ICU重症机械通气患者呼吸肌麻痹发生风险预测模型的构建-现代医学

ICU重症机械通气患者呼吸肌麻痹发生风险预测模型的构建

单位：上海中医药大学附属曙光医院急诊重症监护室, 上海 201203

分类号：R563.8;R473.5

出版年·卷·期（页码）：2026·54·第七期（1125-1132）

摘要：

目的：分析重症监护室(ICU)重症机械通气患者发生呼吸肌麻痹(RMP)的危险因素并构建风险预测模型，为临床早期识别高危人群和实施精准护理干预提供参考。方法：采用回顾性研究方法，选取2022年1月至2024年12月某三级甲等医院ICU接受机械通气的326例重症患者为研究对象，依据是否发生RMP分为病例组(68例)和对照组(258例)。通过单因素分析和多因素Logistic回归分析筛选独立危险因素，构建预测模型并评价其效能。结果：RMP发生率为20.86%。多因素Logistic回归分析显示，机械通气总时长≥72 h(OR=3.08,95%CI:1.652~5.743)、APACHE Ⅱ评分≥20分(OR=2.67,95%CI:1.532~4.651)、有低钾血症(OR=2.87,95%CI:1.562~5.287)、有合并肺部感染(OR=3.43,95%CI:1.825~6.473)、CK-MB＞25 U·L^-1(OR=2.36,95%CI:1.352~4.147)为独立危险因素。预测模型为：Logit(P)=-5.236+1.125×机械通气时间≥72 h+0.982×APACHE Ⅱ评分≥20分+1.056×低钾血症+1.235×合并肺部感染+0.862×CK-MB＞25 U·L^-1。模型ROC曲线下面积为0.886，C-index为0.892，校准度良好，临床实用性强。结论：构建的预测模型具有良好的预测效能，可为医护人员筛查ICU机械通气患者RMP高危人群提供量化工具。

Objective: To analyze the risk factors of respiratory muscle paralysis(RMP) in intensive care unit(ICU) patients with mechanical ventilation and construct a risk prediction model, so as to provide reference for early clinical identification of high-risk groups and implementation of precise nursing intervention. Methods: A retrospective study was performed on 326 critically ill patients receiving mechanical ventilation in the ICU of a tertiary hospital from January 2022 to December 2024. Subjects were divided into the RMP group(68 cases) and control group(258 cases) according to the occurrence of RMP. Independent risk factors were screened via univariate and multivariate Logistic regression analyses to develop the prediction model, followed by efficiency evaluation. Results: The incidence of RMP was 20.86%. Multivariate Logistic regression identified five independent risk factors: mechanical ventilation duration ≥72 h(OR=3.08,95%CI:1.652-5.743), APACHE Ⅱ score ≥20 points(OR=2.67,95%CI:1.532-4.651), hypokalemia(OR=2.87,95%CI:1.562-5.287), complicated pulmonary infection(OR=3.43,95%CI:1.825-6.473), and CK-MB＞25 U·L^-1(OR=2.36,95%CI:1.352-4.147). The prediction model was Logit(P)=-5.236+1.125×mechanical ventilation duration ≥72 h+0.982×APACHE Ⅱ score ≥20+1.056×hypokalemia+1.235×pulmonary infection+0.862×CK-MB>25 U·L^-1. The area under the ROC curve of the model was 0.886 with a C-index of 0.892, showing favorable calibration and prominent clinical applicability. Conclusion: The established prediction model presents satisfactory predictive performance, which can serve as a quantitative tool for clinical staff to screen patients at high risk of RMP among mechanically ventilated ICU patients.

