Correlation Between Circulating Biomarkers of Organs Damage and Intraoperative Hypotension Management

The primary objective of this pilot study is to investigate if an early treatment of intraoperative hypotension driven by an Edwards Lifesciences new technology (Hypotension Probability Index - HPI software) and integrated hemodynamic variables is able to determine a modification of the blood levels of several specific biomarkers of tissue and organ damage compared to a traditional management of hypotension. It will also be evaluated if the management strategy of patient hemodynamics based on the Hypotension Probability Index (HPI) is associated with a lower incidence of hypotensive events and / or a shorter overall duration of intraoperative hypotension.

In the study will be enrolled forty adult patients requiring an arterial line (at discretion of treating physician) undergoing non-cardiac non-day surgery (with an expected duration of more than 2 hours and an aimed medium arterial pressure - MAP of 65 mmHg) at the Universitary Hospital of Catania.

The patients will be randomly (1:1) assigned to one of the subsequent two groups: a group monitored with FloTracIQ with HPI software (Treatment Group) and a group with standard invasive blood pressure monitoring (Control Group).

In the Control Group, all hypotensive episodes during surgery will be treated according to standard of care.

Patients randomized to the Treatment Group will receive monitoring with integration of HPI index and hemodynamic parameters visible on the EV1000 platform; these informations will be used to guide the investigator in the choice of the more appropriate treatment to be carried out. The value of HPI is updated every 20 seconds and expresses in percentage the probability of occurrence of a hypotensive event. The cut-off value of HPI is equal to 85%. Values above the cut-off are related to a higher probability of hypotension. A specific visual and sound "ALERT" will indicate to the investigator if the threshold value is reached / exceeded. Any treatment strategy will be based on integrated analysis of clinical and instrumental data showed on the screen of the EV1000 platform [MAP, cardiac output (CO), systemic vascular resistance (SVR), stroke volume (SV), stroke volume variation (SVV), intra-ventricular pressure rate of rise (dP/dt), dynamic arterial elastance (Eadyn)].

In both groups different blood samplings will be performed in order to assess biomarkers of specific organ dysfunction: T0 (baseline, before starting operating procedures); T1 (2 hours after starting anesthesia); T2 (at the end of surgical procedures). The following biomarkers will be assessed: neuron specific enolase and S100B (for brain monitoring); high sensitive cardiac troponin T (for heart monitoring); Neutrophil Gelatinase-Associated Lipocalin (NGAL, for kidney monitoring); circulating endothelial cells counting and cytofluorimetric analysis (for endothelial monitoring). There will also be determined the systemic effect of intraoperative hypotension as measured by inflammatory cytokines [Interleukin (IL)-6, IL-1 beta and Tumor necrosis factor (TNF)-alfa], oxidative stress (reduced glutathione, lipid hydroperoxides) and markers of hypoxia (HIF1alpha, lactate, acetylCoA, CoA).

Various clinical informations will be collected at the same time: glomerular filtration rate, plasma electrolytes, creatinine, aspartate aminotransferase (AST), alanine aminotransferase (ALT), blood gasses analysis, anion gap.

A telephone interview will be performed one month after surgery, in order to investigate general health condition and any re-admission to hospital.

Sample size calculation:

Given the pilot nature of the study, no formal justification of sample size has been made.

Statistical analysis:

For a test of normal distribution, the Kolmogorov-Smirnov test will be used. Continuous data with normal distribution will be tested with paired or unpaired t tests, non-normally distributed data using Mann-Whitney U test and Wilcoxon rank-sum test for unpaired and paired results, respectively.

Changes in biomarkers over time will be tested using analysis of variance (ANOVA) on repeated measurements. Categorical data will be tested using Chi-square test and Chi-square test for trend. Data will be presented as mean ± standard deviation when normally distributed and as median [interquartile ranges] in case of abnormal distribution. A p < 0.05 will be considered statistically significant for all tests.