Evidence map›Paper›PMID 38447549›Full record

ArticleNeuroepidemiology2024

Age and Sex Disparities in Cardiovascular Risk Factor Management prior to Stroke: Linked Registry and General Practice Data.

Kiran Bam, Monique F Kilkenny, Joosup Kim, Dominique A Cadilhac, Christopher Pearce, Nadine E Andrew, Lauren Sanders, Amanda G Thrift, Mark R Nelson, Seana Gall and 2 more

Open access · greenAbstract read
In one paragraph

Article in Neuroepidemiology, 2024. 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
0.8field-weighted citation impact, top 27% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Observational
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

12 authors at 4 institutions in 1 country.

Kiran BamStroke and Ageing Research, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia, kiran.bam@monash.edu.
Monique F KilkennyStroke and Ageing Research, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
Joosup KimStroke and Ageing Research, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
Dominique A CadilhacStroke and Ageing Research, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
Christopher PearceOutcome Health, Blackburn, Victoria, Australia.
Nadine E AndrewPeninsula Clinical School, Central Clinical School, Monash University, Frankston, Victoria, Australia.
Lauren SandersSt Vincent's Hospital, Melbourne, Victoria, Australia.
Amanda G ThriftStroke and Ageing Research, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
Mark R NelsonMenzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia.
Seana GallStroke and Ageing Research, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
Galina DaraganovaSouth East Melbourne Primary Health Network, Melbourne, Victoria, Australia.
Muideen T OlaiyaStroke and Ageing Research, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
Monash Health · AUMonash University · AUSt Vincent's Hospital · AUUniversity of Tasmania · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThere is limited evidence about the management of cardiovascular risk factors within 12 months before stroke or transient ischaemic attack (TIA) in Australian general practices. We evaluated whether age and sex disparities in cardiovascular risk factor management for primary prevention exist in general practice.

methodsA retrospective cohort study using data from the Australian Stroke Clinical Registry (2014-2018) linked with general practice data from three Primary Health Networks in Victoria, Australia. We included adults who had ≥2 encounters with a general practitioner within 12 months immediately before the first stroke/TIA. Cardiovascular risk factor management within 12 months before stroke/TIA was evaluated in terms of: assessment of risk factors (blood pressure [BP], serum lipids, blood glucose, body weight); prescription of prevention medications (BP-lowering, lipid-lowering, glucose-lowering, antithrombotic agents); and attainment of risk factor targets.

resultsOf 2,880 patients included (median age 76.5 years, 48.4% women), 80.9% were assessed for BP, 49.9% serum lipids, 46.8% blood glucose, and 39.3% body weight. Compared to patients aged 65-84 years, those aged <65 or ≥85 years were less often assessed for risk factors, with women aged ≥85 years assessed for significantly fewer risk factors than their male counterparts. The most prescribed prevention medications were BP-lowering (64.9%) and lipid-lowering agents (42.0%). There were significant sex differences among those aged <65 years (34.7% women vs. 40.2% men) and ≥85 years (34.0% women vs. 44.3% men) for lipid-lowering agents. Risk factor target attainment was generally poorer in men than women, especially among those aged <65 years.

conclusionAge-sex disparity exists in risk factor management for primary prevention in general practice, and this was more pronounced among younger patients and older women.

Indexed as

General PracticeRegistriesStrokeAgedAged, 80 and overAge FactorsCardiovascular DiseasesFemaleHeart Disease Risk FactorsHumansIschemic Attack, TransientMaleMiddle AgedRetrospective StudiesRisk FactorsSex FactorsCardiovascular risk factorsGeneral practiceHealthcare disparitiesPrimary health carePrimary preventionStroke

Identifiers

PMID38447549
PMCPMC11449173
OpenAlexW4394739269

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.