Background And Purpose: The present study examined the relationship between circulatory and metabolic reserve in patients with hemodynamic impairment.
Methods: Positron emission tomography was used to investigate 40 patients with major cerebral artery occlusive disease. The ratio of cerebral blood volume to cerebral blood flow (CBV/CBF) and vasoreactivity in response to hypercapnia (%CBF(hypercapnia)) and acetazolamide (ACZ) stress (%CBF(ACZ)) were measured to evaluate circulatory reserve. Oxygen extraction fraction (OEF) was measured to evaluate metabolic reserve. To detect relationships between circulation reserve and OEF, cerebral hemispheres were grouped into 5 or 6 stepwise groups based on reduction of circulation reserve.
Results: OEF was significantly elevated in hemispheres with CBV/CBF > or =0.11 minutes and in hemispheres with %CBF(hypercapnia) <0%. OEF was significantly increased according to %CBF(ACZ) in hemispheres with %CBF(ACZ) <15% and plateaued at levels below -15%.
Conclusions: Metabolic reserve consumption began at CBV/CBF > or =0.11 minutes, CBF(hypercapnia) <0%, and CBF(ACZ) <15%.
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http://dx.doi.org/10.1161/01.STR.0000199085.40000.cf | DOI Listing |
Eur Heart J Cardiovasc Imaging
January 2025
Faculty of Health and Medicine, Wallace Wurth Building (C27), Cnr High St & Botany St, UNSW Sydney, Kensington, NSW 2033, Australia.
Aims: Although an association between the systemic circulation and transaortic flow rate (TFR) is frequently hypothesized in patients with aortic stenosis (AS), it has not been demonstrated previously. We sought to explore the relationship between blood pressure (BP), vascular afterload measures, clinical history of hypertension, TFR, and survival in patients with severe AS (aortic valve area ≤ 1 cm²).
Methods And Results: We studied 323 patients ≥ 65 years (110 prospective, 213 registry analysis) who underwent transcatheter aortic valve replacement over a 5-year period.
Open Heart
January 2025
Department of Cardiology, Leiden University Medical Center, Leiden, Zuid-Holland, The Netherlands
Background: Coronary microvascular disease (CMD) is defined as impaired coronary flow reserve (CFR) and/or increased microvascular resistance (MR) without significant epicardial coronary stenosis. This definition allows for discordant CFR and MR values within patients with CMD. The aim of this meta-analysis is to characterise the prognostic value and pathophysiological backgrounds of CFR and MR con-/discordance.
View Article and Find Full Text PDFJ Cardiovasc Med (Hagerstown)
February 2025
Center of Excellence in Cardiovascular Sciences, Ospedale Isola Tiberina, Gemelli Isola.
Aims: Coronary microvascular dysfunction (CMD) is a heterogeneous condition defined by reduced coronary flow reserve (CFR). The new index 'microvascular resistance reserve' (MRR) has been developed, but its role is unclear. We investigate the relationships between functional indices in ANOCA (angina and non-obstructive coronary arteries) patients and evaluate the hemodynamic features of different CMD subtypes.
View Article and Find Full Text PDFCurr Cardiol Rep
January 2025
Department of Cardiovascular & Thoracic Surgery, Sandra Atlas Bass Heart Hospital at North Shore University Hospital, Northwell Health, 300 Community Drive, 1 DSU, Manhasset, NY, 11030, USA.
Purpose Of Review: This article discusses a tailored approach to managing cardiogenic shock and temporary mechanical circulatory support (tMCS). We also outline specific mobilization strategies for patients with different tMCS devices and configurations, which can be enabled by this tailored approach to cardiogenic shock management.
Recent Findings: Safe and effective mobilization of patients with cardiogenic shock receiving tMCS can be accomplished.
J Am Heart Assoc
January 2025
Department of Cardiology Beijing Anzhen Hospital, Capital Medical University Beijing China.
Background: Data on the predictive value of coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) for long-term outcomes are limited.
Methods And Results: A retrospective pooled analysis of individual patient data was performed. Deep-learning-based CT-FFR was calculated.
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