Evidence map›Paper›PMID 29182996›Full record

ArticleMultiple sclerosis and related disorders2018

Distinguishing among multiple sclerosis fallers, near-fallers and non-fallers.

Nora E Fritz, Ani Eloyan, Moira Baynes, Scott D Newsome, Peter A Calabresi, Kathleen M Zackowski

Abstract read
In one paragraph

Article in Multiple sclerosis and related disorders, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 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

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Linking Pathogenesis to Fall Risk in Multiple Sclerosis.Archives of internal medicine research · 2025
    Article
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  6. Article
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  17. Spotlight on postural control in patients with multiple sclerosis.Degenerative neurological and neuromuscular disease · 2018
    Review
  18. 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

6 authors.

Nora E FritzWayne State University, Program in Physical Therapy, Detroit, MI, United States; Kennedy Krieger Institute, Motion Analysis Laboratory, Baltimore, MD, United States; Johns Hopkins School of Medicine, Department of Physical Medicine and Rehabilitation, Baltimore, MD, United States. Electronic address: nora.fritz@wayne.edu.
Ani EloyanBrown University School of Public Health, Department of Biostatistics, Providence, RI, United States.
Moira BaynesJohns Hopkins School of Medicine, Department of Neurology, Baltimore, MD, United States.
Scott D NewsomeJohns Hopkins School of Medicine, Department of Neurology, Baltimore, MD, United States.
Peter A CalabresiJohns Hopkins School of Medicine, Department of Neurology, Baltimore, MD, United States.
Kathleen M ZackowskiKennedy Krieger Institute, Motion Analysis Laboratory, Baltimore, MD, United States; Johns Hopkins School of Medicine, Department of Physical Medicine and Rehabilitation, Baltimore, MD, United States; Johns Hopkins School of Medicine, Department of Neurology, Baltimore, MD, United States.

Funding

Imaging Neurodegeneration in Multiple SclerosisR01NS082347 · NINDS · JOHNS HOPKINS UNIVERSITY · PI PETER A CALABRESI, Shiv Saidha · 2013 to 2026
$7.0M
MECHANISMS OF LOCOMOTOR RECOVERY IN MULTIPLE SCLEROSISK01HD049476 · NICHD · HUGO W. MOSER RES INST KENNEDY KRIEGER · PI ZACKOWSKI, KATHLEEN M. · 2006 to 2010
$499k
NICHD NIH HHS K01 HD049476NINDS NIH HHS R01 NS082347
6 · The paper itself

Abstract

backgroundFall rates among adults with multiple sclerosis are consistently greater than 50%, but near-falls (i.e. a trip or stumble) are often undocumented. Furthermore, little is known about the circumstances surrounding fall and near-fall events. The purpose of this study was to examine the similarities and differences among non-fallers, near-fallers and fallers with multiple sclerosis, including the circumstances that surround falls and near-falls.

methodsIn a single visit, 135 multiple sclerosis participants completed the Hopkins Falls Grading Scale, a custom questionnaire investigating circumstances surrounding falls and near-falls, and performed the Timed Up and Go and Timed 25-Foot Walk tests. Mann-Whitney tests were used to examine differences between fallers, near-fallers and non-fallers. Multiple logistic regression with AIC criterion was used to examine associations of circumstances with the odds of falling vs. near-falling. Cumulative odds ordinal logistic regression was used to analyze the association between each of the walking tests and the susceptibility of the individual for falls or near-falls.

results30% of individuals reported falls, while 44% reported near-falls over a 1-year period. Non-fallers completed the walking tests more quickly than near-fallers (p < 0.0045), and fallers (p < 0.0001); near-fallers and fallers demonstrated similar motor profiles. Individuals were more likely to sustain a fall rather than a near-fall under the following circumstances: transferring outside the home (p = 0.015) and tripping over an obstacle (p = 0.025). Performing 1-second slower on the walking tests increased the odds of a history of a fall by 6-20%.

conclusionNear-falls occur commonly in individuals with MS; near-fallers and fallers reported similar circumstances surrounding fall events and demonstrated similar performance on standard timed walking tests. Clinicians monitoring individuals with MS should consider evaluation of the circumstances surrounding falls in combination with quantitative walking measures to improve determination of fall risk and appropriate rehabilitation interventions.

Indexed as

Accidental FallsAdultFemaleHumansMaleMiddle AgedMultiple SclerosisWalkingAccidental fallsFallsMultiple sclerosisNear-fallsWalking

Identifiers

PMID29182996
PMCPMC5803437

What OpenQuestion holds

Textmetadata
LicenceTDM
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.