Myocardial perfusion imaging and risk classification for coronary heart disease in diabetic patients. The IDIS study: a prospective, multicentre trial View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2012-03

AUTHORS

Wanda Acampa, Mario Petretta, Laura Evangelista, Stefania Daniele, Evgjeni Xhoxhi, Maria Luisa De Rimini, Corrado Cittanti, Filippo Marranzano, Marco Spadafora, Sergio Baldari, Luigi Mansi, Alberto Cuocolo

ABSTRACT

PURPOSE: To determine whether stress-rest myocardial perfusion single-photon emission (MPS) computed tomography improves coronary heart disease (CHD) risk classification in diabetic patients. METHODS: In 822 consecutive diabetic patients, risk estimates for a CHD event were categorized as 0% to <3%, 3% to <5%, and ≥5% per year using Cox proportional hazards models. Model 1 used traditional CHD risk factors and electrocardiography (ECG) stress test data and model 2 used these variables plus MPS imaging data. We calculated the net reclassification improvement (NRI) and compared the distribution of risk using model 2 vs. model 1. CHD death, myocardial infarction and unstable angina requiring coronary revascularization were the outcome measures. RESULTS: During follow-up (58 ± 11 months), 148 events occurred. Model 2 improved risk prediction compared to model 1 (NRI 0.25, 95% confidence interval, CI, 0.15-0.34; p < 0.001). Overall, 301 patients were reclassified to a higher risk category, with an event rate of 28%, and 26 to a lower risk category, with an event rate of 15%. Among patients at 3% to <5% risk, 53% were reclassified at higher risk and 25% at lower risk (NRI 0.42, 95% CI 0.07-0.76; p < 0.05). The cost per NRI was $880.80 for MPS imaging as compared to an outpatient visit with an ECG stress test. CONCLUSION: The addition of MPS imaging data to a prediction model based on traditional risk factors and ECG stress test data significantly improved CHD risk classification in patients with diabetes. More... »

PAGES

387-395

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00259-011-1983-x

DOI

http://dx.doi.org/10.1007/s00259-011-1983-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1023099451

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/22109666


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s00259-011-1983-x'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s00259-011-1983-x'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00259-011-1983-x'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00259-011-1983-x'


 

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327 https://www.grid.ac/institutes/grid.9841.4 schema:alternateName Second University of Naples
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