Multiple retrospective analysis of survival and evaluation of 4 cardiac death predictors in a population of dogs affected by 5 degenerative mitral valve disease in ACVIM class C treated 6 with different therapeutic protocols

Clinical records of dogs with spontaneous degenerative mitral valve disease (DMVD) with clinical signs related to congestive heart failure (CHF) that had been recruited during routine clinical practice, between 2001 and 2018 at the Cardiology Unit of the Veterinary Teaching Hospital (University of Milan) were included in this retrospective cohort study. Baseline echocardiographic data were evaluated. Median survival times (MSTs) were calculated. Data on therapeutic treatment, ISACHC or ACVIM classes were reviewed based on the inclusion period and type of endpoint (i.e. cardiac death or death for other causes). The main goal of this data review was to retrospectively evaluate 259 clinical records of subjects belonging to ACVIM C class examined between 2001 to 2018 together with the 202 examined between 2010 to 2018. The MSTs of these subjects was 531 d (2001-2018) and 335.5 d (2010-2018), respectively. Univariate survival regression analysis for subjects included from 2010 to 2018 showed the following variables as being significantly related to cardiac death (CD): LA/Ao ratio (HR 2.754, p=0.000), E wave (HR 2.961, p=0.000), E/A ratio (HR 1.372, p=0.000), EDVI (HR 1.007, p=0.000), ESVI (HR 1.012, p=0.026), Allo(d) (HR 4.018, p=0.000) andAllo(s) (HR 2.674, p=0.049), age (HR 1.006, p=0.009) and PH severity (HR=1.309, p=0.012). Multivariate analysis, adjusted for age, showed that the only variable that determined a statistically significant difference in MST was PH severity (HR 1.334, p=0.033). The type of therapeutic treatment within this class was not significant for the MST of the subjects

Simultaneous Learning of Fuzzy Sets

We extend a procedure based on support vector clustering and devoted to inferring the membership function of a fuzzy set to the case of a universe of discourse over which several fuzzy sets are defined. The extended approach learns simultaneously these sets without requiring as previous knowledge either their number or labels approximating membership values. This data-driven approach is completed via expert knowledge incorporation in the form of predefined shapes for the membership functions. The procedure is successfully tested on a benchmark

Influence of body variables in the development of metabolic syndrome : A long term follow-up study

Objectives. The body variable associated with the diagnosis of Metabolic Syndrome (MetS) is an elevated waist circumference (WC), although a number of other variables have been suggested. Among these, an elevated waist-to-height ratio (WHtR), ie a value higher than 0.5, that may identify abnormality, independently from height. An elevated WHtR provided the best correlation with MetS in a prior study in a large Italian population. In order to assess the validity of this conclusion, a long-term follow-up study re-examined this population, also in order to detect possible associations with cardiovascular (CV) risk. Methods and Results. 1,071 subjects with a complete follow-up of over 6 years were evaluated with a comparative assessment of the three anthropometric variables, namely WHtR, WC and body mass index (BMI). WHtR 65 0.5 had the highest sensitivity for the identification of MetS, both in males and females (94.1% and 86.7% respectively). WHtR was of reduced specificity, occurring, yet less frequently (17.7% in males and 30% in females), in patients without MetS. By contrast, enlarged WC occurred with a lower frequency in male patients who developed MetS (30.2%) whereas in females, frequency was higher than in males (69.3%). Finally, a BMI 65 25 kg/m2 had intermediate sensitivity and specificity regardless of gender. WC showed the highest odds ratio (2.62, 95%CI: 1.18-5.78) for the prediction of CV occurrence. Conclusion. The present study confirms WHtR as an excellent screening tool in identifying MetS carriers, but, different from reports in other countries, it shows a lower specificity in our population

Preliminary Investigation of Cardiovascular–Renal Disorders in Dogs with Chronic Mitral Valve Disease

