用于检测重症监护病房获得性肌无力的渗透评分与机器学习：一项前瞻性观察队列研究。
Perme Score and Machine Learning for Detecting ICU-acquired Weakness: A Prospective Observational Cohort Study.
作者信息
Delazari Lilian Elisabete Bernardes, Ratti Lígia Dos Santos Roceto, da Silva Adria Cristina, Sibinelli Melissa, Heidemann Aline Maria, Montedioca Higor Luiz Marconi, Dos Santos Emanuella Feitoza, Falcão Antonio Luís Eiras
机构信息
Department of Physiotherapy, Clinical Hospital of UNICAMP, University of Campinas (UNICAMP), Campinas, São Paulo, Brazil.
Department of Physiotherapy, Beneficência Portuguesa Hospital, Campinas, São Paulo, Brazil.
出版信息
Indian J Crit Care Med. 2025 Jul;29(7):562-568. doi: 10.5005/jp-journals-10071-25011. Epub 2025 Jul 7.
BACKGROUND AND AIMS
Intensive care unit-acquired weakness (ICUAW) is a common complication in critically ill patients on prolonged mechanical ventilation (MV), impairing recovery and prolonging intensive care unit (ICU) stays. Standard diagnostic tools like the handgrip strength test (HGST) require patient cooperation and may be limited in critical settings. This study evaluated whether the Perme ICU Mobility Score, a multidimensional functional assessment, is associated with ICUAW and can serve as a screening tool using HGST as the diagnostic reference.
PATIENTS AND METHODS
We conducted a prospective observational study in a Brazilian tertiary ICU from May 2021 to October 2023. We assessed adults (≥18 years) undergoing MV for ≥7 days who were clinically stable (pressure support 7 cm HO, PEEP 5 cm HO, RASS -1 to +1). ICUAW was defined using sex-specific HGST cutoffs (<11 kg men, <7 kg women). Logistic regression, least absolute shrinkage and selection operator (LASSO), and Random Forest models assessed the association between ICUAW and Perme Score. ROC curves and the Youden index determined the optimal cutoff.
RESULTS
Among 97 patients, ICUAW was identified in 78.4%. Lower Perme Scores were significantly associated with ICUAW ( < 0.001). A cutoff ≤9 showed 76.3% sensitivity, 71.4% specificity, and OR = 8.06 (95% CI: 2.72-23.8). In multivariate analysis, the Perme Score (OR = 0.86; = 0.0004) and SAPS 3 remained independent predictors. Machine learning models confirmed Perme Score as the most significant variable.
CONCLUSIONS
The Perme Score is a feasible, complementary screening tool for ICUAW. A cutoff ≤9 supports early functional risk stratification but should be interpreted alongside clinical context due to limited specificity and negative predictive value (NPV).
HOW TO CITE THIS ARTICLE
Delazari LEB, Ratti LSR, da Silva AC, Sibinelli M, Heidemann AM, Montedioca HLM, . Perme Score and Machine Learning for Detecting ICU-acquired Weakness: A Prospective Observational Cohort Study. Indian J Crit Care Med 2025;29(7):562-568.
背景与目的
重症监护病房获得性肌无力（ICUAW）是长时间机械通气（MV）的重症患者常见的并发症，会影响康复并延长重症监护病房（ICU）住院时间。像握力测试（HGST）这样的标准诊断工具需要患者配合，在危急情况下可能会受到限制。本研究评估了多维功能评估指标Perme ICU活动能力评分是否与ICUAW相关，以及能否以HGST作为诊断参考，将其作为一种筛查工具。
患者与方法
我们于2021年5月至2023年10月在巴西一家三级ICU进行了一项前瞻性观察性研究。我们评估了年龄≥18岁、接受MV≥7天且临床稳定（压力支持7 cm H₂O，呼气末正压5 cm H₂O， Richmond躁动 - 镇静评分-1至+1）的成年人。ICUAW根据性别特异性HGST临界值定义（男性<11 kg，女性<7 kg）。逻辑回归、最小绝对收缩和选择算子（LASSO）以及随机森林模型评估了ICUAW与Perme评分之间的关联。ROC曲线和尤登指数确定了最佳临界值。
结果
97例患者中，78.4%被诊断为ICUAW。较低的Perme评分与ICUAW显著相关（<0.001）。临界值≤9时，敏感性为76.3%，特异性为71.4%，比值比（OR）=8.06（95%置信区间：2.72 - 23.8）。在多变量分析中，Perme评分（OR = 0.86；P = 0.0004）和简化急性生理学评分Ⅲ（SAPS 3）仍然是独立的预测因素。机器学习模型证实Perme评分是最显著的变量。
结论
Perme评分是一种用于ICUAW的可行的补充筛查工具。临界值≤9支持早期功能风险分层，但由于特异性和阴性预测值有限，应结合临床情况进行解读。
如何引用本文
Delazari LEB, Ratti LSR, da Silva AC, Sibinelli M, Heidemann AM, Montedioca HLM, 等。Perme评分与机器学习用于检测ICU获得性肌无力：一项前瞻性观察队列研究。《印度重症医学杂志》2025；29(7):562 - 568。
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