Severe Postoperative Pain in Total Knee Arthroplasty Patients: Risk Factors, Insights and Implications for Pain Management via a Digital Health Approach

Author:

Lebleu Julien1ORCID,Pauwels Andries1,Poilvache Hervé2ORCID,Anract Philippe3,Belbachir Anissa4ORCID

Affiliation:

1. moveUP, Cantersteen 47, 1000 Brussels, Belgium

2. Orthopedic Surgery Department, CHIREC, 1420 Braine-l’Alleud, Belgium

3. Service de Chirurgie Orthopédique, Hopital Cochin, Université Paris Cité, 75014 Paris, France

4. Service d’Anesthésie, Réanimation et Médecine Périopératoire, Hopital Cochin, Université Paris Cité, 75014 Paris, France

Abstract

Up to 25% of patients undergoing knee arthroplasty report chronic pain postoperatively. Early identification of high-risk individuals can enhance pain management strategies. This retrospective analysis investigates the incidence of severe postoperative pain and its associated risk factors among 740 patients who underwent total knee arthroplasty. Utilizing a digital application, patients provided comprehensive data encompassing pre- and postoperative pain levels, analgesic usage, and completed a chronic pain risk assessment. Participants were categorized into two distinct groups based on their pain status at three months post-op: Group D+ (14%), characterized by pain scores exceeding 40/100 and/or the utilization of level 2 or 3 analgesics, and Group D− (86%), who did not meet these criteria. An analysis of pain trajectories within these groups revealed a non-linear progression, with specific patterns emerging amongst those predisposed to chronic pain. Notably, patients with a trajectory towards chronic pain exhibited a plateau in pain intensity approximately three weeks post-surgery. Significant preoperative risk factors were identified, including elevated initial pain levels, the presence of comorbidities, pain in other body areas, heightened joint sensitivity and stiffness. This study highlights the utility of digital platforms in enhancing patient care, particularly through the continuous monitoring of pain. Such an approach facilitates the early identification of potential complications and enables timely interventions.

Publisher

MDPI AG

Subject

General Medicine

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3