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April 1, 2026Open Access

Risk Factors and Nomogram-Based Risk Stratification for Moderate-to-Severe Acute Postsurgical Pain After Open Lumbar Fusion: A Prospective Cohort Study

Key Points

The aim is to identify risk factors for moderate-to-severe acute postsurgical pain after open lumbar fusion and develop a nomogram for prediction.
Enrolled 275 patients undergoing elective open lumbar fusion surgery.
Collected demographic, clinical, and psychological data preoperatively.
Assessed pain intensity daily from postoperative days 1 to 7 using the Numeric Rating Scale.
Performed binary logistic regression to identify independent predictors and construct the nomogram.
Evaluated model performance using AUC and the Hosmer-Lemeshow test.
67.3% of patients experienced moderate-to-severe acute postsurgical pain.
Identified five independent predictors: age ≤ 50 years, educational level ≤ high school, no history of unrelated pain, Pain Catastrophizing Scale score > 12, and no planned postoperative patient-controlled analgesia.
Nomogram showed acceptable discrimination (AUC = 0.705) with sensitivity of 64.3% and specificity of 73.3% at optimal cutoff.
The model demonstrated good calibration according to the Hosmer-Lemeshow test.

Abstract

Objective: To identify factors associated with moderate-to-severe acute postsurgical pain (APSP) during postoperative days 1– 7 (POD1– 7) after open lumbar fusion and to develop a nomogram-based prediction model for early risk stratification. Methods: A total of 275 patients who underwent elective open lumbar fusion surgery at a tertiary hospital in Suzhou, China, from February to September 2023 were enrolled. Demographic, clinical, and psychological data were collected preoperatively. Postoperative pain intensity was assessed daily from POD1 to POD7 using the Numeric Rating Scale (NRS). Moderate-to-severe APSP was defined as any NRS score ≥ 4 during POD1– 7, a clinically meaningful threshold for analgesic intervention. Binary logistic regression was performed to identify independent predictors and construct a nomogram. Model performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC) and the Hosmer-Lemeshow goodness-of-fit test. Results: Of 275 patients, 185 (67.3%) developed moderate-to-severe APSP. Five independent predictors were identified: age ≤ 50 years (OR = 3.640, P = 0.026), educational level ≤ high school (OR = 3.278, P = 0.026), no history of pain unrelated to the primary disease (OR = 2.679, P = 0.040), Pain Catastrophizing Scale score > 12 (OR = 2.054, P = 0.014), and no planned postoperative patient-controlled intravenous analgesia (PCIA) use (OR = 1.751, P = 0.044). The model showed acceptable discrimination (AUC = 0.705), with sensitivity of 64.3% and specificity of 73.3% at the optimal cutoff (0.684). The Hosmer-Lemeshow test was non-significant (P = 0.194), indicating good calibration. Conclusion: Moderate-to-severe APSP was common after open lumbar fusion. The nomogram, based on five readily available predictors, may support early beside risk stratification and individualized analgesic and nursing management. External validation is needed before broader clinical application. Keywords: open lumbar fusion surgery, acute postsurgical pain, risk factors, nomogram, prediction model, nursing

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Wang et al. (Sun,) studied this question.

synapsesocial.com/papers/69ccb7c216edfba7beb89d2d https://doi.org/https://doi.org/10.2147/jpr.s588610

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