MRI as the optimal imaging modality for assessment and management of osteochondral fractures and loose bodies following traumatic patellar dislocation: a systematic review
Notice bibliographique
Résumé
PURPOSE: To assess the imaging modalities used for diagnosis, as well as the management decisions of patients with osteochondral fractures (OCF) and loose bodies following traumatic patellar dislocation. METHODS: According to the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA), MEDLINE, EMBASE, Web of Science, and PubMed were searched for results from January 1, 2000, to May 18, 2021, in two subsequent searches for English language studies that presented data on traumatic patellar dislocation. Quality of selected papers was assessed using the Methodological Index for Non-Randomised Studies (MINORS) and the Risk of Bias (RoB) 2.0 protocol. Results were qualitatively synthesised, and descriptive statistics were calculated. RESULTS: Forty studies totalling 3074 patients (1407 females) were included for the analysis. The mean age was 18.9 years (range 0-69). The population included 2446 first-time dislocations. The imaging modalities used were: 71.1% MRI, 52.6% plain radiography, 12.1% CT, and 0.68% ultrasound. In the 25 studies that reported the number of OCF, a total of 38.3% of patients were found to have OCF. 43.3% of patients with a first-time dislocation, and 34.7% of patients with previous dislocations, had at least one OCF. In the included paediatric studies (maximum age ≤ 18), the presence of OCF was detected by plain radiography in 10.1% of patients, MRI in 76.6% of patients, and CT in 89.5% of patients. For management of an OCF, the surgical options include fixation for larger pieces, excision for smaller pieces, and conservative management on a case-by-case basis. CONCLUSIONS: Based on the current available evidence, assessment and management of patellar dislocations and subsequent OCFs vary, with radiography and MRI as the main imaging modalities on presentation and particular benefit for MRI in the paediatric population. Findings from this study suggest the highest rate of OCF detection with MRI, and thus, surgeons should consider routinely ordering an MRI in patients with first-time patellar dislocation. Regarding management of OCFs, the main indication for fixation was large fragments, while smaller and poor-quality fragments are excised. Few studies choose conservative management of OCFs due to later requirements for surgical management. Future work should focus on large, high-quality studies, and implementation of randomised control trials to form guidelines for imaging patellar dislocations and management of OCFs. LEVEL OF EVIDENCE: Level IV.
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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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,004 | 0,001 |
| 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 ».