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However, we do not know the cut\u2010off point for the diagnosis of\n ICU<\/jats:styled-content>\n \u2010\n AW<\/jats:styled-content>\n .\n <\/jats:p>\n <\/jats:sec>\n \n Aim<\/jats:title>\n \n To ascertain the best cut\u2010off point for\n CPAx<\/jats:styled-content>\n to diagnose\n ICU<\/jats:styled-content>\n \u2010\n AW<\/jats:styled-content>\n in adult patients with mechanical ventilation.\n <\/jats:p>\n <\/jats:sec>\n \n Study Design<\/jats:title>\n \n A multicentre, prospective cross\u2010sectional study. Participants were recruited from five\n ICUs<\/jats:styled-content>\n in China that ranged from 20 June 2021 to 31 July 2023. The Medical Research Council Sum Scale (\n MRC<\/jats:styled-content>\n \u2010ss) <48 was taken as the standard to calculate the area under the curve (\n AUC<\/jats:styled-content>\n ) of\n CPAx<\/jats:styled-content>\n . The cut\u2010off point was determined by the maximum value of Youden Index (\n \n YI\n max<\/jats:sub>\n <\/jats:styled-content>\n ). The kappa (\u03ba) test was used to test the consistency of the\n MRC<\/jats:styled-content>\n \u2010ss and\n CPAx<\/jats:styled-content>\n .\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n The\n AUC<\/jats:styled-content>\n at baseline, weaning and discharge time point was 0.87 (95%\n CI<\/jats:styled-content>\n 0.81\u20130.93), 0.96 (95%\n CI<\/jats:styled-content>\n 0.92\u20130.99) and 0.91 (95%\n CI<\/jats:styled-content>\n 0.86\u20130.96), respectively. Correspondingly, The\n YImax<\/jats:styled-content>\n was 0.62, 0.91 and 0.65. The best cut\u2010off point of\n CPAx<\/jats:styled-content>\n score to diagnose\n ICU<\/jats:styled-content>\n \u2010\n AW<\/jats:styled-content>\n at baseline, weaning and discharge time point was 30.5 (sensitivity\u2009=\u200972%, specificity\u2009=\u200989%), 31.5 (sensitivity\u2009=\u200995%, specificity\u2009=\u200990%) and 31.5 (sensitivity\u2009=\u200994%, specificity\u2009=\u200971%), respectively. Due to the\n CPAx<\/jats:styled-content>\n being an ordinal scale, it was determined preliminarily that the cut\u2010off point for the\n CPAx<\/jats:styled-content>\n to diagnose\n ICU<\/jats:styled-content>\n \u2010\n AW<\/jats:styled-content>\n was 31 points. We took\n CPAx<\/jats:styled-content>\n \u226431 and\n MRC<\/jats:styled-content>\n \u2010ss <48 as criteria to diagnose\n ICU<\/jats:styled-content>\n \u2010\n AW<\/jats:styled-content>\n and test the consistency of\n MRC<\/jats:styled-content>\n \u2010ss and\n CPAx<\/jats:styled-content>\n . The results showed that there was no significant difference in the incidence of\n ICU<\/jats:styled-content>\n \u2010\n AW<\/jats:styled-content>\n at different time points.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n \n The optimal cut\u2010off point for the\n CPAx<\/jats:styled-content>\n to diagnose\n ICU<\/jats:styled-content>\n \u2010\n AW<\/jats:styled-content>\n is a score of 31 and it has good sensitivity and specificity.\n <\/jats:p>\n <\/jats:sec>\n \n Relevance to Clinical Practice<\/jats:title>\n The CPAx \u226431 score to diagnose ICU\u2010acquired weakness (ICU\u2010AW) has good sensitivity and specificity, and it can help to predict the risk of ICU\u2010AW and guide medical personnel to make interventions.<\/jats:p>\n 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