Evidence map›Paper›PMID 35122222›Full record

ArticleCerebellum (London, England)2023

Multimodal Mobility Assessment Predicts Fall Frequency and Severity in Cerebellar Ataxia.

Roman Schniepp, Anna Huppert, Julian Decker, Fabian Schenkel, Marianne Dieterich, Thomas Brandt, Max Wuehr

Open access · hybridAbstract read
In one paragraph

Article in Cerebellum (London, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 27% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
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

7 authors at 2 institutions in 1 country.

Roman SchnieppDepartment of Neurology, University of Munich, Marchioninistrasse 15, 81377, Munich, Germany. roman.schniepp@med.uni-muenchen.de.ORCID http://orcid.org/0000-0003-3957-7555
Anna HuppertGerman Center for Vertigo and Balance Disorders (DSGZ), University of Munich, 81377, Munich, Germany.
Julian DeckerGerman Center for Vertigo and Balance Disorders (DSGZ), University of Munich, 81377, Munich, Germany.
Fabian SchenkelGerman Center for Vertigo and Balance Disorders (DSGZ), University of Munich, 81377, Munich, Germany.
Marianne DieterichDepartment of Neurology, University of Munich, Marchioninistrasse 15, 81377, Munich, Germany.
Thomas BrandtGerman Center for Vertigo and Balance Disorders (DSGZ), University of Munich, 81377, Munich, Germany.
Max WuehrGerman Center for Vertigo and Balance Disorders (DSGZ), University of Munich, 81377, Munich, Germany.
German Center for Lung Research · DEUkrainian Free University · DE

Funding

BMBF IFB 01EO1401Else Kröner-Fresenius-Stiftung 80766157Else Kröner-Fresenius-Stiftung EKFES
6 · The paper itself

Abstract

This cohort study aims to evaluate the predictive validity of multimodal clinical assessment and quantitative measures of in- and off-laboratory mobility for fall-risk estimation in patients with cerebellar ataxia (CA).Occurrence, severity, and consequences of falling were prospectively assessed for 6 months in 93 patients with hereditary (N = 36) and sporadic or secondary (N = 57) forms of CA and 63 healthy controls. Participants completed a multimodal clinical and functional fall risk assessment, in-laboratory gait examination, and a 2-week inertial sensor-based daily mobility monitoring. Multivariate logistic regression analyses were performed to evaluate the predictive capacity of all clinical and in- and off-laboratory mobility measures with respect to fall (1) status (non-faller vs. faller), (2) frequency (occasional vs. frequent falls), and (3) severity (benign vs. injurious fall) of patients. 64% of patients experienced one or recurrent falls and 65% of these severe fall-related injuries during prospective assessment. Mobility impairments in patients corresponded to a mild-to-moderate ataxic gait disorder. Patients' fall status and frequency could be reliably predicted (78% and 81% accuracy, respectively), primarily based on their retrospective fall status. Clinical scoring of ataxic symptoms and in- and off-laboratory gait and mobility measures improved classification and provided unique information for the prediction of fall severity (84% accuracy).These results encourage a stepwise approach for fall risk assessment in patients with CA: fall history-taking readily and reliably informs the clinician about patients' general fall risk. Clinical scoring and instrument-based mobility measures provide further in-depth information on the risk of recurrent and injurious falling.

Indexed as

Cerebellar AtaxiaCohort StudiesGaitHumansProspective StudiesRetrospective StudiesRisk AssessmentRisk FactorsCerebellar ataxiaFall predictionFallsGait analysisMobility monitoring

Identifiers

PMID35122222
PMCPMC9883327
OpenAlexW4210242490

What OpenQuestion holds

Textmetadata
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.