Effects of Telemedicine for Postural Instability in Independent Patients With Parkinson's Disease
Bibliographic record
Abstract
Background: The purpose of this study is to examine the evidence of the effectiveness of telemedicine in postural stability treatment in independent patients affected by Parkinson's disease (PD). Methods: This is a literature review of studies investigating the effect of telemedicine in postural stability treatment in independent patients affected by PD. PRISMA guidelines were followed during the design, search, and reporting stages of this review. The search was carried out in the MEDLINE databases. Results: A total of 1854 studies were detected and analyzed by performing the proposed searches in the detailed databases. After removing duplicates and analyzing the titles and abstracts of the remaining articles, 6 studies were ultimately selected for this review. At least 50% of the studies included in this review showed positive results in improving postural stability in patients with PD after a home-based intervention. Conclusions: The home-based intervention based upon technologically assisted telerehabilitation may support the aspects of an effective and efficient physical therapy allowing the physiotherapists to deliver functional rehabilitation in the home setting outside the hospital and supervise more than one patient simultaneously during rehabilitation sessions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".