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Record W4286215858 · doi:10.1097/bpo.0000000000002209

Orthopaedic Surgery Pediatric Sports Medicine: Characterizing Practice Patterns and Subspecialization

2022· article· en· W4286215858 on OpenAlexaff
Andrew M. Block, Matthew T. Eisenberg, Henry B. Ellis, Allison Crepeau, Matthew R. Schmitz, Sasha Carsen

Bibliographic record

VenueJournal of Pediatric Orthopaedics · 2022
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal Disorders and Rehabilitation
Canadian institutionsChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsMedicineSubspecialtySports medicineOrthopedic surgeryDemographicsFamily medicinePediatric surgeryMEDLINEPhysical therapyKnee JointSurgeryDemography

Abstract

fetched live from OpenAlex

BACKGROUND: Pediatric sports medicine is a new and rapidly growing subspecialty within orthopaedic surgery. However, there is very limited literature on the practice of pediatric sports medicine in North America. Therefore, the purpose of this study was to evaluate and describe the current practice patterns of orthopaedic surgeons specializing in pediatric sports medicine. METHODS: An online survey was distributed to orthopaedic surgeons specializing in pediatric sports medicine through the Pediatric Research in Sports Medicine Society. The purpose of the survey was to characterize (1) surgeon demographics, (2) the breakdown of different joint specialization, and (3) the specific procedures for joints that the surgeons specialize in. RESULTS: Responses from 55 orthopaedic surgeons were collected and analyzed. Most respondents considered pediatric sports medicine as the primary focus of their practice (89.1%, n=49/55). The number of fellowships completed was almost evenly split between either a single fellowship (52.7%, n=29/55) or 2 or more (47.3%, n=26/55). The most common combination of fellowships was pediatric orthopaedics and adult sports medicine (32.7%, n=18/55). Most survey respondents had been in practice for <10 years (69.0%, n=38/55) and were affiliated with an academic center (61.8%, n=34/55). On average, 77.5% of the patients treated were <18 years old. The knee joint was the most specialized joint, with 98.2% (n=54/55) respondents reporting that the knee joint constituted ≥25% of their practice. The knee joint constituted a mean of 52.1% of the respondents' overall practice, followed by the shoulder (15.2%), hip (13.9%), ankle (7.5%), elbow (7.1%), and wrist (4.2%). CONCLUSIONS: Pediatric sports medicine practices are variable and have distinct practice patterns in pediatric, orthopaedic, and adult sports practices. In the current study, most surgeons are less than 10 years into practice, affiliated with academic centers, and have typically completed either 1 or 2 fellowships after residency. Surgeons were most commonly specialized in the knee joint and cared for patients <18 years old. LEVEL OF EVIDENCE: Level of evidence IV.

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)0.003
metaresearch head score (Gemma)0.003
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 score0.026
Threshold uncertainty score0.840

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
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)0.0010.000

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 head0.013
GPT teacher head0.267
Teacher spread0.254 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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