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

analgesia chronic pain knee surgery mhealth pain management pain trajectory prehabilitation

Journal

Journal of clinical medicine
ISSN: 2077-0383
Titre abrégé: J Clin Med
Pays: Switzerland
ID NLM: 101606588

Informations de publication

Date de publication:
15 Dec 2023
Historique:
received: 26 10 2023
revised: 08 12 2023
accepted: 11 12 2023
medline: 23 12 2023
pubmed: 23 12 2023
entrez: 23 12 2023
Statut: epublish

Résumé

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.

Identifiants

pubmed: 38137764
pii: jcm12247695
doi: 10.3390/jcm12247695
pii:
doi:

Types de publication

Journal Article

Langues

eng

Auteurs

Julien Lebleu (J)

moveUP, Cantersteen 47, 1000 Brussels, Belgium.

Andries Pauwels (A)

moveUP, Cantersteen 47, 1000 Brussels, Belgium.

Hervé Poilvache (H)

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

Philippe Anract (P)

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

Anissa Belbachir (A)

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

Classifications MeSH