Gianluca Folesani

BACKGROUND: Risk stratification is highly desirable in patients with uncomplicated Stanford type B aortic dissection but inadequately supported by evidence. We sought to validate externally a published prediction model for late adverse events (LAEs), consisting of 1 clinical (connective tissue disease) and 4 imaging variables: maximum aortic diameter, false lumen circumferential angle, false lumen outflow, and number of identifiable intercostal arteries. METHODS: We assembled a retrospective multicenter cohort (ROADMAP [Registry of Aortic Diseases to Model Adverse Events and Progression]) of 401 patients with uncomplicated Stanford type B aortic dissection presenting to 1 of 8 aortic centers between 2001 and 2013, followed until 2020. LAEs were defined as fatal or nonfatal aortic rupture, new refractory hypertension or pain, organ or limb ischemia, aortic aneurysm formation (≥6 cm), or rapid growth (≥1 cm per year). We applied the original model parameters to the validation cohort and examined the effect on risk categorization using LAE end points. RESULTS: One hundred and seventy-six patients (44%) with incomplete imaging or clinical data were excluded. Of 225 patients in the final cohort, 90 (40%) developed LAEs, predominantly driven by aneurysm formation. Baseline maximum aortic diameter was significantly larger in patients with (42.6 [95% CI, 39.1–45.8] mm) compared with patients without LAEs (39.9 [95% CI, 36.3–44.2] mm; P =0.001). A multivariable Cox regression model indicated that only maximum diameter was associated with LAEs (hazard ratio, 1.07 [95% CI, 1.03–1.11] per mm; P 0.05). Applying the original prediction model to the validation cohort resulted in a poor 5-year sensitivity (38%) and specificity (69%). CONCLUSIONS: A clinical and imaging-based prediction model performed poorly in the ROADMAP cohort. Maximum aortic diameter remains the strongest predictor of LAEs in uncomplicated Stanford type B aortic dissection.

Background: Bradyarrhythmia requiring pacemaker implantation among patients undergoing valve surgery may occur even after several years, with unclear predictors. Our aim was to investigate the incidence of pacemaker implantation at different follow-up times and identify associated predictors. Methods: We conducted a retrospective study evaluating 1046 consecutive patients who underwent valve surgery at the Cardiac Surgery Division of Bologna University Hospital from 2005 to 2010. Results: During 10 ± 4 years of follow-up, 11.4% of these patients required pacemaker implantation. Interventions on both atrioventricular valves independently predicted long-term pacemaker implantation (SHR 2.1, 95% CI 1.2–3.8, p = 0.014). Preoperative atrioventricular conduction disease strongly predicted long-term atrioventricular block, with right bundle branch block as the major predictor (SHR 7.0, 95% CI 3.9–12.4, p < 0.001), followed by left bundle branch block (SHR 4.9, 95% CI 2.4–10.1, p < 0.001), and left anterior fascicular block (SHR 3.9, 95% CI 1.8–8.3, p < 0.001). Conclusion: Patients undergoing valvular surgery have a continuing risk of atrioventricular block late after surgery until the 12-month follow-up, which was clearly superior to the rate of atrioventricular block observed at long-term. Pre-operative atrioventricular conduction disease and combined surgery on both atrioventricular valves are strong predictors of atrioventricular block requiring pacemaker implantation.

Background: Infective endocarditis (IE) is a serious disease, and in many cases, surgery is necessary. Whether the type of prosthesis implanted for aortic valve replacement (AVR) for IE impacts patient survival is a matter of debate. The aim of the present study is to quantify differences in long-term survival and recurrence of endocarditis AVR for IE according to prosthesis type among patients aged 40 to 65 years. Methods: This was an analysis of the INFECT-REGISTRY. Trends in proportion to the use of mechanical prostheses versus biological ones over time were tested by applying the sieve bootstrapped t-test. Confounders were adjusted using the optimal full-matching propensity score. The difference in overall survival was compared using the Cox model, whereas the differences in recurrence of endocarditis were evaluated using the Gray test. Results: Overall, 4365 patients were diagnosed and operated on for IE from 2000 to 2021. Of these, 549, aged between 40 and 65 years, underwent AVR. A total of 268 (48.8%) received mechanical prostheses, and 281 (51.2%) received biological ones. A significant trend in the reduction of implantation of mechanical vs. biological prostheses was observed during the study period (p < 0.0001). Long-term survival was significantly higher among patients receiving a mechanical prosthesis than those receiving a biological prosthesis (hazard ratio [HR] 0.546, 95% CI: 0.322–0.926, p = 0.025). Mechanical prostheses were associated with significantly less recurrent endocarditis after AVR than biological prostheses (HR 0.268, 95%CI: 0.077–0.933, p = 0.039). Conclusions: The present analysis of the INFECT-REGISTRY shows increased survival and reduced recurrence of endocarditis after a mechanical aortic valve prosthesis implant for IE in middle-aged patients.

