Hypotension During Surgery
Conditions
Brief summary
Intraoperative hypotension is linked to increased incidence of perioperative adverse events such as myocardial and cerebrovascular infarction and acute kidney injury. Hypotension prediction index (HPI) is a novel machine learning guided algorithm which can predict hypotensive events using high fidelity analysis of pulse-wave contour. Goal of this trial is to determine whether use of HPI can reduce the number and duration of hypotensive events in patients undergoing major thoracic procedures.
Interventions
Hypotension prediction index (HPI) available with the Edwards Acumen IQ sensor will be used as an early warning system and a diagnostic screen will be used to guide therapeutic interventions.
Therapeutic interventions guided by real time monitored hemodynamic parameters as measured by Edwards Flotrac sensor.
Sponsors
Study design
Eligibility
Inclusion criteria
* patients over 18 years of age * patients scheduled for elective major thoracic procedure (lung resection, pleurectomy or resection of the esophagus) * planned thoracotomy and intraoperative period of one lung ventilation * planned postoperative admission to the ICU
Exclusion criteria
* persistent atrial fibrillation * structural heart defects (shunting or moderate to severe valvular anomalies) * preoperative serum hemoglobin levels \< 120 g/L * severe heart failure classified as New York Heart Association (NYHA) grade IV
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Time weighted average of area under hypotensive threshold | During surgery |
Secondary
| Measure | Time frame |
|---|---|
| Cumulative duration of hypotension | During surgery |
| Number of hypotensive events | During surgery |
Countries
Croatia