EXPERTS’ PERCEIVED PATIENT BURDEN AND OUTCOMES OF KNEE-ANKLE-FOOT-ORTHOSES (KAFOs) VS. MICROPROCESSOR-STANCE-AND-SWING-PHASE-CONTROLLED-KNEE-ANKLE-FOOT ORTHOSES (MP-SSCOs)
Notice bibliographique
Résumé
BACKGROUND: Patients with neuromuscular knee-instability assisted with orthotic devices experience problems including pain, falls, mobility issues and limited engagement in daily activities. OBJECTIVES: The aim of this study was to analyse current real-life burden, needs and orthotic device outcomes in patients in need for advanced orthotic knee-ankle-foot-orthoses (KAFOs). METHODOLOGY: An observer-based semi-structured telephone interview with orthotic care experts in Germany was applied. Interviews were transcribed and content-analysed. Quantitative questions were analysed descriptively. FINDINGS: Clinical experts from eight centres which delivered an average of 49.9 KAFOs per year and 13.3 microprocessor-stance-and-swing-phase-controlled-knee-ankle-foot orthoses (MP-SSCOs) since product availability participated. Reported underlying conditions comprised incomplete paraplegia (18%), peripheral nerve lesions (20%), poliomyelitis (41%), post-traumatic lesions (8%) and other disorders (13%). The leading observed patient burdens were “restriction of mobility” (n=6), followed by “emotional strain” (n=5) and “impaired gait pattern” (n=4). Corresponding results for potential patient benefits were seen in “improved quality-of-life” (n=8) as well as “improved gait pattern” (n=8) followed by “high reliability of the orthosis” (n=7). In total, experts reported falls occurring in 71.5% of patients at a combined annual frequency of 7.0 fall events per year when using KAFOs or stance control orthoses (SCOs). In contrast, falls were observed in only 7.2 % of MP-SSCO users. CONCLUSION: Advanced orthotic technology might contribute to better quality of life of patients, improved gait pattern and perceived reliability of orthosis. In terms of safety a substantial decrease in frequency of falls was observed when comparing KAFO and MP-SSCO users. Layman's Abstract Patients who are not able to control the muscles of their legs may need to wear a brace to improve their ability to walk. However, some users are reporting problems including pain, falls, mobility issues and limited engagement in daily activities. The aim of this study was to analyse current real-life burden, needs and experiences of patients who need to wear a brace for their knee, ankle and foot (KAFO). Therefor, experts were interviewed via telephone with a structured set of questions. Eight experts provided observations for patients who suffered from several diseases affecting leg muscle control. The leading patient burdens were identified as “restriction of mobility”, followed by “emotional strain” and “impaired way of walking”. Potential patient benefits were seen in “improved quality-of-life” as well as “improved way of walking” followed by a “high trust in the brace”. Experts reported a higher number of falls per year when using KAFO without the active control of a microprocessor. On a long-term basis, experts observed consequences of KAFO use as disorders of the back, reduced amount of muscles as well as swelling in areas not covered by the brace, scrub marks and degenerative impact on joints. Braces with active control of a microprocessor might result in better quality of life of patients, improved normal way of walking and perceived trust in the brace. Article PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/37795/29114 How To Cite: Brüggenjürgen B., Braatz F., Greitemann B., Drewitz H., Ruetz A., Schäfer M., et al. Experts’ perceived patient burden and outcomes of knee-ankle-foot-orthoses (KAFOs) vs. microprocessor-stance-and-swing-phase-controlled-knee-ankle-foot orthoses (MP-SSCOs). Canadian Prosthetics & Orthotics Journal. 2022; Volume 5, Issue 1, No.7.https://doi.org/10.33137/cpoj.v5i1.37795 Corresponding Author: Prof. Dr. med. Bernd Brüggenjürgen,Head Institute Health Services Research and Technical Orthopedics, Orthopedic Department - Medical School Hannover (MHH) at DIAKOVERE Annastift Hospital, Anna-von-Borries-Str. 1-7, 30625 Hannover, Germany. E-Mail:brueggenjuergen.bernd@mh-hannover.de ORCID ID:https://orcid.org/0000-0002-8866-0809
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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».