探讨综合气道干预策略对机械通气患者预后的改善，分析肺通气功能与气道微生态的中介作用。

选取2022年8月至2025年12月我院收治的机械通气患者199例为对象，随机分为观察组102例例，对照组97例。对照组接受常规气道管理，观察组在对照组基础上实施精细化气道干预策略，包括气道动态评估、个体化湿化、精准吸痰、人工气道维护及气道廓清。比较两组治疗前后肺动态顺应性(compliance dynamic, Cdyn)、气道阻力(resistance, Raw)、氧合指数(partial pressure of arterial oxygen/fraction of inspired oxygen, PaO₂/FiO₂)、气道微生态多样性(Chao1指数、Shannon指数)及预后。采用Pearson相关分析、多元线性分层回归分析及PROCESS宏程序模型4进行中介效应检验。

治疗后观察组Cdyn[(58.62±9.47)ml/cmH₂O比(48.35±8.66)ml/cmH₂O，t＝7.869，P<0.001]、PaO₂/FiO₂[(289.62±41.53)mmHg比(231.47±36.82)mmHg，t＝9.905，P<0.001]高于对照组；Raw[(12.15±3.12)cmH₂O/(L·s)比(15.36±3.57)cmH₂O/(L·s)，t＝－6.772，P<0.001] 低于对照组。观察组Chao1指数[(689.25±72.36)比(542.16±65.82)，t＝14.869，P<0.001]及Shannon指数[(5.86±0.72)比(4.23±0.65)，t＝16.392，P<0.001]高于对照组。观察组机械通气时间[(7.82±2.15)d比(11.36±3.42)d，t＝－8.976，P<0.001]、ICU住院时间[(10.15±3.26)d比(14.72±4.15)d，t＝－8.403，P<0.001]及病死率(10.78%比24.74%，χ²＝6.189，P＝0.013)低于对照组。分层回归显示模型4的R²＝0.685，气道干预策略、Cdyn、PaO₂/FiO₂及Shannon指数是机械通气时间的影响因素。中介效应分析显示，肺通气功能与气道微生态的中介效应值为－0.315(95%CI：－0.390~－0.249)，中介效应占比47.37%。

综合气道干预策略可有效改善机械通气患者肺通气功能、气道微生态稳态，缩短机械通气、ICU住院时间，降低病死率具有临床意义。

To evaluate the effect of comprehensive airway intervention strategies on prognosis in mechanically ventilated patients and to analyze the mediating roles of pulmonary ventilation function and airway microbiota.

A total of 199 mechanically ventilated patients admitted to our hospital from August 2022 to December 2025 were enrolled and randomly divided into an observation group (n=102) and a control group (n=97). The control group received routine airway management, while the observation group received additional comprehensive airway interventions, including dynamic airway assessment, individualized humidification, precise sputum suction, artificial airway maintenance, and airway clearance. Pulmonary dynamic compliance (Cdyn), airway resistance (Raw), oxygenation index (PaO₂/FiO₂), airway microbiota diversity (Chao1 index, Shannon index), and clinical outcomes were compared between the two groups before and after treatment. Pearson correlation analysis, multiple linear hierarchical regression, and PROCESS macro model 4 were used for mediation analysis.

After treatment, the observation group showed significantly higher Cdyn [(58.62±9.47) ml/cmH₂O vs. (48.35±8.66) ml/cmH₂O, t=7.869, P<0.001] and PaO₂/FiO₂[(289.62±41.53) mmHg vs. (231.47±36.82) mmHg, t=9.905, P<0.001], and lower Raw [(12.15±3.12) cmH₂O/(L·s) vs. (15.36±3.57) cmH₂O/(L·s), t=-6.772, P<0.001] compared with the control group. The Chao1 index [(689.25±72.36) vs. (542.16±65.82), t=14.869, P<0.001] and Shannon index [(5.86±0.72) vs. (4.23±0.65), t=16.392, P<0.001] were also significantly higher in the observation group. The observation group had shorter duration of mechanical ventilation [(7.82±2.15) d vs. (11.36±3.42) d, t=-8.976, P<0.001], shorter ICU stay[(10.15±3.26) d vs. (14.72±4.15) d, t=-8.403, P<0.001], and lower mortality (10.78% vs. 24.74%, χ²=6.189, P=0.013) than the control group. Hierarchical regression showed that the final model had an R² of 0.685, and airway intervention strategy, Cdyn, PaO₂/FiO₂, and Shannon index were independent influencing factors for mechanical ventilation duration. Mediation analysis revealed that the mediating effect of pulmonary ventilation function and airway microbiota was -0.315 (95%CI: -0.390 to -0.249), accounting for 47.37% of the total effect.

Comprehensive airway intervention strategies can effectively improve pulmonary ventilation function and airway microbiota homeostasis, shorten mechanical ventilation duration and ICU stay, and reduce mortality in mechanically ventilated patients.