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Enregistrement W2735730740 · doi:10.1177/0363546517712952

Surgical Predictors of Clinical Outcomes After Revision Anterior Cruciate Ligament Reconstruction

2017· article· en· W2735730740 sur OpenAlexaboutno aff
Christina R. Allen, Allen F. Anderson, Daniel E. Cooper, Thomas M. DeBerardino, Warren R. Dunn, Amanda K. Haas, Laura J. Huston, Brett A. Lantz, Barton J. Mann, Sam Nwosu, Kurt P. Spindler, Michael J. Stuart, Rick W. Wright, John P. Albright, Annunziato Amendola, Jack T. Andrish, Christopher C. Annunziata, Robert A. Arciero, Bernard R. Bach, Champ L. Baker, Arthur R. Bartolozzi, Keith M. Baumgarten, Jeffery R. Bechler, Jeffrey H. Berg, Geoffrey A. Bernas, Stephen F. Brockmeier, Robert H. Brophy, Charles A. Bush‐Joseph, J. Brad Butler, John Campbell, James L. Carey, James E. Carpenter, Brian J. Cole, Jonathan M. Cooper, Charles L. Cox, R. Alexander Creighton, Diane L. Dahm, Tal S. David, David C. Flanigan, Robert W. Frederick, Theodore J. Ganley, Elizabeth A. Garofoli, Charles J. Gatt, Steven R. Gecha, J. Robert Giffin, Sharon L. Hame, Jo A. Hannafin, Christopher D. Harner, Norman Lindsay Harris, Keith S. Hechtman, Elliott B. Hershman, Rudolf G. Hoellrich, Timothy M. Hosea, David C. Johnson, Timothy S. Johnson, Morgan H. Jones, Christopher C. Kaeding, Ganesh V. Kamath, Thomas E. Klootwyk, Bruce A. Levy, C. Benjamin, G. Peter Maiers, Robert G. Marx, Matthew J. Matava, Gregory M. Mathien, David R. McAllister, Eric C. McCarty, Robert G. McCormack, Bruce S. Miller, Carl W. Nissen, Daniel F. O’Neill, Brett D. Owens, Richard D. Parker, Mark L. Purnell, Arun J. Ramappa, Michael A. Rauh, Arthur C. Rettig, Jon K. Sekiya, Kevin G. Shea, Orrin H. Sherman, James R. Slauterbeck, Matthew V. Smith, Jeffrey T. Spang, Steven J. Svoboda, Timothy N. Taft, Joachim J. Tenuta, Edwin M. Tingstad, Armando F. Vidal, Darius G. Viskontas, Richard A. White, James S. Williams, Michelle L. Wolcott, Brian R. Wolf, James J. York

Notice bibliographique

RevueThe American Journal of Sports Medicine · 2017
Typearticle
Langueen
DomaineMedicine
ThématiqueKnee injuries and reconstruction techniques
Établissements canadiensnon disponible
Organismes subventionnairesNational Institute of Arthritis and Musculoskeletal and Skin Diseases
Mots-clésMedicineAnterior cruciate ligamentBody mass indexAnterior cruciate ligament reconstructionOsteoarthritisSurgeryWOMACArthrotomyACL injuryEvidence-based medicineOrthopedic surgeryPhysical therapyArthroscopyInternal medicine

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Revision anterior cruciate ligament (ACL) reconstruction has been documented to have worse outcomes compared with primary ACL reconstruction. HYPOTHESIS: Certain factors under the control of the surgeon at the time of revision surgery can both negatively and positively affect outcomes. STUDY DESIGN: Case-control study; Level of evidence, 3. METHODS: Patients undergoing revision ACL reconstruction were identified and prospectively enrolled between 2006 and 2011. Data collected included baseline demographics, intraoperative surgical technique and joint disorders, and a series of validated patient-reported outcome instruments (International Knee Documentation Committee [IKDC] subjective form, Knee Injury and Osteoarthritis Outcome Score [KOOS], Western Ontario and McMaster Universities Osteoarthritis Index [WOMAC], and Marx activity rating scale) completed before surgery. Patients were followed up for 2 years and asked to complete an identical set of outcome instruments. Regression analysis was used to control for age, sex, body mass index (BMI), activity level, baseline outcome scores, revision number, time since last ACL reconstruction, and a variety of previous and current surgical variables to assess the surgical risk factors for clinical outcomes 2 years after revision ACL reconstruction. RESULTS: A total of 1205 patients (697 male [58%]) met the inclusion criteria and were successfully enrolled. The median age was 26 years, and the median time since their last ACL reconstruction was 3.4 years. Two-year follow-up was obtained on 82% (989/1205). Both previous and current surgical factors were found to be significant contributors toward poorer clinical outcomes at 2 years. Having undergone previous arthrotomy (nonarthroscopic open approach) for ACL reconstruction compared with the 1-incision technique resulted in significantly poorer outcomes for the 2-year IKDC ( P = .037; odds ratio [OR], 2.43; 95% CI, 1.05-5.88) and KOOS pain, sports/recreation, and quality of life (QOL) subscales ( P ≤ .05; OR range, 2.38-4.35; 95% CI, 1.03-10.00). The use of a metal interference screw for current femoral fixation resulted in significantly better outcomes for the 2-year KOOS symptoms, pain, and QOL subscales ( P ≤ .05; OR range, 1.70-1.96; 95% CI, 1.00-3.33) as well as WOMAC stiffness subscale ( P = .041; OR, 1.75; 95% CI, 1.02-3.03). Not performing notchplasty at revision significantly improved 2-year outcomes for the IKDC ( P = .013; OR, 1.47; 95% CI, 1.08-1.99), KOOS activities of daily living (ADL) and QOL subscales ( P ≤ .04; OR range, 1.40-1.41; 95% CI, 1.03-1.93), and WOMAC stiffness and ADL subscales ( P ≤ .04; OR range, 1.41-1.49; 95% CI, 1.03-2.05). Factors before revision ACL reconstruction that increased the risk of poorer clinical outcomes at 2 years included lower baseline outcome scores, a lower Marx activity score at the time of revision, a higher BMI, female sex, and a shorter time since the patient's last ACL reconstruction. Prior femoral fixation, prior femoral tunnel aperture position, and knee flexion angle at the time of revision graft fixation were not found to affect 2-year outcomes in this revision cohort. CONCLUSION: There are certain surgical variables that the physician can control at the time of revision ACL reconstruction that can modify clinical outcomes at 2 years. Whenever possible, opting for an anteromedial portal or transtibial surgical exposure, choosing a metal interference screw for femoral fixation, and not performing notchplasty are associated with significantly better 2-year clinical outcomes.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,523
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,003
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,019
Tête enseignante GPT0,363
Écart entre enseignants0,345 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations37
Publié2017
Routes d'admission1
Résumé présentoui

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