Estimation of Glomerular Filtration Rate in Obese Patients: Utility of a New Equation.

There is no consensus on the best equation to estimate glomerular filtration rate (eGFR) in obese patients (OP). Objective: to evaluate the performance of the current equations and the new Argentinian Equation ("AE") to estimate GFR in OP. Two validation samples were used: internal (IVS, using 10-fold cross-validation) and temporary (TVS). OP whose GFR was measured (mGFR) with clearance of iothalamate between 2007/2017 (IVS, n = 189) and 2018/2019 (TVS, n = 26) were included. To evaluate the performance of the equations we used: bias (difference between eGFR and mGFR), P30 (percentage of estimates within ±30% of mGFR), Pearson's correlation (r) and percentage of correct classification (%CC) according to the stages of CKD. The median age was 50 years. Sixty percent had grade I obesity (G1-Ob), 25.1% G2-Ob and 14.9% G3-Ob, with a wide range in mGFR (5.6-173.1 mL/min/1.73 m2). In the IVS, AE obtained a higher P30 (85.2%), r (0.86) and %CC (74.4%), with lower bias (-0.4 mL/min/1.73 m2). In the TVS, AE obtained a higher P30 (88.5%), r (0.89) and %CC (84.6%). The performance of all equations was reduced in G3-Ob, but AE was the only one that obtained a P30 > 80% in all degrees. AE obtained better overall performance to estimate GFR in OP and could be useful in this population. Conclusions from this study may not be generalizable to all populations of obese patients since they were derived from a study in a single center with a very specific ethnic mixed population.

Determination of volatile organic compound patterns characteristic of five unifloral honey by solid-phase microextraction-gas chromatography-mass spectrometry coupled to chemometrics.

We report the evaluation of the floral origin of honey by analysis of its volatile organic compounds (VOCs) profile, joined with the use of combined pattern recognition techniques. Honey samples, from five floral origins, were analyzed by headspace solid-phase microextraction-gas chromatography-mass spectrometry, selecting 35 VOCs out of the entire profiles, which were analyzed by hierarchical cluster analysis (HCA), stepwise discriminant analysis (SDA), and K-nearest-neighbor (KNN). Both HCA and SDA were used as exploratory tools to select a group of VOCs representing similitude and differences among studied origins. Thus, six out of 35 VOCs were selected, verifying their discriminating power by KNN, which afforded 93% correct classification. Therefore, we drastically reduced the amount of compounds under consideration but kept a good differentiation between floral origins. Selected compounds were identified as octanal, benzeneacetaldehyde, 1-octanol, 2-methoxyphenol, nonanal, and 2-H-1-benzopyran-2-one. The analysis of VOC profiles, coupled to HCA, SDA, and KNN, provides a feasible alternative to evaluate the botanical source of honey.