A Novel Presurgical Risk Prediction Model for Chronic Post-Surgical Pain in Adults Undergoing Surgical Procedures: Development and Internal Validation of the P4-Prevoque Questionnaire [PERISCOPE Trial]
Davina Wildemeersch,1,2 Eva Wauters,3 Ella Roelant,3 Iris Verhaegen,3 Gudrun R De Clerck,1 Rowan Dankerlui,4 Vera Saldien,2,4 Guy H Hans1,2 1Multidisciplinary Pain Center, Antwerp University Hospital, Edegem, Belgium; 2Laboratory for Pain Research, ASTARC, University of Antwerp, Wilrijk, Belgium; 3C...
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Dove Medical Press
2025-07-01
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| author | Wildemeersch D Wauters E Roelant E Verhaegen I De Clerck GR Dankerlui R Saldien V Hans GH |
| author_facet | Wildemeersch D Wauters E Roelant E Verhaegen I De Clerck GR Dankerlui R Saldien V Hans GH |
| author_sort | Wildemeersch D |
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| description | Davina Wildemeersch,1,2 Eva Wauters,3 Ella Roelant,3 Iris Verhaegen,3 Gudrun R De Clerck,1 Rowan Dankerlui,4 Vera Saldien,2,4 Guy H Hans1,2 1Multidisciplinary Pain Center, Antwerp University Hospital, Edegem, Belgium; 2Laboratory for Pain Research, ASTARC, University of Antwerp, Wilrijk, Belgium; 3Clinical Trial Center, Antwerp University Hospital, Edegem, Belgium; 4Department of Anesthesiology, Antwerp University Hospital, Edegem, BelgiumCorrespondence: Davina Wildemeersch, Multidisciplinary pain center, Antwerp University Hospital, Drie Eikenstraat 655, Edegem, 2650, Belgium, Email davina.wildemeersch@uza.beBackground: Despite extensive research efforts into risk factors and management strategies, the prevalence of chronic post-surgical pain (CPSP) remains high. Additionally, the treatment of chronic pain is often complex, with outcomes frequently falling short of expectations. As chronic pain continues to be a significant global problem affecting medical, psychological and socioeconomic aspects, and with the growing number of surgeries performed, there is a pressing need for an early, comprehensive model to predict CPSP. Various models have been created in recent years to predict postsurgical pain. However, to date, no generalizable CPSP risk stratification model independent for type of surgery is extensively applied. This study aims to create a simple and effective model to predict presurgically the likelihood of CPSP occurring three months after elective surgery.Methods: An observational, single center, pragmatic, pilot cohort study [PERISCOPE] in adult elective surgery patients was conducted at the Antwerp University Hospital, Belgium, between December 2022 and September 2023. More than 40 different types of surgeries in 11 disciplines were included. CPSP was defined as persistent pain in the surgical area, reported by the patient three months after surgery on a 11-level numeric rating scale. Biopsychosocial candidate variables, including health-related quality of life and psychosocial concerns, were identified based on clinical knowledge and literature review.Results: The final study population at our tertiary hospital included 415 patients of which 19.3% reported CPSP. Four predictors: preoperative pain intensity, education level, type of surgery and concerns about the planned surgery were identified leading to the best predictive model (P4-Prevoque™) in terms of area under the curve (0.81; 95% confidence interval [0.76, 0.87]) and significance.Conclusion: The P4-Prevoque™ questionnaire is able to identify presurgically a major part of CPSP patients with a sensitivity of 74%, and specificity of 77%. Using four straightforward and readily available questions, the proposed user-friendly prediction model has the strength to be easily implemented in daily practice. Future research should focus on its further validation.Trial Registration: ClinicalTrials.gov NCT05526976, Ethics Committee B3002022000112.Keywords: chronic post-surgical pain, clinical prediction model, perioperative care, postoperative pain, preoperative evaluation, recovery after surgery |
| format | Article |
| id | doaj-art-928d619f542e49a087f74c9ab55055e6 |
| institution | Kabale University |
| issn | 1178-7090 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Dove Medical Press |
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| series | Journal of Pain Research |
| spelling | doaj-art-928d619f542e49a087f74c9ab55055e62025-08-20T03:30:23ZengDove Medical PressJournal of Pain Research1178-70902025-07-01Volume 18Issue 134153428104543A Novel Presurgical Risk Prediction Model for Chronic Post-Surgical Pain in Adults Undergoing Surgical Procedures: Development and Internal Validation of the P4-Prevoque Questionnaire [PERISCOPE Trial]Wildemeersch D0Wauters E1Roelant E2Verhaegen I3De Clerck GR4Dankerlui R5Saldien V6Hans GH7Multidisciplinary pain center, Laboratory for Pain ResearchClinical Trial CenterClinical Trial CenterClinical Trial CenterMultidisciplinary pain centerDepartment of AnesthesiologyDepartment of Anesthesiology, Laboratory for Pain ResearchMultidisciplinary pain center, Laboratory for Pain ResearchDavina Wildemeersch,1,2 Eva Wauters,3 Ella Roelant,3 Iris Verhaegen,3 Gudrun R De Clerck,1 Rowan Dankerlui,4 Vera Saldien,2,4 Guy H Hans1,2 1Multidisciplinary Pain Center, Antwerp University