Giacomo Aletti

Identification of patient groups at highest risk from traditional approach to ovarian cancer treatment

OBJECTIVE Define subgroups of patients at highest risk for major morbidity and mortality after a traditional approach of maximal surgical efforts followed by chemotherapy for advanced ovarian cancer (AOC). METHODS Preoperative health, intra-operative findings and outcomes were assessed in consecutive patients with primary AOC from 4 centers. Initial tumor dissemination was stratified into 3 groups based on volume of disease. Surgery was categorized using a previously described surgical complexity score (SCS). Statistical analysis was directed toward validating a multivariable risk-adjusted model. RESULTS 576 patients with stage IIIC (N=447, 77.6%) or IV AOC (N=129, 22.4%) were analyzed. Age (HR (per year): 1.02; 95%CI: 1.01-1.03), high tumor dissemination (HTD) (HR: 1.73; 95%CI: 1.19-2.56), residual disease (RD) >1 cm (HR: 2.46; 95%CI: 1.74-3.53), and stage IV (HR: 1.93; 95% CI: 1.51-2.45), independently correlated with OS. We identified a small subgroup of patients who comprised a high-risk group (N=38, 6.6%) characterized by all of the following characteristics: high initial tumor dissemination (HTD) or stage IV plus poor performance or nutritional status plus age ≥ 75. In this group, high SCS to achieve low RD was associated with morbidity of 63.6% and limited survival benefit. CONCLUSIONS Optimal management of AOC requires accurate, risk-adjusted predictors of outcomes allowing a tailored approach starting with primary therapy. Complex surgical procedures to render low RD improve survival, and in the majority of cases, the benefits of such surgery appear to outweigh the morbidity. However careful analysis identifies a subgroup of patients in whom an alternative approach may be the better strategy.

Long-term outcome of patients who require renal replacement therapy after cardiac surgery

Background and objective: Acute renal failure is a serious complication of cardiac surgery. We studied the long‐term survival and quality of life of patients requiring renal replacement therapy after cardiac surgery, since they represent a heavy burden on hospital resources and their outcome has never been adequately evaluated. Methods: Out of 7846 consecutive cardiac surgical patients, 126 (1.6%) required postoperative renal replacement therapy: their preoperative status and hospital course was compared with patients who had no need of postoperative renal replacement therapy. A multivariate analysis identified predictors of renal replacement therapy. Long‐term survival and quality of life was collected in patients who had renal replacement therapy and in case‐matched controls. Results: Hospital mortality in the study group was 84/126 (66.7%) vs. 118/7720 (1.5%) in the control population (P < 0.001). Patients who underwent renal replacement therapy and were discharged from the hospital (42 patients) had a reasonable long‐term outcome: at 42 ± 23 months, 30 out of 42 patients were alive, with only 3 patients complaining of limitations in daily activities. Predictors of in‐hospital renal replacement therapy were: emergency surgery, preoperative renal impairment, intra‐aortic balloon pumping, reoperation for bleeding, previous cardiac surgery, female gender, low ejection fraction, bleeding >1000 mL, chronic obstructive pulmonary disease and age. Conclusions: This study confirms that the in‐hospital mortality of patients requiring renal replacement therapy is high and shows a low long‐term mortality with reasonable quality of life in patients discharged from hospital alive.

First‐Order Continuous Models of Opinion Formation

We study certain nonlinear continuous models of opinion formation derived from a kinetic description involving exchanges of opinion between individual agents. These models imply that the only possible final opinions are the extremal ones, and they are similar to models of pure drift in magnetization. Both analytical and numerical methods allow us to recover the final distribution of opinion between the two extremal ones.

A Central Limit Theorem, and related results, for a two-color randomly reinforced urn

We prove a central limit theorem for the sequence of random compositions of a two-color randomly reinforced urn. As a consequence, we are able to show that the distribution of the urn limit composition has no point masses.

Statistical aspects of fuzzy monotone set-valued stochastic processes. Application to birth-and-growth processes

The paper considers a particular family of fuzzy monotone set-valued stochastic processes. The proposed setting allows us to investigate suitable @a-level sets of such processes, modeling birth-and-growth processes. A decomposition theorem is established to characterize the nucleation and the growth. As a consequence, different consistent set-valued estimators are studied for growth process. Moreover, the nucleation process is studied via the hitting function, and a consistent estimator of the nucleation hitting function is derived.

INTEGRATION IN A DYNAMICAL STOCHASTIC GEOMETRIC FRAMEWORK

We propose a set–valued framework for the well–posedness of birth– and–growth process. Our birth–and–growth model is rigorously defined as a suitable combination, involving Minkowski sum and Aumann integral, of two very general set–valued processes representing nucleation and growth respectively. The simplicity of the used geometrical approach leads us to avoid problems arising by an analytical definition of the front growth such as boundary regularities. In this framework, growth is generally anisotropic and, according to a mesoscale point of view, it is not local, i.e. for a fixed time instant, growth is the same at each space point.

A decomposition theorem for fuzzy set-valued random variables

Let

A Functional Equation Whose Unknown is \mathcal{P}([0,1]) Valued

X

Mathematical characterisation of the transduction chain in growth cone pathfinding

be a fuzzy set--valued random variable (\frv{}), and

Mitral valve surgery and acute renal failure

\huku{X}