Evidence map›Paper›PMID 35807154›Full record

ArticleJournal of clinical medicine2022

Diversity of Hemodynamic Reactive Profiles across Persons-Psychosocial Implications for Personalized Medicine.

Miguel Ángel Gandarillas, Nandu Goswami

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Miguel Ángel GandarillasDepartment of Social, Work, and Differential Psychology, School of Psychology, Complutense University of Madrid, Campus de Somosagua, Ctra. de Húmera, s/n, Pozuelo de Alarcón, 28223 Madrid, Spain.ORCID 0000-0003-0943-4879
Nandu GoswamiPhysiology Division, Otto Loewi Center of Vascular Biology, Immunity and Inflammation, Medical University of Graz, 8036 Graz, Austria.ORCID 0000-0002-6704-0723

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study analyzed the individual differences in hemodynamic time patterns and reactivity to cognitive and emotional tasks, and explored the diversity of psycho-physiological profiles that could be used for the personalized prediction of different diseases. An analysis of heart rate (HR)-blood pressure (BP) relationship patterns across time using cross-correlations (CCs) during a logical-mathematical task and a task recalling negative emotions (rumination) was carried out in a laboratory setting on 45 participants. The results showed maximum HR-BP CCs during the mathematical task significantly more positive than the maximum HR-BP CCs during the rumination task. Furthermore, our results showed a large variety of hemodynamic reactivity profiles across the participants, even when carrying out the same tasks. The most frequent type showed positive HR-BP CCs under cognitive activity, and several positive-negative HR-BP CCs cycles under negative emotional activity. In general terms, our results supported the main hypothesis. We observed some distinct time-based "coordination strategies" in the reactivity of the autonomic nervous system under emotional vs. cognitive loading. Overall, large individual, as well as situational, specificities in hemodynamic reactivity time patterns were seen. The possible relationships between this variety of profiles and different psychosocial characteristics, and the potential for integrative predictive health within the provision of highly personalized medicine, are discussed.

Indexed as

autonomic nervous systemhemodynamicsintegrative medicinepersonalized medicinepredictive healthpsychosocial factors

Identifiers

PMID35807154
PMCPMC9267141

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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.