Hospital, Edegem, Belgium; 2Laboratory for Pain Research, ASTARC, University of Antwerp, Wilrijk, Belgium; 3Clinical Trial Center, Antwerp University Hospital, Edegem, Belgium; 4Department of Anesthesiology, Antwerp University Hospital, Edegem, BelgiumCorrespondence: Davina Wildemeersch, Multidisciplinary pain center, Antwerp University Hospital, Drie Eikenstraat 655, Edegem, 2650, Belgium, Email davina.wildemeersch@uza.beBackground: Despite extensive research efforts into risk factors and management strategies, the prevalence of chronic post-surgical pain (CPSP) remains high. Additionally, the treatment of chronic pain is often complex, with outcomes frequently falling short of expectations. As chronic pain continues to be a significant global problem affecting medical, psychological and socioeconomic aspects, and with the growing number of surgeries performed, there is a pressing need for an early, comprehensive model to predict CPSP. Various models have been created in recent years to predict postsurgical pain. However, to date, no generalizable CPSP risk stratification model independent for type of surgery is extensively applied. This study aims to create a simple and effective model to predict presurgically the likelihood of CPSP occurring three months after elective surgery.Methods: An observational, single center, pragmatic, pilot cohort study [PERISCOPE] in adult elective surgery patients was conducted at the Antwerp University Hospital, Belgium, between December 2022 and September 2023. More than 40 different types of surgeries in 11 disciplines were included. CPSP was defined as persistent pain in the surgical area, reported by the patient three months after surgery on a 11-level numeric rating scale. Biopsychosocial candidate variables, including health-related quality of life and psychosocial concerns, were identified based on clinical knowledge and literature review.Results: The final study population at our tertiary hospital included 415 patients of which 19.3% reported CPSP. Four predictors: preoperative pain intensity, education level, type of surgery and concerns about the planned surgery were identified leading to the best predictive model (P4-Prevoque™) in terms of area under the curve (0.81; 95% confidence interval [0.76, 0.87]) and significance.Conclusion: The P4-Prevoque™ questionnaire is able to identify presurgically a major part of CPSP patients with a sensitivity of 74%, and specificity of 77%. Using four straightforward and readily available questions, the proposed user-friendly prediction model has the strength to be easily implemented in daily practice. Future research should focus on its further validation.Trial Registration: ClinicalTrials.gov NCT05526976, Ethics Committee B3002022000112.Keywords: chronic post-surgical pain, clinical prediction model, perioperative care, postoperative pain, preoperative evaluation, recovery after surgeryhttps://www.dovepress.com/a-novel-presurgical-risk-prediction-model-for-chronic-post-surgical-pa-peer-reviewed-fulltext-article-JPRchronic post-surgical painclinical prediction modelperioperative carepostoperative painpreoperative evaluationrecovery after surgery |
| spellingShingle | Wildemeersch D Wauters E Roelant E Verhaegen I De Clerck GR Dankerlui R Saldien V Hans GH A Novel Presurgical Risk Prediction Model for Chronic Post-Surgical Pain in Adults Undergoing Surgical Procedures: Development and Internal Validation of the P4-Prevoque Questionnaire [PERISCOPE Trial] Journal of Pain Research chronic post-surgical pain clinical prediction model perioperative care postoperative pain preoperative evaluation recovery after surgery |
| title | A Novel Presurgical Risk Prediction Model for Chronic Post-Surgical Pain in Adults Undergoing Surgical Procedures: Development and Internal Validation of the P4-Prevoque Questionnaire [PERISCOPE Trial] |
| title_full | A Novel Presurgical Risk Prediction Model for Chronic Post-Surgical Pain in Adults Undergoing Surgical Procedures: Development and Internal Validation of the P4-Prevoque Questionnaire [PERISCOPE Trial] |
| title_fullStr | A Novel Presurgical Risk Prediction Model for Chronic Post-Surgical Pain in Adults Undergoing Surgical Procedures: Development and Internal Validation of the P4-Prevoque Questionnaire [PERISCOPE Trial] |
| title_full_unstemmed | A Novel Presurgical Risk Prediction Model for Chronic Post-Surgical Pain in Adults Undergoing Surgical Procedures: Development and Internal Validation of the P4-Prevoque Questionnaire [PERISCOPE Trial] |
| title_short | A Novel Presurgical Risk Prediction Model for Chronic Post-Surgical Pain in Adults Undergoing Surgical Procedures: Development and Internal Validation of the P4-Prevoque Questionnaire [PERISCOPE Trial] |
| title_sort | novel presurgical risk prediction model for chronic post surgical pain in adults undergoing surgical procedures development and internal validation of the p4 prevoque questionnaire periscope trial |
| topic | chronic post-surgical pain clinical prediction model perioperative care postoperative pain preoperative evaluation recovery after surgery |
| url | https://www.dovepress.com/a-novel-presurgical-risk-prediction-model-for-chronic-post-surgical-pa-peer-reviewed-fulltext-article-JPR |
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