Σφακιανάκης Αλέξανδρος
ΩτοΡινοΛαρυγγολόγος
Αναπαύσεως 5 Άγιος Νικόλαος
Κρήτη 72100
00302841026182
00306932607174
alsfakia@gmail.com

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! # Ola via Alexandros G.Sfakianakis on Inoreader

Η λίστα ιστολογίων μου

Σάββατο 1 Σεπτεμβρίου 2018

Sex differences in the long-term prognostic value of 13 N-ammonia myocardial perfusion positron emission tomography

Abstract

Purpose

Evidence to date on the unique female determinants of cardiovascular risk is inadequate. Positron Emission Tomography (PET) is considered to have the highest accuracy for the assessment of myocardial perfusion in patients with suspected coronary artery disease (CAD), but its long-term prognostic accuracy in women has not been established.

Methods

A total of 619 consecutive patients (138 women, mean age 60.0 ± 11.8 years) underwent clinically indicated 13N-ammonia PET at our institution and were followed up (median 5.7 years) for major adverse cardiovascular events (MACE) including cardiac death, nonfatal myocardial infarction, hospitalization for any cardiac reason and late revascularization.

Results

During follow-up, 271 patients had at least one cardiac event, including 64 cardiac deaths and 33 nonfatal myocardial infarctions. In both women and men, abnormal myocardial perfusion was associated with reduced event-free survival (log rank p < 0.001). In women, abnormal myocardial perfusion was associated with a higher risk of a worse outcome than in men (adjusted HR 4.1, 95% CI 1.8–9.0 in women; HR 2.4, 95% CI 1.5–3.8 in men; pinteraction < 0.001). In contrast, abnormal coronary flow reserve (CFR) was a significant predictor of 10-year MACE in men (p = 0.006) but not in women (p = NS). Accordingly, an interaction term of sex and abnormal myocardial perfusion or CFR was significant (p < 0.001).

Conclusion

While perfusion findings in 13N-ammonia PET provide effective risk stratification in women and men, CFR adds incremental prognostic value for long-term cardiac outcomes only in men. Refined strategies in noninvasive imaging are needed in women to improve CAD risk prediction.



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