Evidence map›Paper›PMID 41409581›Full record

ArticleBioImpacts : BI2025

Enantioselective analysis of metoprolol in plasma of hypertensive patients undergoing long-term therapy: Insights for personalized medicine.

Behrouz Seyfinejad, Kimiya Jouyban, Jalil Houshyar, Amirreza Jabbaripour Sarmadian, Abolghasem Jouyban

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Article in BioImpacts : BI, 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

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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

5 authors.

Behrouz SeyfinejadCellular and Molecular Research Center, Cellular and Molecular Medicine Research Institute, Urmia University of Medical Sciences, Urmia, Iran.ORCID https://orcid.org/0000-0001-6449-6007
Kimiya JouybanExperimental Medicine Research Center, Tehran University of Medical Sciences, Tehran, Iran.ORCID https://orcid.org/0000-0001-6170-1693
Jalil HoushyarEndocrine Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
Amirreza Jabbaripour SarmadianKidney Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
Abolghasem JouybanPharmaceutical Analysis Research Center, Pharmaceutical Sciences Institute, Tabriz University of Medical Sciences, Tabriz, Iran.ORCID https://orcid.org/0000-0002-4670-2783

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Metoprolol is therapeutically formulated as a racemate with stereoselective pharmacokinetics influenced by CYP2D6 polymorphism. Understanding enantioselective disposition is critical for optimizing therapy in hypertensive patients, particularly during long-term treatment, where metabolic and excretory pathways may interact unpredictably. Methods: This study analyzed plasma samples from 18 hypertensive patients on long-term metoprolol therapy using a validated chiral capillary electrophoresis method. Enantiomer concentrations were quantified, and S/R ratios were evaluated alongside patient demographics, dosing regimens, and co-administered drugs. The study design focused on identifying deviations from expected enantiomeric patterns observed in single-dose or short-term multi-dose administration in healthy individuals studies. Results: While most patients (70%) exhibited the anticipated S/R ratio≥1, 30% demonstrated inverted plasma S/R ratios (<1), suggesting altered renal excretion or CYP2D6 saturation. Conclusion: Long-term metoprolol therapy reveals complex enantioselective disposition influenced by metabolic phenotype, renal excretion and drug interactions. The unexpected S/R inversion underscores the need for personalized dosing, particularly in patients with renal impairment or polypharmacy. Enantiomer monitoring may complement pharmacogenomic strategies to optimize therapeutic outcomes.

Indexed as

CYP2D6EnantiomersEnantioselective excretionHypertensionMetoprololPersonalized medicine

Identifiers

PMID41409581
PMCPMC12705282

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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.