Preoperative frailty predicts postoperative pain after total knee arthroplasty in older patients: a prospective observational study

PURPOSE

Frailty is reportedly associated with postoperative adverse outcomes and may increase the risk of post-surgical pain. Our study aimed to explore whether frailty was an independent risk factor for pain after total knee arthroplasty (TKA) in older patients.

METHODS

Included in this prospective observational study were patients aged 65 or older who underwent primary TKA. Frailty of the patients was assessed before surgery using the comprehensive geriatric assessment-frailty index and pain was evaluated before and after surgery using the Numerical Rating Scale.

RESULTS

Of the 164 patients including 125 females with a mean age of 71.4 ± 4.6 years, 51 patients were identified as being frail. Patients with chronic post-surgical pain had a significantly higher frailty index than those without chronic post-surgical pain, which was the same in patients with acute post-surgical pain. After adjusting for other confounding factors, frailty was shown to be an independent risk factor for both acute (OR: 13.23, 95% CI 3.73-46.93, P < 0.001) and chronic post-surgical pain (OR: 4.24, 95% CI 1.29-14.00, P = 0.02). The area under the receiver operating characteristic curve for frailty predicting chronic post-surgical pain was 0.73 (P < 0.001, 95% CI 0.65-0.81).

CONCLUSIONS

Our findings demonstrated that preoperative frailty in older patients was a predictor of acute and chronic post-surgical pain after TKA, suggesting that frailty assessment should become a necessary procedure before operations, especially in older patients.

Development and validation of a prediction model for chronic post-surgical pain risk: a single-center prospective study of video-assisted thoracoscopic lung cancer surgery

BACKGROUND

Chronic post-surgical pain (CPSP) is a common complication following video-assisted thoracoscopic surgery (VATS) that significantly impacts the quality of life of patients. Although multiple risk factors have been identified, no systematically validated prediction model exists to guide clinical decision-making.

OBJECTIVES

This study aimed to develop and validate a risk prediction model for CPSP in patients undergoing VATS for lung cancer.

METHODS

This prospective cohort study included clinical data from 400 patients with non-small cell lung cancer who underwent VATS from June 2022 to June 2023. Patients were randomly assigned to a training cohort and an internal test cohort and assessed for sleep quality, psychological status, and pain levels. A nomogram prediction model was established based on variables significantly associated with CPSP in the training cohort. The model was internally validated in the internal test cohort to evaluate its discrimination, calibration, and clinical utility.

RESULTS

Independent risk factors for CPSP included female gender, severe acute pain post-surgery, lymph node dissection, and cold pain sensation, while paravertebral nerve block was identified as a protective factor. The AUC values were 0.878 in training cohort and 0.805 in internal test cohort, respectively, indicating that the model performed well in identifying patients at risk for CPSP. The calibration curves in both cohorts showed a good fit, indicating that the model's predictions were reliable. And the DCA curve showed that using our model to guide decisions resulted in a higher net benefit compared to a strategy of not screening or treating all patients.

CONCLUSION

An effective risk prediction model for CPSP was successfully developed and validated in this study. This model can aid physicians in conducting more accurate assessments of CPSP risk in patients prior to surgery and in offering personalized strategies for managing CPSP.

CLINICAL REGISTRATION NUMBER

Registration website: https://www.chictr.org.cn/ . Registration date: 2022/5/21.

REGISTRATION NUMBER

ChiCTR2200060196.