Early prediction of intensive care unit-acquired weakness using quadriceps ultrasound and routine clinical variables: development and temporal validation of a prospective multicentre machine-learning model

Intensive care unit-acquired weakness (ICUAW) is frequent in critically ill adults and is associated with adverse outcomes, but early recognition is difficult because standard diagnosis relies on volitional strength testing. In this prospective multicentre cohort study across 16 tertiary ICUs in southwest China, adults expected to remain in the ICU for ≥ 3 days underwent quadriceps ultrasound and routine clinical assessment within 24 h of admission. ICUAW was defined by the first evaluable Medical Research Council (MRC) score during ICU stay. We developed and compared nine algorithms in a development cohort ( n = 858) and performed temporal external validation in a later cohort ( n = 345). ICUAW occurred in 579/858 (67.5%) patients in the development cohort and 181/345 (52.5%) in the validation cohort. In external validation, a random forest model integrating unpressurised ultrasound and clinical features achieved an area under the receiver operating characteristic curve (AUC) of 0.810 (95% CI 0.765–0.855), with sensitivity 0.983 (0.952–0.997) and specificity 0.726 (0.651–0.792). The corresponding pressurised-ultrasound model showed lower discrimination (AUC 0.730 [0.676–0.783]) and specificity (0.506 [0.427–0.585]). Shapley additive explanations (SHAP) highlighted quadriceps muscle thickness, Sequential Organ Failure Assessment (SOFA) score, albumin, and inflammatory markers as key contributors. In additional incremental-value analyses using the General RF model as the reference, the unpressurised RF model improved risk reclassification and discrimination (cf-NRI 0.490, 95% CI 0.277–0.698; IDI 0.072, 95% CI 0.045–0.099), whereas the pressurised RF model showed a smaller cf-NRI improvement (0.231, 95% CI 0.011–0.463) with less consistent IDI improvement (0.019, 95% CI − 0.002 to 0.040). This early ultrasound-clinical model may identify patients at high risk of ICUAW before strength testing becomes feasible and support earlier targeting of preventive and rehabilitation strategies. Trial registration Registered in the Chinese Clinical Trial Registry (ChiCTR2300075581) on September 8, 2023.

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Journal
Journal of Intensive Care
Published
2026-07-26
DOI
https://doi.org/10.1186/s40560-026-00919-x
Primary Topic
Sepsis Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
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article

Early prediction of intensive care unit-acquired weakness using quadriceps ultrasound and routine clinical variables: development and temporal validation of a prospective multicentre machine-learning model

陈雪华, Xicheng Zhang, Wanhong Yin, Z Zhang et al.
Journal of Intensive Care
Sepsis Diagnosis and Treatment
article

Early prediction of intensive care unit-acquired weakness using quadriceps ultrasound and routine clinical variables: development and temporal validation of a prospective multicentre machine-learning model

陈雪华, Xicheng Zhang, Wanhong Yin, Z Zhang, Tongjuan Zou, Bo Wang, Li Zhang, Yan Kang, X Y Zeng, Hengyu Cai, Jun Li, Critical Care Ultrasound Study Group (CCUSG), Xianying Lei, Qionglan Dong, Xiaodong Jin
article en

Abstract

Intensive care unit-acquired weakness (ICUAW) is frequent in critically ill adults and is associated with adverse outcomes, but early recognition is difficult because standard diagnosis relies on volitional strength testing. In this prospective multicentre cohort study across 16 tertiary ICUs in southwest China, adults expected to remain in the ICU for ≥ 3 days underwent quadriceps ultrasound and routine clinical assessment within 24 h of admission. ICUAW was defined by the first evaluable Medical Research Council (MRC) score during ICU stay. We developed and compared nine algorithms in a development cohort ( n = 858) and performed temporal external validation in a later cohort ( n = 345). ICUAW occurred in 579/858 (67.5%) patients in the development cohort and 181/345 (52.5%) in the validation cohort. In external validation, a random forest model integrating unpressurised ultrasound and clinical features achieved an area under the receiver operating characteristic curve (AUC) of 0.810 (95% CI 0.765–0.855), with sensitivity 0.983 (0.952–0.997) and specificity 0.726 (0.651–0.792). The corresponding pressurised-ultrasound model showed lower discrimination (AUC 0.730 [0.676–0.783]) and specificity (0.506 [0.427–0.585]). Shapley additive explanations (SHAP) highlighted quadriceps muscle thickness, Sequential Organ Failure Assessment (SOFA) score, albumin, and inflammatory markers as key contributors. In additional incremental-value analyses using the General RF model as the reference, the unpressurised RF model improved risk reclassification and discrimination (cf-NRI 0.490, 95% CI 0.277–0.698; IDI 0.072, 95% CI 0.045–0.099), whereas the pressurised RF model showed a smaller cf-NRI improvement (0.231, 95% CI 0.011–0.463) with less consistent IDI improvement (0.019, 95% CI − 0.002 to 0.040). This early ultrasound-clinical model may identify patients at high risk of ICUAW before strength testing becomes feasible and support earlier targeting of preventive and rehabilitation strategies. Trial registration Registered in the Chinese Clinical Trial Registry (ChiCTR2300075581) on September 8, 2023.

Journal of Intensive Care
Sichuan University (CN), Affiliated Hospital of Southwest Medical University (CN), West China Hospital of Sichuan University (CN), Mianyang Third People's Hospital (CN), Affiliated Hospital of North Sichuan Medical College (CN), Wuhou District People's Hospital, Chengdu (CN), First People's Hospital of Nanning (CN), Zigong First People's Hospital (CN)
Peace, Justice and strong institutions, Reduced inequalities
Openalex Percentile: Top 9%
Sepsis Diagnosis and Treatment
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