Evidence map›Paper›PMID 35992499›Full record

ArticleInternational journal of exercise science2022

Prediction of Functional Threshold Power from Graded Exercise Test Data in Highly-Trained Individuals.

Eanna McGRATH, Nick Mahony, Neil Fleming, Alessio Benavoli, Bernard Donne

Abstract read
In one paragraph

Article in International journal of exercise science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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

2 citing papers in PubMed.

  1. Article
  2. 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.

Eanna McGRATHHuman Performance Laboratory, Disciplines of Anatomy and Physiology, School of Medicine, Trinity College Dublin, IRL.
Nick MahonyHuman Performance Laboratory, Disciplines of Anatomy and Physiology, School of Medicine, Trinity College Dublin, IRL.
Neil FlemingHuman Performance Laboratory, Disciplines of Anatomy and Physiology, School of Medicine, Trinity College Dublin, IRL.
Alessio BenavoliSchool of Computer Science and Statistics, Trinity College Dublin, IRL.
Bernard DonneHuman Performance Laboratory, Disciplines of Anatomy and Physiology, School of Medicine, Trinity College Dublin, IRL.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of the current investigation was to derive an equation that could predict Functional Threshold Power (FTP) from Graded Exercise Test (GxT) data. The FTP test has been demonstrated to represent the highest cycling power output that can be maintained in a quasi-steady state for 60-min. Previous investigations to determine a comparable marker derived from a Graded Exercise test have had limited success to date. Consequently, the current study aimed to predict FTP from GxT data to provide an additional index of cycling performance. FTP has been reported to provide an insight not provided by a GxT and, in addition, does not require a formal exercise testing facility. The study design facilitated a deliberate and transparent sequence of statistical decisions, resolved in part from the perspective of exercise physiology. Seventy triathletes (male n=50, female n=20) completed cycling GxT and FTP tests in sequential order. Collected data (power output, blood lactate indices, VO

Indexed as

cross-validationlactate profilemodellingstepwise regressionTriathlon

Identifiers

PMID35992499
PMCPMC9365101

What OpenQuestion holds

Textmetadata
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.