ArticleBMC anesthesiology2025
A nomogram to predict hypoxemia in the post-anesthesia care unit after laparoscopic bariatric surgery.
Article in BMC anesthesiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundHypoxemia in the post-anesthesia care unit (PACU) is a common and distressing complication following laparoscopic bariatric surgery (LBS). Despite its clinical significance, there remains a lack of effective, integrated predictive models to guide the prevention and management of hypoxemia in the PACU for this patient population.
methodsIn this retrospective single-center study, a total of 1,220 cases were included. The database was randomly divided into training and validation cohorts at a 7:3 ratio. Using least absolute shrinkage and selection operator (LASSO) regression combined with multivariable logistic regression, we identified independent predictors and constructed a nomogram for hypoxemia prediction. The nomogram’s performance was evaluated and validated through assessment of the area under the receiver operating characteristic curve (AUC), calculation of the concordance index (C-index), generation of calibration plots, and performance of decision curve analysis (DCA).
resultsThe study cohort of 1,220 patients was randomly divided into training (n = 854) and validation (n = 366) cohorts. A nomogram prediction model was constructed using five independent predictors: age, BMI, presence of two or more comorbidities, intraoperative opioid use ≥ 60 mg, and use of a neuromuscular blocking (NMB) reversal agent. In the training cohort, the AUC and the optimism-corrected C-index were 0.738 (95% CI 0.701–0.775) and 0.731, while in the validation cohort they were 0.735 (95% CI 0.682–0.789) and 0.715, respectively. Calibration plots demonstrated good agreement between predicted probabilities and actual observations. The DCA results confirmed the clinical utility of the nomogram across a range of threshold probabilities.
conclusionsWe developed and validated a nomogram-based prediction model for postoperative hypoxemia in the PACU among patients undergoing elective LBS. This model integrates five key clinical variables and demonstrates acceptable discriminative ability and good calibration, offering a valuable tool for individualized risk assessment and perioperative management.
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