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Record W4280519023 · doi:10.1177/2325967121s00497

The Effects of The Covid-19 Pandemic on Pediatric Orthopaedic Sports Medicine & Arthroscopy: Practice Implications, and The Management and Triaging of Surgical Cases

2022· article· en· W4280519023 on OpenAlexaff
Sasha Carsen, Aristides I. Cruz, Henry B. Ellis, Curtis VandenBerg, Stephanie W. Mayer, Emily Niu, Jennifer J. Beck

Bibliographic record

VenueOrthopaedic Journal of Sports Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsMedicineSports medicineVignettePandemicArthroscopyMeniscusPhysical therapyCoronavirus disease 2019 (COVID-19)General surgerySurgeryDiseasePathology

Abstract

fetched live from OpenAlex

Background: The COVID-19 pandemic has had a significant impact on pediatric sports medicine patients. Many surgeons found themselves simultaneously managing surgical pathology, concerns of exposure, and limited resources. This led to challenging decisions regarding relative patient and case urgency. Purpose: 1. Define through expert opinion the relative urgency of prototypical pediatric arthroscopic surgical cases 2. Define current practices regarding pre-surgical testing and findings relevant to the recent, current, and potentially forthcoming challenges inherent to the COVID-19 pandemic. We further gathered information regarding variability of current practices and access to resources. Methods: A mixed-methods survey was performed of the POSNA membership, specific to surgeons identifying as sub-specialized in pediatric sports medicine. A clinical vignette style survey was developed by the POSNA QSVI: Sports Committee. Cases included patients with a: meniscal tear, a bucket handle meniscus tear, ACL tear, unstable osteochondritis dissecans (OCD) lesion of the knee, locked knee due to a loose body, OCD of the capitellum, recurrent and primary shoulder instability, traumatic patellar instability with a loose osteochondral fragment, and a patient with a symptomatic discoid meniscus. The survey further asked how resource limitations could impact surgical decision-making, and how pre-operative testing might impact surgical timing and decisions. Information regarding personal and institutional experiences and limitations during the first 6 months of the pandemic was also collected. Results: There were 119 survey respondents, of whom 54 met inclusion criteria. Seventy-five percent were primarily based at a university or academic hospital. Almost 56% of respondents had all scheduled cases cancelled for 4-7 weeks, 22% for 8-11 weeks, and 17% were shut down for more than 12 weeks. Forty-two percent followed guidance from an orthopaedic governing body, most commonly national orthopaedic organizations. There was significant variation in pre-operative testing protocols, ranging from screening questions to PCR testing and rapid testing. Triaging factors chosen by respondents for determining relative urgency, in order, were: Diagnosis, severity of symptoms/pathology, duration of symptoms, age, activity level, originally planned surgical date, and patient request. Each clinical vignette elicited variability in responses, but each had clear leaders in opinion regarding relative urgency. Most cases had more than 2/3 of respondents in relative agreement with respect to urgency. Conclusion: This study provides comparative details of the challenges and resource limitations experienced in pediatric sports medicine, and provides much-needed sub-specialty opinions on standards with respect to relative urgency and triaging for related cases. These experiences and opinions may be of benefit when advocating for patient access and care.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.053
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.053
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.036
GPT teacher head0.369
Teacher spread0.334 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2022
Admission routes1
Has abstractyes

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