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Enregistrement W4399215318 · doi:10.33137/cpoj.v7i1.42799

PATIENTS’ BURDEN USING MICROPROCESSOR-STANCE-AND-SWING-CONTROL KNEE-ANKLE-FOOT ORTHOSES AND OUTCOMES COMPARED TO THOSE WITH PRIOR TRADITIONAL KNEE-ANKLE-FOOT-ORTHOSIS

2024· article· en· W4399215318 sur OpenAlexvenueaboutno aff
Bernd Brüggenjürgen, Lena Eilers, Susanne Seidinger, Andreas Kannenberg, Christina Stukenborg‐Colsman

Notice bibliographique

RevueCanadian Prosthetics & Orthotics Journal · 2024
Typearticle
Langueen
DomaineEngineering
ThématiqueProsthetics and Rehabilitation Robotics
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPhysical therapyMedicineBracePhysical medicine and rehabilitationAnkleFoot (prosody)SurgeryEngineering

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Patients with neuromuscular knee instability who are fitted with orthotic devices experience issues such as pain, falls, mobility limitations, and restricted participation. OBJECTIVES: To analyze the burden of disease in patients using a microprocessor-stance-and-swing-control orthosis (MP-SSCO) and, if they had a previous orthosis, to compare their outcomes to those with previous use of a traditional knee-ankle-foot-orthosis (KAFO) under real-world conditions. METHODOLOGY: A structured cross-sectional survey was conducted in six orthotic and prosthetic clinics in Germany. Individuals who had been using an MP-SSCO (C-Brace) for at least six months, answered an internet-based survey to rate their current and recall previous device outcomes and experience. The questionnaire was self-developed based on established questionnaire design principles and pretested. Patients' well-being dimensions were analyzed with Likert scales. Experiences with current and previous orthotic devices were compared. Falls were analyzed both with and without outliers. FINDINGS: 21 individuals who had used a MP-SSCO for an average duration of two years participated. Fourteen patients had prior experience with a traditional KAFO orthosis. Among them, 78.6% recalled experiencing falls, with a combined annual frequency of 67.9 (SD=167.0, Median=12.0) events. After excluding the two outliers (624 and 182 falls), a mean of 12.1 falls per patient per year was reported (range: 0 to 54, SD=15.9, Median=8.5). With the MP-SSCO, only 42.7% reported falls with an annual frequency of 5.3 (SD=17.0, Median=0.0) falls (p<0.01). After excluding outliers for MP-SSCO users, the average number of falls was 0.5 per year (range 0 to 3, SD=0.9, Median=0.0). This value was significantly lower compared to the previous orthosis (p<0.01). With their previous KAFO, 57.1% of the participants reported being able to walk downstairs, 14.3% to descend stairs with reciprocal gait, and 42.9% to vary their walking speeds. In contrast, 90.5% of MP-SSCO users reported being capable of descending stairs, 81.0% reported to descend stairs with reciprocal gait (p<0.01), and 76.2% claimed they had the ability to walk with varying speeds (p=0.03). Additionally, 71.4% of the respondents experienced an improvement in their engagement in activities with the MP-SSCO. 50.0% reported pain with the previous orthosis, compared to 38.1% with the MP-SSCO. Pain intensity was higher for the previous orthosis use (3.8) compared to MP-SSCO use (2.8) on a 1-5 scale (p=0.06). 93.3% of the participants regarded the MP-SSCO as superior, noting an enhanced quality of life (QoL) compared to the previous orthosis. CONCLUSION: Advanced orthotic technology may positively impact outcomes such as fall frequency, activities of daily living, fear of falling and pain. However, in this study, results from the previous orthosis use might have been influenced by recall bias. Layman's Abstract People with an unstable knee due to nerve and muscle problems who wear orthotic devices frequently deal with issues including pain, falls, difficulty moving around, and being unable to participate in activities. We wanted to see how much these burdens affect people who used a traditional knee-ankle-foot orthosis and compare it to a newer type of brace with advanced technology. People who had been using a new microprocessor controlled device (product: C-Brace) for at least 6 months were invited to answer questions online about how they are doing with the new brace. They rated items like how they feel and their experiences with different braces. Twenty-one people who had been using the C-Brace for an average of about 2 years participated. Fourteen had used a traditional brace before. Most of them remembered falling more often with the previous brace than with the microprocessor controlled device. With the previous brace, not many could walk downstairs easily or at all, but with the C-Brace, most could. Many also said they felt less pain with the C-Brace. People with knee problems due to nerve and muscle issues have a hard time moving around and can experience falls when they use regular braces. But using newer, microprocessor controlled braces can help them move better, fall less, and feel less pain, which makes their lives better. It is important to note that results from previous use of knee-ankle-foot orthoses (KAFOs) may have been affected by memory bias. Article PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/42799/32845 How To Cite: Brüggenjürgen B, Eilers L, Seidinger S, Kannenberg A, Stukenborg-Colsman C. Patients’ burden using microprocessor-stance-and-swing-control knee-ankle-foot orthoses and outcomes compared to those with prior traditional knee-ankle-foot-orthosis. Canadian Prosthetics & Orthotics Journal. 2024; Volume 7, Issue 1, No.1. https://doi.org/10.33137/cpoj.v7i1.42799 Corresponding Author: Prof. Dr. med. Bernd Brüggenjürgen, MPHHead 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.Tel.: +49 (511) 5354 821E-Mail: brueggenjuergen.bernd@mh-hannover.de; bernd.brueggenjuergen@diakovere.deORCID 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 machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,006

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,015
Tête enseignante GPT0,223
Écart entre enseignants0,208 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
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

Citations1
Publié2024
Routes d'admission2
Résumé présentoui

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