Evidence map›Paper›PMID 26407602›Full record

ArticlePsychopharmacology2016

High H1-affinity antidepressants and risk of metabolic syndrome in bipolar disorder.

Virginio Salvi, Francesco Barone-Adesi, Virginia D'Ambrosio, Umberto Albert, Giuseppe Maina

Open access · greenAbstract read
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In one paragraph

Article in Psychopharmacology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 2 pooled it
1.9field-weighted citation impact, top 16% 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

19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 38 citations in OpenAlex.

  1. Pooled it
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  10. Use of State Sequence Analysis in Pharmacoepidemiology: A Tutorial.International journal of environmental research and public health · 2021
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  14. Cardiovascular risk in patients with severe mental illness in Italy.European psychiatry : the journal of the Association of European Psychiatrists · 2020
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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 3 institutions in 1 country.

Virginio SalviDepartment of Neurosciences, University of Turin, Turin, Italy.
Francesco Barone-AdesiDepartment of Pharmaceutical Sciences, University of Eastern Piedmont, Novara, Italy.
Virginia D'AmbrosioDepartment of Neurosciences, University of Turin, Turin, Italy.
Umberto AlbertDepartment of Neurosciences, University of Turin, Turin, Italy.
Giuseppe MainaDepartment of Neuroscience, AOU San Luigi Gonzaga, University of Turin, Turin, Italy. giuseppe.maina@unito.it.
University of Turin · ITOspedale San Luigi Gonzaga · ITUniversità degli Studi del Piemonte Orientale “Amedeo Avogadro” · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

rationaleMetabolic syndrome (MetS) is common in patients with bipolar disorder, with a relative risk of 1.6-2 compared to the general population. The increased risk is believed to be due to unhealthy lifestyles and use of medications. Although antipsychotics and mood stabilizers have been associated with weight gain and MetS, the impact of antidepressants has not been comprehensively evaluated.

objectiveThe objective of the study is to assess the risk of MetS in patients exposed to different types of antidepressants.

methodsIn this cross-sectional study, 294 patients with bipolar disorder were consecutively recruited. MetS was diagnosed according to NCEP ATP-III modified criteria. Antidepressants used by the patients were classified according to the usual nomenclature (SSRI, TCA, SNRI, and other antidepressants) and a pharmacodynamic classification taking into account histamine 1-receptor (H1-R) affinity.

resultsUse of antidepressants in general was not associated with MetS (prevalence ratio [PR], 1.08; 95% confidence interval, 0.73 to 1.62; p = 0.70). However, subjects using H1-R high-affinity antidepressants (N = 15) showed a substantial increase in the prevalence of MetS (PR, 2.17; 95 % confidence interval, 1.24 to 3.80; p = 0.007). When we included the inhibition constant (Ki) as a continuous covariate in the models, we found an inverse association between Ki and prevalence of MetS (p = 0.004).

conclusionWe observed for the first time in a clinical setting that a pharmacodynamic-based classification of antidepressants could be more useful than the traditional one to predict the risk of MetS in patients with bipolar disorder. Clinical consequences may be relevant. However larger studies are warranted to generalize these results.

Indexed as

AdultAgedAntidepressive AgentsBipolar DisorderCross-Sectional StudiesFemaleHumansMaleMetabolic SyndromeMiddle AgedReceptors, Histamine H1Risk FactorsWeight GainAntidepressive AgentsReceptors, Histamine H1AffinityAntidepressantCardiovascularHistamineMetabolism

Identifiers

PMID26407602
OpenAlexW1766176086

What OpenQuestion holds

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Registered trials

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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.