Juan M Mejía-Vilet1, Bertha M Córdova-Sánchez2, Dheni A Fernández-Camargo3, R Angélica Méndez-Pérez4, Luis E Morales-Buenrostro5, Thierry Hernández-Gilsoul6. 1. Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán. juan.mejiav@incmnsz.mx. 2. Instituto Nacional de Cancerología. berthax@hotmail.com. 3. Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán. dheni.fernandez94@gmail.com. 4. Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán. rossaangelica_95@hotmail.com. 5. Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán. luis_buenrostro@yahoo.com. 6. Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán. thierry.hernandezg@incmnsz.mx.
Abstract
OBJECTIVE: To develop a score to predict the need for ICU admission in COVID-19. METHODS: We assessed patients admitted to a COVID-19 center in Mexico. Patients were segregated into a group that required ICU admission, and a group that never required ICU admission. By logistic regression, we derived predictive models including clinical, laboratory, and imaging findings. The ABC-GOALS was constructed and compared to other scores. RESULTS: We included 329 and 240 patients in the development and validation cohorts, respectively. One-hundred-fifteen patients from each cohort required ICU admission. The clinical (ABC-GOALSc), clinical+laboratory (ABC-GOALScl), clinical+laboratory+image (ABC-GOALSclx) models area under the curve were 0.79 (95%CI=0.74-0.83) and 0.77 (95%CI=0.71-0.83), 0.86 (95%CI=0.82-0.90) and 0.87 (95%CI=0.83-0.92), 0.88 (95%CI=0.84-0.92) and 0.86 (95%CI=0.81-0.90), in the development and validation cohorts, respectively. The ABC-GOALScl and ABC-GOALSclx outperformed other COVID-19 and pneumonia predictive scores. CONCLUSION: ABC-GOALS is a tool to timely predict the need for admission to ICU in COVID-19.
OBJECTIVE: To develop a score to predict the need for ICU admission in COVID-19. METHODS: We assessed patients admitted to a COVID-19 center in Mexico. Patients were segregated into a group that required ICU admission, and a group that never required ICU admission. By logistic regression, we derived predictive models including clinical, laboratory, and imaging findings. The ABC-GOALS was constructed and compared to other scores. RESULTS: We included 329 and 240 patients in the development and validation cohorts, respectively. One-hundred-fifteen patients from each cohort required ICU admission. The clinical (ABC-GOALSc), clinical+laboratory (ABC-GOALScl), clinical+laboratory+image (ABC-GOALSclx) models area under the curve were 0.79 (95%CI=0.74-0.83) and 0.77 (95%CI=0.71-0.83), 0.86 (95%CI=0.82-0.90) and 0.87 (95%CI=0.83-0.92), 0.88 (95%CI=0.84-0.92) and 0.86 (95%CI=0.81-0.90), in the development and validation cohorts, respectively. The ABC-GOALScl and ABC-GOALSclx outperformed other COVID-19 and pneumonia predictive scores. CONCLUSION:ABC-GOALS is a tool to timely predict the need for admission to ICU in COVID-19.
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Authors: José J Valdés-Aguayo; Idalia Garza-Veloz; José R Vargas-Rodríguez; María C Martinez-Vazquez; Lorena Avila-Carrasco; Sofia Bernal-Silva; Carolina González-Fuentes; Andreu Comas-García; Diana E Alvarado-Hernández; Alba S H Centeno-Ramirez; Iram P Rodriguez-Sánchez; Ivan Delgado-Enciso; Margarita L Martinez-Fierro Journal: Front Cell Infect Microbiol Date: 2021-12-16 Impact factor: 5.293
Authors: Karrar Hameed Abdulkareem; Mohammed Nasser Al-Mhiqani; Ahmed M Dinar; Mazin Abed Mohammed; Mustafa Jawad Al-Imari; Alaa S Al-Waisy; Abed Saif Alghawli; Mohammed A A Al-Qaness Journal: Bioengineering (Basel) Date: 2022-09-08