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Background Other studies have assessed nonadherence to proton pump inhibitors (PPIs), but none has developed a screening test for its detection. Objectives To construct and internally validate a predictive model for nonadherence to PPIs. Methods This prospective observational study with a one-month follow-up was carried out in 2013 in Spain, and included 302 patients with a prescription for PPIs. The primary variable was nonadherence to PPIs (pill count). Secondary variables were gender, age, antidepressants, type of PPI, non-guideline-recommended prescription (NGRP) of PPIs, and total number of drugs. With the secondary variables, a binary logistic regression model to predict nonadherence was constructed and adapted to a points system. The ROC curve, with its area (AUC), was calculated and the optimal cut-off point was established. The points system was internally validated through 1,000 bootstrap samples and implemented in a mobile application (Android). Results The points system had three prognostic variables: total number of drugs, NGRP of PPIs, and antidepressants. The AUC was 0.87 (95% CI [0.83–0.91], p

Background Dual-energy X-ray absorptiometry (DXA) provides separate measurements of fat mass, fat-free mass and bone mass, and is a quick, accurate, and safe technique, yet one that is not readily available in routine clinical practice. Consequently, we aimed to develop statistical formulas to predict fat mass (%) and fat mass index (FMI) with simple parameters (age, sex, weight and height). Methods We conducted a retrospective observational cross-sectional study in 416 overweight or obese patients aged 4–18 years that involved assessing adiposity by DXA (fat mass percentage and FMI), body mass index (BMI), sex and age. We randomly divided the sample into two parts (construction and validation). In the construction sample, we developed formulas to predict fat mass and FMI using linear multiple regression models. The formulas were validated in the other sample, calculating the intraclass correlation coefficient via bootstrapping. Results The fat mass percentage formula had a coefficient of determination of 0.65. This value was 0.86 for FMI. In the validation, the constructed formulas had an intraclass correlation coefficient of 0.77 for fat mass percentage and 0.92 for FMI. Conclusions Our predictive formulas accurately predicted fat mass and FMI with simple parameters (BMI, sex and age) in children with overweight and obesity. The proposed methodology could be applied in other fields. Further studies are needed to externally validate these formulas.

Background. Little research exists on the impact of paid work on academic performance of students of health sciences. No research exists on this subject for students in Colombia. Objectives. This paper seeks to analyze the impact of paid work on academic performance among nursing students. Design, settings and participants: cross-sectional research, involving 430 of nursing students from the National University of Colombia (N = 566). Methods. Variables analyzed: sex, age, work activity, attendance, current semester, degree subjects studied and unavailable, lost credits, grades during the second semester of 2013, and delayed semesters. Subgroups analyzed: (i) according to labor activity: do not work, work up to 20 h and work more than 20 h per week; (ii) Grade point average: failing is considered as less than 3.0 and passing 3.0 or above out of 5.0. Percentage of delayed semesters were calculated. Qualitative and quantitative variables were analyzed for groups by work activity. The percentage and probability of students getting a grade point average less than 3.0 and delaying semesters were calculated by multivariate logistic regression. Results. A total of 219 of the students work (50.9%), the main reason is socioeconomic, of which 99 (45.2%) work more than 20 h per week and have an increased risk of failing, which is higher in the first semester. They also get lower grades, lose more credits and take longer to finish the degree. The logistic bivariate regressions of success (grade point average, credits gained, courses gained and not having delayed semesters) reduce with work, above all in those who work more than 20 h per week and increase as the number of semesters completed increases, independent of sex. Conclusion. A high percentage of nursing students work more than 20 h per week. The compatibility of paid work with studies in university nursing students has a negative impact on academic performance, more so when they work more than 20 h per week. This negative impact diminishes as the student completes semesters, irrespective of the sex of the students.

Objective. The objective of this study is to evaluate the effectiveness of telenutrition versus traditional nutritional consultations for female obese patients in need of nutritional treatment.Methods. A comparative clinical study was conducted among 233 obese or overweight women (including 20 who dropped out and 60 who failed) who consulted a nutrition clinic in Barranquilla (Colombia) for nutritional assessment and chose either telenutrition or a traditional consultation that included a weekly follow-up consultation over 16 weeks, food consumption patterns, Body Mass Index (BMI, kg/m2) registeration and waist and hip circumference registeration. Treatment responses and differences between telenutrition and the traditional consultations were made according to BMI, waist, hip and initial-waist/height ratio (iWaist), calculating for the relative risk.Results. In 68 (29.2%) women who chose traditional attention, 9 (37.5%) dropped out, 24 (40%) failed and 35 (23.5%) were successful, showing 1.4% (1.0 SD) BMI loss, 5.8% (3.4 SD) in waist circumference, 4.5% (2.8 SD) in hip circumference and 0.04% (0.02 SD) in iWaist/height ratio. In 165 (70.8%) women who chose telenutrition, 15 (62.5%) dropped out, 36 (60%) failed and 114 (76.5%) were successful, showing 1.1% (1.0 SD) BMI loss, 5.0% (3.2 SD) in waist circumference, 3.5% (3.1 SD) in hip circumference and 0.03% (0.02 SD) in iWaist/height ratio. A significance level of p < 0.05 is considered.Conclusion. Telenutrition has a failure or dropout risk factor of about half of the value of traditional consultation, and showed slight, statistically significant differences. This study concludes that telenutrition can support or sometimes replace traditional consultations when developing weight loss programs for obese women.

Objective. To explore anthropometric changes in normal-weight, overweight and obese subjects who did not dropout or fail a weight loss program over the 16 treatment weeks to improve patient motivation and treatment adherence.Methods. A clinical intervention study was conducted among 271 (including 100 dropouts and/or failures) obese and overweight patients who consulted a nutrition clinic in Barranquilla (Colombia) for the purpose of nutritional assessment. They were subject to a personalized weekly follow-up consultation over the course of 16 weeks in which initial and the final Body Mass Index (BMI, kg/m2), photographs, food consumption patterns, percentage weight loss, waist and hip circumference were registered and grouped according to BMI, measuring treatment response. Data’s nonparametric statistical comparison was made.Results. In 62 patients from the BMI < 25 group, there is weight loss of 2.6% (3.1 SD), 5.5% (3.3 SD) in waist circumference and 3.0% (2.5 SD) in hip circumference. In 67 patients from the 25 ≥ BMI < 30 group, there is weight loss of 3.8% (4.1 SD), 5.7% (4.5 SD) in waist circumference loss and 3.7% (3.0 SD) in hip circumference loss. In 42 patients from the BMI > 30 group, there is weight loss of 4.8% (3.7 SD), 7.0% (3.6 SD) in waist circumference loss and 3.9% (2.4 SD) in hip circumference loss. Monitoring is done every 4 weeks by the Friedman test, with significant differences between the three groups (p < 0.001). Patients do not drop out of treatment because they start to see physical results in waist decrease. When comparing final values of initial waist/hip circumference ratios and waist/height ratios, a clear decrease in the three BMI groups was observed (p < 0.001).Conclusion. After three weeks of continuous treatment patients improved in all overweight and obesity parameter indicators; there were not statistically significant differences in hip circumference (HC) and waist loss (WC) (%) among the three BMI groups (normal-weight, overweight, and obesity). In contrast, there were statistically significant differences in weight loss (%) and waist-to-hip ratios. Based on anthropometric outcomes and patient perception of their body image it can be concluded that the waist circumference loss is the parameter that retains obese patients in the weight loss program.