Arthrofibrosis after ACL reconstruction is best treated in a step-wise approach with early recognition and intervention: a systematic review
Notice bibliographique
Résumé
PURPOSE: Arthrofibrosis is the most common post-operative complication of anterior cruciate ligament (ACL) reconstruction. Risk factors and management strategies for arthrofibrosis remain unclear. The purpose of this review was to: (a) describe existing definitions of arthrofibrosis, and (b) characterize the management strategies and outcomes of arthrofibrosis treatment. METHODS: MEDLINE, EMBASE, and PubMed were searched from database inception to search date (March 21, 2016) and screened in duplicate for relevant studies. Data regarding patient demographics, indications, index surgery, management strategy, and outcomes were collected. RESULTS: Twenty-five studies of primarily level IV evidence (88%) were included. A total of 647 patients (648 knees) with a mean age of 28.2 ± 1.8 years (range 14-62 years) were treated for arthrofibrosis following ACL reconstruction and followed for a mean 30.1 ± 16.9 months (range 2 months-9.6 years). Definitions of arthrofibrosis varied widely and included subjective definitions and the Shelbourne classification system. Patients were treated by one or more of: arthroscopic arthrolysis (570 patients), manipulation under anaesthesia (MUA) (153 patients), oral corticosteroids (31 patients), physiotherapy (81 patients), drop-casting (17 patients), epidural therapy combined with inpatient physiotherapy (six patients), and intra-articular interleukin-1 antagonist injection (four patients). All studies reported improvement in range of motion post-operatively, with statistically significant improvement reported for 306 patients (six studies, p range <0.001 to =0.05), and one study (18 patients) reporting significantly better results if arthrofibrosis was treated within 8 months of reconstruction (p < 0.03). The greatest improvements for extension loss were seen with drop-casting (mean 6.2° ± 0.6° improvement), whereas MUA produced the greatest improvement for flexion deficit (mean 47.8° ± 3.3° improvement). CONCLUSIONS: Arthrofibrosis is poorly defined and outcome measures range varies widely. Amongst the studies included in this review, arthrofibrosis was most commonly managed surgically by arthroscopic arthrolysis, and most patients showed at least some improvement, including six studies that reported statistically significant change in ROM. In studies that used a step-wise approach to treating arthrofibrosis, more than half of patients were successfully treated without an operation. A more well-defined concept of arthrofibrosis, along with large, prospective studies will provide a clearer understanding of how to describe and manage this complication. The issue of arthrofibrosis following ACL reconstruction is clinically relevant as it represents a common complication of a commonly performed operation that nonetheless remains poorly defined and without clear treatment guidelines. LEVEL OF EVIDENCE: Systematic Review of Level III and IV Studies, Level IV.
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 | 0,004 | 0,021 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,005 |
| Bibliométrie | 0,006 | 0,008 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».