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Enregistrement W4287405278

Stance-Control Knee-Ankle-Foot Orthoses for People With Knee Instability: A Health Technology Assessment.

2021· review· en· W4287405278 sur OpenAlexaboutno aff

Notice bibliographique

RevuePubMed · 2021
Typereview
Langueen
DomaineEngineering
ThématiqueProsthetics and Rehabilitation Robotics
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPhysical medicine and rehabilitationPhysical therapyMedicineAnkleGrading (engineering)Economic evaluationSurgeryEngineering
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Knee instability can arise from various causes and conditions such as neuromuscular disease, central nervous system conditions, and trauma. For people with knee instability, knee orthosis devices are prescribed to help with standing, walking, and performing tasks. We conducted a health technology assessment of stance-control knee-ankle-foot orthoses (SCKAFOs) for people with knee instability, which included an evaluation of the effectiveness, safety, and budget impact of publicly funding SCKAFOs, as well as patient preferences and values. METHODS: We performed a systematic literature search of the clinical evidence. We assessed the risk of bias of each included study using the Risk of Bias in Nonrandomized Studies (RoBANS) tool and the quality of the body of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria. We performed a systematic economic literature search and also analyzed the budget impact of publicly funding SCKAFOs in people with knee instabilities in Ontario. We did not conduct a primary economic evaluation as there was limited comparative clinical evidence to inform an economic model. Our reference case budget impact analysis was done from the perspective of the Ontario Ministry of Health; it compared the total costs of a basic mechanical SCKAFO and locked KAFO (LKAFO) for people with knee instability. We also performed scenario analyses varying the following parameters: the price of all classes of SCKAFO (mechanical, electronic, and microprocessor), and the uptake of SCKAFO. To contextualize the potential value of SCKAFO, we spoke with people with knee instability. RESULTS: We included four studies in the clinical evidence review. We are uncertain if SCKAFOs improve walking ability, energy consumption, or activities of daily living compared with LKAFOs (GRADE: Very low). Our economic evidence review identified one costing analysis that suggested that the costs of orthotic devices such as LKAFOs and SCKAFOs are highly variable according to the cost of materials, professional time, and customization required by the individual patient. The budget impact of publicly funding mechanical SCKAFOs in Ontario over the next 5 years (at a full device cost of $10,784) ranged from an additional $0.50 million in year 1 (at an uptake rate of 30% in the target population [429 eligible people]) to $0.83 million in year 5 (at an uptake rate of 50%), with a total budget impact of $3.34 million over 5 years. We found that the greatest increase in budget impact in the scenario analysis came from the microprocessor SCKAFO device, which had an additional cost of $10.07 million in year 1, increasing to $16.78 million in year 5. When we decreased the cost of a mechanical SCKAFO device (to $7,384), this reduced the 5-year budget impact to $0.89 million (vs. $3.34 million in the reference case). The people with knee instability with whom we spoke reported that they preferred a device that would provide a more typical gait, but starting with this type of device would be easier than switching from an existing LKAFO. CONCLUSIONS: We are uncertain if SCKAFOs improve walking ability, reduce energy consumption, or improve activities of daily living compared with LKAFOs. We estimate that the additional cost to provide public funding for a mechanical SCKAFO in people with knee instability would range from about $0.50 million in year 1 to $0.83 million in year 5, yielding a total budget impact of $3.34 million over 5 years. Depending on the class of SCKAFO and the uptake rate for the device, the budget impact may vary. People who met the criteria for the use of a SCKAFO did have a strong preference for it over an LKAFO.

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)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,996
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
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 Opus0,025
Tête enseignante GPT0,283
Écart entre enseignants0,258 · 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'étudeSans objet
Domainenon disponible
GenreSynthèse

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

En bref

Citations7
Publié2021
Routes d'admission1
Résumé présentoui

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