A Novel Decision Tree Model for Predicting the Cancer-Specific Survival of Patients with Bladder Cancer Treated with Radical Cystectomy.

Background/Objectives: The aim was to develop a decision tree and a new prognostic tool to predict cancer-specific survival in patients with urothelial bladder cancer treated with radical cystectomy. Methods: A total of 11,834 patients with bladder cancer treated with radical cystectomy between 2004 and 2019 from the SEER database were randomly split into the derivation (n = 7889) and validation cohorts (n = 3945). Survival curves were estimated using conditional decision tree analysis. We used Multiple Imputation by Chained Equations for the treatment of missing values and the pec package to compare the predictive performance. We extracted data from our model following CHARMS and assessed the risk of bias and applicability with PROBAST. Results: A total of 4824 (41%) patients died during the follow-up period due to bladder cancer. A decision tree was made and 12 groups were obtained. Patients with a higher AJCC stage and older age have a worse prognosis. The risk groups were summarized into high, intermediate and low risk. The integrated Brier scores between 0 and 191 months for the bootstrap estimates of the prediction error are the lowest for our conditional survival tree (0.189). The model showed a low risk of bias and low concern about applicability. The results must be externally validated. Conclusions: Decision tree analysis is a useful tool with significant discrimination. With this tool, we were able to stratify patients into 12 subgroups and 3 risk groups with a low risk of bias and low concern about applicability.

Characterization and prediction of gambling behavior in adolescents using the COM-B model.

Gambling is an international phenomenon, posing a serious threat to adolescents who begin gambling at a young age. This study aims, to explore gambling behavior in adolescents and interpret its risk factors. We conducted a three-waves cohort longitudinal study assessing gambling and associated risk factors in south-eastern Spain. Data were analyzed using the Capabilities, Opportunities, Motivations, Behavior (COM-B) model and the partial least squares path modelling (PLS-PM) technique. Gambling was measured by frequency and money spent; associated factors were knowledge about gambling, parental attitude towards gambling, risk perception, normative perception, and intention to gamble. These items were assigned as indicators of each construct of the COM-B model-capability, opportunity, motivation, and behavior-using the theoretical domains framework. Once the behavior was performed, feedback on future capability, opportunity, and motivation was observed. Results show that capability, determined by past experience, and opportunity, determined by parental attitudes, motivates adolescents to seek gambling experiences in the future. Identifying such factors that affect gambling behavior in adolescents and establishing relationships between them through a robust theoretical model is essential for designing effective interventions.

A Longitudinal Analysis of Gambling Predictors among Adolescents.

Although gambling is forbidden for minors, the prevalence of gambling among adolescents is increasing. In order to improve preventive interventions, more evidence on predictors of gambling onset is needed. A longitudinal study was proposed to (1) establish the prevalence of gambling; (2) identify factors associated with gambling behavior the following year; and (3) adjust a model to predict gambling behavior. A cohort of 1074 students (13-18 years old) was followed for 12 months. The prevalence of gambling reached 42.0% in the second measure. Boys gambled 2.7 times more than girls, and the highest percentages of gambling onset showed up between 13 and 14 years old. Gambling onset and maintenance was associated with gender, age, sensation-seeking, risk perception, self-efficacy for not gambling, parents' attitude towards gambling, group pressure (friends), subjective norm, exposure to advertising, accessibility, normative perception, gambling in T1 and parents gambling behavior. Gender, gambling in T1 and risk perception were significant in all three logistic adjusted regression models, with the fourth variable being sensation seeking, peer pressure (friends) and accessibility, respectively. It is suggested that universal prevention should be aimed preferably at children under 15 years old and to alert regulators and public administrations to the directly proportional relationship between accessibility and gambling onset.

Footprint Curvature in Spanish Women: Implications for Footwear Fit.

