Evidence mapPaperPMID 35743575Full record

ArticleJournal of clinical medicine2022

Efficacy of Transcranial Direct Current Stimulation (tDCS) on Balance and Gait in Multiple Sclerosis Patients: A Machine Learning Approach.

Nicola Marotta, Alessandro de Sire, Cinzia Marinaro, Lucrezia Moggio, Maria Teresa Inzitari, Ilaria Russo, Anna Tasselli, Teresa Paolucci, Paola Valentino, Antonio Ammendolia

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 4 pooled it
3.0field-weighted citation impact, top 8% of its field
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

18 citing papers in PubMed, 4 syntheses or guidelines pooled it, 36 citations in OpenAlex.

  1. Effects of transcranial direct current stimulation on motor function in patients with multiple sclerosis: a systematic review and meta-analysis.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026
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  9. Multidimensional evaluation of clinical and functional impairment in a large population of patients with Charcot-Marie-Tooth.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025
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  10. How Early Is Early Multiple Sclerosis?Journal of clinical medicine · 2023
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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

10 authors at 2 institutions in 1 country.

Nicola MarottaDepartment of Medical and Surgical Sciences, University of Catanzaro "Magna Graecia", Via Tommaso Campanella 115, 88100 Catanzaro, Italy.ORCID 0000-0002-5568-7909
Alessandro de SireDepartment of Medical and Surgical Sciences, University of Catanzaro "Magna Graecia", Via Tommaso Campanella 115, 88100 Catanzaro, Italy.ORCID 0000-0002-5541-8346
Cinzia MarinaroDepartment of Medical and Surgical Sciences, University of Catanzaro "Magna Graecia", Via Tommaso Campanella 115, 88100 Catanzaro, Italy.ORCID 0000-0002-6283-4831
Lucrezia MoggioDepartment of Medical and Surgical Sciences, University of Catanzaro "Magna Graecia", Via Tommaso Campanella 115, 88100 Catanzaro, Italy.ORCID 0000-0002-3791-4047
Maria Teresa InzitariDepartment of Medical and Surgical Sciences, University of Catanzaro "Magna Graecia", Via Tommaso Campanella 115, 88100 Catanzaro, Italy.ORCID 0000-0002-1456-3221
Ilaria RussoDepartment of Medical and Surgical Sciences, University of Catanzaro "Magna Graecia", Via Tommaso Campanella 115, 88100 Catanzaro, Italy.
Anna TasselliDepartment of Medical and Surgical Sciences, University of Catanzaro "Magna Graecia", Via Tommaso Campanella 115, 88100 Catanzaro, Italy.
Teresa PaolucciPhysical Medicine and Rehabilitation, Department of Oral, Medical and Biotechnological Sciences, University of Gabriele D'Annunzio of Chieti, 66100 Chieti, Italy.
Paola ValentinoInstitute of Neurology, University of Catanzaro "Magna Graecia", Viale Europa, 88100 Catanzaro, Italy.
Antonio AmmendoliaDepartment of Medical and Surgical Sciences, University of Catanzaro "Magna Graecia", Via Tommaso Campanella 115, 88100 Catanzaro, Italy.ORCID 0000-0002-2828-2455
Magna Graecia University · ITUniversity of Chieti-Pescara · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transcranial direct current stimulation (tDCS) has emerged as an appealing rehabilitative approach to improve brain function, with promising data on gait and balance in people with multiple sclerosis (MS). However, single variable weights have not yet been adequately assessed. Hence, the aim of this pilot randomized controlled trial was to evaluate the tDCS effects on balance and gait in patients with MS through a machine learning approach. In this pilot randomized controlled trial (RCT), we included people with relapsing−remitting MS and an Expanded Disability Status Scale >1 and <5 that were randomly allocated to two groups—a study group, undergoing a 10-session anodal motor cortex tDCS, and a control group, undergoing a sham treatment. Both groups underwent a specific balance and gait rehabilitative program. We assessed as outcome measures the Berg Balance Scale (BBS), Fall Risk Index and timed up-and-go and 6-min-walking tests at baseline (T0), the end of intervention (T1) and 4 (T2) and 6 weeks after the intervention (T3) with an inertial motion unit. At each time point, we performed a multiple factor analysis through a machine learning approach to allow the analysis of the influence of the balance and gait variables, grouping the participants based on the results. Seventeen MS patients (aged 40.6 ± 14.4 years), 9 in the study group and 8 in the sham group, were included. We reported a significant repeated measures difference between groups for distances covered (6MWT (meters), p < 0.03). At T1, we showed a significant increase in distance (m) with a mean difference (MD) of 37.0 [−59.0, 17.0] (p = 0.003), and in BBS with a MD of 2.0 [−4.0, 3.0] (p = 0.03). At T2, these improvements did not seem to be significantly maintained; however, considering the machine learning analysis, the Silhouette Index of 0.34, with a low cluster overlap trend, confirmed the possible short-term effects (T2), even at 6 weeks. Therefore, this pilot RCT showed that tDCS may provide non-sustained improvements in gait and balance in MS patients. In this scenario, machine learning could suggest evidence of prolonged beneficial effects.

Indexed as

gait analysismachine learningmobilitymultiple factor analysismultiple sclerosisneurorehabilitationrehabilitationtDCS

Identifiers

PMID35743575
PMCPMC9224780
OpenAlexW4283011342

What Socratic holds

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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 Socratic graph.