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Record W7161966099 · doi:10.82308/22774

Risk factors related to chronic neuropathic pain after breast cancer surgery - a prospective cohort study

2020· dissertation· en· W7161966099 on OpenAlexaboutno aff
Navpreet Arora

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsnot available
Fundersnot available
KeywordsNeuropathic painBreast cancerProspective cohort studyLogistic regressionCohort studyBreast surgeryCancerCohort

Abstract

fetched live from OpenAlex

Aim: Chronic neuropathic pain after breast cancer surgery (neuropathic CPBCS) is a significant clinical problem with a prevalence estimate ranging from 8% to 26%. The primary aim of this prospective cohort study was to identify pre, intra and postoperative risk factors related to neuropathic CPBCS at 3 months following breast cancer surgery.Methods: We recruited 268 female breast cancer patients, scheduled to undergo first breast cancer surgery at Segal Cancer Centre, Montreal. Age, preoperative pain, psychological factors, and comorbidities were assessed at baseline. Data regarding type of surgery, axillary status, opioids prescribed for pain management in the recovery room, chemotherapy, and radiotherapy was gathered from patients’ charts after surgery. The information pertaining to acute postoperative pain was collected via telephone interviews using the modified Brief Pain Inventory at seven days after surgery. The participants were also contacted to collect the data on neuropathic CPBCS and DN4 score using short form of Douleur Neuropathique 4 at three months post-surgery. Multivariable logistic and linear regression analyses were performed to assess the factors implicated in neuropathic CPBCS risk, and in the risk of higher DN4 score, at 3 months follow-up.Results: One hundred ninety-nine participants completed the 3-months follow-up. Out of these, 47 (23.62%) participants reported neuropathic CPBCS with a mean DN4 score = 3.53 (SD = 0.72). From all putative risk factors evaluated, only acute pain during movement at 7 days after surgery was associated with an increased risk of neuropathic CPBCS at 3 months follow-up (RR = 1.85, 95%CI: 1.05-3.26). However, acute pain at rest appears to be a protective factor against neuropathic CPBCS (RR = 0.58, 95%CI: 0.34-0.99). Preoperative pain (β = 0.59, 95%CI: 0.04 to 1.14) and acute pain during movement (β = 0.51, 95%CI: 0.10 to 0.92) significantly contributed to higher DN4 score at 3 months after breast cancer surgery. Type of surgery (RR = 1.73, 95%CI: 0.91-3.29) and acute pain during movement (RR = 1.67, 95%CI: 0.99-2.80) were borderline associated with increased risk of neuropathic CPBCS relative to no CPBCS. Acute pain at rest appears to be a protective risk factor neuropathic CPBCS relative to non-neuropathic CPBCS (RR = 0.56, 95%CI: 0.35-0.89).Conclusion: Our study findings suggest that acute pain during movement and preoperative pain should be evaluated and managed meticulously to scale down the burden of neuropathic CPBCS and DN4 score at 3 months following breast cancer 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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.007
GPT teacher head0.254
Teacher spread0.247 · 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 designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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