Evidence map›Paper›PMID 30141022›Full record

SynthesisSports medicine (Auckland, N.Z.)2018

Biomarkers of Physiological Responses to Periods of Intensified, Non-Resistance-Based Exercise Training in Well-Trained Male Athletes: A Systematic Review and Meta-Analysis.

Grace Greenham, Jonathan D Buckley, Joel Garrett, Roger Eston, Kevin Norton

Abstract readMeta-AnalysisSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Sports medicine (Auckland, N.Z.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 3 pooled it
5.4field-weighted citation impact, top 4% 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

38 citing papers in PubMed, 3 syntheses or guidelines pooled it, 66 citations in OpenAlex.

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  2. Probiotics for preventing acute upper respiratory tract infections.The Cochrane database of systematic reviews · 2022
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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 at 1 institution in 1 country.

Grace GreenhamAlliance for Research in Exercise, Nutrition and Activity (ARENA), Sansom Institute for Health Research and School of Health Sciences, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia. grace.greenham@mymail.unisa.edu.au.
Jonathan D BuckleyAlliance for Research in Exercise, Nutrition and Activity (ARENA), Sansom Institute for Health Research and School of Health Sciences, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia.
Joel GarrettAlliance for Research in Exercise, Nutrition and Activity (ARENA), Sansom Institute for Health Research and School of Health Sciences, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia.
Roger EstonAlliance for Research in Exercise, Nutrition and Activity (ARENA), Sansom Institute for Health Research and School of Health Sciences, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia.
Kevin NortonAlliance for Research in Exercise, Nutrition and Activity (ARENA), Sansom Institute for Health Research and School of Health Sciences, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia.
University of South Australia · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIntensified training is important for inducing adaptations to improve athletic performance, but detrimental performance effects can occur if prescribed inappropriately. Monitoring biomarker responses to training may inform changes in training load to optimize performance.

objectiveThis systematic review and meta-analysis aimed to identify biomarkers associated with altered exercise performance following intensified training.

methodsEmbase, MEDLINE, CINAHL, Scopus and SPORTDiscus were searched up until September 2017. Included articles were peer reviewed and reported on biomarkers collected at rest in well-trained male athletes before and after periods of intensified training.

resultsThe full text of 161 articles was reviewed, with 59 included (708 participants) and 42 (550 participants) meta-analysed. In total, 118 biomarkers were evaluated, with most being cellular communication and immunity markers (n = 54). Studies most frequently measured cortisol (n = 34), creatine kinase (n = 25) and testosterone (n = 20). Many studies reported decreased immune cell counts following intensified training, irrespective of performance. Moreover, reduced performance was associated with a decrease in neutrophils (d = - 0.57; 95% confidence interval (CI) - 1.07 to - 0.07) and glutamine (d = - 0.37; 95% CI - 0.43 to - 0.31) and an increase in urea concentration (d = 0.80; 95% CI 0.30 to 1.30). In contrast, increased performance was associated with an increased testosterone:cortisol ratio (d = 0.89; 95% CI 0.54 to 1.24). All remaining biomarkers showed no consistent patterns of change with performance.

conclusionsMany biomarkers were altered with intensified training but not in a manner related to changes in exercise performance. Neutrophils, glutamine, urea and the testosterone:cortisol ratio exhibited some evidence of directional changes that corresponded with performance changes therefore indicating potential to track performance. Additional investigations of the potential for these markers to track altered performance are warranted.

Indexed as

AthletesExerciseAthletic PerformanceBiomarkersCreatine KinaseGlutamineHumansHydrocortisoneLymphocyte CountMaleNeutrophilsTestosteroneUreaBiomarkersCreatine KinaseGlutamineHydrocortisoneTestosteroneUrea

Identifiers

PMID30141022
OpenAlexW2888450235

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.