Evidence map›Paper›PMID 38063528›Full record

Observational studyInternational journal of environmental research and public health2023

Respiratory Parameters as Predictors of Balance and Gait Ability in Patients with Stroke at Discharge.

Hee-Yong Park, Oh-Yun Kwon, Chung-Hwi Yi, Hye-Seon Jeon, Woochol Joseph Choi, So-Young Ahn, Ui-Jae Hwang

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-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

4 citing papers in PubMed, 2 citations in OpenAlex.

  1. Observational
  2. Review
  3. Review
  4. 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.

Hee-Yong ParkDepartment of Rehabilitation Medicine, Chungnam National University Hospital, Daejeon 35015, Republic of Korea.
Oh-Yun KwonDepartment of Physical Therapy, College of Software and Digital Healthcare Convergence, Yonsei University, Wonju 26493, Republic of Korea.
Chung-Hwi YiDepartment of Physical Therapy, College of Software and Digital Healthcare Convergence, Yonsei University, Wonju 26493, Republic of Korea.ORCID 0000-0003-2554-8083
Hye-Seon JeonDepartment of Physical Therapy, College of Software and Digital Healthcare Convergence, Yonsei University, Wonju 26493, Republic of Korea.
Woochol Joseph ChoiDepartment of Physical Therapy, College of Software and Digital Healthcare Convergence, Yonsei University, Wonju 26493, Republic of Korea.
So-Young AhnDepartment of Rehabilitation Medicine, Chungnam National University Hospital, Daejeon 35015, Republic of Korea.
Ui-Jae HwangDepartment of Physical Therapy, College of Software and Digital Healthcare Convergence, Yonsei University, Wonju 26493, Republic of Korea.
Yonsei University · KRChungnam National University Hospital · KR

Funding

Chungnam National University Hospital 2022-CF-008
6 · The paper itself

Abstract

Pulmonary complications are frequent in stroke, contributing to both mortality and morbidity rates. Respiratory parameters in such patients encompass both pulmonary function and respiratory muscle strength. Identifying respiratory function variables that influence the balance and gait ability of patients with stroke is crucial for enhancing their recovery in these aspects. However, no study has assessed predictions for a comprehensive array of balance and gait abilities in such patients. We aimed to examine whether initial respiratory muscle strength and pulmonary function can predict balance and gait ability at discharge from a rehabilitation program. Thirty-one patients with stroke were included in this prospective observational study. Multiple regression models with a forward selection procedure were employed to identify respiratory parameters (including peak expiratory flow and maximal expiratory pressure) that contributed to the results of balance assessments and gait evaluations at the time of discharge. The peak expiratory flow (PEF) served as a predictor explaining 42.0% of the variance. Similarly, the maximal expiratory pressure (MEP) was a predictor variable explaining 32.0% of the variance. PEF and MEP assessments at the initial stage as predictive factors for both balance and gait ability are important in stroke management.

Indexed as

StrokeStroke RehabilitationGaitHumansLungMuscle StrengthPostural BalanceRespiratory Musclesbalancegaitpulmonary function testrespiratory muscle strengthstroke

Identifiers

PMID38063528
PMCPMC10706095
OpenAlexW4388909009

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.