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R. Imai1, T. Kubo2, T. Nishigami3, Y. Yonemoto4, T. Fuji5
1Osaka Kawasaki Rehabilitation Univesiy, Department of Rehabilitation, Kaizuka, Japan, 2Kashiba Asahigaoka Hospital, Department of Rehabilitation, Kashiba, Japan, 3Prefectural University of Hiroshima, Department of Physical Therapy, Mihara, Japan, 4Higashiosaka Yamaji Hospital, Department of Rehabilitation, Higashiosaka, Japan, 5Kashiba Asahigaoka Hospital, Department of Orthopaedic Surgery, Kashiba, Japan
Background: Most patients experience pain relief within 6-12 weeks after total knee arthroplasty (TKA); however, 8-34% of patients experience chronic postsurgical pain (CPSP). Since many patients suffer from CPSP, there is a need for an early detection or prediction method, so that health care providers can identify patients who are likely to experience continued pain and initiate treatment earlier. Imai et al. report that the pain trajectory of patients calculated at 1 postoperative week based on pain intensity after surgery predicted their prognosis at 1 month after surgery. However, this previous study did not extend beyond 1 postoperative month, and it is unclear whether the pain trajectory can predict long-term pain intensity.
Purpose: Our purpose was to determine whether the pain trajectory during the first postoperative week is a precise predictor of pain intensity 1 year after TKA. In addition, we identified the pain trajectory characteristics of patients who have higher pain intensity or worse physical function at 1 year after surgery.
Methods: Pain intensity was measured in 134 postoperative patients using a visual analog scale (VAS; 0 = no pain, 100 = highest possible degree of pain) from which we calculated the pain trajectory (slope and intercept) using pain intensity at Days 1, 3, 5, and 7 after surgery. Pain normally decreases in intensity over time, and a linear fit of an individual patient’s pain intensity score defines his or her trajectory. Under this simple linear model (X, days; Y, pain intensity), each patient’s trajectory has two key features: the slope (rate of resolution) and the intercept (initial pain level after surgery). Structural equation modeling (SEM) was used to investigate the model of multiple regression analysis.
Results: The “slope and intercept model” showed the best fit of the hypothesized models, because its Akaike information criterion (AIC; 1126.65) and Bayesian information criterion (BIC; 1135.241) values were the lowest of all the models. The prevalence of patients with more than moderate pain intensity was 10.4% at 1 year after surgery. Our results demonstrate that patients with higher pain intensity or worse physical function at 1 year after surgery are those with a high intercept and a low slope, or a positive slope.
Conclusion(s): Our study revealed that pain intensity values during the first postoperative week can be used to predict CPSP. The pain trajectory characteristics associated with CPSP were found to be a mild negative slope or a positive slope.
Implications: By considering pain trajectory, clinicians may be able to identify patients with a risk of prolonged pain earlier than with other methods so that treatment can be initiated earlier to prevent CPSP from developing.
Funding, acknowledgements: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Keywords: postoperative pain, pain trajectory, pain intensity
Topic: Pain & pain management
Did this work require ethics approval? Yes
Institution: Osaka Kawasaki Rehabilitation University
Committee: The Ethics Committee of the Kashiba Asahigaoka Hospital
Ethics number: 2019051-002
All authors, affiliations and abstracts have been published as submitted.
