Evidence map›Paper›PMID 41036582›Full record

ArticlePhysiological reports2025

Hormonal and inflammatory responses to high-intensity functional training in male soldiers.

Joonas Helén, Heikki Kyröläinen, Tommi Ojanen, Kai Pihlainen, Risto Heikkinen, Jani P Vaara

Abstract read
In one paragraph

Article in Physiological reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Joonas HelénDepartment of Leadership and Military Pedagogy, National Defence University, Helsinki, Finland.
Heikki KyröläinenDepartment of Leadership and Military Pedagogy, National Defence University, Helsinki, Finland.
Tommi OjanenFaculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland.
Kai PihlainenTraining Division, Defence Command, Finnish Defence Forces, Helsinki, Finland.
Risto HeikkinenStatistical Analysis Services, Analyysitoimisto Statisti Oy, Jyväskylä, Finland.
Jani P VaaraDepartment of Leadership and Military Pedagogy, National Defence University, Helsinki, Finland.

Funding

Finnish Defence Forces Defence CommandNational Defence Foundation
6 · The paper itself

Abstract

This study investigated the effects of high-intensity functional training (HIFT) on hormonal and inflammatory biomarker responses during military service. One hundred and twenty-seven male conscripts were assessed over a 19-week training period. The experimental group (EXP: n = 64) followed a structured HIFT program, while the control group (CON: n = 63) adhered to conventional military physical training. Blood samples were collected at baseline (PRE), week 10 (MID), and post-intervention (POST) to measure serum testosterone, cortisol, testosterone/cortisol ratio, insulin-like growth factor 1 (IGF-1), sex hormone-binding globulin (SHBG), high-sensitivity C-reactive protein (hs-CRP), interleukin 6 (IL-6), and tumor necrosis factor alpha (TNF-α). Body composition and physical performance were also measured. Serum testosterone increased in both groups between PRE and POST (EXP: +3.3 ± 3.8 nmol·L

Indexed as

InflammationMilitary PersonnelPhysical Conditioning, HumanTestosteroneAdultBiomarkersC-Reactive ProteinHumansHydrocortisoneInsulin-Like Growth Factor IInterleukin-6MaleSex Hormone-Binding GlobulinTumor Necrosis Factor-alphaYoung AdultBiomarkersC-Reactive ProteinHydrocortisoneInsulin-Like Growth Factor IInterleukin-6Sex Hormone-Binding GlobulinTestosteroneTumor Necrosis Factor-alphabiomarkersfitnesshigh intensityhormonesinflammationmilitary

Identifiers

PMID41036582
PMCPMC12489465

What OpenQuestion holds

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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.