Evidence map›Paper›PMID 20352257›Full record

ArticleEuropean journal of applied physiology2010

The validity and reliability of predicting maximal oxygen uptake from a treadmill-based sub-maximal perceptually regulated exercise test.

Michael Morris, Kevin L Lamb, John Hayton, David Cotterrell, John Buckley

Abstract readValidation Study
PubMed Publisher
In one paragraph

Article in European journal of applied physiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing 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.

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

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

  1. Pooled it
  2. Pooled it
  3. Article
  4. Assessment of Maximal Aerobic Capacity in Ski Mountaineering: A Laboratory-Based Study.International journal of environmental research and public health · 2021
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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

5 authors.

Michael MorrisUniversity of Chester, Parkgate Road, Chester, UK.
Kevin L Lamb
John Hayton
David Cotterrell
John Buckley

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of this study was to determine for the first time whether VO2max could be predicted accurately and reliably from a treadmill-based perceptually regulated exercise test (PRET) incorporating a safer and more practical upper limit of RPE 15 ("Hard") than used in previous investigations. Eighteen volunteers (21.7 +/- 2.8 years) completed three treadmill PRETs (each separated by 48 h) and one maximal graded exercise test. Participants self-regulated their exercise at RPE levels 9, 11, 13 and 15 in a continuous and incremental fashion. Oxygen uptake VO2 was recorded continuously during each 3 min bout. VO2 values for the RPE range 9-15 were extrapolated to RPE(19) and RPE(20) using regression analysis to predict individual VO2max scores. The optimal limits of agreement (LoA) between actual (48.0 +/- 6.2 ml kg(-1) min(-1)) and predicted scores were -0.6 +/- 7.1 and -2.5 +/- 9.4 ml kg(-1) min(-1) for the RPE(20) and RPE(19) models, respectively. Reliability analysis for the VO2max predictions yielded LoAs of 1.6 +/- 8.5 (RPE(20)) and 2.7 +/- 9.4 (RPE(19)) ml kg(-1) min(-1) between trials 2 and 3. These findings demonstrate that (with practice) a novel treadmill-based PRET can yield predictions of VO2max that are acceptably reliable and valid amongst young, healthy, and active adults.

Indexed as

Exercise TestExerciseFemaleHumansMaleOxygen ConsumptionPerceptionPhysical ExertionPredictive Value of TestsRegression AnalysisReproducibility of ResultsYoung Adult

Identifiers

What OpenQuestion holds

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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.