New reference tables and user-friendly Internet application for predicted heart weights.

BACKGROUND: Knowledge of normal heart weight ranges is important information for pathologists. Comparing the measured heart weight to reference values is one of the key elements used to determine if the heart is pathological, as heart weight increases in many cardiac pathologies. The current reference tables are old and in need of an update. AIMS: The purposes of this study are to establish new reference tables for normal heart weights in the local population and to determine the best predictive factor for normal heart weight. We also aim to provide technical support to calculate the predictive normal heart weight. METHODS: The reference values are based on retrospective analysis of adult Caucasian autopsy cases without any obvious pathology that were collected at the University Centre of Legal Medicine in Lausanne from 2007 to 2011. We selected 288 cases. The mean age was 39.2 years. There were 118 men and 170 women. Regression analyses were performed to assess the relationship of heart weight to body weight, body height, body mass index (BMI) and body surface area (BSA). RESULTS: The heart weight increased along with an increase in all the parameters studied. The mean heart weight was greater in men than in women at a similar body weight. BSA was determined to be the best predictor for normal heart weight. New reference tables for predicted heart weights are presented as a web application that enable the comparison of heart weights observed at autopsy with the reference values. CONCLUSIONS: The reference tables for heart weight and other organs should be systematically updated and adapted for the local population. Web access and smartphone applications for the predicted heart weight represent important investigational tools.

Who eats healthily? A population-based study among young Swiss residents.

OBJECTIVE: To assess whether Swiss residents aged 15-24 years follow current nutritional guidelines and whether differences exist according to gender and weight status. DESIGN: Cross-sectional national survey. SETTING: Switzerland. SUBJECTS: The 1786 participants (48·4 % women) were divided into overweight, normal weight and underweight. We used traditional BMI cut-offs for people ≥18 years of age (underweight = BMI < 18·5 kg/m2, normal weight = BMI ≥ 18·5 kg/m2 and <25 kg/m2, overweight = BMI ≥ 25 kg/m2) and age- and gender-appropriate tables for people aged <18 years, with BMI calculated from self-reported weight and height. We performed bivariate analyses by gender, and then bivariate and multivariate analyses comparing overweight to normal weight people (excluding underweight, n 129, 71·6 % women) regarding adherence to recommendations for fruit, vegetables, meat, fish and dairy products; physical activity; attitude towards body weight; depression, smoking and alcohol consumption. RESULTS: Overall, adherence to nutritional guidelines was low, particularly for vegetables and dairy products. Women had a higher adherence than men except for fish and dairy products. In the multivariate analyses, overweight women had a lower vegetable intake, were less satisfied with body weight and had more often been on a diet, whereas overweight men were less satisfied with body weight and wanted to lose weight more often than their normal weight peers. There were no significant differences for physical activity. CONCLUSIONS: Overweight prevention programmes should target youth specifically by gender and promote an appropriate self-perception. Overweight women should be encouraged to eat more vegetables and men to be more sensitised on healthy food. Further research is needed to assess how to make nutritional guidelines more adaptable to young people's daily life.

New reference tables and user-friendly Internet application for predicted heart weights.

BACKGROUND: Knowledge of normal heart weight ranges is important information for pathologists. Comparing the measured heart weight to reference values is one of the key elements used to determine if the heart is pathological, as heart weight increases in many cardiac pathologies. The current reference tables are old and in need of an update. AIMS: The purposes of this study are to establish new reference tables for normal heart weights in the local population and to determine the best predictive factor for normal heart weight. We also aim to provide technical support to calculate the predictive normal heart weight. METHODS: The reference values are based on retrospective analysis of adult Caucasian autopsy cases without any obvious pathology that were collected at the University Centre of Legal Medicine in Lausanne from 2007 to 2011. We selected 288 cases. The mean age was 39.2 years. There were 118 men and 170 women. Regression analyses were performed to assess the relationship of heart weight to body weight, body height, body mass index (BMI) and body surface area (BSA). RESULTS: The heart weight increased along with an increase in all the parameters studied. The mean heart weight was greater in men than in women at a similar body weight. BSA was determined to be the best predictor for normal heart weight. New reference tables for predicted heart weights are presented as a web application that enable the comparison of heart weights observed at autopsy with the reference values. CONCLUSIONS: The reference tables for heart weight and other organs should be systematically updated and adapted for the local population. Web access and smartphone applications for the predicted heart weight represent important investigational tools.

Could machine learning improve the prediction of pelvic nodal status of prostate cancer patients? Preliminary results of a pilot study.

We tested and compared performances of Roach formula, Partin tables and of three Machine Learning (ML) based algorithms based on decision trees in identifying N+ prostate cancer (PC). 1,555 cN0 and 50 cN+ PC were analyzed. Results were also verified on an independent population of 204 operated cN0 patients, with a known pN status (187 pN0, 17 pN1 patients). ML performed better, also when tested on the surgical population, with accuracy, specificity, and sensitivity ranging between 48-86%, 35-91%, and 17-79%, respectively. ML potentially allows better prediction of the nodal status of PC, potentially allowing a better tailoring of pelvic irradiation.