Pharmacokinetic Simulation and Area under the Curve Estimation of Drugs Subject to Enterohepatic Circulation.

Enterohepatic circulation (EHC) is a complex process where drugs undergo secretion and reabsorption from the intestinal lumen multiple times, resulting in pharmacokinetic profiles with multiple peaks. The impact of EHC on area under the curve (AUC) has been a topic of extensive debate, questioning the suitability of conventional AUC estimation methods. Moreover, a universal model for accurately estimating AUC in EHC scenarios is lacking. To address this gap, we conducted a simulation study evaluating five empirical models under various sampling strategies to assess their performance in AUC estimation. Our results identify the most suitable model for EHC scenarios and underscore the critical role of meal-based sampling strategies in accurate AUC estimation. Additionally, we demonstrate that while the trapezoidal method performs comparably to other models with a large number of samples, alternative models are essential when sample numbers are limited. These findings not only illuminate how EHC influences AUC but also pave the way for the application of empirical models in real-world drug studies.

Fat Mass Index (FMI) as a Trustworthy Overweight and Obesity Marker in Mexican Pediatric Population.

Predictive formulas to estimate body composition in children have been explored for some time, to this date, the most accurate obesity diagnostic tool is to determine fat mass. The aim of this study is to establish cutoff points that allow for a precise interpretation of nutritional status using the Fat Mass Index (FMI) in a Mexican pediatric population. A literature review using PubMed and Cochrane databases was made, searching for research articles on childhood obesity that compared BMI, FM percentage, and FMI, as well as those proposing diagnostic cutoff points. Mathematic formulas and linear regressions were then used to make a proposal on accurate cutoff points for this population. Our findings show that FM percentage is less precise than BMI and FMI in diagnosing obesity, and FMI seems to be a more complete tool for assessment as it differentiates fat and muscle mass of the total body weight. Both BMI and FMI should be considered when clinical evaluations regarding weight, with BMI complementing FMI by establishing fat-free mass. Our proposed cutoff points need to be validated in this population.

Smoothed Body Composition Percentiles Curves for Mexican Children Aged 6 to 12 Years.

Overweight children and childhood obesity are a public health problem in Mexico. Obesity is traditionally assessed using body mass index (BMI), but an excess of adiposity does not necessarily reflect a high BMI. Thus, body composition indexes are a better alternative. Our objective was to generate body composition percentile curves in children from Mexico City. A total of 2026 boys and 1488 girls aged 6 to 12 years old were studied in Mexico City. Body weight, height, and BMI calculation were measured. Total body fat percentage (TBFP) was derived from the skinfold thicknesses, and fat mass (FMI) and free fat mass indexes (FFMI) were calculated. Finally, age- and gender-specific smoothed percentile curves were generated with Cole's Lambda, Mu, and Sigma (LMS) method. In general, height, weight, waist circumference (WC), and TBFP were higher in boys, but FFM was higher in girls. TBFP appeared to increase significantly between ages 8 and 9 in boys (+2.9%) and between ages 10 and 11 in girls (+1.2%). In contrast, FFM% decreased noticeably between ages 8 and 9 until 12 years old in boys and girls. FMI values peaked in boys at age 12 (P97 = 14.1 kg/m²) and in girls at age 11 (P97 = 8.8 kg/m²). FFMI percentiles increase at a steady state reaching a peak at age 12 in boys and girls. Smoothed body composition percentiles showed a different pattern in boys and girls. The use of TBFP, FMI, and FFMI along with BMI provides valuable information in epidemiological, nutritional, and clinical research.

Comparación del HOMA IR con el modelo mínimo para medir sensibilidad a la insulina en el síndrome de ovarios poliquísticos / Comparison of HOMA-IR with minmod for measure insulin sensitivity in policystic ovary syndrome

Introducción. - El síndrome de ovarios poliquísticos (SOP) es la alteración más común en mujeres en edad reproductiva. Estas mujeres presentan resistencia a la insulina independientemente de la obesidad; y la resistencia a la insulina se reconoce como un factor de riesgo para desarrollar diabetes mellitus tipo 2, hipertensión arterial y enfermedad cardiovascular. Propósito. En este estudio evaluamos la correlación entre una sola medición en ayuno para sensibilidad a la insulina (Modelo homeostático) y el Modelo-mínimo en este síndrome. Métodos . Se estudiaron 33 pacientes con diagnóstico de SOP y edad promedio de 22.7 ñ 6.2 años e Indice de Masa Corporal (IMC) 29.1 ñ 5.4 a quienes se les efectuó la prueba de tolerancia iv a la glucosa (modelo-mínimo). Resultados. El 51.5 por ciento (17 pacientes) tuvo sensibilidad a la insulina menor de 1.5 x 10 -4 min. -1 µU -1 mL -1. El grupo con IMC > de 27 (20 mujeres obesas), presentó mayor resistencia a la insulina que aquellas con IMC = de 27 (p= 0.004). La correlación entre sensibilidad a la insulina (Si) del Modelo Mínimo y HOMA IR fue significativa con p = 0.0001 y R RANK = -0.76 para todo el grupo de estudio; R RANK = -0.77 para las pacientes con IMC = 27 (p=0.00006) y R RANK = -0.43 para aquellas con IMC = 27 (p = 0.13). Conclusión. El HOMA IR es una prueba útil para medir la sensibilidad a la insulina en el grupo de las mujeres obesas o con sobrepeso y SOP, pero no en las delgadas.