Evidence map›Paper›PMID 42701570›Full record

ArticleQuantitative imaging in medicine and surgery2026

Peak filling rate assessed by myocardial perfusion imaging predicts adverse outcomes in women with chronic coronary syndromes.

Yuanyuan Li, Jiaxin Cao, Yuting Zhao, Ping Wu, Ruonan Wang, Zhifang Wu, Haiyan Liu, Sijin Li

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Article in Quantitative imaging in medicine and surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Yuanyuan LiDepartment of Nuclear Medicine, First Hospital of Shanxi Medical University, Taiyuan, China.ORCID https://orcid.org/0000-0002-2010-3459
Jiaxin CaoDepartment of Nuclear Medicine, First Hospital of Shanxi Medical University, Taiyuan, China.
Yuting ZhaoDepartment of Nuclear Medicine, First Hospital of Shanxi Medical University, Taiyuan, China.
Ping WuDepartment of Nuclear Medicine, First Hospital of Shanxi Medical University, Taiyuan, China.
Ruonan WangDepartment of Nuclear Medicine, First Hospital of Shanxi Medical University, Taiyuan, China.
Zhifang WuDepartment of Nuclear Medicine, First Hospital of Shanxi Medical University, Taiyuan, China.
Haiyan Liu *Department of Nuclear Medicine, First Hospital of Shanxi Medical University, Taiyuan, China.ORCID https://orcid.org/0000-0002-4961-4252
Sijin Li *Department of Nuclear Medicine, First Hospital of Shanxi Medical University, Taiyuan, China.ORCID https://orcid.org/0009-0008-1029-2592

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Diastolic dysfunction may represent an important risk dimension beyond myocardial ischemia and systolic impairment, particularly in women with chronic coronary syndromes (CCS). However, the prognostic value of myocardial perfusion imaging (MPI)-derived diastolic parameters and their potential sex-specific differences remain uncertain. Therefore, this study aimed to evaluate the prognostic significance of single photon emission computed tomography (SPECT) MPI-derived diastolic parameters in patients with CCS without reduced ejection fraction (EF <40%). Methods: In this retrospective cohort study, data of 1,446 patients undergoing resting MPI were analyzed at the First Hospital of Shanxi Medical University [2016-2021]. The diastolic parameters obtained from MPI included peak filling rate (PFR), mean filling rate over the first third of the end-systole to end-diastole phase (MFR/3), and time to peak filling from end-systole (TTPF). Propensity score matching balanced baseline clinical characteristics between sexes. Multivariable Cox regression evaluated the associations between sex, diastolic parameters, and major adverse cardiovascular events (MACEs). These analyses were further differentiated by total perfusion deficit (TPD) ≥10% and EF ≥50% groups. Results: (I) Over a median 3.05-year follow-up, 519 patients (35.9%) experienced MACE. (II) No statistically significant differences were observed in the predictive value for MACE among PFR, MFR/3, TTPF, and the combination of these three parameters (P=0.956). (III) Reduced PFR independently predicted MACE in women [hazard ratio (HR) 0.61, P=0.028] but not in men (P=0.167). This sex difference persisted in patients with TPD ≥10% (HR 0.36) and EF ≥50% groups (HR 0.57, all P<0.05). Conclusions: In patients of CCS without reduced EF, MPI-derived PFR demonstrates sex-specific prognostic value, serving as an independent predictor of MACE in women but not men. These findings highlight the potential of diastolic analysis to refine risk stratification in women.

Indexed as

Diastolic functiongated single photon emission computed tomography myocardial perfusion imaging (gated SPECT MPI)peak filling rate (PFR)prognosissex differences

Identifiers

PMID42701570
PMCPMC13545591

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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 Socratic graph.