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10.21149/11684 http://scihub22266oqcxt.onion/10.21149/11684 33021362!ä!33021362 Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=33021362&cmd=llinks): Failed to open stream: HTTP request failed! 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A Risk Score to Predict Admission to the Intensive Care Unit in Patients with COVID-19: the ABC-GOALS score |pdf=|usr=}}{{33021362}} gab.com Text A Risk Score to Predict Admission to the Intensive Care Unit in Patients with COVID-19: the ABC-GOALS score JO: Salud Publica Mex http://www.kidney.de/pget.php?&tw=1&pmid=33021362 #FOAvip 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. Twit Text FOAVip A Risk Score to Predict Admission to the Intensive Care Unit in Patients with COVID-19: the ABC-GOALS score ????Salud Publica Mex http://www.kidney.de/pget.php?&tw=1&pmid=33021362 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33021362 #FOAvip English Wikipedia <ref>{{Cite pmid|33021362}}</ref> A Risk Score to Predict Admission to the Intensive Care Unit in Patients with COVID-19: the ABC-GOALS score #MMPMID33021362 Mejia-Vilet JM; Cordova-Sanchez BM; Fernandez-Camargo DA; Mendez-Perez RA; Morales-Buenrostro LE; Hernandez-Gilsoul T Salud Publica Mex 2020[Dec]; 63 (1, ene-feb): 1-11 PMID33021362show ga 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. |Adult[MESH] |Area Under Curve[MESH] |COVID-19/*epidemiology[MESH] |Confidence Intervals[MESH] |Female[MESH] |Hospitalization/*statistics & numerical data[MESH] |Humans[MESH] |Intensive Care Units/*statistics & numerical data[MESH] |Logistic Models[MESH] |Male[MESH] |Mexico/epidemiology[MESH] |Middle Aged[MESH] |Prospective Studies[MESH]A Risk Score to Predict Admission to the Intensive Care Unit in Patien(epmc).pdf DeepDyve Pubget Overpricing