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Record W4415439012 · doi:10.1302/1358-992x.2025.10.065

OPIOID PRESCRIPTION PATTERNS AND FACTORS AFFECTING PAIN CONTROL AFTER PAEDIATRIC KNEE ARTHROSCOPIC SURGERY: A RETROSPECTIVE COHORT STUDY

2025· article· en· W4415439012 on OpenAlexaff
Lee Benaroch, Simon Martel, James Meterissian, Sami Chergui, Jessica Collins, Thierry Pauyo

Bibliographic record

VenueOrthopaedic Proceedings · 2025
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsWestern University
Fundersnot available
KeywordsRetrospective cohort studyMedical prescriptionPain controlOpioidPopulationKnee painCohort studyCohort

Abstract

fetched live from OpenAlex

Effective post-operative pain management remains a challenge in the pediatric population, and opioids continue to be the mainstay of peri-operative pain management. There is limited literature on opioid prescription patterns and patient and surgical factors that affect postoperative pain in pediatric patients who undergo arthroscopic knee surgery. The objectives of this study were to perform a quantitative evaluation of peri-operative opioid administration and prescription patterns following arthroscopic knee surgery in the pediatric population and identify patient and surgical factors that affect postoperative pain control in the studied population. A retrospective chart review of patients aged 8 to 20 having undergone arthroscopic knee surgery for either meniscal repair and/or anterior cruciate ligament reconstruction over a 48-month period was conducted. Demographic data, discharge prescriptions, surgical information, and pain scores were collected. Patients/parents were called 48 hours post-operatively and asked whether their pain control was adequate or inadequate with the prescribed regimen. Patients were then separated into two groups for the statistical analysis, with the two groups being adequate pain control (pain controlled) or inadequate pain control (pain uncontrolled). One hundred and fifty-two patients (50 male) were available for phone follow-up 48 hours post-operatively and were included in the study. One hundred and twenty-three patients described their pain as controlled (PC), and 29 patients described their pain as uncontrolled (PU). Patients who described their pain as uncontrolled (PU group) were on average younger (p-value = 0.038) and lighter (p-value = 0.010) than the group who reported adequate pain control at follow-up (Table 1). There was no significant difference between the groups in opioid prescription dose at discharge (p-value = 0.065). Gender, tourniquet use, multimodal analgesia, and regional anesthesia did not significantly affect post-operative pain control at 48-hour follow-up. Isolated ACL procedures had the highest percentage of patients reporting adequate pain control at follow-up (88.9%) compared to isolated meniscus (71.4%) and concomitant ACL and meniscus procedures (78.3%) (p-value = 0.303) (Figure 1). In this study, exit opioid prescriptions (mg/dose) did not differ significantly based on age, weight, or surgery type. Identifying the factors that affect postoperative pain control in the pediatric population is essential to establish effective and evidence-based guidelines for opioid prescriptions. Patients may be receiving generic postoperative opioid prescriptions instead of prescriptions individualized to the patient. Higher doses of opioids following surgery were not associated with improved postoperative pain management. Postoperative opioid prescriptions should be tailored to individual patients and procedure types to optimize the dose of opioids prescribed to every patient. Further prospective research is warranted into multimodal pain management strategies targeting better postoperative pain control and decreased opioid use. For any figures or tables, please contact the authors directly.

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)0.004
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.006
GPT teacher head0.237
Teacher spread0.230 · 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 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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