Effects of Intra-operative Cardiopulmonary Variability On Post-operative Pulmonary Complications in Major Non-cardiac Surgery: A Retrospective Cohort Study

Abstract

Intraoperative cardiopulmonary variables are well-known predictors of postoperative pulmonary complications (PPC), traditionally quantified by median values over the duration of surgery. However, it is unknown whether cardiopulmonary instability, or wider intra-operative variability of the same metrics, is distinctly associated with PPC risk and severity. We leveraged a retrospective cohort of adults (n = 1202) undergoing major non-cardiothoracic surgery. We used multivariable logistic regression to evaluate the association of two outcomes (1)moderate-or-severe PPC and (2)any PPC with two sets of exposure variables- (a)variability of cardiopulmonary metrics (inter-quartile range, IQR) and (b)median intraoperative cardiopulmonary metrics. We compared predictive ability (receiver operating curve analysis, ROC) and parsimony (information criteria) of three models evaluating different aspects of the intra-operative cardiopulmonary metrics: Median-based: Median cardiopulmonary metrics alone, Variability-based: IQR of cardiopulmonary metrics alone, and Combined: Medians and IQR. Models controlled for peri-operative/surgical factors, demographics, and comorbidities. PPC occurred in 400(33%) of patients, and 91(8%) experienced moderate-or-severe PPC. Variability in multiple intra-operative cardiopulmonary metrics was independently associated with risk of moderate-or-severe, but not any, PPC. For moderate-or-severe PPC, the best-fit predictive model was the Variability-based model by both information criteria and ROC analysis (area under the curve, AUC_{Variability-based} = 0.74 vs AUC_Median-based = 0.65, p = 0.0015; AUC_{Variability-based} = 0.74 vs AUC_Combined = 0.68, p = 0.012). For any PPC, the Median-based model yielded the best fit by information criteria. Predictive accuracy was marginally but not significantly higher for the Combined model (AUC_Combined = 0.661) than for the Median-based (AUC_Median-based = 0.657, p = 0.60) or Variability-based (AUC_{Variability-based} = 0.649, p = 0.29) models. Variability of cardiopulmonary metrics, distinct from median intra-operative values, is an important predictor of moderate-or-severe PPC.

Keywords: Intraoperative hemodynamic variability; Intraoperative respiratory variability; Lung protective ventilation; Postoperative pulmonary complications.

Fig. 1

Association between intraoperative exposure variables and post-operative pulmonary outcomes. Abbreviations: PPC, postoperative pulmonary complications; M-S, moderate or severe; , direct relationship; , inverse relationship; -, no significant relationship

Fig. 2

Comparison of predictive ability for models of ‘any’ (A) and ‘severe’ (B) PPC by receiver operating curve (ROC) analysis. AUC: area under the curve. M1: model including only medians of intra-operative cardiopulmonary variables. M2: model including only IQRs of intra-operative cardiopulmonary variables. M3: model including both medians and IQRs of intra-operative cardiopulmonary variables