A risk score to predict admission to the intensive care unit in patients with Covid-19: the ABC-GOALS score
Abstract: Objective: To develop a score to predict the need for intensive care unit (ICU) admission in Covid-19. Materials and 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-GOALScland ABC-GOALSclxoutperformed 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.
| Main Authors: | , , , , , |
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| Format: | Digital revista |
| Language: | English |
| Published: |
Instituto Nacional de Salud Pública
2021
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| Online Access: | http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S0036-36342021000100001 |
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