NOVEL VARUS STRESS CT SCAN FOR ELBOW STABILITY ASSESSMENT IN ISOLATED CORONOID FRACTURES
Notice bibliographique
Résumé
Varus posteromedial rotatory instability (VPMRI) is an infrequent injury associated with anteromedial facet fractures. Accurate diagnosis of VPMRI is essential, as untreated, can lead to the rapid progression of devastating post-traumatic arthritis. However, not all isolated coronoid fractures are associated with VPMRI. Stability of the elbow can be challenging to determine clinically in the setting of trauma. When physical examination is inconclusive, examination under anesthesia is generally performed but requires access to the operating room. The goal of this study was to determine whether a novel stress computed tomography (CT) protocol allows for accurate diagnosis of instability in isolated coronoid fractures. We designed a novel varus stress CT scan to assess elbow stability in the setting of isolated coronoid fractures. CT imaging was performed with the affected arm resting on a bolster to allow elbow and forearm hand free, exerting a gravity varus force on the elbow. Coronal, sagittal and axial images were obtained in pronation only in 10 patients, and both in pronation and supination in 4 patients. The study was performed in 2 tertiary care centers. Demographic data, fracture classification according to O'Driscoll classification, and pattern of fracture on CT images were evaluated. CT varus stress views were correlated with fluoroscopic stress examination under anesthesia using varus, valgus, hypersupination and hyperpronation stress. CT varus stress was considered positive if medial collapse into the defect was observed on coronal images, anterior ulnohumeral subluxation or posterior radiocapitellar subluxation on sagittal images, or medial ulnohumeral widening on axial images. Fourteen patients, 8 males and 6 females, were included in this retrospective case series with a mean age of 47 years (range 20–63). Subtype 2 anteromedial facet fractures based on O'Driscoll classification was the most common fracture pattern observed in 10/14 patients. Other fracture patterns included: subtype 3 anteromedial facet (n=3), and subtype 1 basal coronoid (n=1). Two patients were treated non operatively with an overhead rehabilitation protocol while twelve patients were treated surgically. Varus CT scan yielded a sensitivity of 64% and a specificity of 67%. Positive predictive value and negative predictive value were respectively 88% and 33%. Varus stress CT scan can demonstrate instability that may be overlooked on clinical examination or absent on standard elbow CT scan and could potentially avoid the need for examination under anesthesia in the operating room. However, the specificity and NPV still remained low. This could be related to inappropriate patient positioning as the forearm should not be resting on the table and the patient needs to be able to tolerate a gravity stress on the elbow. Increased flexion position during imaging could also lead to reduction of an otherwise unstable joint. Potential solutions include supervised positioning by musculoskeletal radiologists. Unfortunately, we had low number of cases with both supination and pronation to determine if the stability is more pronounced in one position of forearm rotation over the other and this needs to be further investigated with larger cohorts.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».