Evidence map›Paper›PMID 39121088›Full record

ArticlePloS one2024

Lifestyle and mood correlates of cardiometabolic risk in people with serious mental illness on second-generation antipsychotic medications.

Susanne U Miedlich, Priya Sahay, Telva E Olivares, J Steven Lamberti, Diane S Morse, Kevin P Brazill, Kavaljit H Chhabra, Lauren Bainbridge

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

8 authors.

Susanne U MiedlichDivision of Endocrinology and Metabolism, Department of Medicine, University of Rochester School of Medicine and Dentistry, Rochester, New York, United States of America.ORCID 0000-0003-1024-0959
Priya SahayBarnegat Medical Associates, Toms River, New Jersey, United States of America.
Telva E OlivaresDepartment of Psychiatry, University of Rochester School of Medicine and Dentistry, Rochester, New York, United States of America.
J Steven LambertiDepartment of Psychiatry, University of Rochester School of Medicine and Dentistry, Rochester, New York, United States of America.
Diane S MorseDepartment of Psychiatry, University of Rochester School of Medicine and Dentistry, Rochester, New York, United States of America.
Kevin P BrazillDepartment of Psychiatry, University of Rochester School of Medicine and Dentistry, Rochester, New York, United States of America.
Kavaljit H ChhabraDepartment of Pharmacology and Nutritional Sciences, College of Medicine, University of Kentucky, Lexington, KY, United States of America.ORCID 0000-0001-6378-3645
Lauren BainbridgeDivision of Endocrinology and Metabolism, Department of Medicine, University of Rochester School of Medicine and Dentistry, Rochester, New York, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionCardiovascular morbidity and mortality are high in people with serious mental illness (SMI). This problem is mediated, at least in part, by metabolic side effects of second-generation antipsychotics (SGAs) and by unhealthy lifestyle behaviors. We asked whether oral glucose tolerance testing (oGTT) or hemoglobin A1c (HbA1c) is superior in identifying people with SMI at high cardiometabolic risk and whether this risk is shaped by mood, cognition, or lifestyle habits.

methodsWe evaluated 40 patients with schizophrenia, schizoaffective, or bipolar disorder receiving SGAs by oGTT, HbA1c, comprehensive metabolic and lipid panels, and CRP. Mood was assessed using the Patient Health Questionnaire (PHQ-9), and cognition was assessed using the Saint Louis University Mental Status examination. Diet was assessed using the UK Diabetes and Diet Questionnaire (UKDDQ), and physical activity was assessed using daily step counts.

resultsMost patients had prediabetes (preDM) or diabetes mellitus (DM), 72.5% by oGTT, and 52.5% by HbA1c criteria. Pulse rates and insulin resistance indices (Homeostatic Model Assessment of Insulin Resistance, HOMA IR; Matsuda) were significantly different between patients classified as normal or with preDM/DM, using either oGTT or HbA1c criteria. Patients with preDM/DM by HbA1c but not oGTT criteria also had higher waist/hip ratios, triglyceride, and CRP levels (p<0.05). A strong negative correlation was found between average daily step counts and CRP levels (rho = -0.62, p<0.001). Higher UKDDQ scores, or unhealthier diet habits, were associated with higher fasting plasma glucose (rho = 0.28, p = 0.08), triglyceride levels (rho = 0.31, p = 0.05), and insulin resistance (HOMA IR: rho = 0.31, p = 0.06). Higher PHQ-9 scores correlated with lower 2h-oGTT glucose levels (rho = -0.37, p<0.05).

conclusionsOGTT screening is superior to HbA1c screening in detecting preDM and DM early. Patients identified with preDM/DM by oGTT or HbA1c screening are insulin-resistant and have higher pulse rates. Abdominal obesity, unfavorable lipid profiles, and higher CRP levels were noted in patients screened by HbA1c, but not by oGTT. Low physical activity, low depression scores, and unhealthy diet habits were associated with higher CRP and higher glucose and triglyceride levels, respectively. Future studies should assess the impact of specifically tailored individual lifestyle counseling and medical management interventions in this high-risk population.

Indexed as

AffectAntipsychotic AgentsGlucose Tolerance TestGlycated HemoglobinLife StyleAdultBipolar DisorderCardiovascular DiseasesDiabetes MellitusFemaleHumansInsulin ResistanceMaleMental DisordersMiddle AgedPrediabetic StateAntipsychotic AgentsGlycated Hemoglobinhemoglobin A1c protein, human

Identifiers

PMID39121088
PMCPMC11315299

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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.