Evidence map›Paper›PMID 31823327›Full record

ArticleJournal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology2021

Pretest models for predicting abnormal stress single-photon emission computed tomography myocardial perfusion imaging.

Rosario Megna, Roberta Assante, Emilia Zampella, Valeria Gaudieri, Carmela Nappi, Renato Cuocolo, Teresa Mannarino, Andrea Genova, Roberta Green, Valeria Cantoni and 3 more

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Article in Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Combined evaluation of CAC score and myocardial perfusion imaging in patients at risk of cardiovascular disease: where are we and what do the data say.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023
    Review
  4. Article
  5. Machine learning to predict hemodynamically significant CAD based on traditional risk factors, coronary artery calcium and epicardial fat volume.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023
    Article
  6. Article
  7. External validation and update of the J-ACCESS model in an Italian cohort of patients undergoing stress myocardial perfusion imaging.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023
    Article
  8. A novel cardiovascular risk assessment tool for the prediction of myocardial ischemia on imaging.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023
    Article
  9. Development and validation of ischemia risk scores.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023
    Article
  10. Prognostic value of heart rate reserve in patients with suspected coronary artery disease undergoing stress myocardial perfusion imaging.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2022
    Article
  11. Article
  12. Diagnostic value of clinical risk scores for predicting normal stress myocardial perfusion imaging in subjects without coronary artery calcium.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2022
    Article
  13. Stress myocardial perfusion imaging: Can we tell the results without doing the test?Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2021
    Article
  14. Nuclear cardiac imaging between implementation and globalization: The key role of integration.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2021
    Article
  15. Article
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

13 authors.

Rosario MegnaInstitute of Biostructure and Bioimaging, National Council of Research, Naples, Italy.
Roberta AssanteDepartment of Advanced Biomedical Sciences, University Federico II, Via Pansini 5, 80131, Naples, Italy.
Emilia ZampellaDepartment of Advanced Biomedical Sciences, University Federico II, Via Pansini 5, 80131, Naples, Italy.
Valeria GaudieriInstitute of Biostructure and Bioimaging, National Council of Research, Naples, Italy.
Carmela NappiDepartment of Advanced Biomedical Sciences, University Federico II, Via Pansini 5, 80131, Naples, Italy.
Renato CuocoloDepartment of Advanced Biomedical Sciences, University Federico II, Via Pansini 5, 80131, Naples, Italy.
Teresa MannarinoDepartment of Advanced Biomedical Sciences, University Federico II, Via Pansini 5, 80131, Naples, Italy.
Andrea GenovaDepartment of Advanced Biomedical Sciences, University Federico II, Via Pansini 5, 80131, Naples, Italy.
Roberta GreenDepartment of Advanced Biomedical Sciences, University Federico II, Via Pansini 5, 80131, Naples, Italy.
Valeria CantoniDepartment of Advanced Biomedical Sciences, University Federico II, Via Pansini 5, 80131, Naples, Italy.
Wanda AcampaInstitute of Biostructure and Bioimaging, National Council of Research, Naples, Italy.
Mario PetrettaDepartment of Translational Medical Sciences, University Federico II, Naples, Italy.
Alberto CuocoloDepartment of Advanced Biomedical Sciences, University Federico II, Via Pansini 5, 80131, Naples, Italy. cuocolo@unina.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe frequency of abnormal stress SPECT myocardial perfusion imaging (MPS) decreased over the past decades despite an increase in the prevalence of cardiovascular risk factors. These findings strengthen the need to develop more effective strategies for appropriately referring patients with suspected coronary artery disease (CAD) to cardiac imaging. The aim of this study was to develop pretest assessment models for predicting abnormal stress MPS.

methodsWe included 5,601 consecutive patients with suspected CAD, who underwent stress MPS at our academic center. Two different models were considered: a basic model including age, gender, and anginal symptoms; and a clinical model including also diabetes, hypertension, hypercholesterolemia, smoking, and family history of CAD.

resultsIn patients with abnormal MPS, the basic model classified more than 75% of patients as intermediate risk, whereas only 23% were incorrectly classified as low risk. In patients with normal MPS, 45% were correctly classified as low risk and none as high risk. Basic and clinical models had a limited discriminating capacity (area under the receiver operating characteristic curve 0.644 for basic model and 0.647 for clinical model) between individuals with and without abnormal stress MPS. The decision curve analysis demonstrates a high net benefit across a range of threshold probabilities from ~ 15% to ~30% for both models.

conclusionsA pretest risk stratification based on traditional cardiovascular risk factors has a limited value for predicting an abnormal stress MPS in patients with suspected CAD. However, selecting a proper threshold probability enhances the appropriateness of referral to stress MPS.

Indexed as

Myocardial Perfusion ImagingTomography, Emission-Computed, Single-PhotonAgedCoronary Artery DiseaseExercise TestFemaleHeart Disease Risk FactorsHumansMaleMiddle AgedModels, CardiovascularPatient SelectionPredictive Value of TestsRetrospective StudiesRisk AssessmentROC CurveCADdiagnostic and prognostic applicationMPISPECT

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Registered trials

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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.