A Bayesian model for estimating the malaria transition probabilities considering individuals lost to follow-up

It is known that patients may cease participating in a longitudinal study and become lost to follow-up. The objective of this article is to present a Bayesian model to estimate the malaria transition probabilities considering individuals lost to follow-up. We consider a homogeneous population, and it is assumed that the considered period of time is small enough to avoid two or more transitions from one state of health to another. The proposed model is based on a Gibbs sampling algorithm that uses information of lost to follow-up at the end of the longitudinal study. To simulate the unknown number of individuals with positive and negative states of malaria at the end of the study and lost to follow-up, two latent variables were introduced in the model. We used a real data set and a simulated data to illustrate the application of the methodology. The proposed model showed a good fit to these data sets, and the algorithm did not show problems of convergence or lack of identifiability. We conclude that the proposed model is a good alternative to estimate probabilities of transitions from one state of health to the other in studies with low adherence to follow-up.

Saliva flow rate, buffer capacity, and pH of autistic individuals

The objective of the study was to evaluate saliva flow rate, buffer capacity, pH levels, and dental caries experience (DCE) in autistic individuals, comparing the results with a control group (CG). The study was performed on 25 noninstitutionalized autistic boys, divided in two groups. G1 composed of ten children, ages 3-8. G2 composed of 15 adolescents ages 9-13. The CG was composed of 25 healthy boys, randomly selected and also divided in two groups: CG3 composed of 14 children ages 4-8, and CG4 composed of 11 adolescents ages 9-14. Whole saliva was collected under slight suction, and pH and buffer capacity were determined using a digital pHmeter. Buffer capacity was measured by titration using 0.01 N HCl, and the flow rate expressed in ml/min, and the DCE was expressed by decayed, missing, and filled teeth (permanent dentition [DMFT] and primary dentition [dmft]). Data were plotted and submitted to nonparametric (Kruskal-Wallis) and parametric (Student`s t test) statistical tests with a significance level less than 0.05. When comparing G1 and CG3, groups did not differ in flow rate, pH levels, buffer capacity, or DMFT. Groups G2 and CG4 differ significantly in pH (p = 0.007) and pHi = 7.0 (p = 0.001), with lower scores for G2. In autistic individuals aged 3-8 and 9-13, medicated or not, there was no significant statistical difference in flow rate, pH, and buffer capacity. The comparison of DCE among autistic children and CG children with deciduous (dmft) and mixed/permanent decayed, missing, and filled teeth (DMFT) did not show statistical difference (p = 0.743). Data suggest that autistic individuals have neither a higher flow rate nor a better buffer capacity. Similar DCE was observed in both groups studied.

Does the neuromotor abnormality type affect the salivary parameters in individuals with cerebral palsy?

Background: Previous studies reported alterations in salivary flow rate and biochemical parameters of saliva in cerebral palsy (CP) individuals; however, none of these considered the type of neuromotor abnormality among CP individuals, thus it remains unclear whether the different anatomical and extended regions of the brain lesions responsible for the neurological damage in CP might include disruption of the regulatory mechanism of saliva secretion as part of the encephalopathy. The aim of this study was to evaluate salivary flow rate, pH and buffer capacity in saliva of individuals with CP, aged 3-16 years, with spastic neuromotor abnormality type and clinical patterns of involvement. Methods: Sixty-seven individuals with CP spasticity movement disorder, were divided in two groups according to age (3-8- and 9-16-years-old) and compared with 35 sibling volunteers with no neurological damage, divided in two groups according to age (3-8- and 9-16-years-old). Whole saliva was collected under slight suction and pH and buffer capacity were determined using a digital pHmeter. Buffer capacity was measured by titration using 0.01N HCL, and flow rate was calculated in ml/min. Results: In both age groups studied, whole saliva flow rate, pH and buffer capacity were significantly lower in the spastic CP group (P < 0.05). The clinical patterns of involvement did not influence the studied parameters. Conclusion: These findings show that individuals with spastic cerebral palsy present lower salivary flow rate, pH and buffer capacity that can increase the risk of oral disease in this population.