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Record W4300981863 · doi:10.1001/jama.2022.16844

Effect of a Postoperative Multimodal Opioid-Sparing Protocol vs Standard Opioid Prescribing on Postoperative Opioid Consumption After Knee or Shoulder Arthroscopy

2022· article· en· W4300981863 on OpenAlexaffabout
Andrew Duong, Andrea K. Ponniah, Caitlin VanDeCapelle, Franca Mossuto, Eric Romeril, Steve Phillips, Herman Johal, Jamal Al‐Asiri, Daniel Tushinski, Thomas J. Wood, Devin Peterson, Matthew Denkers, Anthony Adili, Vickas Khanna, Jaydeep Moro, Imad Kashir, Grace Mwakijele, Darren Young Shing, Aaron Gazendam, Seper Ekhtiari, Nolan S. Horner, Nicole Simunovic, Moin Khan, Darren de, Kim Madden, Olufemi R. Ayeni

Bibliographic record

VenueJAMA · 2022
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineKnee arthroscopyOpioidAnesthesiaArthroscopySurgeryInternal medicine

Abstract

fetched live from OpenAlex

Importance: In arthroscopic knee and shoulder surgery, there is growing evidence that opioid-sparing protocols may reduce postoperative opioid consumption while adequately addressing patients' pain. However, there are a lack of prospective, comparative trials evaluating their effectiveness. Objective: To evaluate the effect of a multimodal, opioid-sparing approach to postoperative pain management compared with the current standard of care in patients undergoing arthroscopic shoulder or knee surgery. Design, Setting, and Participants: This randomized clinical trial was performed at 3 clinical sites in Ontario, Canada, and enrolled 200 patients from March 2021 to March 2022 with final follow-up completed in April 2022. Adult patients undergoing outpatient arthroscopic shoulder or knee surgery were followed up for 6 weeks postoperatively. Interventions: The opioid-sparing group (100 participants randomized) received a prescription of naproxen, acetaminophen (paracetamol), and pantoprazole; a limited rescue prescription of hydromorphone; and a patient educational infographic. The control group (100 participants randomized) received the current standard of care determined by the treating surgeon, which consisted of an opioid analgesic. Main Outcomes and Measures: The primary outcome was postoperative oral morphine equivalent (OME) consumption at 6 weeks after surgery. There were 5 secondary outcomes, including pain, patient satisfaction, opioid refills, quantity of OMEs prescribed at the time of hospital discharge, and adverse events at 6 weeks all reported at 6 weeks after surgery. Results: Among the 200 patients who were randomized (mean age, 43 years; 73 women [38%]), 193 patients (97%) completed the trial; 98 of whom were randomized to receive standard care and 95 the opioid-sparing protocol. Patients in the opioid-sparing protocol consumed significantly fewer opioids (median, 0 mg; IQR, 0-8.0 mg) than patients in the control group (median, 40.0 mg; IQR, 7.5-105.0; z = -6.55; P < .001). Of the 5 prespecified secondary end points, 4 showed no significant difference. The mean amount of OMEs prescribed was 341.2 mg (95% CI, 310.2-372.2) in the standard care group and 40.4 mg (95% CI, 39.6-41.2) in the opioid-sparing group (mean difference, 300.8 mg; 95% CI, 269.4-332.3; P < .001). There was no significant difference in adverse events at 6 weeks (2 events [2.1%] in the standard care group vs 3 events [3.2%] in the opioid-sparing group), but more patients reported medication-related adverse effects in the standard care group (32% vs 19%, P = .048). Conclusions and Relevance: Among patients who underwent arthroscopic knee or shoulder surgery, a multimodal opioid-sparing postoperative pain management protocol, compared with standard opioid prescribing, significantly reduced postoperative opioid consumption over 6 weeks. Trial Registration: ClinicalTrials.gov Identifier: NCT04566250.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.527
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.326
Teacher spread0.310 · 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 designBench or experimental
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".

Quick stats

Citations79
Published2022
Admission routes2
Has abstractyes

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