Evidence map›Paper›PMID 39398595›Full record

ArticleAmerican journal of translational research2024

Influencing factors of chronic pain after total knee replacement in osteoarthritis patients: a nomogram prediction model.

Bei Zhang, Hui Meng, Hua Zhang, Rui Zang, Xinwei Zhu

Abstract read
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Article in American journal of translational research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Bei ZhangDepartment of Surgery, Jinan Central Hospital Jinan 250013, Shandong, China.
Hui MengDepartment of Surgery, Jinan Central Hospital Jinan 250013, Shandong, China.
Hua ZhangDepartment of Surgery, Jinan Central Hospital Jinan 250013, Shandong, China.
Rui ZangDepartment of Surgery, Jinan Central Hospital Jinan 250013, Shandong, China.
Xinwei ZhuDepartment of Pain, The Fourth People's Hospital of Jinan Jinan 250031, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo analyze the factors influencing chronic pain in patients with knee osteoarthritis after total knee replacement surgery (TKRS) and to construct a nomogram risk prediction model, providing an economically effective screening method for clinical use.

methodsThis retrospective study included 100 consecutive patients at the Jinan Central Hospital, with knee osteoarthritis who underwent TKRS from January 2023 to December 2023. Patients were divided into the observation group (n=55) and the control group (n=45) based on the presence of chronic pain. Logistic regression was performed to explore factors associated with chronic pain, including medical records, laboratory data, previous history, and independent clinical risk factors. The identified independent factors were then incorporated to construct a nomogram for chronic pain prediction.

resultsSix variables were identified as independent predictors of chronic pain after TKRS: age, BMI, diabetes, severity of preoperative pain, severity of postoperative acute pain, and postoperative wound infection (P<0.05). The area under the curve (AUC) of this nomogram was 0.836 [95% confidence interval (CI): 0.615-0.884], demonstrating good calibration and clinical practicability.

conclusionAge, BMI, diabetes, severity of preoperative pain, severity of postoperative acute pain, and postoperative wound infection are risk factors for chronic pain after TKRS. The predictive nomogram developed in this study shows good prediction ability and accuracy for chronic pain in patients with knee osteoarthritis after surgery.

Indexed as

Chronic painknee osteoarthritisnomogramtotal knee replacement surgery

Identifiers

PMID39398595
PMCPMC11470368

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