ArticleJournal of pain research2023
Development and Validation of a Predictive Model for Chronic Postsurgical Pain After Arthroscopic Rotator Cuff Repair: A Prospective Cohort Study.
Article in Journal of pain research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Development of a clinical prediction model for chronic post-surgical shoulder pain following arthroscopic rotator cuff repair: A prospective cohort study.Shoulder & elbow · 2026Article
- Beyond the Surgery: The Impact of Coping Strategies on Persistent Pain After Rotator Cuff Repair.Journal of clinical medicine · 2024Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Chronic pain management continues to present a significant challenge following arthroscopic shoulder surgery. Our purpose was to detect chronic postsurgical pain (CPSP) in patients who had undergone arthroscopic rotator cuff repair (ARCR) and develop a nomogram capable of predicting the associated risk. Patients and Methods: We collected the demographic and clinical data of 240 patients undergoing ARCR in our hospital from January 2021 to May 2022. The pain level was monitored and evaluated three months after ARCR. LASSO regression was used to screen out pain-predicting factors, which were subsequently used to construct a nomogram. Internal validation was carried out using Bootstrap resampling. The data of 78 patients who underwent ARCR in our hospital from August 2022 to December 2022 were also collected for external verification of the nomogram. The predictive model was evaluated using the receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA). Results: Age, duration of preoperative shoulder pain (DPSP), C-reactive protein (CRP), number of tear tendons, and American Shoulder and Elbow Surgical Score (ASES) were screened by LASSO regression as predictive factors for CPSP. These factors were then used to construct a chronic pain risk nomogram. The area under the curve (AUC) of the predictive and validation models were 0.756 (95% CI: 0.6386-0.8731) and 0.806 (95% CI: 0.6825-0.9291), respectively. Furthermore, the calibration curves and decision curve analysis (DCA) for both models indicated strong performance, affirming the reliability of this predictive model. Conclusion: The CPSP risk model that has been developed exhibits strong predictive capabilities and practical utility. It offers valuable support to clinical healthcare professionals in making informed treatment decisions, reducing the unnecessary use of analgesic drugs, and optimizing the allocation of medical resources.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.