Clinical and Topographic Screening for Scoliosis in Children Participating in Routine Sports: A Prevalence and Accuracy Study in a Spanish Population
Notice bibliographique
Résumé
Background: Idiopathic scoliosis (IS) is a common spinal deformity affecting 0.5% to 5.2% of children worldwide, with a higher reported range in Spain (0.7–7.5%). Early detection through screening is crucial to prevent the progression of mild cases to severe deformities. Clinical methods such as the ADAM test and trunk rotation angle (TRA) are widely used, but the development of three-dimensional (3D) surface topography (ST) technologies has opened new avenues for non-invasive screening. The objectives of this study were (1) to perform clinical and ST-based scoliosis screening in a sample of healthy children involved in club sports, (2) to estimate the agreement between clinical and ST screening methods, (3) to describe the prevalence of scoliosis by sport, sex, and age, and (4) to evaluate the diagnostic performance of both screening approaches using available radiographs as a reference standard. Methods: A total of 343 children (58.7% males, 41.3% females; mean age 11.69 ± 2.05 years) were screened using both clinical and ST methods. Clinical screening included the ADAM test and TRA measurement, while ST screening was performed using BackSCNR®, a markerless 3D scanning software. The children with positive screening results were recommended to obtain radiographs to confirm the diagnosis. Kappa agreement, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated for both screening modalities using radiographic results as the gold standard. Results: The prevalence of scoliosis was 3.2% (n = 11) based on radiographic confirmation. The prevalence by sport was highest in swimming (17.6%), with minimal differences by sex (males 3.6%, females 2.5%). The clinical screening showed a sensitivity of 73%, specificity of 97%, PPV of 47%, NPV of 99%, and accuracy of 96%. The ST screening showed a sensitivity of 36%, specificity of 99%, PPV of 80%, NPV of 97%, and accuracy of 97%. The kappa values indicate a moderate influence of chance for both methods (clinical κ = 0.55; ST κ = 0.48). The balanced accuracy was 84% for the clinical screening and 68% for the ST screening. Conclusions: The clinical screening method showed superior sensitivity and balanced accuracy compared to ST screening. However, ST screening showed higher specificity and PPV, suggesting its potential as a complementary tool to reduce the high positive predictive value. These results highlight the importance of combining screening methods to improve the accuracy of the early detection of IS in physically active children, with the radiographic confirmation of the positive screened cases remaining essential for accurate diagnosis.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».