Classifying multicenter approaches to invasive mechanical ventilation for infants with bronchopulmonary dysplasia using hierarchical clustering analysis.
Classifying multicenter approaches to invasive mechanical ventilation for infants with bronchopulmonary dysplasia using hierarchical clustering analysis.
复制标题
使用层次聚类分析对支气管肺发育不良婴儿的有创机械通气多中心方法进行分类。
DOI：
10.1002/ppul.26488
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发表时间：
2023
影响因子：
3.1
通讯作者：
Nelin,
中科院分区：
文献类型：
--
作者：
Kielt,MatthewJ;Hatch3rd,LDupree;Levin,JonathanC;Napolitano,Natalie;Abman,StevenH;Baker,ChristopherD;Eldredge,LaurieC;Collaco,JosephM;McGrath-Morrow,SharonA;Rose,RebeccaS;Lai,Khanh;Keszler,Martin;Sindelar,Richard;Nelin,
简介针对患有严重支气管肺发育不良 (BPD) 的婴儿的循证通气策略仍然未知。确定当代通气方法是否聚类为特定的 BPD 策略可能会更好地描述护理特征并增强临床试验的设计。本研究的目的是检验这样的假设：对点流行率呼吸机设置数据进行无监督的多因素聚类分析，可以对严重 BPD 婴儿的多中心队列中离散数量的基于生理学的机械通气方法进行分类。方法我们对接受有创机械通气治疗的严重 BPD 婴儿的多中心点流行率研究进行了二次分析。我们使用 Ward 层次聚类分析 (HCA)，根据平均气道压力 (MAP)、呼气末正压 (PEEP)、设定呼吸频率和吸气时间 (Ti) 对队列进行聚类。结果 纳入了来自 14 个中心的 78 名严重 BPD 患者。 HCA 根据凝聚系数 0.97 将三个离散簇分类。根据聚类 1、2 和 3 的 Jaccard 系数平均值分别为 0.79、0.85 和 0.77 确定，聚类稳定性相对较强。通过 Kruskall-Wallis 检验进行的每次比较，各簇之间的中位 PEEP、MAP、速率、Ti 和 PIP 存在显着差异 (p< 0.0001)。结论在本研究中，对呼吸机设置数据进行无监督聚类分析，确定了多中心重度 BPD 婴儿队列中的三种离散机械通气方法。需要进行前瞻性试验来确定这些机械通气方法是否与特定的严重 BPD 临床表型相关，并差异性地改变呼吸结果。
IntroductionEvidence‐based ventilation strategies for infants with severe bronchopulmonary dysplasia (BPD) remain unknown. Determining whether contemporary ventilation approaches cluster as specific BPD strategies may better characterize care and enhance the design of clinical trials. The objective of this study was to test the hypothesis that unsupervised, multifactorial clustering analysis of point prevalence ventilator setting data would classify a discrete number of physiology‐based approaches to mechanical ventilation in a multicenter cohort of infants with severe BPD.MethodsWe performed a secondary analysis of a multicenter point prevalence study of infants with severe BPD treated with invasive mechanical ventilation. We clustered the cohort by mean airway pressure (MAP), positive end expiratory pressure (PEEP), set respiratory rate, and inspiratory time (Ti) using Ward's hierarchical clustering analysis (HCA).ResultsSeventy‐eight patients with severe BPD were included from 14 centers. HCA classified three discrete clusters as determined by an agglomerative coefficient of 0.97. Cluster stability was relatively strong as determined by Jaccard coefficient means of 0.79, 0.85, and 0.77 for clusters 1, 2, and 3, respectively. The median PEEP, MAP, rate, Ti, and PIP differed significantly between clusters for each comparison by Kruskall–Wallis testing (p< 0.0001).ConclusionsIn this study, unsupervised clustering analysis of ventilator setting data identified three discrete approaches to mechanical ventilation in a multicenter cohort of infants with severe BPD. Prospective trials are needed to determine whether these approaches to mechanical ventilation are associated with specific severe BPD clinical phenotypes and differentially modify respiratory outcomes.