ArticleInternational journal of women's health2026
Integrating Preoperative NLR and PLR with Perioperative Clinical Factors: A Nomogram for Predicting Postoperative CRP Elevation After Laparoscopic Hysterectomy.
Article in International journal of women's health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.