Evidence map›Paper›PMID 27896227›Full record

ArticleTranslational medicine @ UniSa2016

Stress-first single photon emission computed myocardial perfusion imaging.

C I Aquino, M Scarano, F Squame, G Casaburi, S L Nori, L Pace

Abstract read
In one paragraph

Article in Translational medicine @ UniSa, 2016. 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
–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

1 citing paper in PubMed.

  1. Myocardial perfusion stress test: is it worth?The international journal of cardiovascular imaging · 2020
    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

6 authors.

C I AquinoDipartimento di Medicina, Chirurgia e Odontoiatria "Scuola Medica Salernitana", Università degli Studi di Salerno, Italy.
M ScaranoA.O.U. S. Giovanni di Dio e Ruggi d'Aragona, Salerno, Italy.
F SquameA.O.U. S. Giovanni di Dio e Ruggi d'Aragona, Salerno, Italy.
G CasaburiA.O.U. S. Giovanni di Dio e Ruggi d'Aragona, Salerno, Italy.
S L NoriDipartimento di Medicina, Chirurgia e Odontoiatria "Scuola Medica Salernitana", Università degli Studi di Salerno, Italy.
L PaceDipartimento di Medicina, Chirurgia e Odontoiatria "Scuola Medica Salernitana", Università degli Studi di Salerno, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMyocardial perfusion imaging (MPI) with single photon emission tomography (SPET) is widely used in coronary artery disease evaluation. Recently major dosimetric concerns have arisen. The aim of this study was to evaluate if a pre-test scoring system could predict the results of stress SPET MPI, thus avoiding two radionuclide injections.

methodsAll consecutive patients (n=309) undergoing SPET MPI during the first 6 months of 2014 constituted the study group. The scoring system is based on these characteristics: age >65 years (1 point), diabetes (2 points), typical chest pain (2 points), congestive heart failure (3 points), abnormal ECG (4 points), male gender (4 points), and documented previous CAD (5 points). The patients were divided on the basis of the prediction score into 3 classes of risk for an abnormal stress-first protocol.

resultsAn abnormal stress SPET MPI was present in 7/31 patients (23%) with a low risk score, in 24/90 (27%) with an intermediate score risk, and in 124/188 (66%) with an high score risk. ROC curve analysis showed good prediction of abnormal stress MPI.

conclusionsOur results suggest an appropriate use of a pre-test clinical prediction formula of abnormal stress MPI in a routine clinical setting.

Indexed as

Coronary Artery DiseaseMyocardial Perfusion ImagingRadiation DoseStress-First

Identifiers

PMID27896227
PMCPMC5120750

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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.