Abstract
BACKGROUND: Enhanced Recovery After Surgery (ERAS) is a multidisciplinary, evidence-based protocol designed to accelerate patient recovery after surgery. While applied to total knee arthroplasty (TKA) to optimize perioperative care, a significant risk of early postoperative pain persists. This study aims to investigate the current status and identify key high-risk factors for early pain in TKA patients under ERAS, facilitating the development of targeted strategies to alleviate pain and enhance recovery. METHODS: We conducted a retrospective analysis of 183 patients who underwent TKA under the ERAS protocol at our hospital. On postoperative day 3, patients were categorized using the Numerical Rating Scale (NRS): those with NRS scores ≤3 formed the mild pain group (n=132), and those with scores >3 constituted the moderate-to-severe pain group (n=51). Clinical data were compared, and univariate along with multivariate logistic regression analyses were employed to identify independent risk factors for early postoperative pain. RESULTS: Of the 183 patients, 51 (27.87%) experienced moderate-to-severe pain. Comparative analysis revealed significant differences between the two groups in intraoperative tourniquet time, preoperative Hamilton Anxiety Scale (HAMA) score, preoperative quadriceps thickness, and preoperative Knee Society Score (KSS). Multivariate analysis confirmed these four factors as independent risk factors. A predictive nomogram model built on these factors demonstrated good calibration and a high predictive value, with an Area Under the Curve (AUC) of 0.892. Furthermore, NRS scores showed a positive correlation with tourniquet time and HAMA scores, and a negative correlation with quadriceps thickness and KSS scores. CONCLUSION: A notable proportion of TKA patients under ERAS still experience moderate-to-severe early postoperative pain. This pain is independently associated with longer tourniquet time, higher preoperative anxiety, thinner quadriceps, and lower preoperative KSS. These factors are valuable for predicting pain, enabling early targeted interventions to minimize its occurrence and promote recovery.