Evidence map›Paper›PMID 37924340›Full record

ArticleEuropean journal of nuclear medicine and molecular imaging2024

CT attenuation correction improves quantitative risk prediction by cardiac SPECT in obese patients.

Attila Feher, Konrad Pieszko, Aakash Shanbhag, Mark Lemley, Bryan Bednarski, Robert J H Miller, Cathleen Huang, Leonidas Miras, Yi-Hwa Liu, Albert J Sinusas and 2 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in European journal of nuclear medicine and molecular imaging, 2024. 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
1.6field-weighted citation impact, top 16% 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, 7 citations in OpenAlex.

  1. 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

12 authors at 4 institutions in 2 countries.

Attila FeherSection of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, Dana 3, P.O. Box 208017, New Haven, CT, 06520, USA. attila.feher@yale.edu.ORCID 0000-0002-2561-4282
Konrad PieszkoDepartments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Aakash ShanbhagDepartments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Mark LemleyDepartments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Bryan BednarskiDepartments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Robert J H MillerDepartments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Cathleen HuangDepartments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Leonidas MirasDivision of Cardiology, Bridgeport Hospital, Yale University School of Medicine, Bridgeport, CT, USA.
Yi-Hwa LiuSection of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, Dana 3, P.O. Box 208017, New Haven, CT, 06520, USA.
Albert J Sinusas *Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, Dana 3, P.O. Box 208017, New Haven, CT, 06520, USA.
Piotr J Slomka *Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Edward J MillerSection of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, Dana 3, P.O. Box 208017, New Haven, CT, 06520, USA.
Cedars-Sinai Medical Center · USDana (United States) · USBridgeport Hospital · USYale University · US

Funding

Quantitative Prediction of Disease and Outcomes from Next Generation SPECT and CTR01HL089765 · NHLBI · CEDARS-SINAI MEDICAL CENTER · PI SLOMKA, PIOTR J · 2007 to 2021
$6.1M
Patient-specific Outcome Prediction from Cardiovascular Multimodality Imaging by Artificial IntelligenceR35HL161195 · NHLBI · CEDARS-SINAI MEDICAL CENTER · PI Piotr J Slomka · 2022 to 2026
$5.0M
NHLBI NIH HHS R01 HL089765NHLBI NIH HHS R01HL089765NHLBI NIH HHS R35 HL161195NHLBI NIH HHS R35HL161195
6 · The paper itself

Abstract

purposeThis study aimed to compare the predictive value of CT attenuation-corrected stress total perfusion deficit (AC-sTPD) and non-corrected stress TPD (NC-sTPD) for major adverse cardiac events (MACE) in obese patients undergoing cadmium zinc telluride (CZT) SPECT myocardial perfusion imaging (MPI).

methodsThe study included 4,585 patients who underwent CZT SPECT/CT MPI for clinical indications (chest pain: 56%, shortness of breath: 13%, other: 32%) at Yale New Haven Hospital (age: 64 ± 12 years, 45% female, body mass index [BMI]: 30.0 ± 6.3 kg/m

resultsDuring a median follow-up of 25 months, 453 patients (10%) experienced MACE. In patients with BMI ≥ 35 kg/m

conclusionsAC sTPD outperformed NC sTPD in predicting MACE in patients undergoing SPECT MPI with BMI ≥ 35 kg/m

Indexed as

Coronary Artery DiseaseMyocardial InfarctionMyocardial Perfusion ImagingAgedFemaleHumansMaleMiddle AgedObesityPrognosisTomography, Emission-Computed, Single-PhotonTomography, X-Ray ComputedAttenuation correctionHybrid imagingMyocardial perfusionObesityPrognosisSPECT

Identifiers

PMID37924340
PMCPMC11774509
OpenAlexW4388348399

What OpenQuestion holds

Textmetadata
LicenceTDM
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.