Background: Infective endocarditis(IE) is a serious disease and in many cases surgery is necessary. Whether the type of prosthesis implanted for aortic valve replacement(AVR) for IE impacts patient survival is a matter of debate. The aim of the present study is to quantify differences in long-term survival, recurrence of endocarditis AVR for IE according to prosthesis type among patients aged 40 to 65 years. Methods: This was an analysis of the INFECT-REGISTRY. Overall, 4365 patients were diagnosed and operated on for IE from 2000 to 2021. Of these, 549 aged between 40 and 65 years underwent AVR. 268(48.8%) received mechanical prostheses, and 281(51.2%) biological ones. Confounders were adjusted using optimal full matching propensity score. Results: A significant trend in reduction of implantation of mechanical vs biological prostheses was observed during the study period(p<0.0001). Long-term survival was significantly higher among patients receiving a mechanical prosthesis than those receiving a biological prosthesis (hazard ratio [HR] 0.546,95%CI: 0.322-0.926, p=0.025). Mechanical prostheses were significantly associated with less recurrent endocarditis after AVR (HR 0.268,95%CI:0.077-0.933,p=0.039).Conclusions: The present analysis of the INFECT-REGISTRY shows increased survival and reduced recurrence of endocarditis after mechanical aortic valve prosthesis implant for IE in middle-aged patients.

Primary cardiac sarcomas are considered rare malignant entities associated with poor prognosis. In fact, knowledge regarding their gene signature and possible treatments is still limited. In our study, whole-transcriptome sequencing on formalin-fixed paraffin-embedded (FFPE) samples from one cardiac osteosarcoma and one cardiac leiomyosarcoma was performed, to investigate their mutational profiles and to highlight differences and/or similarities to other cardiac histotypes. Both cases have been deeply detailed from a pathological point of view. The osteosarcoma sample presented mutations involving ATRX, ERCC5, and COL1A1, while the leiomyosarcoma case showed EXT2, DNM2, and PSIP1 alterations. Altered genes, along with the most differentially expressed genes in the leiomyosarcoma or osteosarcoma sample versus the cardiac angiosarcomas and intimal sarcomas (e.g., YAF2, PAK5, and CRABP1), appeared to be associated with cell growth, proliferation, apoptosis, and the repair of DNA damage, which are key mechanisms involved in tumorigenesis. Moreover, a distinct gene expression profile was detected in the osteosarcoma sample when compared to other cardiac sarcomas. For instance, WIF1, a marker of osteoblastic differentiation, was upregulated in our bone tumor. These findings pave the way for further studies on these entities, in order to identify targeted therapies and, therefore, improve patients’ prognoses.

This report presents the design and methodological approach of a multicenter, retrospective study to validate a clinical and imaging-based risk prediction model for late adverse events in patients ... Purpose To describe the design and methodological approach of a multicenter, retrospective study to externally validate a clinical and imaging-based model for predicting the risk of late adverse ev...

