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Utility of Dynamic Variables Measured by Calibrated Pulse Contour Analysis of Oesophageal Doppler Monitor for Predicting Fluid Responsiveness During Robot-Assisted Laparoscopic Prostatectomy

NCT02886546 · Hallym University Kangnam Sacred Heart Hospital · Updated 30 Jan 2026

What is being tested
pneumoperitoneum; oesophageal Doppler monitor
For
Prostate Cancer
Kind of study
Tests a treatment or device on volunteers. No drug phase (a device or procedure study).
Who can join
Ages 55 years to 80 years. About 26 people. The full rules are on the registry page.
Where
Not stated
When
Starts or started 1 Sept 2016, ends 1 Sept 2017. Registered 1 Sept 2016.
Results
None posted yet.

In the researchers' words

Robot-assisted laparoscopic prostatectomy (RALP) is widely performed due to its many advantages, including a reduced need for blood transfusion and fewer surgical complications compared with conventional open prostatectomy. As this approach is also recommended in elderly patients with serious comorbidities, optimal fluid therapy guidance during this procedure is important. Dynamic variables such as pulse pressure variation (PPV) and stroke volume variation (SVV) are used to predict and guide fluid therapy during controlled ventilation. These variables arise from heart-lung interactions during positive pressure ventilation, which influence left ventricular stroke volume (SV). RALP requires carbon dioxide insufflation and the steep Trendelenburg position to optimise surgical conditions, and can reduce cardiac output and respiratory compliance. Accordingly, the usefulness of PPV and SVV, which are affected by changes in intrathoracic pressure, in predicting fluid responsiveness during laparoscopic surgery under these conditions may be questioned. A recent study established that PPV and SVV derived by uncalibrated pulse contour analysis had a relatively poor capacity to predict fluid responsiveness during laparoscopy on dynamic preload indices. In contrast, another study SVV measured by oesophageal Doppler monitor (ODM) could predict fluid responsiveness during laparoscopic…
ClinicalTrials.gov, NCT02886546