decision tool that can provide explainable and patient-specific prediction of in-hospital mortality and LOS for COVID-19-positive patients. The model can aid health care systems in bed allocation and distribution of vital resources.
ANC, absolute neutrophil count; AST, aspartate aminotransferase; BMI, body mass index; CK, creatinine kinase; COVID-19, coronavirus disease 2019; CRP, C-reactive protein; CXR, chest radiograph; D1, day 1; ICU, intensive care unit; INR, international normalized ratio; LDH, lactate dehydrogenase; LOS, length of stay; LightGBM, Light Gradient Boosting Machine; NC, nasal cannula; Nan, missing value; PTT, partial thromboplastin time; Q, quartile; ROC AUC, area under the receiver operating characteristics curve; SHAP, SHapley Additive exPlanations; SUN, serum urea nitrogen
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Type of study:
Cohort study
/
Observational study
/
Prognostic study
Language:
English
Journal:
Mayo Clin Proc Innov Qual Outcomes
Year:
2021
Document Type:
Article
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