Evidence map›Paper›PMID 38413661›Full record

ArticleScientific reports2024

Spatial analysis of 10-year predicted risk and incident atherosclerotic cardiovascular disease: the CoLaus cohort.

Guillaume Jordan, David Ridder, Stephane Joost, Peter Vollenweider, Martin Preisig, Pedro Marques-Vidal, Idris Guessous, Julien Vaucher

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
3.4field-weighted citation impact, top 7% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

8 authors at 4 institutions in 1 country.

Guillaume JordanDepartment of Medicine, Division of Internal Medicine, Lausanne University Hospital and University of Lausanne, Rue du Bugnon 46, 1011, Lausanne, Switzerland. guillaume.jordan@chuv.ch.
David RidderDepartment of Primary Care Medicine, Division of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland.
Stephane JoostDepartment of Primary Care Medicine, Division of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland.
Peter VollenweiderDepartment of Medicine, Division of Internal Medicine, Lausanne University Hospital and University of Lausanne, Rue du Bugnon 46, 1011, Lausanne, Switzerland.
Martin PreisigCEPP, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, Switzerland.
Pedro Marques-VidalDepartment of Medicine, Division of Internal Medicine, Lausanne University Hospital and University of Lausanne, Rue du Bugnon 46, 1011, Lausanne, Switzerland.
Idris GuessousDepartment of Primary Care Medicine, Division of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland.
Julien VaucherDepartment of Medicine, Division of Internal Medicine, Lausanne University Hospital and University of Lausanne, Rue du Bugnon 46, 1011, Lausanne, Switzerland.
University of Lausanne · CHÉcole Polytechnique Fédérale de Lausanne · CHUniversity Hospital of Geneva · CHUniversity of Geneva · CH

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 3247730_204523Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 33CS30-139468Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 33CS30-148401Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 33CS30_177535Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 33CSCO-122661The Swiss Personalized Health Network 2018DRI01
6 · The paper itself

Abstract

Whether cardiovascular risk scores geographically aggregate and inform on spatial development of atherosclerotic cardiovascular diseases (ASCVD) remains unknown. Our aim is to determine the spatial distribution of 10-year predicted cardiovascular risk and ASCVD, and to compare the overlap of the resulting spatial distributions. Using prospective data from the CoLaus|PsyCoLaus cohort study (2003-2021) we computed SCORE2 in participants free from ASCVD. Geographical distributions of predicted risk and events were determined using the Gi* Getis-Ord autocorrelation statistic. 6203 individuals (54% women, mean age 52.5 ± SD 10.7, ASCVD incidence rate 5.7%) were included. We identified clusters of high versus low predicted risk (4%, 6%, respectively) and ASCVD (5%, 5% respectively) at baseline. They persisted at follow-up. Overlap of SCORE2 and ASCVD clusters was marginal. Body-mass index and alcohol consumption explained most of the predicted risk distribution. For ASCVD, high clusters persisted or were reinforced after multivariate adjustment, while low incidence clusters were reduced, multifactorial determinants. Incidence rate of ASCVD was 2.5% higher (IC 95%, 1.4-3.7) in clusters of higher incidence of ASCVD. To develop up-to-date, geographically targeted prevention strategies, there is a need to study novel geographically risk factors affecting ASCVD and to update commonly used prediction models for a population approach.

Indexed as

AtherosclerosisCardiovascular DiseasesCohort StudiesFemaleHumansMaleMiddle AgedProspective StudiesRisk AssessmentRisk FactorsSpatial Analysis

Identifiers

PMID38413661
PMCPMC10899582
OpenAlexW4392198823

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.