Our Proof-Of-Concept study
The PICA trial
PICA= Pre-Interventional Complication Assessment
A monocentric study assessing the efficacy of the nitrosylated hemoglobin as biomarker
for detecting the development of a cardiovascular complication during or after surgery
The main objective of this study is to assess the relevance of the nitrosylated hemoglobin (HbNO) in predicting perioperative cardiovascular complications. This could provide an objective predictive tool in the anesthetic management of high-risk patients scheduled for non-cardiac surgery.
This monocentric study is a prospective, interventional trial with one arm.
2500 subjects aged between 18 and 100 years with a forthcoming non-cardiac surgery will be enrolled.
No drug will be administered in this study. At the first visit, the anesthetist will fill the EPI form (part of the standard of care procedure). Based on the EPI form, a survey focusing on specific risk factors will be filled. Then he will prescribe a blood sampling for measuring vital signs. If the subject accepts to participate to this study, an additional sampling of 10 mL will be performed to measure the endothelial function. So, the subject will have only one blood drawing.
The patients that have not been seen at EPI and that correspond to the inclusion criteria will be recruited directly by the anesthetist and be enrolled as the other patients.
Then, to assess the eventual peri-operative complication, the patient will be called by phone after 6 and 12 months from his/her surgery and his/her medical record will be consulted at 3 and 12 months.
The demography of patients considered in the analysis (845) showed a good balance over the different patient profiles.
Gender: more women were enrolled as surgeries such as hysterectomy, endometriosis and hyperthyroidia affect mostly females.
Age: good representation over all the range
BMI: equal distribution between normal BMI, overweighted and obese people
Smoking: patients smoking and ex-smokers were discriminated
Diabetes: patients with a treated diabetes were differentiated from patients without treatment
Hypertension: about 50% of patients did not have hypertension. one thrird of patients had a treated hypertension. This is in correlation with the prevalence of hypertension.
Hypercholesterolemia: about 50% of patients did not have a reported hypercholesterolemia.
DASI: most of the patients had a normal physical activity
Surgery grade: most of the patients had a surgery grade of 3 according to the KCE classification.
RCRI: most of the patients had a RCRI score of 2
ASA: most of the patients had an ASA of 2
Overall the distribution of the patient profiles is representative of the patients admitted for an elective surgery.
Spinovit demonstrated a univariate significant link between HbNO and CV complications
Spinovit used a machine learning-based strategy (11,000 simulations) to establish a probability cutoff from a series of simulated dataset divided into a trainset (80%) and a testset (20%)
For each tested threshold, calculation of different metrics from the testset: AUC, sensitivity, specificity, geometric mean, PPV, NPV, etc.
The most frequent threshold maximizing sensitivity and specificity (geometric mean) is kept as final cutoff.
cutoff = 111 nM HbNO
Based on this calculated cutoff of 111 nM of HbNO, patients could be sorted for an elevated risk of having a peroperative major non-CV complication. The negative positive value (NPV) is calculated to be 99.2%.
•HbNO is the basis of a biological scale
•Suited for assessing the personalized risk
•Complementary to other scales based on population like Lee score
•Calculate the perioperative CV risk for anyone, not only > 45 years like Lee score
•Allows a direct preoperative risk stratification : low vs high risk
•Objective decision tool for triggering appropriate pre- and post-operative cardiac monitoring:
HbNO >111 nM no preoperative cardiac monitoring
•In combination with other variables (past medical history, family history, and past surgical outcomes,…) could help to determine an appropriate treatment of patients.