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Background
The purpose of this analysis is to describe the differences in cardiac magnetic resonance characteristics between benign and malignant tumors, which would be helpful for surgical planning.Methods
This was a prospective cohort study of 130 patients who underwent cardiac magnetic resonance imaging for evaluation of a suspected cardiac mass. After excluding thrombi and tumors without definitive diagnosis, 66 tumors were evaluated for morphologic features and tissue composition.Results
Of the 66 patients, 39 (59.0%) had malignant tumors and 27 (41.0%) had benign tumors. Patients with malignant tumors were younger when compared with those with benign tumors (age 51 years [42.8-60.0] vs 65 years [60.0-71.0] median). Malignant tumors more often demonstrated tumor invasion (69% vs 0% P < .001) and were more often associated with pericardial effusion (41% vs 7.4% P = .004). Presence of first-pass perfusion (100% vs 33% P < .001) and late gadolinium enhancement (100% vs 59.2%, P < .001) were significantly higher in malignant tumors. In logistic regression modeling, tumor invasion (P < .001) and first-pass perfusion (P < .001) were independently associated with malignancy. Furthermore, using classification and regression tree analysis, we developed a decision tree algorithm to help differentiate benign from malignant tumors (diagnostic accuracy ～90%). The algorithm-weighted cost of misclassifying a malignant tumor as benign was twice that of classifying a benign tumor as malignant.Conclusions
Our study demonstrates that cardiac magnetic resonance imaging is a useful noninvasive method for differentiating malignant from benign cardiac tumors. Tumor size, invasion, and first-pass perfusion were useful imaging characteristics in differentiating benign from malignant tumors. 相似文献Robotic approaches have been steadily replacing laparoscopic approaches in metabolic and bariatric surgeries (MBS); however, their superiority has not been rigorously evaluated. The main goal of the study was to evaluate the 5-year utilization trends of robotic MBS and to compare to laparoscopic outcomes.
MethodsRetrospective analysis of 2015–2019 MBSAQIP data. Kruskal-Wallis test/Wilcoxon and Fisher’s exact/chi-square were used to compare continuous and categorical variables, respectively. Generalized linear models were used to compare surgery outcomes.
ResultsThe use of robotic MBS increased from 6.2% in 2015 to 13.5% in 2019 (N= 775,258). Robotic MBS patients had significantly higher age, BMI, and likelihood of 12 diseases compared to laparoscopic patients. After adjustment, robotic MBS patients showed higher 30-day interventions and 30-day readmissions alongside longer surgery time (26–38 min).
ConclusionRobotic MBS shows higher intervention and readmission even after controlling for cofounding variables.
Graphical Abstract