Probabilistic Model for Prediction of Prognostics in Myocardial Revascularization : Complications in Coronary Surgery

Mailing Address: Felipe Coelho Argolo Rua Oito de Dezembro, 190. Postal Code: 40150-000, Graça, Salvador, BA – Brazil E-mail: felipe.c.argolo@hotmail.com, felipe.c.argolo@h1estatistica.com.br Probabilistic Model for Prediction of Prognostics in Myocardial Revascularization: Complications in Coronary Surgery Valcellos José da Cruz Viana,1,2 Felipe Coelho Argolo,3 Nilzo Augusto Mendes Ribeiro,2 Augusto Ferreira da Silva Junior,2 Luis Claudio Lemos Correia1 Escola Bahiana de Medicina e Saúde Pública,1 Hospital Santa Izabel da Santa Casa de Misericórdia da Bahia,2 Hospital Universitário Professor Edgard Santos,3 Salvador, BA Brazil


Introduction
Multivariate probabilistic models have been used in cardiac surgery to estimate the risk of fatal and nonfatal complications. 1 The goal is to evaluate the balance between risks and benefits of procedures for patients, with a better allocation of resources. 2There are some risk scores of death and occurrence of complications in patients undergoing myocardial revascularization surgery such as EuroSCORE 3 and STS Score. 4 Assessing the prognosis related to the natural history of a clinical condition, predictive variables are reproducible in different settings. 5,6On the other hand, when predicting the success or complications of medical procedures, it is possible that predictor variables have a variable value depending on the environment in which the procedure is implemented.This is because differences in the way a treatment is applied can make patients more or less vulnerable to risk determinants.Using a retrospective cohort performed at a tertiary hospital in Salvador, the present study aimed to test the external validity of traditional risk scores for surgical myocardial revascularization, to identify risk markers for Viana et al.

Predicting complications in coronary surgery
Int J Cardiovasc Sci.2017;30(4):307-312 Original Article myocardial revascularization surgery, and to construct a regional prediction model for complications related to the procedure.

Study design
Observational study of a retrospective cohort, using a database retrieved from the institution's records, fed with variables recorded between preoperative and patient discharge, used for research, after approval by the hospital's ethics council, under the registry number 24304713.9.3001.5544.

Sample selection criteria
All patients submitted to myocardial revascularization surgery at our service at Santa Izabel Hospital between October 2010 and April 2015 were included in the study sample.Patients with associated surgeries or those performed at other institutions were excluded.

Variables studied
The variables included in the analysis were: Gender, age, weight, height, body mass index, chronic obstructive pulmonary disease (COPD) -use of bronchodilator or corticoid, peripheral arteriopathyintermittent claudication, carotid artery obstruction greater than 50%; left ventricular dysfunctionmoderate 30-50% and significant less than 30%; previous neurological dysfunction -motor dysfunction affecting ambulation or daily function; previous cardiac surgery -previous opening of the pericardium; pre-and postoperative serum creatinine; endocarditis -antibiotic therapy for endocarditis at the time of surgery; unstable angina -use of venous nitrate; recent infarction -less than 90 days; pulmonary hypertension -pulmonary artery systolic pressure greater than 60 mmHg; previous myocardial revascularization; post-infarction ventricular septal defect; diabetes -use of oral hypoglycemic or insulin; smoking; hypertension -antihypertensive use; dyslipidemia -total cholesterol greater than 200 mg / dl, hypertriglyceridemia greater than 150 mg / dl, HDL cholesterol less than 40 mg / dl women and less than 50 mg / dl men; number of coronary lesions greater than 75%; left coronary trunk lesion greater than 50%; preoperative hypoxemia -artery oxygen pressure lower than 60 mmHg, emergency / urgency surgeryneed for intervention within 48 hours due to imminent risk of death or unstable clinical-hemodynamic status; hemodynamic instability -ventricular tachycardia, ventricular fibrillation, cardiac arrest, mechanical ventilation, intra-aortic balloon use.

Definition of outcome
The main analysis was performed considering the composite outcome of major morbidity, including: stroke, stroke (central neurological deficit persisting for more than 72 hours); Prolonged intubation (more than 48 hours); Reoperation (tamponade or hemostasis); Mediastinitis (need for surgical reintervention, plus antibiotic therapy with or without positive culture), and death within 30 days after the surgical procedure.The events that made up the outcome were chosen based on models developed and validated from previous studies in cardiovascular surgery. 7

Statistical analysis
Three logistic regression models were adjusted to test the predictive power of the scores in the sample: EuroSCORE, STS Mortality, and STS Morbidity.Each model was adjusted using the points of the respective score as the only independent variable.A proper model was adjusted following the algorithm proposed by Hosmer and Lemeshow 8 considering results of bivariate analysis and biological plausibility.The sample was divided into two parts: cohort derivation, intended for bivariate analysis and fit of the models (2/3 of the original sample, randomly selected); Cohort validation to test the obtained model (1/3 of the original sample, randomly selected).After obtaining the coefficients from the sample used for derivation, the model was tested using the validation sample.The Area under ROC Curve (AUROC) and model adequacy statistics are presented for comparison purposes.The analyzes were conducted using the programming language and R development environment.

Derivation of the proper model
The variables predictor candidates were selected in 2/3 random of the total sample through univariate analysis, considering statistical significance (p < 0.20).Table 1

Discussion
The use of multivariate models in the form of scores represents the most accurate mean to predict risk, being superior to that predicted subjectively by clinical impression. 9And even showing good accuracy in different populations, especially in the clinical context, 5,6 the results of the present study suggest greater caution regarding the external validity of these scores in the field of cardiac surgery.In addition, a score developed in our local sample demonstrated good accuracy in an independent validation cohort, which may be the predictor in places with different characteristics of the traditional score validator centers.Models not readjusted to the local context may present bias in predicting risk in cardiac surgery and should be systematically compared with regional models. 10mong the various scores used to predict death and occurrence of complications in cardiac surgery, EuroSCORE 3 and STSscore 4 are the most widespread and validated.][13] In the United States, it was more accurate compared to other predictor models when validated in the database with more than 500.000patients of the Society of Thorac Surgery. 14However, a systematic review evaluating the performance of the EuroSCORE concluded that the model overestimates surgical risk based on five studies of different nationalities. 15he present study corroborates the findings, finding unsatisfactory results for the predictive capacity of the evaluated scores, in contrast to a good performance of the locally adjusted model.7][18] A recent body of results shows a better performance of models fitted with local data in relation to EuroSCORE, Parsonet Score and Ontario Risk Score. 19ther studies in cardiovascular surgery suggest that most information on prognosis is contained in a few clinical variables, showing that simple models are as effective as complex models. 20Although it is better suited than traditional scores, the score derived from the sample in this study is not intended for use in other services.Performing in only one center limits the external validity, where characteristics of the patients and the care body of the institution may vary.