Diagnostics for Statistical Variable Selection Methods for Prediction of Peptic Ulcer Disease in Helicobacter pylori Infection

Association of Left Atrial Function Index with Atrial Fibrillation and Cardiovascular Disease: The Framingham Offspring Study

BACKGROUND

Left atrial (LA) size, a marker of atrial structural remodeling, is associated with increased risk for atrial fibrillation (AF) and cardiovascular disease (CVD). LA function may also relate to AF and CVD, irrespective of LA structure. We tested the hypothesis that LA function index (LAFI), an echocardiographic index of LA structure and function, may better characterize adverse LA remodeling and predict incident AF and CVD than existing measures.

METHODS AND RESULTS

In 1786 Framingham Offspring Study eighth examination participants (mean age, 66±9 years; 53% women), we related LA diameter and LAFI (derived from the LA emptying fraction, left ventricular outflow tract velocity time integral, and indexed maximal LA volume) to incidence of AF and CVD on follow-up. Over a median follow-up of 8.3 years (range, 7.5-9.1 years), 145 participants developed AF and 139 developed CVD. Mean LAFI was 34.5±12.7. In adjusted Cox regression models, lower LAFI was associated with higher risk of incident AF (hazard ratio=3.83, 95% confidence interval=2.23-6.59, lowest [Q1] compared with highest [Q4] LAFI quartile) and over 2-fold higher risk of incident CVD (hazard ratio=2.20, 95% confidence interval=1.32-3.68, Q1 versus Q4). Addition of LAFI, indexed maximum LA volume, or LA diameter to prediction models for AF or CVD did not significantly improve model discrimination for either outcome.

CONCLUSIONS

In our prospective investigation of a moderate-sized community-based sample, LAFI, a composite measure of LA size and function, was associated with incident AF and CVD. Addition of LAFI to the risk prediction models for AF or CVD, however, did not significantly improve their performance.

Supervised Machine-Learning Reveals That Old and Obese People Achieve Low Dapsone Concentrations

The human species is becoming increasingly obese. Dapsone, which is extensively used across the globe for dermatological disorders, arachnid bites, and for treatment of several bacterial, fungal, and parasitic diseases, could be affected by obesity. We performed a clinical experiment, using optimal design, in volunteers weighing 44-150 kg, to identify the effect of obesity on dapsone pharmacokinetic parameters based on maximum-likelihood solution via the expectation-maximization algorithm. Artificial intelligence-based multivariate adaptive regression splines were used for covariate selection, and identified weight and/or age as predictors of absorption, systemic clearance, and volume of distribution. These relationships occurred only between certain patient weight and age ranges, delimited by multiple hinges and regions of discontinuity, not identified by standard pharmacometric approaches. Older and obese people have lower drug concentrations after standard dosing, but with complex patterns. Given that efficacy is concentration-dependent, optimal dapsone doses need to be personalized for obese patients.

The Non-Linear Child: Ontogeny, Isoniazid Concentration, and NAT2 Genotype Modulate Enzyme Reaction Kinetics and Metabolism

N-acetyltransferase 2 (NAT2) catalyzes the acetylation of isoniazid to N-acetylisoniazid. NAT2 polymorphism explains 88% of isoniazid clearance variability in adults. We examined the effects of clinical and genetic factors on Michaelis-Menten reaction kinetic constants of maximum velocity (V_max) and affinity (K_m) in children 0–10 years old. We measured the rates of isoniazid elimination and N-acetylisoniazid production in the blood of 30 children. Since maturation effects could be non-linear, we utilized a pharmacometric approach and the artificial intelligence method, multivariate adaptive regression splines (MARS), to identify factors predicting NAT2 V_max and K_m by examining clinical, genetic, and laboratory factors in toto. Isoniazid concentration predicted both V_max and K_m and superseded the contribution of NAT2 genotype. Age non-linearly modified the NAT2 genotype contribution until maturation at ≥ 5.3 years. Thus, enzyme efficiency was constrained by substrate concentration, genes, and age. Since MARS output is in the form of basis functions and equations, it allows multiscale systems modeling from the level of cellular chemical reactions to whole body physiological parameters, by automatic selection of significant predictors by the algorithm.

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We identified the NAT2 K_m and V_max in children treated with isoniazid.

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Artificial intelligence (AI) algorithms were used to find predictors of K_m and V_max.

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Isoniazid concentration affected V_max and K_m, and superseded NAT2 genotype.

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Age non-linearly modified NAT2 genotype contribution until maturation at ≥ 5.3 years.

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AI output is in the form of equations that allow multiscale systems modeling.

The effects of maturation on drug metabolism have not been studied for the type phase II enzymes such as NAT2, which metabolizes the drug isoniazid. Genes have been found to control speed of isoniazid metabolism. Studies to characterize affinity and maximum velocity for isoniazid metabolism in people were last performed in two individuals' livers in the 1960s. We identified NAT2 affinity and maximum velocity in 30 tuberculosis children treated with isoniazid. Artificial intelligence methods found that metabolism was affected by the drug's concentration more than by genes, which were affected by age up to 5.3 years.