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Record W7032853380

Osgood-Schlatter disease: long-term impact on quality of life

2023· dissertation· en· W7032853380 on OpenAlexaboutno aff

Bibliographic record

VenueHAL AMU · 2023
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPhysical activityHealth related quality of lifePerceived qualityQuality of life (healthcare)
DOInot available

Abstract

fetched live from OpenAlex

Introduction : la maladie d’Osgood-Schlatter est une ostéochondrose de la tubérosité tibiale affectant les adolescents sportifs. L’objectif de cette revue de littérature est d’observer l’impact de cette pathologie sur la qualité de vie à long terme. Méthode : les questionnaires retenus afin d’évaluer la qualité de vie sont le KOOS et le SF-36. Des recherches ont été effectuées sur les bases de données Pubmed, Cochrane Library, Mendeley et Google Scholar. Résultats : six articles ont été inclus dans cette revue de littérature. Le risque de biais a été évalué à l’aide de la grille de lecture Newcastle-Ottawa. Les résultats de ces études montrent une diminution de la qualité de vie dans le groupe porteur de la maladie, en comparaison avec le groupe témoin. Discussion : Le niveau de preuve apporté pour chaque critère de jugement a été évalué à l’aide du système GRADE et varie de faible, pour le KOOS sport et loisirs, à très faible dans les autres domaines de la qualité de vie. L’évaluation à l’aide des critères de Bradford Hill montre une association non-causale entre le diagnostic de la pathologie et une diminution de la qualité de vie à long terme. Conclusion : la maladie d’Osgood-Schlatter semble être négativement associée à la qualité de vie. Cependant, cette diminution varie selon les sous-parties évaluées et peut ne pas dépasser le seuil de Différence Minimale Cliniquement Importante (MCID).

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)0.003
metaresearch head score (Gemma)0.010
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: none
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.081
GPT teacher head0.302
Teacher spread0.221 · 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 routes1
Has abstractyes

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Same venueHAL AMUSame topicDiverse Scientific and Economic StudiesFrench-language works237,207