Evidence map›Paper›PMID 37386363›Full record

Observational studyBMC geriatrics2023

Comparative study of young-old and old-old people using functional evaluation, gait characteristics, and cardiopulmonary metabolic energy consumption.

Eunhye Chung, Su-Hyun Lee, Hwang-Jae Lee, Yun-Hee Kim

Registry-linked trialAbstract readObservational Study
In one paragraph

Observational study in BMC geriatrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04723927 (Development of Fall Prediction Model for Older Adults by Analysis of Walking Patterns Based on Multi-faceted Biosignal Data), which is not on this map. Cited by 26 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 2 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.

NCT04723927 completednot on this map

Development of Fall Prediction Model for Older Adults by Analysis of Walking Patterns Based on Multi-faceted Biosignal Data

TypeobservationalSponsorSamsung Medical CenterRan2021 to 2022Enrolled100ConditionsGaitArmsOlder adults
3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Automatic Detection of Gait Perturbations With Everyday Wearable Technology.IEEE open journal of engineering in medicine and biology · 2025
    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

4 authors.

Eunhye ChungDepartment of Medical Device Management & Research, SAIHST, Sungkyunkwan University, Seoul, 06351, Republic of Korea.
Su-Hyun LeeDepartment of Physical and Rehabilitation Medicine, Sungkyunkwan University School of Medicine, Suwon, 16419, Republic of Korea.
Hwang-Jae LeeRobot Business Team, Samsung Electronics, Suwon, 16677, Republic of Korea.
Yun-Hee KimDepartment of Medical Device Management & Research, SAIHST, Sungkyunkwan University, Seoul, 06351, Republic of Korea. yunkim@skku.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWalking is an important factor in daily life. Among older adults, gait function declines with age. In contrast to the many studies revealing gait differences between young adults and older adults, few studies have further divided older adults into groups. The purpose of this study was to subdivide an older adult population by age to identify age-related differences in functional evaluation, gait characteristics and cardiopulmonary metabolic energy consumption while walking.

methodsThis was a cross-sectional study of 62 old adult participants who were classified into two age groups of 31 participants each as follows: young-old (65-74 years) and old-old (75-84 years) group. Physical functions, activities of daily living, mood state, cognitive function, quality of life, and fall efficacy were evaluated using the Short Physical Performance Battery (SPPB), Four-square Step Test (FSST), Timed Up and Go Test (TUG), Korean Version of the Modified Barthel Index, Geriatric Depression Scale (GDS), Korean Mini-mental State Examination, EuroQol-5 Dimensions (EQ-5D) questionnaire, and the Korean version of the Fall Efficacy Scale. A three-dimensional motion capture system (Kestrel Digital RealTime System®; Motion Analysis Corporation, Santa Rosa, CA, USA) and two force plates (TF-4060-B; Tec Gihan, Kyoto, Japan) were used to investigate spatiotemporal gait parameters (velocity, cadence, stride length, stride width, step length, single support, stance phase, and swing phase), kinematic variables (hip, knee, and ankle joint angles), and kinetic variables (hip, knee, and ankle joint moment and power) of gait. A portable cardiopulmonary metabolic system (K5; Cosmed, Rome, Italy) was used to measure cardiopulmonary energy consumption.

resultsThe old-old group showed significantly lower SPPB, FSST, TUG, GDS-SF, and EQ-5D scores (p < 0.05). Among spatiotemporal gait parameters, velocity, stride length, and step length were significantly lower in the old-old group than in the young-old group (p < 0.05). Among the kinematic variables, the knee joint flexion angles during initial contact and terminal swing phase were significantly higher in the old-old than the young-old group (P < 0.05). The old-old group also showed a significantly lower ankle joint plantarflexion angle during the pre- and initial swing phases (P < 0.05). Among the kinetic variables, the hip joint flexion moment and knee joint absorption power in the pre-swing phase were significantly lower in the old-old than the young-old group (P < 0.05).

conclusionThis study demonstrated that participants 75-84 years of age had less functional gaits than their young-old counterparts (65-74 years old). As the walking pace of old-old people diminishes, driving strength to move ahead and pressure on the knee joint also tend to decrease together with stride length. These differences in gait characteristics according to age among older adults could improve our understanding of how aging causes variations in gait that increase the risk of falls. Older adults of different ages may require customized intervention plans, such as gait training methods, to prevent age-related falls.

trial registrationClinical trials registration information: ClinicalTrials.gov Identifier: NCT04723927 (26/01/2021).

Indexed as

Activities of Daily LivingPostural BalanceAgedAged, 80 and overCross-Sectional StudiesGaitHumansQuality of LifeTime and Motion StudiesAgingCardiopulmonary metabolic energy consumptionGait characteristics

Identifiers

PMID37386363
PMCPMC10311791

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.