目的：观察不同肺力学模型在压力控制通气(pressure controlled ventilation， PCV)时潮气量变化对吸气流量指数的影响。方法：使用ASL 5000机械模拟肺模拟健康成年人、轻度和重度慢性阻塞性肺疾病(chronic obstructive pulmonary diseases， COPD)及急性呼吸窘迫综合征(acute respiratory distress syndrome， ARDS)患者，构建4种呼吸力学模型。系统顺应性(C_rs)为30.0和60.0 mL/cmH₂O，气道阻力(R_aw)分别为5.0、10.0和20.0 cmH₂O/(L·s)。呼吸机以PCV模式运行，输出潮气量(V_T)达到5.0、7.0和10.0 mL/kg，呼气末正压(PEEP)设置为5.0 cmH₂O，通气频率为10次/min，吸气时间为3.0 s。收集不同肺力学模型通气参数的变化，并计算流量指数和呼气时间常数(RC_exp)。结果：PCV通气时，所有4种肺力学模型的流量指数均小于1.0。随着V_T的增大，PCV通气时吸气峰流量(peak inspiratory flow， PIF)和呼气峰流量(peak expiratory flow， PEF)逐渐增高，驱动压增大，流量指数却逐渐减小。ARDS模型的流量指数与健康成年人相近，但RC_exp显著降低。重度COPD模型的流量指数和吸气末流量(end-inspiratory flow， EIF)也较其他几种肺疾病模型显著增高，小潮气量（V_T=5.0 mL/kg)通气时吸气流量指数达到0.80。结论：吸气流量指数具有无创性、可连续监测等特点，潮气量和呼吸力学特性的变化均会影响其数值，连续监测有助于评估患者气流受限的严重程度以及自主吸气努力与机械通气辅助水平间的匹配程度。

Objective: To observe the influence of tidal volume(VT) variation on the inspiratory flow index during pressure controlled ventilation (PCV) in different lung models. Methods: The Hamilton C3 ventilator was connected to an ASL5000 lung simulator, which simulated lung mechanics in patients with healthy adult, patients with mild and severe chronic obstructive pulmonary disease (COPD) and acute respiratory distress syndrome (ARDS), and 4 respiratory mechani-cs models were constructed. mild and severe chronic obstructive pulmonary disease (COPD)The [system compliance (C_rs) was 30.0 and 60.0 mL/cmH₂O, the airway resistance (R_aw) was 5.0, 10.0 and 20.0 cmH₂O/(L•s)]. The Hamilton C3 ventilator was operated in PCV mode were actived with output V_T at 5.0, 7.0 and 10.0 ml/kg, positive end-expiratory pressure (PEEP) was set at 5.0 cmH₂O, breathing rate at 10 bpm, and inspiratory time was set at 3.0 sec. The performance characteristics were collected, and the inspiratory flow index and expiratory time constant(RCexp) were estimated by specical equationscalculated. Results: The flow index was not aboveless than 1.0 in all four lung mechanics profiles models during passive ventilation with PCV mode. Peak inspiratory flow (PIF), peak expiratory flow (PEF) and inspiratory driving pressure (DP) were increased gradually with the increment of tidal volume, whereas the flow index was decreased. There were the similar value in the estimation of The flow index in health adult and of the ARDS lung models was similar to that of healthy adults, but RC_exp was significantly reduced in severe restrictive model. Flow index and end-inspiratory flow (EIF) were significantly higher in severe COPD model than in the other lung models, which with flow index was close toreaching 0.80 when V_T was at 5.0 mL/kg. Conclusions: Flow index has the characteristics ofis an non-invasive derivative parameter and continuous can be monitoringed continuously, and is affected by the alteration of tidal volume and respiratory mechanical properties. During pressure controlled ventilation, the estimation continuous monitoring of flow index is useful to evaluate the severity of airflow limitation and the association between the patient’s inspiratory effort and ventilator outputted assistance level.