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Record W6887745777 · doi:10.17605/osf.io/phgxy

Delayed Diagnosis of Developmental Dysplasia of the Hip, Slipped Capital Femoral Epiphysis, and Legg-Calve-Perthes Disease in British Columbia

2023· other· en· W6887745777 on OpenAlexaffabout

Bibliographic record

VenueOpen Science Framework · 2023
Typeother
Languageen
FieldMedicine
TopicHip disorders and treatments
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSlipped capital femoral epiphysisIncidence (geometry)DiseaseLimpDysplasiaKnee painLegg-Calve-Perthes disease

Abstract

fetched live from OpenAlex

Objective: The objective of this scoping review is to understand the extent and type of evidence in relation to factors influencing delayed diagnosis in Slipped capital femoral epiphysis (SCFE), developmental dysplasia of the hip (DDH), and Legg-Calvé-Perthes Disease (LCPD). Introduction: Slipped capital femoral epiphysis (SCFE), developmental dysplasia of the hip (DDH), and Legg-Calvé-Perthes Disease (LCPD) are three of the most common childhood hip disorders (Yagdiran et al., 2020). Incidence rates lie at 660, 0.3-25, and 10 per 100,000 for DDH, SCFE, and LCPD respectively. Incidence rates vary significantly due to several factors including race, ethnicity, country, and socioeconomic status (SES) (Pollet et al., 2017; Loder & Skopelja, 2011; Bratio et al., 2021). The delayed diagnosis of DDH, SCFE, and LCPD has been examined in the past. Previous studies have found that a delayed diagnosis of DDH was more likely in patients with a vertex birth, where non-white, non-english speaking families, from lower income areas, and in areas without a universal screening program (Lindberg et al., 2017; Donnelly et al., 2015). Research examining the time from symptom onset to diagnosis of patients presenting with SCFE has shown a mean delay range of 64 to 181 days in patients with SCFE (Greene et al., 2005; Pihl et al., 2014; Samelis et al., 2020). Delays in diagnosis were associated with the type of healthcare specialist visited, the type of pain patients initially presented with where initial presentations of knee pain were associated with significant delays, type of imaging ordered, and SES (Phil et al., 2014; Hosseinzadeh et al., 2017; Samelis et al., 2020; Kocker et al., 2004). Less information is available on the delayed diagnosis of LCPD. However, one chart review of 57 patients in Hong Kong showed that delayed diagnosis and presentation with painless limb and stiffness were common (Wang et al., 1990). Currently, studies have focused on each disorder individually and there has been a lack of work done at Canadian hospitals to identify potential delays in diagnosis of DDH, SCFE and LCPD. Additionally there is a lack of information on patient perspectives when it comes to the diagnosis of these conditions. Inclusion criteria: We included articles that discussed the incidence of delayed diagnosis of DDH, SCFE or LCPD in pediatric populations. Methods: We will search MEDLINE (Ovid), Embase (Ovid) and CINAHL (EBSCO) for articles published after 1997 with full text available in English. Studies were selected if they discussed DDH, SCFE or LCPD risk factors or incidence of delayed diagnosis. Data extraction will be carried out, with population age, population size, incidence of delay, and risk factors being some major variables we plan to collect. We will then analyze the evidence and present the results.

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)0.004
metaresearch head score (Gemma)0.028
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.156
Threshold uncertainty score0.313

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.028
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0080.013
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0010.001
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 head0.014
GPT teacher head0.285
Teacher spread0.271 · 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
Published2023
Admission routes2
Has abstractyes

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