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Accurate hemodynamic monitoring is critical in cardiothoracic surgery, where left atrial pressure (LAP) serves as the gold standard for assessing left-sided cardiac filling pressures. However, its invasive nature limits use, favoring pulmonary capillary wedge pressure (PCWP) via Swan-Ganz catheter as a surrogate. Despite widespread use, evidence on their agreement under dynamic conditions-such as varying cardiac index (CI) flows during cardiopulmonary bypass (CPB) or left ventricular (LV) unloading-remains inconsistent and unstudied in adult cardiac surgery.
Existing data show conflicting correlations: one study found that PCWP 35% higher than LAP in non-surgical patients, and another study found closer alignment in specific cohorts. This knowledge gap carries clinical urgency, as decisions on pulmonary edema management, vasopressor use, and LV decompression rely on these measurements.
Building on Laplace's law, we hypothesize that LV unloading reduces ventricular wall stress (afterload), lowering myocardial oxygen demand and altering the LAP-PCWP relationship. Elevated CI during CPB may further distort this interaction via increased pulmonary-left atrial pressure gradients.
The primary objective is to determine if PCWP reliably reflects LAP under standard CI-flow (2.4 L/min/m²) without unloading, using Bland-Altman analysis (±5 mmHg clinical margin). Secondary objectives assess agreement at other CI levels (1.8-2.6 L/min/m²), LV unloading effects, and patient/surgical variable impacts.
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Effective hemodynamic monitoring is essential for optimizing postoperative management in cardiothoracic surgery. Left atrial pressure (LAP) is considered the gold standard for assessing left-sided cardiac filling pressures, but is typically measured directly only in selected cases due to its invasive nature. Pulmonary capillary wedge pressure (PCWP), measured via a Swan-Ganz catheter, is widely used as a less invasive surrogate for LAP. However, evidence suggests that the agreement between PCWP and directly measured LAP may vary under different hemodynamic conditions, particularly at higher cardiac index (CI) flow rates and with or without left ventricular (LV) unloading. To date, no in-vivo study has systematically quantified the agreement between these two methods in adult patients during cardiopulmonary bypass (CPB) at varying flow rates and unloading conditions.
Existing studies report inconsistent correlations between LAP and PCWP. For example, one study observed PCWP values 35% higher than LAP in non-surgical patients, while another study noted tighter correlations in specific cohorts. However, no in-vivo data exist for adult cardiac surgery patients under controlled CI-flow rates (+/- LV unloading). This gap is clinically critical, as decisions regarding pulmonary edema management, vasopressor use, and LV decompression rely on these measurements.
Building on Laplace's law, we hypothesize that LV unloading reduces ventricular wall stress (afterload), thereby lowering myocardial oxygen demand and improving recovery. Computational models and animal studies suggest that unloading decreases LV end-diastolic pressure (LVEDP) and left atrial (LA) volume, which may alter the LAP-PCWP relationship. Elevated CI during CPB could further modulate this interaction, as increased flow rates may exacerbate pressure gradients between the pulmonary vasculature and left atrium.
The primary objective of our study is therefore to determine whether PCWP can be considered an adequate surrogate for directly measured LAP under standard CI-flow (2.4 L/min/m²) without LV unloading, using a Bland-Altman analysis. Secondary objectives include evaluating the agreement between LAP and PCWP at other CI-flow rates and with LV unloading, as well as exploring the influence of patient characteristics and surgical variables. By addressing these questions, we hope to provide evidence to guide the interpretation of PCWP in clinical practice, potentially improving the safety and outcomes of patients undergoing cardiac surgery.
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136 participants in 1 patient group
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B U Baldan, MD
Data sourced from clinicaltrials.gov
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