Evidence map›Paper›PMID 41368274›Full record

ArticleClinical interventions in aging2025

Risk Factors for Chronic Post-Surgical Pain in the Elderly: A Single-Center Retrospective Study.

Li-Heng Li, Hao Guo, Feng-Zhi Su, Jie Chen, Yu-Bo Xie

Abstract read
In one paragraph

Article in Clinical interventions in aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Li-Heng Li *Department of Anesthesiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, People's Republic of China.ORCID 0009-0007-0986-5325
Hao Guo *Department of Anesthesiology, Renmin Hospital, Hubei University of Medicine, Shiyan, People's Republic of China.ORCID 0000-0002-6547-5686
Feng-Zhi SuDepartment of Anesthesiology, People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, People's Republic of China.
Jie ChenDepartment of Anesthesiology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, People's Republic of China.
Yu-Bo XieDepartment of Anesthesiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, People's Republic of China.ORCID 0000-0002-7198-7506

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Chronic Post-Surgical Pain (CPSP) is a common surgical complication, but the association between perioperative complications, patients' intrinsic mental status, and 3-month CPSP remains unclear in elderly surgical populations. This study thus aims to identify perioperative risk factors for 3-month CPSP in elderly patients after non-cardiac surgery, with CPSP here defined as pain intensity ≥3 on the Numerical Rating Scale at 3-month follow-up. Patients and Methods: This retrospective study included 367 elderly patients. We first analyzed variables with descriptive statistics, then conducted all subsequent analyses separately for each of the three surgical subgroups, allowing for potential nuances in the contributory patterns of key factors across groups. To predict 3-month CPSP, we used 10 machine learning algorithms. Model performance was assessed via repeated 5-fold cross-validation, and top-performing models were interpreted using SHapley Additive exPlanations (SHAP) to clarify how key factors contribute. Results: Of 367 patients, the overall prevalence of 3-month CPSP was 25.07%, with significant variation across surgical subgroups: 48.05% in orthopedic surgery, 10.34% in urinary tumor surgery, and 7.14% in abdominal tumor surgery. The Random Forest model showed strong, consistent predictive ability across the three subgroups. Frailty was a key shared risk factor for CPSP across all surgical types, and further analyses identified surgery-specific risk factors. Conclusion: These findings demonstrate that data-driven models can reliably predict CPSP across studied surgical types, with frailty state as a universal risk factor and distinct surgery-specific profiles supporting tailored perioperative risk assessment and prevention strategies.

Indexed as

Chronic PainPostoperative PainAgedAged, 80 and overFemaleFrailtyHumansMachine LearningMalePain MeasurementPrevalenceRetrospective StudiesRisk Factorschronic post-surgical painelderly patientsmachine learning algorithmsrisk factors

Identifiers

PMID41368274
PMCPMC12683256

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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 OpenQuestion graph.