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Record W7066785766

Identification of Presurgical Risk Factors for the Development of Chronic Postsurgical Pain in Adults: A Comprehensive Umbrella Review

2024· article· en· W7066785766 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2024
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsnot available
Fundersnot available
KeywordsPerioperativeRehabilitationChronic painPain medicineIdentification (biology)MEDLINEPain management
DOInot available

Abstract

fetched live from OpenAlex

Beate C Sydora,1 Lindsay Jane Whelan,1,2 Benjamin Abelseth,2 Gurpreet Brar,3 Sumera Idris,3 Rachel Zhao,4 Ashley Jane Leonard,4 Brittany N Rosenbloom,5 Hance Clarke,6 Joel Katz,6,7 Sanjay Beesoon,1 Nivez Rasic2,8 1Department of Surgery Strategic Clinical Network, Alberta Health Services, Edmonton, AB, Canada; 2Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; 3Health Systems Knowledge and Evaluation, Alberta Health Services, Edmonton, AB, Canada; 4Knowledge Resource Service, Alberta Health Services, Edmonton, AB, Canada; 5Toronto Academic Pain Medicine Institute, Toronto, ON, Canada; 6Department of Anesthesia and Pain Management, Toronto General Hospital, UHN, Toronto, ON, Canada; 7Department of Psychology, York University, Toronto, ON, Canada; 8Department of Anesthesiology, Perioperative & Pain Medicine, University of Calgary, Calgary, AB, CanadaCorrespondence: Nivez Rasic, Department of Anesthesiology, Perioperative and Pain Medicine, University of Calgary, Medical Lead, Vi Riddell Pain & Rehabilitation Program, Acute Pain Lead, Alberta Pain Strategy, Alberta Children’s Hospital, 28 Oki Drive NW, Calgary, AB, T3B 6A8, Canada, Tel +403-955-7810, Email Nivez.Rasic@albertahealthservices.ca Sanjay Beesoon, Assistant Scientific Director, Surgery Strategic Clinical Network, Alberta Health Services, 02-048 South Tower, Seventh Street Plaza, 10030 107 St NW, Edmonton, AB, T5J 3E4, Canada, Tel +780-735-1682 ; +780-218-4786, Email Sanjay.Beesoon@albertahealthservices.caPurpose: Risk factors for the development of chronic postsurgical pain (CPSP) have been reported in primary studies and an increasing number of reviews. The objective of this umbrella review was to compile and understand the published presurgical risk factors associated with the development of CPSP for various surgery types.Methods: Six databases were searched from January 2000 to June 2023 to identify meta-analyses, scoping studies, and systematic reviews investigating presurgical CPSP predictors in adult patients. Articles were screened by title/abstract and subsequently by full text by two independent reviewers. The selected papers were appraised for their scientific quality and validity. Data were extracted and descriptively analyzed.Results: Of the 2344 retrieved articles, 36 reviews were selected for in-depth scrutiny. The number of primary studies in these reviews ranged from 4 to 317. The surgery types assessed were arthroplasty (n = 13), spine surgery (n = 8), breast surgery (n = 4), shoulder surgery (n = 2), thoracic surgery (n = 2), and carpal tunnel syndrome (n = 1). One review included a range of orthopedic surgeries; six reviews included a variety of surgeries. A total of 39 presurgical risk factors were identified, some of which shared the same defining tool. Risk factors were themed into six broad categories: psychological, pain-related, health-related, social/lifestyle-related, demographic, and genetic. The strength of evidence for risk factors was inconsistent across different reviews and, in some cases, conflicting. A consistently high level of evidence was found for preoperative pain, depression, anxiety, and pain catastrophizing.Conclusion: This umbrella review identified a large number of presurgical risk factors which have been suggested to be associated with the development of CPSP after various surgeries. The identification of presurgical risk factors is crucial for the development of screening tools to predict CPSP. Our findings will aid in designing screening tools to better identify patients at risk of developing CPSP and inform strategies for prevention and treatment.Plain Language Summary: Chronic postsurgical pain (CPSP) is pain experienced predominantly at the surgical site for longer than 3 months after a surgical procedure. Depending on surgery type, it can affect between 10 and 80% of people undergoing major surgeries, which may have negative effects such as a lower quality of life, disability, and persistent opioid use. Targeted identification and management of at risk patients in the presurgical phase may decrease the risk of CPSP. This umbrella review generated a list of potential risk factors for CPSP from evidence-based reviews of the current literature.Thirty-nine presurgical risk factors were identified in this review. Risk factors are divided into six broad categories: psychological, pain-related, health-related, demographic, genetic, and social/lifestyle-related. Although the strength of evidence for individual risk factors varied across reviews, risk factors in the psychological category consistently showed a strong impact on the development of CPSP.It is vital to understand which individuals are vulnerable and at risk for CPSP. The findings of this umbrella review will aid in designing screening tools to identify surgical candidates at risk. Some risk factors, such as genetics, cannot be altered. However, many identified risk factors are modifiable and may inform strategies for the prevention and treatment of CPSP using screening tools. Our findings may guide future research to consider an in-depth analysis of risk factor characterization to group modifiable presurgical risk factors. At risk patients will be offered psychological, physical, and pharmacological treatments accordingly to mitigate their risk of developing CPSP and ultimately improve patient outcomes in surgery.Keywords: chronic postsurgical pain, risk factors, predictors, umbrella review, surgery

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.193
GPT teacher head0.519
Teacher spread0.326 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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