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Integrating Preoperative NLR and PLR with Perioperative Clinical Factors: A Nomogram for Predicting Postoperative CRP
Chanjuan Chen1, Huan Yi2, Yihan Zheng1
1Department of Anesthesiology, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, Fujian, People's Republic of China.
Purpose:
To develop and validate a perioperative nomogram integrating preoperative inflammatory indices (neutrophil-to-lymphocyte ratio [NLR] and platelet-to-lymphocyte ratio [PLR]) and perioperative clinical factors to predict postoperative C-reactive protein (CRP) elevation (>10 mg/L) in patients undergoing laparoscopic hysterectomy.
Patients And Methods:
A retrospective clinical prediction study was conducted involving 1199 patients who underwent laparoscopic hysterectomy. Patients were randomly divided into a training cohort (n=839, 70%) and an internal validation cohort (n=360, 30%). Candidate predictors included preoperative variables (body mass index [BMI], heart rate [HR], NLR, PLR, and systemic immune-inflammation index [SII]) and intraoperative variables (surgical duration, infusion quantity, and estimated blood loss). Least absolute shrinkage and selection operator (LASSO) regression was used for feature selection, and multivariable logistic regression was applied to construct the prediction model. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA).
Results:
Multivariable analysis identified BMI (odds ratio [OR] 1.08, 95% confidence interval [CI] 1.02-1.14, P = 0.008), HR (OR 0.97, 95% CI 0.96-0.99, P < 0.001), infusion quantity (OR 1.00, 95% CI 1.00-1.00, P = 0.009), estimated blood loss (OR 1.00, 95% CI 1.00-1.01, P = 0.044), NLR (OR 2.37, 95% CI 1.53-3.67, P < 0.001), and PLR (OR 1.01, 95% CI 1.00-1.01, P = 0.003) as significant predictors. The nomogram showed good discrimination, with an AUC of 0.772 (95% CI: 0.733-0.811) in the training cohort and 0.741 (95% CI: 0.677-0.804) in the validation cohort. Calibration curves and DCA indicated satisfactory model fit and clinical utility.
Conclusion:
The nomogram provides an easy-to-use perioperative tool for individualized prediction of postoperative CRP elevation. It may assist clinicians in early risk stratification and inform targeted monitoring and personalized perioperative management strategies following laparoscopic hysterectomy.