Background: Veterinary literature lacks data about cardiovascular\u2013renal disorders (CvRD) and cardiorenal-anemia syndrome (CRAS) in dogs. Hypothesis: A direct correlation exists between ACVIM class and IRIS stage; chronic kidney disease (CKD) complicates chronic mitral valve disease (CMVD) more often than does anemia in dogs. Animals: One hundred and fifty-eight client-owned dogs with CMVD. Methods: Signalment, physical examination findings, electrocardiography, thoracic radiographs, echocardiography, and blood analysis were retrospectively evaluated to assess the prevalence of CKD and anemia in dogs with CMVD and to investigate the relationships among ACVIM class, IRIS stage, and survival. Results: The prevalence of CKD and anemia in dogs with CMVD was significantly higher than in the general population of dogs. Dogs being treated for heart failure had a significantly higher prevalence of CKD than did dogs that had not received treatment. A statistically significant direct correlation was found between ACVIM class and IRIS stage. Severe heart disease, severe renal disease or both, furosemide administration, and advanced age at diagnosis of heart disease were associated with shorter survival time. Survival time of dogs affected by CvRD was statistically shorter than survival time of dogs affected by CMVD alone. Conclusion and Clinical Relevance: Chronic mitral valve disease is associated with increased prevalence of CKD and anemia in dogs. Treatment for medical management of heart failure may play a role in inducing CKD. Class of heart disease and IRIS stage were directly correlated. Cardiovascular\u2013renal disorders decrease survival time compared to the only presence of CMVD alone, whereas anemia does not play a central role in worsening heart function

An integrated symbolic/subsymbolic architecture for parsing Italian sentences containing PP-attachment ambiguities

This paper describes a hybrid (symbolic/connectionist) system that performs PP-attachment disambiguation by taking advantage of three distinguishing features of neutral networks: distributed representation, functional compositionality, and inductive learning. The connectionist part of the system follows all the steps performed by the symbolic parser, and drives the parser's behavior by inducing a bias towards the most semantically plausible attachment choices. The sentence to be parsed is read one word at a time. When the symbolic parser has more than one production to apply, the connectionist module has already developed an inner representation of the sentence and a distribution of probabilities over the possible choices. The parser continues its work according to such a distribution. Copyrigh

Learning fuzzy rules with Tabu Search: an application to control

In this paper, we present a new approach for the automatic definition of the fuzzy rules for a fuzzy controller based on the use of the tabu search (TS) scheme. We show also how the application of the TS process to the learning of a fuzzy rule base can be improved using heuristic symbolic meta rules. The paper is divided in two parts. The first part (Sections I-III) presents an introduction to TS and different learning schemes which can be used to apply it for the determination of the fuzzy control rules. The second part (Sections IV-VI) illustrates the application of the proposed techniques to a specific control problem - the parking of a truck and trailer. In particular, Section V illustrates the definition of a rule base for a static fuzzy controller, while Section VI presents the construction of an adaptive parking controller

Synthesis of fuzzy controllers through neural networks

Most of the current fuzzy logic control applications are designed using different heuristics for the controller synthesis, and then implemented using conventional programming languages on general purpose microcontrollers. We are proposing a methodology for the design of fuzzy controllers based on the cell-to-cell mapping approach for the fuzzy control law synthesis, and on neural networks for: (a) the discovery of the set of appropriate fuzzy rules that characterise a control law, and (b) the tuning of parameters that characterise membership functions (namely position and width). We suppose that training data are coming from sampling of the analytical control function. Two examples are shown, and a comparison with the results obtained by a generalized multilayer perceptron is discussed

Waist-to-height ratio is a highly sensitive index for the metabolic syndrome in a mediterranean population

Background: The waist-to-height ratio (WHtR) is a potentially more reliable anthropometric index, particularly for populations of lower height. Performance of the WHtR versus body mass index (BMI) and enlarged waist circumference (WC) in the assessment of the metabolic syndrome was tested in nonobese males and females in a high-risk Italian population. Methods: WHtR, BMI, and WC were determined in 552 males and 552 females, together with the evaluation of associated metabolic syndrome variables (hypertension, hyperglycemia, hypertriglyceridemia, and low high-density lipoprotein cholesterol [HDL-C]). Results: WHtR 65 0.5, the most frequently suggested threshold value, when added to any two nonanthropometric variables, gave a sensitivity for the identification of a metabolic syndrome of, respectively, 92.0% for males and 87.4% for females. Sensitivities for elevated WC (American Heart Association [AHA] criteria) and BMI 65 25 proved lower. Areas under the receiver operating characteristic (ROC) curves for the different anthropometric indices confirmed that a WHtR 65 0.5 provides a satisfactory balance between sensitivity and specificity. Conclusions: WHtR 65 0.5 may be the most effective anthropometric index for screening high-risk patients in the diagnosis of metabolic syndrome, with the advantage of the opportunity of direct comparisons with other population