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Record W4206717718 · doi:10.1177/17585732211070193

The role of preoperative opioid use in shoulder surgery—A systematic review

2022· review· en· W4206717718 on OpenAlexaff
Omar A. Al-Mohrej, Carlos Prada, Kim Madden, Harsha Shanthanna, Timothy Leroux, Moin Khan

Bibliographic record

VenueShoulder & Elbow · 2022
Typereview
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsImpactUniversity of TorontoMcMaster University
Fundersnot available
KeywordsMedicineOpioidCINAHLOrthopedic surgeryMEDLINEAnesthesiaShoulder surgerySurgeryInternal medicine

Abstract

fetched live from OpenAlex

Background: Emerging evidence suggests preoperative opioid use may increase the risk of negative outcomes following orthopedic procedures. This systematic review evaluated the impact of preoperative opioid use in patients undergoing shoulder surgery with respect to preoperative clinical outcomes, postoperative complications, and postoperative dependence on opioids. Methods: EMBASE, MEDLINE, CENTRAL, and CINAHL were searched from inception to April, 2021 for studies reporting preoperative opioid use and its effect on postoperative outcomes or opioid use. The search, data extraction and methodologic assessment were performed in duplicate for all included studies. Results: Twenty-one studies with a total of 257,301 patients were included in the final synthesis. Of which, 17 were level III evidence. Of those, 51.5% of the patients reported pre-operative opioid use. Fourteen studies (66.7%) reported a higher likelihood of opioid use at follow-up among those used opioids preoperatively compared to preoperative opioid-naïve patients. Eight studies (38.1%) showed lower functional measurements and range of motion in opioid group compared to the non-opioid group post-operatively. Conclusion: Preoperative opioid use in patients undergoing shoulder surgeries is associated with lower functional scores and post-operative range of motion. Most concerning is preoperative opioid use may predict increased post-operative opioid requirements and potential for misuse in patients. Level of evidence: Level IV, Systematic review.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.571
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.056
GPT teacher head0.348
Teacher spread0.292 · 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 teacher head, not a consensus.

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

Citations11
Published2022
Admission routes1
Has abstractyes

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