Adult: Perioperative Management
A nomogram to predict postoperative pulmonary complications after cardiothoracic surgery

https://doi.org/10.1016/j.jtcvs.2021.08.034Get rights and content

Abstract

Objective

The objective was to develop a novel scoring system that would be predictive of postoperative pulmonary complications in critically ill patients after cardiac and major vascular surgery.

Methods

A total of 17,433 postoperative patients after coronary artery bypass graft, valve, or thoracic aorta repair surgery admitted to the cardiovascular intensive care units at Cleveland Clinic Main Campus from 2009 to 2015. The primary outcome was the composite of postoperative pulmonary complications, including pneumonia, prolonged postoperative mechanical ventilation (>48 hours), or reintubation occurring during the hospital stay. Elastic net logistic regression was used on the training subset to build a prediction model that included perioperative predictors. Five-fold cross-validation was used to select an appropriate subset of the predictors. The predictive efficacy was assessed with calibration and discrimination statistics. Post hoc, of 13,353 adult patients, we tested the clinical usefulness of our risk prediction model on 12,956 patients who underwent surgery from 2015 to 2019.

Results

Postoperative pulmonary complications were observed in 1669 patients (9.6%). A prediction model that included baseline and demographic risk factors along with perioperative predictors had a C-statistic of 0.87 (95% confidence interval, 0.86-0.88), with a corrected Brier score of 0.06. Our prediction model maintains satisfactory discrimination (C-statistics of 0.87) and calibration (Brier score of 0.07) abilities when evaluated on an independent dataset of 12,843 recent adult patients who underwent cardiovascular surgery.

Conclusions

A novel prediction nomogram accurately predicted postoperative pulmonary complications after major cardiac and vascular surgery. Intensivists may use these predictors to allow for proactive and preventative interventions in this patient population.

Graphical abstract

Strong multivariate baseline and perioperative predictors were factored into a novel nomogram to predict PPCs. Bootstrapped calibration curve demonstrated the model calibration showing ideal (green line), apparent (blue line), and bias-corrected (red line) model. High agreement was noted between observed (frequencies), and predicted pulmonary complications events were plotted against predicted probabilities. The prediction nomogram was further internally validated in an independent dataset to estimate clinical usefulness that demonstrated excellent discrimination with preserved calibration ability. Early identification of pulmonary complications in at-risk patients provides latitude to the clinicians to use preemptive measures and may help modify postoperative outcomes.

  1. Download : Download high-res image (235KB)
  2. Download : Download full-size image

Section snippets

Materials and Methods

With Institutional Review Board approval (15-1046) and waived consent, we conducted a single-center, large, retrospective observational cohort study. The analysis included 17,433 adult patients who underwent coronary artery bypass graft, valve, or thoracic aorta repair surgery between January 2, 2009, and September 24, 2015, at the Cleveland Clinic's main campus. Patients were excluded if they were aged less than 18 years; information regarding main demographic or baseline characteristics and

Results

Among 24,124 patients who underwent cardiac and vascular surgery between January 2, 2009, and September 24, 2015, a total of 17,433 met our inclusion and exclusion criteria with complete accumulated data required to build the prediction models (Figure 1). The summary of the demographic and baseline characteristics of patients, intraoperative and ICU characteristics, and postoperative pulmonary outcomes is shown in Table 1. PPCs were observed in 1669 patients (9.6%), of whom 1361 (7.8%)

Discussion

Our augmented model of PPCs that included intraoperative and postoperative variables, and baseline characteristics (area under the curve 0.87; 0.86-0.88) showed a statistically superior performance compared with the base model (area under the curve, 0.80; 0.79-0.81) that only included baseline characteristics. Furthermore, bootstrapped validation showed satisfactory internal validity with excellent ability to discriminate PPC (area under receiver operating characteristic of 0.80; 95% CI,

Conclusions

We identified 25 strong multivariate perioperative predictors associated with PPCs after cardiovascular surgery and simultaneously compared our augmented model with a base model that has excellent discriminative power. Finally, we validated our prediction nomogram in an independent set to estimate clinical usefulness. Intensivists and surgeons practicing cardiac surgical critical care should be able to use this nomogram to predict and intervene proactively to prevent PPCs in these patients.

References (38)

  • D.J. Birnkrant et al.

    American College of Chest Physicians consensus statement on the respiratory and related management of patients with Duchenne muscular dystrophy undergoing anesthesia or sedation

    Chest

    (2007)
  • A.S. Neto et al.

    Association between driving pressure and development of postoperative pulmonary complications in patients undergoing mechanical ventilation for general anaesthesia: a meta-analysis of individual patient data

    Lancet Respir Med

    (2016)
  • A. Serpa Neto et al.

    Incidence of mortality and morbidity related to postoperative lung injury in patients who have undergone abdominal or thoracic surgery: a systematic review and meta-analysis

    Lancet Respir Med

    (2014)
  • R.S.M. Barros et al.

    Continuous versus interrupted suture technique in microvascular anastomosis in rats

    Acta Cir Bras

    (2017)
  • G.W. Smetana

    Postoperative pulmonary complications: an update on risk assessment and reduction

    Cleve Clin J Med

    (2009)
  • C.C. Canver et al.

    Intraoperative and postoperative risk factors for respiratory failure after coronary bypass

    Ann Thorac Surg

    (2003)
  • C. Weissman

    Pulmonary complications after cardiac surgery

    Semin Cardiothorac Vasc Anesth

    (2004)
  • S.A. Nashef et al.

    EuroSCORE II

    Eur J Cardiothorac Surg

    (2012)
  • M. Ranucci et al.

    Risk of assessing mortality risk in elective cardiac operations: age, creatinine, ejection fraction, and the law of parsimony

    Circulation

    (2009)

    • Cited by (5)

    Institutional Review Board (IRB) Approval: Date of approval: August 21, 2015; IRB number: 15-1046. Consent Statement: IRB (No. 15-1046) waived written consent for this study.

    View full text
    © 2021 by The American Association for Thoracic Surgery