Evidence map›Paper›PMID 41675412›Full record

ArticlePain reports2026

Baseline vagal tone and pain reactivity: linking autonomic function to endogenous pain inhibition in women.

Einav Gozansky, Hadas Okon-Singer, Irit Weissman-Fogel

Abstract read
In one paragraph

Article in Pain reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Trial
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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

3 authors.

Einav GozanskyDepartment of Psychology, School of Psychological Sciences, University of Haifa, Haifa, Israel.
Hadas Okon-SingerDepartment of Psychology, School of Psychological Sciences, University of Haifa, Haifa, Israel.
Irit Weissman-FogelThe Integrated Brain and Behavior Research Center (IBBR), University of Haifa, Haifa, Israel.ORCID https://orcid.org/0000-0001-5675-8919

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Conditioned pain modulation (CPM) is a laboratory test of the efficacy of endogenous pain inhibition. Although the vagus nerve is thought to contribute to analgesia via descending inhibitory pathways, its role in CPM remains unclear. In addition, as vagal tone fluctuates across the menstrual cycle due to hormonal changes, the menstrual cycle's influence on the vagal-CPM association warrants investigation. Methods: Sixty-seven healthy females completed psychological questionnaires and underwent psychophysical assessments (1-minute tonic heat pain [THP] given alone and during CPM). An electrocardiogram was recorded at rest, and in 1-minute segments before, during, and after the THP alone, as well as during a conditioning stimulus (CPM paradigm). Heart rate variability was assessed using time- and frequency-domain indices. Menstrual phase was categorized as either follicular or luteal based on standard cycle-length division. Results: The interaction between the resting root mean square of successive differences (RMSSD) and the menstrual cycle predicted better CPM efficiency. Post-hoc analysis revealed that the vagal-CPM association emerged solely in the follicular phase (β = -1.05, Conclusions: The findings suggest a tentative menstrual cycle-dependent association between baseline vagal tone and pain inhibition in healthy females. Further, greater vagal activity contributes to more efficient pain inhibition. Future studies should use within-subject designs to examine how interactions between vagal and sympathetic activity across the menstrual cycle influence pain modulation.

Indexed as

Healthy femalesMenstrual cyclePain inhibitionVagal reactivityVagal tone

Identifiers

PMID41675412
PMCPMC12889303

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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.