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Record W3034744030 · doi:10.2106/jbjs.rvw.19.00154

Factors Predictive of Prolonged Postoperative Narcotic Usage Following Orthopaedic Surgery

2020· review· en· W3034744030 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJBJS Reviews · 2020
Typereview
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineOpioidOxycodoneRelative riskCINAHLNarcoticOrthopedic surgeryChronic painMEDLINESubspecialtyFibromyalgiaInternal medicineAnesthesiaPhysical therapySurgeryPsychiatryConfidence interval

Abstract

fetched live from OpenAlex

BACKGROUND: The purpose of this comprehensive review was to investigate risk factors associated with prolonged opioid use after orthopaedic procedures. A comprehensive review of the opioid literature may help to better guide preoperative management of expectations as well as opioid-prescribing practices. METHODS: A systematic review of all studies pertaining to opioid use in relation to orthopaedic procedures was conducted using the MEDLINE, Embase, and CINAHL databases. Data from studies reporting on postoperative opioid use at various time points were collected. Opioid use and risk of prolonged opioid use were subcategorized by subspecialty, and aggregate data for each category were calculated. RESULTS: There were a total of 1,445 eligible studies, of which 45 met inclusion criteria. Subspecialties included joint arthroplasty, spine, trauma, sports, and hand surgery. A total of 458,993 patients were included, including 353,330 (77%) prolonged postoperative opioid users and 105,663 (23%) non-opioid users. Factors associated with prolonged postoperative opioid use among all evaluated studies included body mass index (BMI) of ≥40 kg/m (relative risk [RR], 1.06 to 2.32), prior substance abuse (RR, 1.08 to 3.59), prior use of other medications (RR, 1.01 to 1.46), psychiatric comorbidities (RR, 1.08 to 1.54), and chronic pain conditions including chronic back pain (RR, 1.01 to 10.90), fibromyalgia (RR, 1.01 to 2.30), and migraines (RR, 1.01 to 5.11). Age cohorts associated with a decreased risk of prolonged postoperative opioid use were those ≥31 years of age for hand procedures (RR, 0.47 to 0.94), ≥50 years of age for total hip arthroplasty (RR, 0.70 to 0.80), and ≥70 years of age for total knee arthroplasty (RR, 0.40 to 0.80). Age cohorts associated with an increased risk of prolonged postoperative opioid use were those ≥50 years of age for sports procedures (RR, 1.11 to 2.57) or total shoulder arthroplasty (RR, 1.26 to 1.40) and those ≥70 years of age for spine procedures (RR, 1.61). Identified risk factors for postoperative use were similar across subspecialties. CONCLUSIONS: We provide a comprehensive review of the various preoperative and postoperative risk factors associated with prolonged opioid use after elective and nonelective orthopaedic procedures. Increased BMI, prior substance abuse, psychiatric comorbidities, and chronic pain conditions were most commonly associated with prolonged postoperative opioid use. Careful consideration of elective surgical intervention for painful conditions and perioperative identification of risk factors within each patient's biopsychosocial context will be essential for future modulation of physician opioid-prescribing patterns. LEVEL OF EVIDENCE: Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.920
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0100.005
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.104
GPT teacher head0.366
Teacher spread0.262 · 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