Evidence map›Paper›PMID 39236299›Full record

SynthesisAnnals of clinical and translational neurology2024

Innovative technology-based interventions in Parkinson's disease: A systematic review and meta-analysis.

Chun En Yau, Eric Chi Kiat Ho, Natasha Yixuan Ong, Clifton Joon Keong Loh, Aaron Shengting Mai, Eng-King Tan

Abstract readSystematic ReviewNetwork Meta-Analysis
In one paragraph

Synthesis in Annals of clinical and translational neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Chun En YauYong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Eric Chi Kiat HoYong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.ORCID 0009-0005-1826-4623
Natasha Yixuan OngYong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Clifton Joon Keong LohYong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Aaron Shengting MaiYong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.ORCID 0000-0002-7644-5538
Eng-King TanDepartment of Neurology, Singapore General Hospital Campus, National Neuroscience Institute, Singapore, Singapore.

Funding

National Medical Research Council PD LCG 000207
6 · The paper itself

Abstract

objectiveNovel technology-based interventions have the potential to improve motor symptoms and gait in Parkinson's disease (PD). Promising treatments include virtual-reality (VR) training, robotic assistance, and biofeedback. Their effectiveness remains unclear, and thus, we conducted a Bayesian network meta-analysis.

methodsWe searched the Medline, Embase, Cochrane CENTRAL, and Clinicaltrials.gov databases until 2 April 2024 and only included randomized controlled trials. Outcomes included changes in UPDRS-III/MDS-UPDRS-III score, stride length, 10-meter walk test (10MWT), timed up-and-go (TUG) test, balance scale scores and quality-of-life (QoL) scores. Results were reported as mean differences (MD) or standardized mean differences (SMD), with 95% credible intervals (95% CrI).

resultsFifty-one randomized controlled trials with 2095 patients were included. For UPDRS (motor outcome), all interventions had similar efficacies. VR intervention was the most effective in improving TUG compared with control (MD: -4.36, 95% CrI: -8.57, -0.35), outperforming robotic, exercise, and proprioceptive interventions. Proprioceptive intervention significantly improved stride length compared to control intervention (MD: 0.11 m, 95% CrI: 0.03, 0.19), outperforming VR, robotic and exercise interventions. Virtual reality improved balance scale scores significantly compared to exercise intervention (SMD: 0.75, 95% CrI: 0.12, 1.39) and control intervention (SMD: 1.42, 95% CrI: 0.06, 2.77). Virtual reality intervention significantly improved QoL scores compared to control intervention (SMD: -0.95, 95% CrI: -1.43, -0.52), outperforming Internet-based interventions.

interpretationVR-based and proprioceptive interventions were the most promising interventions, consistently ranking as the top treatment choices for most outcomes. Their use in clinical practice could be helpful in managing motor symptoms and QoL in PD.

Indexed as

Digital HealthParkinson DiseaseBiofeedback, PsychologyHumansQuality of LifeRandomized Controlled Trials as TopicRoboticsVirtual Reality Exposure Therapy

Identifiers

PMID39236299
PMCPMC11514937

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.