参考文献：

[1] MIREA L,COBILINSCHI C,UNGUREANU R,et al.A trend towards diaphragmatic muscle waste after invasive mechanical ventilation in multiple trauma patients—what to expect [J].J Clin Med,2023,12(9):3338.
[2] DRES M,GOLIGHER E C,DUBÉ B P,et al.Diaphragm function and weaning from mechanical ventilation:an ultrasound and phrenic nerve stimulation clinical study[J].Ann Intensive Care,2018,8(1):53.
[3] MEDRINAL C,COMBRET Y,HILFIKER R,et al.ICU outcomes can be predicted by noninvasive muscle evaluation:a meta-analysis[J].Eur Respir J,2020,56(4),1902482.
[4] SCHMIDT P,OKOBI T,ATOGWE I D,et al.COVID-19-induced myopathy and diaphragmatic weakness:a case report[J].Cureus,2023,15(5):e38515.
[5] GONZALEZ A,ABRIGO J,ACHIARDI O,et al.Intensive care unit-acquired weakness:a review from molecular mechanisms to its impact in COVID-2019[J].Eur J Transl Myol,2022,32(3):10511.
[6] WANG T H,WU C P,WANG L Y.Impact of peripheral muscle strength on prognosis after extubation and functional outcomes in critically ill patients:a feasibility study[J].Sci Rep,2021,11:16082.
[7] SHI X,SHI Y,FAN L,et al.Prognostic value of oxygen saturation index trajectory phenotypes on ICU mortality in mechanically ventilated patients:a multi-database retrospective cohort study[J].J Intensive Care,2023,11(1):59.
[8] XU H,MA Y,ZHUANG Y,et al.Machine learning-based risk prediction model construction of difficult weaning in ICU patients with mechanical ventilation[J].Sci Rep,2024,14:20875.
[9] KLEINPELL R,GRABENKORT W R,BOYLE W A,et al.The society of critical care medicine at 50 years:interprofessional practice in critical care:looking back and forging ahead[J].Crit Care Med,2021,49(12):2017-2032.
[10] EMAMI ZEYDI A,GHAZANFARI M J,SHAIKHI SANANDAJ F,et al.Coronavirus disease 2019(COVID-19):a literature review from a nursing perspective[J].BioMedicine,2021,11(3):5-14.
[11] MEITNER C,FEUERSTEIN R A,STEELE A M.Nursing strategies for the mechanically ventilated patient[J].Front Vet Sci,2023,10:1145758.
[12] ADNET F,DHISSI G,BORRON S W,et al.Complication profiles of adult asthmatics requiring paralysis during mechanical ventilation[J].Intensive Care Med,2001,27(11):1729-1736.
[13] PU H,DOIG G S,LV Y,et al.Modifiable risk factors for ventilator associated diaphragmatic dysfunction:a multicenter observational study[J].BMC Pulm Med,2023,23(1):343.
[14] 胡良平,鲍晓蕾.多因素Logistic回归分析样本量的估算方法[J].中华预防医学杂志,2015,49(7):669-671.
[15] American Thoracic Society/European Respiratory Society.ATS/ERS statement on respiratory muscle testing[J].Am J Respir Crit Care Med,2002，166(4):518-624.
[16] CALEFFI-PEREIRA M,PEREIRA DE ALBUQUERQUE A L.Measurements of respiratory muscle function as diagnostic criteria for diaphragmatic paralysis[J].J Bras Pneumol,2021:e20210310.
[17] GOLIGHER E C,DRES M,FAN E,et al.Mechanical ventilation-induced diaphragm atrophy strongly impacts clinical outcomes[J].Am J Respir Crit Care Med,2018,197(2):204-213.
[18] POWERS S K.Ventilator-induced diaphragm dysfunction:phenomenology and mechanism(s) of pathogenesis[J].J Physiol,2024,602(19):4729-4752.
[19] SU F,MOREAU A,SAVI M,et al.Circulating nucleosomes as a novel biomarker for sepsis:a scoping review[J].Biomedicines,2024,12(7):1385.
[20] SUN G D,ZHANG Y,MO S S,et al.Multiple organ dysfunction syndrome caused by sepsis:risk factor analysis[J].Int J Gen Med,2021,14:7159-7164.
[21] HUANG A,SALAZAR M,WEBER H,et al.ICU-acquired weakness:critical illness myopathy and polyneuropathy[J].J Crit Care,2025,88:155074.
[22] YANG Q,LUO Y,LAN B,et al.Fighting fire with fire:exosomes and acute pancreatitis-associated acute lung injury[J].Bioengineering,2022,9(11):615.
[23] Teymouri N,Mesbah S,Navabian S M H,et al.ECG frequency changes in potassium disorders:a narrative review[J].Am J Cardiovasc Dis,2022,12(3):112-124.
[24] HAMADA H,TOMO T,KIM S T,et al.The impact of potassium dynamics on cardiomyocyte beating in hemodialysis treatment[J].J Clin Med,2024,13(8):2289.
[25] NANJUNDAPPA S M,SAFEERA ALIKUTTY K,MABEL KURIAKOSE E V,et al.Analysis of ADRs with hypokalaemia for severity,preventability and causality in a tertiary care centre in south India[J].Pharmacol Clin Phar Res,2023,8(1):12.
[26] SAWOO R,DEY R,GHOSH R,et al.TLR4 and TNFR1 blockade dampen M1 macrophage activation and shifts them towards an M2 phenotype[J].Immunol Res,2021,69(4):334-351.
[27] 于翠香,王西艳.《中国成人医院获得性肺炎与呼吸机相关性肺炎诊断和治疗指南(2018年版)》解读[J].中国医刊,2021,56(9):951-953.
[28] YANG C,GUO J,NI K,et al.Mechanical ventilation-related high stretch mainly induces endoplasmic reticulum stress and thus mediates inflammation response in cultured human primary airway smooth muscle cells[J].Int J Mol Sci,2023,24(4):3811.
[29] SPADARO S,DALLA CORTE F,SCARAMUZZO G,et al.Circulating skeletal troponin during weaning from mechanical ventilation and their association to diaphragmatic function:a pilot study[J].Front Med,2021,8:770408.

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