Evidence map›Paper›PMID 37745667›Full record

ArticleFrontiers in neurology2023

Antonio Caronni, Michela Picardi, Stefano Scarano, Chiara Malloggi, Peppino Tropea, Giulia Gilardone, Evdoxia Aristidou, Giuseppe Pintavalle, Valentina Redaelli, Paola Antoniotti and 1 more

Abstract read
In one paragraph

Article in Frontiers in neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–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

17 citing papers in PubMed.

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  7. Validation of the Czech adaptation of Mini-BESTest into clinical practice.European journal of physical and rehabilitation medicine · 2026
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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

11 authors.

Antonio CaronniDepartment of Neurorehabilitation Sciences, IRCCS Istituto Auxologico Italiano, Ospedale San Luca, Milan, Italy.
Michela PicardiDepartment of Neurorehabilitation Sciences, Casa di Cura Igea, Milan, Italy.
Stefano ScaranoDepartment of Neurorehabilitation Sciences, IRCCS Istituto Auxologico Italiano, Ospedale San Luca, Milan, Italy.
Chiara MalloggiDepartment of Neurorehabilitation Sciences, IRCCS Istituto Auxologico Italiano, Ospedale San Luca, Milan, Italy.
Peppino TropeaDepartment of Neurorehabilitation Sciences, Casa di Cura Igea, Milan, Italy.
Giulia GilardoneDepartment of Neurorehabilitation Sciences, Casa di Cura Igea, Milan, Italy.
Evdoxia AristidouDepartment of Neurorehabilitation Sciences, Casa di Cura Igea, Milan, Italy.
Giuseppe PintavalleDepartment of Neurorehabilitation Sciences, Casa di Cura Igea, Milan, Italy.
Valentina RedaelliDepartment of Neurorehabilitation Sciences, Casa di Cura Igea, Milan, Italy.
Paola AntoniottiDepartment of Neurorehabilitation Sciences, Casa di Cura Igea, Milan, Italy.
Massimo CorboDepartment of Neurorehabilitation Sciences, Casa di Cura Igea, Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Balance, i.e., the ability not to fall, is often poor in neurological patients and this impairment increases their risk of falling. The Mini-Balance Evaluation System Test (Mini-BESTest), a rating scale, the Timed Up and Go (TUG) test, and gait measures are commonly used to quantify balance. This study assesses the criterion validity of these measures as balance measures. Methods: The probability of being a faller within nine months was used as the balance criterion. The Mini-BESTest, TUG (instrumented with inertial sensors), and walking test were administered before and after inpatient rehabilitation. Multiple and LASSO logistic regressions were used for the analysis. The diagnostic accuracy of the model was assessed with the area under the curve (AUC) of the receiver operating characteristic curve. Mobility measure validity was compared with the Akaike Information Criterion (AIC). Results: Two hundred and fourteen neurological patients (stroke, peripheral neuropathy, or parkinsonism) were recruited. In total, 82 patients fell at least once in the nine-month follow-up. The Mini-BESTest (AUC = 0.69; 95%CI: 0.62-0.76), the duration of the TUG turning phase (AUC = 0.69; 0.62-0.76), and other TUG measures were significant faller predictors in regression models. However, only the turning duration (AIC = 274.0) and Mini-BESTest (AIC = 276.1) substantially improved the prediction of a baseline model, which only included fall risk factors from the medical history (AIC = 281.7). The LASSO procedure selected gender, disease chronicity, urinary incontinence, the Mini-BESTest, and turning duration as optimal faller predictors. Conclusion: The TUG turning duration and the Mini-BESTest predict the chance of being a faller. Their criterion validity as balance measures in neurological patients is substantial.

Indexed as

balance assessmentcriterion validityfalling riskgait assessmentinertial measurement unitneurological rehabilitationpsychometrics

Identifiers

PMID37745667
PMCPMC10516579

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Registered trials

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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.