Author: Mancilla-Galindo, J.; Vera-Zertuche, J. M.; Navarro-Cruz, A. R.; Segura-Badilla, O.; Reyes-Velázquez, G.; Tepepa-López, F. J.; Aguilar-Alonso, P.; Vidal-Mayo, J. de J.; Kammar-GarcÃa, A.
Title: Development and validation of the patient history COVID-19 (PH-Covid19) scoring system: a multivariable prediction model of death in Mexican patients with COVID-19 Cord-id: s21u7j1j Document date: 2020_11_26
ID: s21u7j1j
Snippet: 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
Document: 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.
Search related documents:
Co phrase search for related documents- adjusted risk and admission pneumonia: 1, 2, 3, 4, 5, 6, 7
- adjusted risk and admission pneumonia invasive mechanical ventilation: 1
- adjusted risk and admission pneumonia invasive mechanical ventilation hospitalisation: 1
- adjusted risk and logistic regression: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
- adjusted risk and logistic regression analysis: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
- adjusted risk and logistic regression analysis result: 1
- adjusted risk and low income: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12
- adjusted risk and low mortality: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24
- adjusted risk and low proportion: 1, 2
- adjusted risk and low resource: 1, 2, 3, 4, 5, 6
- admission date and logistic regression: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
- admission date and logistic regression analysis: 1, 2, 3
- admission date and low income: 1
- admission pneumonia and logistic regression: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
- admission pneumonia and logistic regression analysis: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17
- admission pneumonia and low income: 1
- admission pneumonia and low income country: 1
- admission pneumonia and low mortality: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
- admission pneumonia and low resource: 1, 2
Co phrase search for related documents, hyperlinks ordered by date