Evidence map›Paper›PMID 37141260›Full record

ArticlePloS one2023

Efficacy of home-based inspiratory muscle training in patients post-covid-19: Protocol for a randomized clinical trial.

Gabriely Azevêdo Gonçalo Silva, Ivan Daniel Bezerra Nogueira, Gaspar Rogério da Silva Chiappa, Patrícia Angélica de Miranda Silva Nogueira

Registry-linked trialOpen access · goldAbstract readClinical Trial Protocol
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05077241 (Efficacy of Home Inspiratory Muscle Training in Post-covid-19 Patients), which is not on this map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.4field-weighted citation impact, top 18% 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.

NCT05077241 naunknown statusnot on this map

Efficacy of Home Inspiratory Muscle Training in Post-covid-19 Patients: a Randomized Clinical Trial

TypeinterventionalSponsorUniversidade Federal do Rio Grande do NorteRan2023 to 2024Enrolled10ConditionsCovid19ArmsInspiratory muscle training
3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
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  5. Observational
  6. Review
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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 at 1 institution in 1 country.

Gabriely Azevêdo Gonçalo SilvaPostgraduate Program in Physiotherapy (PPGFIS), Laboratory of Measures and Evaluation in Health, Federal University of Rio Grande do Norte (UFRN), Natal, Rio Grande do Norte, Brazil.ORCID 0000-0002-6995-1280
Ivan Daniel Bezerra NogueiraDepartment of Physical Therapy, Federal University of Rio Grande do Norte (UFRN), Natal, Rio Grande do Norte, Brazil.ORCID 0000-0001-8190-7656
Gaspar Rogério da Silva ChiappaUniversity Center of Anápolis (Evangelical University of Goiás), Human Movement and Rehabilitation Graduate Program, Anápolis, Goiás, Brazil.
Patrícia Angélica de Miranda Silva NogueiraDepartment of Physical Therapy, Federal University of Rio Grande do Norte (UFRN), Natal, Rio Grande do Norte, Brazil.ORCID 0000-0002-3763-2410
Universidade Federal do Rio Grande do Norte · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionCurrent evidence suggests the emergence of a novel syndrome (long COVID syndrome) due to sequels and persistent COVID-19 symptoms. Respiratory muscle training improves respiratory muscle strength, exercise capacity, diaphragm thickness, and dyspnea, especially in patients with decreased respiratory muscle strength. This study aims to evaluate the effectiveness of a protocol for home-based inspiratory muscle training to improve respiratory muscle strength, dyspnea, and quality of life of patients post-COVID-19. METHODS AND ANALYSES: This randomized, controlled, double-blind clinical trial will be conducted at the Instituto de Medicina Tropical of Universidade Federal do Rio Grande do Norte (Brazil). Sample size will be determined using maximal inspiratory pressure after a pilot study with five patients per group (total of 10 patients). Patients included in the study will be evaluated in three moments: pre-training (initial), post-training (three weeks), and retention (24 weeks). The sample will be randomized in two groups: active (IMT using 30% of IMT and load increase of 10% of initial IMT every week. Patients will perform 30 repetitions, twice a day (morning and afternoon), for seven consecutive days, and six weeks) and SHAM (IMT without load). The following measurements will be assessed: anthropometry, respiratory muscle strength, pulmonary volume and capacity, dyspnea, perception of effort and lower limb fatigue, handgrip strength, functional capacity, anxiety, depression, and functional status. After initial evaluation, all patients will receive a POWERbreathe® (POWERbreathe®, HaB Ltd, Southam, UK) device to perform the training. Normality will be verified using Shapiro-Wilk or Kolmogorov-Smirnov, according to the number of patients included. Variables presenting nonparametric distribution will be compared using Wilcoxon (intragroup analysis) and Mann-Whitney test (intergroup analysis), whereas repeated measures two-way ANOVA will be performed in case of parametric distribution. Dunn's post hoc test will be used to identify significant differences in the two-way ANOVA test. PRIMARY OUTCOMES: Respiratory muscle strength, dyspnea, and quality of life of post-COVID-19 patients. SECOND OUTCOMES: Pulmonary function, dyspnea, exercise tolerance, handgrip strength, anxiety, depression, and functional status.

trial registrationTrial register number NCT05077241.

Indexed as

COVID-19Quality of LifeBreathing ExercisesDiaphragmDyspneaExercise ToleranceHand StrengthHumansMuscle StrengthPilot ProjectsPost-Acute COVID-19 SyndromeRandomized Controlled Trials as TopicRespiratory Muscles

Identifiers

PMID37141260
PMCPMC10159136
OpenAlexW4368358110

What OpenQuestion holds

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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.