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Record W4318912712 · doi:10.1097/bpo.0000000000002344

Variability in Pain Management Practices for Pediatric Anterior Cruciate Ligament Reconstruction

2023· article· en· W4318912712 on OpenAlexaff
K. John Wagner, Jennifer J. Beck, Sasha Carsen, Allison Crepeau, Aristides I. Cruz, Henry B. Ellis, Stephanie W. Mayer, Emily Niu, Andrew T. Pennock, Zachary S. Stinson, Curtis VandenBerg, Matthew D. Ellington

Bibliographic record

VenueJournal of Pediatric Orthopaedics · 2023
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsMedicineAnterior cruciate ligamentAnterior cruciate ligament reconstructionAnterior Cruciate Ligament InjuriesPain managementOrthodonticsPhysical therapyPhysical medicine and rehabilitationSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: The opioid epidemic in the United States is a public health crisis. Pediatric orthopaedic surgeons must balance adequate pain management with minimizing the risk of opioid misuse or dependence. There is limited data available to guide pain management for anterior cruciate ligament reconstruction (ACLR) in the pediatric population. The purpose of this study was to survey current pain management practices for ACLR among pediatric orthopaedic surgeons. METHODS: A cross-sectional survey study was conducted, in which orthopaedic surgeons were asked about their pain management practices for pediatric ACLR. The voluntary survey was sent to members of the Pediatric Orthopaedic Society of North America. Inclusion criteria required that the surgeon perform anterior cruciate ligament repair or reconstruction on patients under age 18. Responses were anonymous and consisted of surgeon demographics, training, practice, and pain management strategies. Survey data were assessed using descriptive statistics. RESULTS: Of 64 included responses, the average age of the survey respondent was 48.9 years, 84.4% were males, and 31.3% practiced in the southern region of the United States. Preoperative analgesia was utilized by 39.1%, 90.6% utilized perioperative blocks, and 89.1% prescribed opioid medication postoperatively. For scheduled non-narcotic medications postoperatively 82.8% routinely advocated and 93.8% recommended cryotherapy postoperatively.Acetaminophen was the most used preoperative medication (31.3%), the most common perioperative block was an adductor canal block (81.0%), and the most common postoperative analgesic medication was ibuprofen (60.9%). Prior training or experience was more frequently reported than published research as a primary factor influencing pain management protocols. CONCLUSIONS: Substantial variability exists in pain management practices in pediatric ACLR. There is a need for more evidence-based practice guidelines regarding pain management. LEVEL OF EVIDENCE: Level V.

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)0.016
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.138
Threshold uncertainty score0.664

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.002
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 integrity0.0000.000
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 head0.029
GPT teacher head0.300
Teacher spread0.272 · 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.

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".

Quick stats

Citations4
Published2023
Admission routes1
Has abstractyes

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