Predictors for moderate to severe acute postoperative pain after total hip and knee replacement
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The ability to identify and focus care to patients at higher risk of moderate to severe postoperative pain should improve analgesia and patient satisfaction, and may affect reimbursement. We undertook this multi-centre cross-sectional study to identify preoperative risk factors for moderate to severe pain after total hip (THR) and knee (TKR) replacement.
A total of 897 patients were identified from electronic medical records. Preoperative information and anaesthetic technique was gained by retrospective chart review. The primary outcomes were moderate to severe pain (pain score ≥ 4/10) at rest and with activity on postoperative day one. Logistic regression was performed to identify predictors for moderate to severe pain.
Moderate to severe pain was reported by 20 % at rest and 33 % with activity. Predictors for pain at rest were female gender (OR 1.10 with 95 % CI 1.01–1.20), younger age (0.96, 0.94–0.99), increased BMI (1.02, 1.01–1.03), TKR vs. THR (3.21, 2.73–3.78), increased severity of preoperative pain at the surgical site (1.15, 1.03–1.30), preoperative use of opioids (1.63, 1.32–2.01), and general anaesthesia (8.51, 2.13–33.98). Predictors for pain with activity were TKR vs. THR (1.42, 1.28–1.57), increased severity of preoperative pain at the surgical site (1.11, 1.04–1.19), general anaesthesia (9.02, 3.68–22.07), preoperative use of anti-convulsants (1.78, 1.32–2.40) and anti-depressants (1.50, 1.08–2.80), and prior surgery at the surgical site (1.28, 1.05–1.57).
Our findings provide clinical guidance for preoperative stratification of patients for more intensive management potentially including education, nursing staffing, and referral to specialised pain management.
KeywordsTotal Knee Replacement Generalise Estimate Equation Preoperative Pain Improve Patient Satisfaction Acute Postoperative Pain
Funding was provided by the Department of Anesthesiology, Hospital for Special Surgery. Dr. Ma was partially supported by Clinical Translational Science Center (NIH UL1-RR024996). Dr. Della Valle is a consultant for Biomet, Convatec and Smith & Nephew and receives research support from Smith & Nephew and Zimmer. Dr. Sculco receives research support from Exactech.
Conflict of interest
The authors declare that they have no conflict of interest.
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