Evidence map›Paper›PMID 36227638›Full record

ArticleJMIR medical informatics2022

Coronary Artery Computed Tomography Angiography for Preventing Cardio-Cerebrovascular Disease: Observational Cohort Study Using the Observational Health Data Sciences and Informatics' Common Data Model.

Woo Kyung Bae, Jihoon Cho, Seok Kim, Borham Kim, Hyunyoung Baek, Wongeun Song, Sooyoung Yoo

Open access · goldAbstract read
In one paragraph

Article in JMIR medical informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 38% 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, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
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

7 authors at 1 institution in 1 country.

Woo Kyung Bae *Department of Family Medicine, Health Promotion Center, Seoul National University Bundang Hospital, Republic of Korea, Bundang-gu, Seongnam-si, Gyeonggi-do, Republic of Korea.ORCID https://orcid.org/0000-0001-6729-4128
Jihoon Cho *Healthcare Information and Communication Technology Research Center, Office of eHealth Research and Business, Seoul National University Bundang Hospital, Republic of Korea, Seongnam-si, Republic of Korea.ORCID https://orcid.org/0000-0003-0568-9380
Seok KimHealthcare Information and Communication Technology Research Center, Office of eHealth Research and Business, Seoul National University Bundang Hospital, Republic of Korea, Seongnam-si, Republic of Korea.ORCID https://orcid.org/0000-0003-4996-8613
Borham KimHealthcare Information and Communication Technology Research Center, Office of eHealth Research and Business, Seoul National University Bundang Hospital, Republic of Korea, Seongnam-si, Republic of Korea.ORCID https://orcid.org/0000-0002-6914-5721
Hyunyoung BaekHealthcare Information and Communication Technology Research Center, Office of eHealth Research and Business, Seoul National University Bundang Hospital, Republic of Korea, Seongnam-si, Republic of Korea.ORCID https://orcid.org/0000-0003-0810-9396
Wongeun SongHealthcare Information and Communication Technology Research Center, Office of eHealth Research and Business, Seoul National University Bundang Hospital, Republic of Korea, Seongnam-si, Republic of Korea.ORCID https://orcid.org/0000-0003-4314-3995
Sooyoung YooHealthcare Information and Communication Technology Research Center, Office of eHealth Research and Business, Seoul National University Bundang Hospital, Republic of Korea, Seongnam-si, Republic of Korea.ORCID https://orcid.org/0000-0001-8620-4925
Seoul National University Bundang Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCardio-cerebrovascular diseases (CVDs) result in 17.5 million deaths annually worldwide, accounting for 46.2% of noncommunicable causes of death, and are the leading cause of death, followed by cancer, respiratory disease, and diabetes mellitus. Coronary artery computed tomography angiography (CCTA), which detects calcification in the coronary arteries, can be used to detect asymptomatic but serious vascular disease. It allows for noninvasive and quick testing despite involving radiation exposure.

objectiveThe objective of our study was to investigate the effectiveness of CCTA screening on CVD outcomes by using the Observational Health Data Sciences and Informatics' Observational Medical Outcomes Partnership Common Data Model (OMOP-CDM) data and the population-level estimation method.

methodsUsing electronic health record-based OMOP-CDM data, including health questionnaire responses, adults (aged 30-74 years) without a history of CVD were selected, and 5-year CVD outcomes were compared between patients undergoing CCTA (target group) and a comparison group via 1:1 propensity score matching. Participants were stratified into low-risk and high-risk groups based on the American College of Cardiology/American Heart Association atherosclerotic cardiovascular disease (ASCVD) risk score and Framingham risk score (FRS) for subgroup analyses.

resultsThe 2-year and 5-year risk scores were compared as secondary outcomes between the two groups. In total, 8787 participants were included in both the target group and comparison group. No significant differences (calibration P=.37) were found between the hazard ratios of the groups at 5 years. The subgroup analysis also revealed no significant differences between the ASCVD risk scores and FRSs of the groups at 5 years (ASCVD risk score: P=.97; FRS: P=.85). However, the CCTA group showed a significantly lower increase in risk scores at 2 years (ASCVD risk score: P=.03; FRS: P=.02).

conclusionsAlthough we could not confirm a significant difference in the preventive effects of CCTA screening for CVDs over a long period of 5 years, it may have a beneficial effect on risk score management over 2 years.

Indexed as

angiographycardiologycardiovascular diseasescommon data modelcomputed tomographycoronary artery computed tomography angiographydata modelingelectronic health recordhealth data sciencemedical informaticsobservational studypopulation level estimationrisk scorevascular disease

Identifiers

PMID36227638
PMCPMC9614618
OpenAlexW4304974837

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.