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PURPOSE Recurrently mutated genes and chromosomal abnormalities have been identified in myelodysplastic syndromes (MDS). We aim to integrate these genomic features into disease classification and prognostication. METHODS We retrospectively enrolled 2,043 patients. Using Bayesian networks and Dirichlet processes, we combined mutations in 47 genes with cytogenetic abnormalities to identify genetic associations and subgroups. Random-effects Cox proportional hazards multistate modeling was used for developing prognostic models. An independent validation on 318 cases was performed. RESULTS We identify eight MDS groups (clusters) according to specific genomic features. In five groups, dominant genomic features include splicing gene mutations ( SF3B1, SRSF2, and U2AF1) that occur early in disease history, determine specific phenotypes, and drive disease evolution. These groups display different prognosis (groups with SF3B1 mutations being associated with better survival). Specific co-mutation patterns account for clinical heterogeneity within SF3B1- and SRSF2-related MDS. MDS with complex karyotype and/or TP53 gene abnormalities and MDS with acute leukemia–like mutations show poorest prognosis. MDS with 5q deletion are clustered into two distinct groups according to the number of mutated genes and/or presence of TP53 mutations. By integrating 63 clinical and genomic variables, we define a novel prognostic model that generates personally tailored predictions of survival. The predicted and observed outcomes correlate well in internal cross-validation and in an independent external cohort. This model substantially improves predictive accuracy of currently available prognostic tools. We have created a Web portal that allows outcome predictions to be generated for user-defined constellations of genomic and clinical features. CONCLUSION Genomic landscape in MDS reveals distinct subgroups associated with specific clinical features and discrete patterns of evolution, providing a proof of concept for next-generation disease classification and prognosis.

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Considering the linear relationships between WT, amount of fibrosis and both UV and BV, the search for any distinct voltage cut-off to identify fibrosis in NICM is futile. The amount of fibrosis can be calculated, if WT and voltages are known. Fibrosis pattern and architecture are different from ischaemic cardiomyopathy and findings on ischaemic substrates may not be applicable to NICM.

The aims of the study were to analyze the clinical and epidemiological characteristics and treatments for patients who developed zygomycosis enrolled in Italy during the European Confederation of Medical Mycology of medical mycology survey. This prospective multicenter study was performed between 2004 and 2007 at 49 italian Departments. 60 cases of zygomycosis were enrolled: the median age was 59.5 years (range 1-87), with a prevalence of males (70%). The majority of cases were immunocompromised patients (42 cases, 70%), mainly hematological malignancies (37). Among non-immunocompromised (18 cases, 30%), the main category was represented by patients with penetrating trauma (7/18, 39%). The most common sites of infection were sinus (35%) with/without CNS involvement, lung alone (25%), skin (20%), but in 11 cases (18%) dissemination was observed. According to EORTC criteria, the diagnosis of zygomycosis was proven in 46 patients (77%) and in most of them it was made in vivo (40/46 patients, 87%); in the remaining 14 cases (23%) the diagnosis was probable. 51 patients received antifungal therapy and in 30 of them surgical debridement was also performed. The most commonly used antifungal drug was liposomal amphotericin B (L-AmB), administered in 44 patients: 36 of these patients (82%) responded to therapy. Altogether an attributable mortality rate of 32% (19/60) was registered, which was reduced to 18% in patients treated with L-AmB (8/44). Zygomycosis is a rare and aggressive filamentous fungal infection, still associated with a high mortality rate. This study indicates an inversion of this trend, with a better prognosis and significantly lower mortality than that reported in the literature. It is possible that new extensive, aggressive diagnostic and therapeutic procedures, such as the use of L-AmB and surgery, have improved the prognosis of these patients.

ObjectiveMitral valve prolapse (MVP) has been associated with ventricular arrhythmias (VA), but little is known about VA in patients with significant primary mitral regurgitation (MR). Our aim was to describe the prevalence of symptomatic VA in patients with MVP (fibro-elastic deficiency or Barlow’s disease) referred for mitral valve (MV) surgery because of moderate-to-severe MR, and to identify clinical, electrocardiographic, standard and advanced echocardiographic parameters associated with VA.Methods610 consecutive patients (64±12 years, 36% female) were included. Symptomatic VA was defined as symptomatic and frequent premature ventricular contractions (PVC, Lown grade ≥2), non-sustained or sustained ventricular tachycardia (VT) or ventricular fibrillation (VF) without ischaemic aetiology.ResultsA total of 67 (11%) patients showed symptomatic VA, of which 3 (4%) had VF, 3 (4%) sustained VT, 27 (40%) non-sustained VT and 34 (51%) frequent PVCs. Patients with VA were significantly younger, more often female and showed T-wave inversions; furthermore, they showed significant MV morphofunctional abnormalities, such as mitral annular disjunction (39% vs 20%, p<0.001), and dilatation (annular diameter 37±5 mm vs 33±6 mm, p<0.001), lower global longitudinal strain (GLS 20.9±3.1% vs 22.0±3.6%, p=0.032) and prolonged mechanical dispersion (45±12 ms vs 38±14 ms, p=0.003) as compared with patients without VA. Female sex, increased MV annular diameter, lower GLS and prolonged mechanical dispersion were identified as independent associates of symptomatic VA.ConclusionIn patients with MVP with moderate-to-severe MR, symptomatic VA are relatively frequent and associated with significant MV annular abnormalities, subtle left ventricular function impairment and heterogeneous contraction. Assessment of these parameters might help decision-making over further diagnostic analyses and improve risk-stratification.