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Aging and cardiopulmonary interactions: physiologic and pathophysiologic consequences
Eduardo Butturini de Carvalho1,2, Felipe Cavalcante Brambila de Barros3, Nazareth N Rocha2,4
1Vassouras University, Rio de Janeiro, Brazil.
None:
Monitoring hemodynamics and its response to fluid challenges is important for in-hospital patients to maintain adequate tissue perfusion without leading to organ edema or dysfunction. The physiologic background of bedside hemodynamic indexes depends on the cardiopulmonary interactions. However, monitoring fluid responsiveness in older adults may be particularly challenging because age-related physiologic changes and prevalent comorbidities can alter cardiopulmonary interactions. Those alterations are often neglected in clinical studies and even in the classic formulas used to estimate basic variables for hemodynamics. This issue becomes even more important because many studies on fluid responsiveness include cohorts composed of older adults, but few directly address the unique physiologic and pathophysiologic features of aging as the central variable of interest. This narrative review aims to highlight the physiologic consequences of aging and the difficulty in assessing fluid responsiveness in an aging population. Conditions such as heart failure with preserved ejection fraction may shift the Frank-Starling relationship, thereby reducing preload dependence in older adults and narrowing the therapeutic window between the beneficial and deleterious effects of intravenous fluid administration. Additional conditions, including aortic stenosis, may further confound the interpretation of dynamic indices used to assess fluid responsiveness. Future experimental and clinical research agendas should adopt a phenotype-oriented approach, investigating the impacts on hemodynamic assessment from age-related physiologic adaptations and the most prevalent cardiopulmonary conditions, such as heart failure with preserved ejection fraction, chronic obstructive pulmonary disease, and aortic stenosis. The stratification of older adults and data analysis from clinical studies could be of great value.
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