ArticleCardiovascular diagnosis and therapy2013
Improved diagnosis and prognosis using Decisions Informed by Combining Entities (DICE): results from the NHLBI-sponsored Women's Ischemia Syndrome Evaluation (WISE).
Article in Cardiovascular diagnosis and therapy, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed, 3 citations in OpenAlex.
- Even "WISE-R?"-an Update on the NHLBI-Sponsored Women's Ischemia Syndrome Evaluation.Current atherosclerosis reports · 2020Review
- Use of bio-informatics assessment schema (BIAS) to improve diagnosis and prognosis of myocardial perfusion data: results from the NHLBI-sponsored women's ischemia syndrome evaluation (WISE).Cardiovascular diagnosis and therapy · 2016Article
- The potential value of discordant studies.Cardiovascular diagnosis and therapy · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 9 institutions in 1 country.
Funding
Abstract
objectivesTo introduce an algorithmic approach to improve the interpretation of myocardial perfusion images in women with suspected myocardial ischemia.
backgroundGated single photon emission computed tomography (SPECT) and magnetic resonance (MR) myocardial perfusion imaging (MPI) approaches have relatively poor diagnostic and prognostic value in women with suspected myocardial ischemia. Here we introduce an approach: Decisions Informed by Combining Entities (DICE) that forms a mathematical model utilizing MPI and cardiac dimensions generated by one modality to predict the perfusion status of another modality. The effect of the model is to systematically incorporate cardiac metrics that influence the interpretation of perfusion images, leading to greater consistency in designation of myocardial perfusion status between studies.
methodsWomen (n=213), with suspected myocardial ischemia, underwent MPI assessment for regional perfusion defects using two modalities: gated SPECT (n=207) and MR imaging (n=203). To determine perfusion status, MR data were evaluated qualitatively and semi-quantitatively while SPECT data were evaluated using conventional clinical criteria. These perfusion status readings were designated "Original". Four regression models were generated to model perfusion status obtained with one modality [e.g., semi-quantitative magnetic resonance imaging (MRI)] against another modality (e.g., SPECT) and a threshold applied (DICE modeling) to designate perfusion status as normal or low. The DICE models included perfusion status, left ventricular (LV) chamber volumes and myocardial wall thickness. Women were followed for 40±16 months for the development of first major adverse cardiovascular event (MACE: CV death, nonfatal myocardial infarction (MI) or hospitalization for congestive heart failure). Original and DICE perfusion status were compared in their ability to detect high-grade coronary artery disease (CAD) and for prediction of MACE.
resultsAdverse events occurred in 25 (12%) women and CAD was present in 34 (16%). In receiver-operator characteristic (ROC) analysis for CAD detection, the average area under the curve (AUC) for DICE vs. Original status was 0.77±0.03 vs. 0.70±0.03, P<0.01. Similarly, in Kaplan-Meier survival analysis the average log-rank statistic was higher for DICE vs. the Original readings (10.6±5.2 vs. 3.0±0.6, P<0.05).
conclusionsWhile two data sets are required to generate the DICE models no knowledge of follow-up results is needed. DICE modeling improved diagnostic and prognostic value vs. the Original interpretation of the myocardial perfusion status.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.