AI Article Synopsis

  • The PREDICT study investigates whether preoperative pulmonary function tests (PFTs) can enhance the prediction of postoperative pulmonary complications (PPCs) in patients with chronic obstructive pulmonary disease (COPD) undergoing major surgery.
  • The study involved analyzing 31,714 patients, where 1,271 received PFTs, ultimately focusing on 320 patients for follow-up—240 with confirmed COPD (categorized from GOLD I to IV) and 80 without.
  • Results showed that the ability of various risk prediction models to forecast PPCs was similar, indicating that standard medical and demographic data may be as effective as models that include specific PFT parameters.

Article Abstract

Background: Pulmonary function tests (PFTs) such as spirometry and blood gas analysis have been claimed to improve preoperative pulmonary risk assessment, but the scientific literature is conflicting. The Preoperative Diagnostic Tests for Pulmonary Risk Assessment in Chronic Obstructive Pulmonary Disease (PREDICT) study aimed to determine whether preoperative PFTs improve the prediction of postoperative pulmonary complications (PPCs) in patients with known or suspected chronic obstructive pulmonary disease (COPD) undergoing major surgery. A secondary aim was to determine whether the Global Initiative for Chronic Obstructive Lung Diseases (GOLD) classification of airflow limitation severity (grades I-IV) is associated with PPC.

Methods: In this prospective, single-center study, patients with GOLD key indicators for COPD scheduled for major surgery received PFTs. Patients with confirmed COPD (forced expiratory volume in 1 second [FEV1]/forced vital capacity [FVC] ≤0.7) were included in the COPD cohort and compared with a reference cohort without COPD. We developed 3 multivariable risk prediction models and compared their ability to predict PPC: the "standard model" (medical preconditions, and sociodemographic and surgical data), the "COPD assessment model" (additional GOLD key indicators, pack-years, and poor exercise capacity), and the "PFT model" (additional PFT parameters selected by adaptive least absolute shrinkage and selection operator [LASSO] regression). Multiple LASSO regressions were used for cross-validation.

Results: A total of 31,714 patients were assessed for eligibility; 1271 individuals received PFTs. Three hundred twenty patients (240 with confirmed COPD: 78 GOLD I, 125 GOLD II, 28 GOLD III, 9 GOLD IV, and 80 without COPD) completed follow-up. The diagnostic performance was similar among the standard model (cross-validated area under the curve [cvAUC], 0.723; bias-corrected bootstrapped [bc-b] 95% confidence interval [CI], 0.663-0.775), COPD assessment model (cvAUC, 0.724; bc-b 95% CI, 0.662-0.777), and PFT model (cvAUC, 0.729; bc-b 95% CI, 0.668-0.782). Previously known COPD was an independent predictor in the standard and COPD assessment model. %FEV1 PRED was the only PFT parameter selected by LASSO regression and was an independent predictor in the PFT model (adjusted odds ratios [OR], 0.98; 95% CI, 0.967-.0.998; P = .030). The risk for PPC significantly increased with GOLD grades ( P < .001). COPD was newly diagnosed in 53.8% of the patients with confirmed COPD; however, these individuals were not at increased risk for PPC ( P = .338).

Conclusions: COPD is underdiagnosed in surgical patients. Patients with newly diagnosed COPD commonly presented with low GOLD severity grades and were not at higher risk for PPC. Neither a structured COPD-specific assessment nor preoperative PFTs added incremental diagnostic value to the standard clinical preassessment in patients with known or suspected COPD. Unnecessary postponement of surgery and undue health care costs can be avoided.

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Source
http://dx.doi.org/10.1213/ANE.0000000000006235DOI Listing

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