Most of the existing prediction models for COVID-19 lack validation, are inadequately reported or are at high risk of bias, a reason which has led to discourage their use. Few existing models have the potential to be extensively used by healthcare providers in low-resource settings since many require laboratory and imaging predictors. Therefore, we sought to develop and validate a multivariable prediction model of death in Mexican patients with COVID-19, by using demographic and patient history predictors. We conducted a national retrospective cohort study in two different sets of patients from the Mexican COVID-19 Epidemiologic Surveillance Study. Patients with a positive reverse transcription-polymerase chain reaction for SARS-CoV-2 and complete unduplicated data were eligible. In total, 83 779 patients were included to develop the scoring system through a multivariable Cox regression model; 100 000, to validate the model. Eight predictors (age, sex, diabetes, chronic obstructive pulmonary disease, immunosuppression, hypertension, obesity and chronic kidney disease) were included in the scoring system called PH-Covid19 (range of values: −2 to 25 points). The predictive model has a discrimination of death of 0.8 (95% confidence interval (CI) 0.796–0.804). The PH-Covid19 scoring system was developed and validated in Mexican patients to aid clinicians to stratify patients with COVID-19 at risk of fatal outcomes, allowing for better and efficient use of resources.
【저자키워드】 COVID-19, SARS-CoV-2, Prediction model, Mexico, scoring system, 【초록키워드】 obesity, Immunosuppression, Sex, risk, Chronic kidney disease, predictors, diabetes, hypertension, Laboratory, outcomes, Patient, death, age, predictor, pulmonary disease, high risk, Predictive, retrospective cohort study, Healthcare provider, clinician, 95% confidence interval, National, multivariable Cox regression, positive, MOST, resources, Complete, multivariable, lack, develop, reported, conducted, chronic obstructive, eligible, patients with COVID-19, 【제목키워드】 death, development, multivariable, the patient, patients with COVID-19,