Leila Khedmat - Health Management research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran
Hossein Khedmat - Department of Gastroenterology, Baqiyatallah Research Center for Gastroenterology & Liver Disease, Baqiyatallah University of Medical Sciences, Tehran, Iran
Mohammad Hasan Shafiee - Department of Gastroenterology, Baqiyatallah Research Center for Gastroenterology & Liver Disease, Baqiyatallah University of Medical Sciences, Tehran, Iran
Ashraf Karbasi - Department of Gastroenterology, Baqiyatallah Research Center for Gastroenterology & Liver Disease, Baqiyatallah University of Medical Sciences, Tehran, Iran
Elham Bazmi - Baharloo hospital
Behnam Behnoush - Baharloo hospital

Introduction: Opioid drugs poisoning is a major social and health care problem in the world and prediction of complications due to poisoning that creates an unprecedented national crisis is important. Also, cardiovascular complication is the main factor in mortality and morbidity in Iran. Theaim of this study is to create a prediction model to identify risk factors of cardiovascular complications in acute tramadol poisoning. Methods: A prospective cohort study was conducted on patients that referred to emergency department with pure acute tramadol poisoning (2017-2018). For each patient, etiological, clinical and laboratory findings were gathered from clinical files. We performed logistic regression model to identify the risk factors and predict cardiovascular outcomes in acute tramadol poisoning. Predictive performances of model was analyzed by receive operating characteristic (ROC) curve and discrimination of the model was done. Results: For multivariate logistic regression (MLR) model, the sensitivity and specificity were 83% (CI: 0.80-0.87) and 0.85 % (CI: 0.81-0.88) respectively. Key independent variables in the analysis were age, sex, dose and period of consumption. R2 in logistic regression model was 0.85 and AUC was 0.89. Discussion and conclusion: While investigation findingswere exploratory and lacked generatibility, we suggest that MLR model holds promise as an effective classification approach for identification risk factors related to cardiovascular complications in tramadol toxicity. Therefore, prediction of these outcomes may be helpful in reducing mortality and morbidity due to tramadol poisoning. It can be assessed at emergency department and quick and easy to use and applicable in hospital

cardiovascular complications, poisoning, prediction, tramadol