IntroductionThe interest in Expert systems has increased in the medical area. Some of them are employed even for diagnosis. With the variability of transcatheter prostheses, the most appropriate choice can be complex. This scenario reveals an enabling environment for the use of an Expert system. The goal of the study was to develop an Expert system based on artificial intelligence for supporting the transcatheter aortic prosthesis selection.MethodsThe system was developed on Expert SINTA. The rules were created according to anatomical parameters indicated by the manufacturing company. Annular aortic diameter, aortic area, aortic perimeter, ascending aorta diameter and Valsalva sinus diameter were considered. After performing system accuracy tests, it was applied in a retrospective cohort of 22 patients with submitted to the CoreValve prosthesis implantation. Then, the system indications were compared to the real heart team decisions.ResultsFor 10 (45.4%) of the 22 patients there was no concordance between the Expert system and the heart team. In all cases with discordance, the software was right in the indication. Then, the patients were stratified in two groups (same indication vs. divergent indication). The baseline characteristics did not show any significant difference. Mortality, stroke, acute myocardial infarction, atrial fibrillation, atrioventricular block, aortic regurgitation and prosthesis leak did not present differences. Therefore, the maximum aortic gradient in the post-procedure period was higher in the Divergent Indication group (23.9 mmHg vs. 11.9 mmHg, P=0.03), and the mean aortic gradient showed a similar trend.ConclusionThe utilization of the Expert system was accurate, showing good potential in the support of medical decision. Patients with divergent indication presented high post-procedure aortic gradients and, even without clinical repercussion, these parameters, when elevated, can lead to early prosthesis dysfunction and the necessity of reoperation.
Objective After coronary artery bypass grafting (CABG), studies testing strict glycemic control did not took into account previous insulin use. Our aim was to evaluate the effect of perioperative (PO) control in patients with NonDM (ND), noninsulin- (NIDDM) and insulin-dependent (IDDM) diabetes submitted to CABG. Methods We included CABG patients (2010–2017), stratified by DM presence and type. PO glucose was managed with a standardized protocol (IV insulin targeting a glucose <180 mg/dL. Endpoints included in-hospital death, major adverse cardiac and cerebrovascular (MACCE) events, deep sternal wound infection [DSWI], and major infections. PO glucose control was stratified in 4 quartiles using the highest glucose level: 1st, <140mg/dL; 2nd, 140–179mg/dL; 3rd, 180–239mg/dL; and 4th, >240mg/dL). Multivariable analysis was used to model the association of PO glucose control with outcomes, taking the presence and type of DM into account. All analysis on SPSS 23 (SPSS, IBM, 2018), with p<0.05 as statistically significant. Results 2020 CABG pts, age 64±10 y, 31% female, DM 37,5% (66% NIDDM, 34% IDDM). Compared with DM, neither NIDDM nor IDDM were associated with mortality (OR=0.99 [0.61–1.61], p=0.985) or MACCE (OR=0.12 [0.81–1.54], p=0.477). In multivariable analysis, DM (OR=1.58 [1.01–2.49], p=0.049) and IDDM (OR=2.55 [1.57–4.16], p<0.001) were independently associated with DSWI. In a mediation analysis, the inclusion of IDDM in the model, weakened the association of DM with DSWI into nonsignificance (OR=1.20 [0.73–1.98], p=0.456), while IDDM retained significant association with DSWI (OR=2.37 [1.39–4.01], p=0.001), indicating that the impact of DM on the incidence of DSWI is fully explained by the IDDM patients. Poor PO glycemic control was an independent predictor of death (OR=1.09, 95% CI 1.04–1.13, p<0.001; 9% higher mortality to each 10mg/dL increase). Accordingly, patients from ND group in the highest stratum of glucose control (4th quartile), compared with the other 3 quartiles, showed increased mortality (3.8%, 2.9%, 4.4%, and 17.9%, p<0.001) and MACCE (8.7%, 8.5%, 14.3%, and 39.3%, p<0.001). However, in IDDM patients, poor PO glycemic control was not an independent predictor of mortality (OR=3.34, 95% CI 0.34–38.23, p=0.347). In fact, strict PO glycemic control in IDDM patients (but not in ND and NIDDM) increased the incidence of DSWI (<140mg/dL, 19.8%, vs >240mg/dL, 8.2%, p=0.015) and other major infections (<140mg/dL, 26.2%, vs >240mg/dL, 12.2%, p=0.048). Conclusion After CABG, poor glycemic control is an independent predictor of mortality. However, in IDDM patients, PO hyperglycemia is not associated with mortality, and strict glycemic control increased DSWI, major infections and LOS in these patients. These results suggest that IDDM patients submitted to CABG may benefit from less stringent glycemic targets in PO management. Funding Acknowledgement Type of funding source: None