Background: The diagnosis of periprocedural myocardial infarction (PMI) after coronary artery bypass graft (CABG) is based on biochemical markers along with clinical and instrumental findings. However, there is not a clear cutoff value of high-sensitivity cardiac troponin (hs-cTn) to identify PMI. We hypothesized that isolated hs-cTn concentrations in the first 24 h following CABG could predict cardiac adverse events (in-hospital death and PMI) and/or left ventricular ejection fraction (LVEF) decrease. Methods: We retrospectively enrolled all consecutive adult patients undergoing CABG, alone or in association with other cardiac surgery procedures, over 1 year. Hs-cTn I concentrations (Access, Beckman Coulter) were serially measured in the post-operative period and analyzed according to post-operative outcomes. Results: 300 patients were enrolled; 71.3% underwent CABG alone, 33.7% for acute coronary syndrome. Most patients showed hs-cTn I values superior to the limit required by the latest guidelines for the diagnosis of PMI. Five patients (1.7%) died, 8% developed a PMI, 10.6% showed a LVEF decrease ≥ 10%. Hs-cTn I concentrations did not significantly differ with respect to death and/or PMI whereas they were associated with LVEF decrease ≥ 10% (p value < 0.005 at any time interval), in particular hs-cTn I values at 9–12 h post-operatively. A hs-cTn I cutoff of 5556 ng/L, a value 281 (for males) and 479 (for females) times higher than the URL, at 9–12 h post-operatively was identified, representing the best balance between sensitivity (55%) and specificity (79%) in predicting LVEF decrease ≥ 10%. Conclusions: Hs-cTn I at 9–12 h post-CABG may be useful to early identify patients at risk for LVEF decrease and to guide early investigation and management of possible post-operative complications.

Objectives Establishing the reproducibility of expert-derived measurements on CTA exams of aortic dissection is clinically important and paramount for ground-truth determination for machine learning. Methods Four independent observers retrospectively evaluated CTA exams of 72 patients with uncomplicated Stanford type B aortic dissection and assessed the reproducibility of a recently proposed combination of four morphologic risk predictors (maximum aortic diameter, false lumen circumferential angle, false lumen outflow, and intercostal arteries). For the first inter-observer variability assessment, 47 CTA scans from one aortic center were evaluated by expert-observer 1 in an unconstrained clinical assessment without a standardized workflow and compared to a composite of three expert-observers (observers 2–4) using a standardized workflow. A second inter-observer variability assessment on 30 out of the 47 CTA scans compared observers 3 and 4 with a constrained, standardized workflow. A third inter-observer variability assessment was done after specialized training and tested between observers 3 and 4 in an external population of 25 CTA scans. Inter-observer agreement was assessed with intraclass correlation coefficients (ICCs) and Bland-Altman plots. Results Pre-training ICCs of the four morphologic features ranged from 0.04 (−0.05 to 0.13) to 0.68 (0.49–0.81) between observer 1 and observers 2–4 and from 0.50 (0.32–0.69) to 0.89 (0.78–0.95) between observers 3 and 4. ICCs improved after training ranging from 0.69 (0.52–0.87) to 0.97 (0.94–0.99), and Bland-Altman analysis showed decreased bias and limits of agreement. Conclusions Manual morphologic feature measurements on CTA images can be optimized resulting in improved inter-observer reliability. This is essential for robust ground-truth determination for machine learning models. Key Points • Clinical fashion manual measurements of aortic CTA imaging features showed poor inter-observer reproducibility. • A standardized workflow with standardized training resulted in substantial improvements with excellent inter-observer reproducibility. • Robust ground truth labels obtained manually with excellent inter-observer reproducibility are key to develop reliable machine learning models.

The application of digital technologies such as 3D modeling, 3D printing, and virtual surgery implemented in the medical field makes it possible to improve the representation of the patient's anatomy and to analyze the clinical case in more detail than the two-dimensional visualization of images from CT, MRI, and ultrasound. In particular, the use of technologies such as 3D printing in cardiac surgery is useful for studying patient-specific cardiac anatomy and manipulating the object of study preoperatively. The integration of a preoperative planning methodology integrated with the new advanced tools facilitates the cardiac surgeon in developing a more informed and precise surgical strategy. Indeed, new technologies allow surgery to be designed and planned in a virtual environment before it is performed in the operating room. This study reports the application of advanced technologies for aortic arch reconstruction in a virtual and physical environment as a tool for the analysis of cardiac pathologies, e.g., aortic dissection. The process involves the use of software that can convert the patient's medical information into a three-dimensional digital model that can be imported into a virtual environment and then 3D printed.