Elucidating the causal relationship of mechanical power and lung injury: a dynamic approach to ventilator management.

IF 2.8 Q2 CRITICAL CARE MEDICINE
ChaoPing Wu, Arif Canakoglu, Jacob Vine, Anya Mathur, Ronit Nath, Markos Kashiouris, Piyush Mathur, Ari Ercole, Paul Elbers, Abhijit Duggal, Ken Koon Wong, Anirban Bhattacharyya
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引用次数: 0

Abstract

Background: Mechanical power (MP) serves as a crucial predictive indicator for ventilator-induced lung injury and plays a pivotal role in tailoring the management of mechanical ventilation. However, its application across different diseases and stages remains nuanced.

Methods: Using AmsterdamUMCdb, we conducted a retrospective study to analyze the causal relationship between MP and outcomes of invasive mechanical ventilation, specifically SpO2/FiO2 ratio (P/F) and ventilator-free days at day 28 (VFD28). We employed causal inferential analysis with backdoor linear regression and double machine learning, guided by directed acyclic graphs, to estimate the average treatment effect (ATE) in the whole population and conditional average treatment effect (CATE) in the individual cohort. Additionally, to enhance interpretability and identify MP thresholds, we conducted a simulation analysis.

Results: In the study, we included 11,110 unique admissions into analysis, of which 58.3% (6391) were surgical admissions. We revealed a negative and significant causal effect of median MP on VFD28, with estimated ATEs of -0.135 (95% confidence interval [CI]: -0.15 to -0.121). The similar effect was not observed in Maximal MP and minimal MP. The effect of MP was more pronounced in the medical subgroup, with a CATE of -0.173 (95% CI: -0.197 to -0.143) determined through backdoor linear regression. Patients with cardio, respiratory, and infection diagnoses, who required long-term intubation, sustained higher impact on CATEs across various admission diagnoses. Our simulations showed that there is no single MP threshold that can be applied to all patients, as the optimal threshold varies depending on the patient's condition.

Conclusion: Our study underscores the importance of tailoring MP adjustments on an individualized basis in ventilator management. This approach opens up new avenues for personalized treatment strategies and provides fresh insights into the real-time impact of MP in diverse clinical scenarios. It highlights the significance of median MP while acknowledging the absence of universally applicable thresholds.

背景:机械功率(MP)是呼吸机诱发肺损伤的重要预测指标,在调整机械通气管理方面发挥着关键作用。然而,该指标在不同疾病和不同阶段的应用仍有细微差别:我们使用 AmsterdamUMCdb 进行了一项回顾性研究,分析 MP 与有创机械通气结果之间的因果关系,特别是 SpO2/FiO2 比值(P/F)和第 28 天无呼吸机天数(VFD28)。在有向无环图的指导下,我们采用了后门线性回归和双重机器学习的因果推理分析方法,估算了整个人群的平均治疗效果(ATE)和单个队列的条件平均治疗效果(CATE)。此外,为了提高可解释性并确定MP阈值,我们还进行了模拟分析:在这项研究中,我们分析了 11110 例住院病例,其中 58.3%(6391 例)为手术住院病例。我们发现,中位数 MP 对 VFD28 有显著的负向因果效应,估计 ATE 为 -0.135(95% 置信区间 [CI]:-0.15 至 -0.121)。在最大 MP 和最小 MP 中没有观察到类似的效应。在内科亚组中,MP的效果更为明显,通过后门线性回归确定的CATE为-0.173(95% CI:-0.197至-0.143)。在各种入院诊断中,需要长期插管的心外科、呼吸科和感染科患者对 CATE 的影响更大。我们的模拟结果表明,并不存在适用于所有患者的单一 MP 阈值,因为最佳阈值因患者的病情而异:我们的研究强调了在呼吸机管理中根据个体情况调整 MP 的重要性。这种方法为个性化治疗策略开辟了新的途径,并为不同临床情况下 MP 的实时影响提供了新的见解。它强调了MP中值的重要性,同时也承认缺乏普遍适用的阈值。
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来源期刊
Intensive Care Medicine Experimental
Intensive Care Medicine Experimental CRITICAL CARE MEDICINE-
CiteScore
5.10
自引率
2.90%
发文量
48
审稿时长
13 weeks
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