Background The results of coronary artery bypass graft surgery (CABG) performed with and without the support of cardiopulmonary bypass have already been widely discussed and studied, including through a few large randomized clinical trials. Despite the efforts, the findings of these studies still generate controversy and doubts about the outcomes achieved by the two techniques. One of the contested points is the heterogeneity of the degree of specialization in the off-pump technique in relation to the surgical groups that participated in the studies. Purpose To compare the results in 30 days of on-pump and off-pump CABG. Methods A single centre cohort with 1,767 patients undergoing isolated CABG was initially evaluated (January 2013 – December 2018). 397 patients undergoing off-pump CABG and 1,370 patients undergoing on-pump surgery were identified. To obtain two completely homogeneous study groups, a propensity score matching was applied. For this, a logistic regression model was built with the variable use of CPB support as dependent variable. In the group of independent variables, 14 baseline and operative characteristics were included. The probabilities generated for each patient were used as scores to establish the match. To establish a pair, it was necessary to have three squares after the comma, with the fourth decimal place being the tiebreaker criterion in the pairing. In this way it was possible to obtain 332 pairs (N=664). The paired groups, on and off-pump, were compared by descriptive and univariate analysis and later a logistic regression model was applied to identify possible risk predictors and to verify the impact of CPB support on 30-day mortality. The level of significance was 5% and the analysis was performed using Python 3.0. Results None of the 29 baseline and operative characteristics showed a significant difference between the groups, demonstrating a high degree of homogeneity obtained from the propensity score matching, which enabled a solid comparison between the incidences of outcomes in 30 days. None of the analysed outcomes showed any difference between the groups on and off-pump, including AMI, stroke, major reoperation and death (1.5% vs 2.4%; p=0.401). Through regression analysis it was possible to establish that the use of CPB was not an independent predictor of risk for the occurrence of death (p=0.246). Conclusion After matching by propensity score, patients who underwent surgery with and without CPB had similar incidences of 30-day mortality. In addition, it was possible to verify that the use of CPB was not an independent predictor of risk for the occurrence of death in 30 days. FUNDunding Acknowledgement Type of funding sources: None. Propensity score adjustment by group 30-day outcomes vs CABG technique
Background Coronary artery bypass graft surgery (CABG) is the most common cardiac surgery performed in the world and a significant part of these surgeries are performed without cardiopulmonary bypass (off pump). Although none of the main surgical risk scores include pump use in their prediction model, the scores are widely used in risk stratification, including for patients who will be submitted to off pump CABG. Purpose To analyse and compare the predictive accuracy of EuroScore I, EuroScore II and STS Score for 30-day mortality after off pump CABG. Methods Single-centre cohort with 943 patients consecutively submitted to off pump CABG between January 2010 and December 2020. 31 baseline and operative variables were analysed. The primary outcome was the occurrence of death in the first 30 days after the surgery. Descriptive analysis, normality for quantitative data and univariate inference were performed to compare proportions and means between the survival group (n=930) and death group (n=13). Next, three logistic regression models were performed. Each of them had 30-day mortality as a dependent variable and one of the scores as an independent variable. The probabilities generated by the three models were saved and analysed by ROC curves. Thus, it was possible to assess the predictive accuracy of each of the scores. Finally, the values of the areas under the curves were compared using the DeLong test. The level of significance was 5% and the analysis was performed using the Python 3.0 programming language. Results The mean age of the general group was 63 years old and there was a predominance of male patients (68.4%). The means of the three evaluated risk scores were significantly higher in the Death group (p<0,05). This pattern confirmed the findings of higher prevalence of several comorbidities in the death group. The 30-day mortality rate was 1.37%. Through the analysis of regressions and the probabilities generated through them, it was possible to verify that the predictive accuracy of EuroScore II was significantly higher than that of the other two scores. While the predictive accuracy of EuroScore II was 77.3%, the accuracy of two other scores was in the range of 69% (AUC EsI: 0.697; AUC EsII: 0.773; AUC STS: 0.695; p=0.029). Conclusion EuroScore II seems to be the most adequate surgical risk score for the assessment of mortality risk of patients who will undergoing to off pump CABG. The score had a predictive accuracy of 77.3%, almost 8% more than the other two scores. Therefore, although EuroScore II does not include in its model the use of cardiopulmonary bypass, it has a satisfactory accuracy to be used in clinical-surgical practice. On the other hand, the EuroScore I and the STS Score showed predictive accuracy not adequate for this type of surgery. FUNDunding Acknowledgement Type of funding sources: None. Predictive accuracies of risk scores
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