The incorrect adjustment of footwear produces alterations in the foot that affect quality of life. The usual measurements for shoe design are lengths, widths and girths, but these measures are insufficient. The foot presents an angle between the forefoot and the rearfoot in the transverse plane, which is associated with foot pronation, hallux valgus and metatarsus adductus. Here, we aimed at identifying the groups formed by the angulations between the forefoot and rearfoot using a sample of footprints from 102 Spanish women. The angle between the forefoot and rearfoot was measured according to the method described by Bunch. A cluster analysis was performed using the K-means algorithm. Footprints were grouped into three types: curved, semi-curved and straight, according to the degrees of angulation between the forefoot and rearfoot. There is great variability in the morphology of the foot. Based on our findings, to achieve a better footwear fit, we propose the manufacture of three types of lasts with different curvatures.

Screening based on risk factors for abdominal aortic aneurysm in the cardiology clinic.

BACKGROUND: The risk factors for abdominal aortic aneurysm (AAA) are present in many of the patients that attend our cardiology service. The aim of this study was the evaluation of the prospects of examining the abdominal aorta during our consultations and the relationship of AAA with risk factors and ischemic cardiopathy. METHODS: A descriptive transversal observational study was designed including 274 male patients aged ≥60 years, attended consecutively in the cardiology service, in which we studied the abdominal aorta and adjusted a logistic regression model to determine the risk factors associated with AAA. RESULTS: We were able to visualize and measure the abdominal aorta in 95.4% of cases in a fast and reliable way. The prevalence of AAA was 8.76%. 75% of patients with AAA presented ischemic heart disease. Patients with AAA were characterized by the presence of ischemic cardiopathy (Odds Ratio (OR): 4.27, 95% Confidence Interval (CI): 1.37-13.31, p = 0.012), dyslipidemia (OR: 4.99, 95% CI: 1, 07-23.31; p = 0.041), arterial hypertension (OR: 4.14, 95% CI: 1.07-15.98, p = 0.039), and a longer history of smoking (OR: 1.03; 95% CI: 1002-1.054; p = 0.037). CONCLUSIONS: The evaluation of the abdominal aorta during cardiology consultations is feasible with the standard resources. Patients treated in the cardiology service present a high prevalence of AAA. We have adjusted and validated a clinical prediction model based on risk factors that allows the identification, in the cardiology consult, of patients with the highest risk of suffering from AAA.

Derivation and validation model for hospital hypoglycemia.

BACKGROUND: An objective and simple prognostic model for hospitalized patients with hypoglycemia could be helpful in guiding initial intensity of treatment. METHODS: We carried out a derivation rule for hypoglycemia using data from a nationwide retrospective cohort study of patients with diabetes or hyperglycemia carried out in 2014 (n=839 patients). The rule for hypoglycemia was validated using a second data set from a nationwide retrospective cohort study carried out in 2016 (n=561 patients). We derived our prediction rule using logistic regression with hypoglycemia (glucose less than 70mg/dL) as the primary outcome. RESULTS: The incidence of hypoglycemia in the derivation cohort was 10.3%. Patient's characteristics independently associated with hypoglycemia included episodes of hypoglycemia during the previous three months (odds ratio [OR]: 6.29, 95% confidence interval [95%CI]: 3.37-11.79, p<0.001) estimated glomerular filtration rate lower than 30mL/min/1.73m2 (OR: 2.32, 95%CI: 1.23-4.35, p=0.009), daily insulin dose greater than 0.3units per Kg (OR: 1.74, 95%CI: 1.06-2.85, p=0.028), and days of hospitalization (OR: 1.03, 95%CI: 1.01-1.04, p=0.001). The model showed an area under the curve (AUC): 0.72 (95%CI: 0.66-0.78, p<0.001). The AUC in the validation cohort was: 0.71 (95%CI: 0.63-0.79, p<0.001). CONCLUSIONS: The rule showed fair accuracy to predict hypoglycemia. Implementation of the rule into computer systems could be used in guiding initial insulin therapy.