Evidence map›Paper›PMID 37488548›Full record

ArticleBMC psychiatry2023

Cardiovascular risk assessment methods yield unequal risk predictions: a large cross-sectional study in psychiatric secondary care outpatients.

Davy Quadackers, Edith Liemburg, Fionneke Bos, Bennard Doornbos, Arne Risselada, PHAMOUS investigators, Marjolein Berger, Ellen Visser, Danielle Cath

Open access · goldAbstract read
In one paragraph

Article in BMC psychiatry, 2023. 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
1.6field-weighted citation impact, top 18% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Predicting cardiovascular disease in patients with mental illness using machine learning.European psychiatry : the journal of the Association of European Psychiatrists · 2025
    Article
  3. Review
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

9 authors at 2 institutions in 1 country.

Davy QuadackersMental Health Services Drenthe, P.O. box 30007, 9400 RA, Assen, The Netherlands. davy.quadackers@ggzdrenthe.nl.ORCID 0000-0002-7103-369X
Edith LiemburgDepartment of Psychiatry, University of Groningen, University Medical Center Groningen, Rob Giel Research Center, P.O. box 30.001, 9700 RB, Groningen, The Netherlands.
Fionneke BosDepartment of Psychiatry, University of Groningen, University Medical Center Groningen, Rob Giel Research Center, P.O. box 30.001, 9700 RB, Groningen, The Netherlands.
Bennard DoornbosResearch Department, Lentis Psychiatric Institute, Hereweg 80, 9725 AG, Groningen, The Netherlands.
Arne RisseladaDepartment of Clinical Pharmacy, Wilhelmina Hospital, Assen, The Netherlands.
PHAMOUS investigators
Marjolein BergerDepartment of General Practice & Elderly Care Medicine, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
Ellen VisserDepartment of Psychiatry, University of Groningen, University Medical Center Groningen, Rob Giel Research Center, P.O. box 30.001, 9700 RB, Groningen, The Netherlands.
Danielle CathMental Health Services Drenthe, P.O. box 30007, 9400 RA, Assen, The Netherlands.
University Medical Center Groningen · NLLentis · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients with a mental illness are more likely to develop, and die from, cardiovascular diseases (CVD), necessitating optimal CVD-risk (CVR)-assessment to enable early detection and treatment. Whereas psychiatrists use the metabolic syndrome (MetS)-concept to estimate CVR, GPs use absolute risk-models. Additionally, two PRIMROSE-models have been specifically designed for patients with severe mental illness. We aimed to assess the agreement in risk-outcomes between these CVR-methods.

methodsTo compare risk-outcomes across the various CVR-methods, we used somatic information of psychiatric outpatients from the PHAMOUS-, and MOPHAR-database, aged 40-70 years, free of past or current CVD and diabetes. We investigated: (1) the degree-of-agreement between categorical assessments (i.e. MetS-status vs. binary risk-categories); (2) non-parametric correlations between the number of MetS-criteria and absolute risks; and (3) strength-of-agreement between absolute risks.

resultsSeven thousand twenty-nine measurements of 3509 PHAMOUS-patients, and 748 measurements of 748 MOPHAR-patients, were included. There was systematic disagreement between the categorical CVR-assessments (all p < 0.036). Only MetS-status versus binary Framingham-assessment had a fair strength-of-agreement (κ = 0.23-0.28). The number of MetS-criteria and Framingham-scores, as well as MetS-criteria and PRIMROSE lipid-scores, showed a moderate-strong correlation (τ = 0.25-0.34). Finally, only the continuous PRIMROSE desk and lipid-outcomes showed moderate strength-of-agreement (ρ = 0.91).

conclusionsThe varying methods for CVR-assessment yield unequal risk predictions, and, consequently, carry the risk of significant disparities regarding treatment initiation in psychiatric patients. Considering the significantly increased health-risks in psychiatric patients, CVR-models should be recalibrated to the psychiatric population from adolescence onwards, and uniformly implemented by health care providers.

trial registrationThe MOPHAR research has been prospectively registered with the Netherlands Trial Register on 19th of November 2014 (NL4779).

Indexed as

Cardiovascular DiseasesMetabolic SyndromeAdolescentCross-Sectional StudiesHeart Disease Risk FactorsHumansLipidsOutpatientsRisk FactorsSecondary Health CareLipidsCardiovascular risk assessmentMetabolic syndromePsychiatric patients

Identifiers

PMID37488548
PMCPMC10367364
OpenAlexW4385225800

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.