Impact of physical therapy on various variants of Parkinson's disease
Notice bibliographique
Résumé
Labinsky Andriy. Impact of physical therapy on various variants of Parkinson's disease. Journal of Education, Health and Sport. 2017;7(2):840-849. eISSN 2391-8306. DOI http://dx.doi.org/10.5281/zenodo.3727211 http://ojs.ukw.edu.pl/index.php/johs/article/view/7716 The journal has had 7 points in Ministry of Science and Higher Education parametric evaluation. Part B item 1223 (26.01.2017). 1223 Journal of Education, Health and Sport eISSN 2391-8306 7 © The Author (s) 2017; This article is published with open access at Licensee Open Journal Systems of Kazimierz Wielki University in Bydgoszcz, Poland Open Access. This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. This is an open access article licensed under the terms of the Creative Commons Attribution Non Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted, non commercial use, distribution and reproduction in any medium, provided the work is properly cited. This is an open access article licensed under the terms of the Creative Commons Attribution Non Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted, non commercial use, distribution and reproduction in any medium, provided the work is properly cited. The authors declare that there is no conflict of interests regarding the publication of this paper. Received: 02.02.2017. Revised 24.02.2017. Accepted: 27.02.2017. Impact of physical therapy on various variants of Parkinson's disease Andriy Labinsky Stepan Gzhytskyi National University of Veterinary Medicine and Biotechnologies, Lviv, Ukraine Abstract Topicality. To determine the effectiveness of the use of physical therapy in Parkinson's disease with different onset (early and late) course of the disease and the level of blood pressure. Objectives of the study: to develop and apply to patientswith various forms with Parkinson's disease with predominantly non-motor manifestations program of physical therapy. To study the effectiveness of the developed physical therapy program on the scale of assessment of the state of non-motor symptoms, mental disorders and cognitive impairment in early and late onset of Parkinson's disease with different levels of blood pressure. Research results. After the physical therapy, the condition of the patients improved in all groups of patients surveyed not to the same extent. Improvement was more commonly observed in groups of patients with early onset Parkinson's disease with relatively normal blood pressure, with the use of exercise and the entire range of physical therapy we developed. Changes in the status of patients after physical therapy for the better were recorded by both subjective and objective survey data. Particularly significant were the data from the study on the scale of assessment of patients with non-motor manifestations of Parkinson's disease (scale of non-motor symptoms – NMSS, scale of mental disorders – MMSE, Montreal scale of cognitive disorders-MOCA). They demonstrated a significant statistically difference between control and study groups of patients with normal blood pressure toward improvement in the final examination scores. Conclusions. The condition of patients with normal blood pressure and early onset of the disease who received the developed complex of physical therapy according to the studies was significantly better than in the group of patients who did not receive physical therapy with high blood pressure, which testifies to the higher efficiency of the developed by us and applied complex physical therapy of non-motor manifestations of Parkinson's disease in patients with early-onset development of Parkinson's disease with normal blood pressure. Key words: physical therapy; Parkinson's disease with different onset and blood pressure
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 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 ».