Evidence map›Paper›PMID 41063293›Full record

ArticlePerioperative medicine (London, England)2025

A predictive tool for early identification of moderate-to-severe pain following open colorectal surgery in older adults: a retrospective cohort study.

Yan Jin, Rongrong Feng, Hui Wang, Jianhui Huo

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Article in Perioperative medicine (London, England), 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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5 · Who and what money

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4 authors.

Yan Jin *Department of Nursing, The Second Affiliated Hospital of Naval Medical University, Shanghai, 200001, China.
Rongrong Feng *Department of Nursing, The Second Affiliated Hospital of Naval Medical University, Shanghai, 200001, China.
Hui WangDepartment of Nursing, The Second Affiliated Hospital of Naval Medical University, Shanghai, 200001, China. huiw0118@163.com.
Jianhui HuoDepartment of Nursing, The Second Affiliated Hospital of Naval Medical University, Shanghai, 200001, China. 13120903607@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundModerate-to-severe pain is a common but often under-recognized complication after open colorectal surgery in older adults, leading to delayed recovery and extended hospitalization. Early identification of high-risk patients is essential for timely pain management. The objective of this study was to develop and internally validate a predictive model, presented as a nomogram, for estimating the risk of moderate-to-severe postoperative pain within 24 h among elderly patients undergoing open colorectal surgery.

methodsWe conducted a retrospective cohort study of 300 patients aged ≥ 60 years who underwent elective open colorectal surgery. Postoperative pain within 24 h was assessed using the Numerical Rating Scale (NRS); NRS ≥ 4 was defined as moderate-to-severe pain. Preoperative psychosocial, cognitive, inflammatory, and perioperative factors were evaluated. Multivariable logistic regression with stepwise AIC selection identified independent predictors. Model performance was assessed using ROC curves, calibration plots, the Hosmer-Lemeshow test, and decision curve analysis (DCA). A nomogram was developed for clinical use.

resultsOf the 300 patients, 120 (40.0%) experienced moderate-to-severe pain. These patients were older and had higher preoperative NRS and CRP levels, along with worse psychosocial and cognitive scores (P < 0.01). Seven variables independently predicted pain severity: GAD-7, PHQ-9, MMSE, MOS-SSS, CRP, operative duration, and undergoing a Miles procedure (P < 0.05). The model showed good discrimination (AUC = 0.79 in training; 0.77 in validation) and calibration. DCA demonstrated net clinical benefit across a range of thresholds.

conclusionWe developed and validated a nomogram incorporating psychosocial, inflammatory, and procedural factors to predict moderate-to-severe postoperative pain. This tool may enable early risk stratification and guide individualized analgesic strategies in elderly patients.

Indexed as

Abdominal surgeryNomogramPostoperative painPsychological assessmentRisk prediction model

Identifiers

PMID41063293
PMCPMC12505875

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