Evidence map›Paper›PMID 32089816›Full record

ArticleParkinson's disease2020

Assessing the Relationship between the Enhanced Gait Variability Index and Falls in Individuals with Parkinson's Disease.

Abigail C Schmitt, Sidney T Baudendistel, Michaela S Fallon, Jaimie A Roper, Chris J Hass

Open access · goldAbstract read
In one paragraph

Article in Parkinson's disease, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
4.3field-weighted citation impact, top 6% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Functional Connectivity of Vermis Correlates with Future Gait Impairments in Parkinson's Disease.Movement disorders : official journal of the Movement Disorder Society · 2021
    Article
  7. 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

5 authors at 2 institutions in 1 country.

Abigail C SchmittApplied Neuromechanics Laboratory, Department of Applied Physiology and Kinesiology, University of Florida, 1864 Stadium Road, Gainesville, FL 32611, USA.ORCID https://orcid.org/0000-0002-6626-3968
Sidney T BaudendistelApplied Neuromechanics Laboratory, Department of Applied Physiology and Kinesiology, University of Florida, 1864 Stadium Road, Gainesville, FL 32611, USA.ORCID https://orcid.org/0000-0003-3689-8767
Michaela S FallonApplied Neuromechanics Laboratory, Department of Applied Physiology and Kinesiology, University of Florida, 1864 Stadium Road, Gainesville, FL 32611, USA.
Jaimie A RoperLocomotor and Movement Control Laboratory, School of Kinesiology, Auburn University, 301 Wire Road, Auburn, AL 36849, USA.
Chris J HassApplied Neuromechanics Laboratory, Department of Applied Physiology and Kinesiology, University of Florida, 1864 Stadium Road, Gainesville, FL 32611, USA.
University of Florida · USAuburn University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gait impairment and increased gait variability are common among individuals with Parkinson's disease (PD) and have been associated with increased risk for falls. The development of composite scores has gained interest to aggregate multiple aspects of gait into a single metric. The Enhanced Gait Variability Index (EGVI) was developed to compare an individual's gait variability to the amount of variability in a healthy population, yet the EGVI's individual parts may also provide important information that may be lost in this conversion. We sought to contrast individual gait measures as predictors of fall frequency and the EGVI as a single predictor of fall frequency in individuals with PD. 273 patients (189M, 84F; 68 ± 10 yrs) with idiopathic PD walked over an instrumented walkway and reported fall frequency over three months (never, rarely, monthly, weekly, or daily). The predictive ability of gait velocity, step length, step time, stance time, and single support time and the EGVI was assessed using regression techniques to predict fall frequency. The EGVI explained 15.1% of the variance in fall frequency (

Identifiers

PMID32089816
PMCPMC7029296
OpenAlexW3004796275

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.