Martín Ríos

A statistical analysis of the seasonality in pulmonary tuberculosis.

The present study examines whether pulmonary tuberculosis (PTB) has an annual seasonal pattern. A mathematical model is also obtained to forecast the pattern of incidence. The data for the study are the cases of PTB reported throughout Spain, published in the Epidemiology Bulletin by the Carlos III Health Center of the Spanish Ministry of Health in a 26-year period, 1971–1996. The analytical results show that the low rates in tuberculosis notifications over the period 1971–1981 have changed, halting in 1982 and reversing with high incidence from 1983 onwards. An annual seasonal pattern was also shown with higher incidence during summer and autumn. With the mathematical model we predicted the disease behaviour in 1997 and the results were compared to the reported cases. In Spain, as in several industrialised countries, the reason for this recent increase in the number of reported cases is, mainly, the human immunodeficiency virus (HIV) infection. The seasonal trend, with higher incidence in winter, can be attributed to the increase in indoor activities, much more common than in a warm climate. The tubercle bacilli expelled from infected persons in a room with closed windows may remain infectious for a long time, increasing the risk of exposure of healthy persons to the bacilli. As the preclinical period, from exposure to clinical onset, may be of several weeks, the high incidence in spring would be explained. Moreover, in winter and spring the infections of viral aetiology, like flu, are more frequent and cause immunological deficiency which is another reason for the seasonal trend observed. An incidence greater than that foreseen by the mathematical model would express a failure in epidemiologic surveillance, and thus the results of this study may be used to assess a quality of the preventive measures.

High prevalence of abnormal glucose tolerance and metabolic disturbances in first degree relatives of NIDDM patients. A study in Catalonia, a mediterranean community

Our study aimed to analyse clinical and metabolic characteristics of first degree relatives of patients with non-insulin-dependent diabetes mellitus (NIDDM) in Catalonia. Two hundred and five subjects (39.8 +/- 14.2 year-old, 61% women) were included in the study. An oral glucose tolerance test (OGTT) was performed, obtaining basal plasma glucose and insulin, in order to calculate, %B (HOMA beta cell function) and %S (HOMA insulin sensitivity). A 30.7% of subjects showed an abnormal glucose tolerance, either as impaired glucose tolerance (IGT) (20.5%) or as NIDDM (10.2%). Glycaemia after the OGTT (120 min) was independently determined by fasting glycaemia and age (R2 = 0.50; P < 0.001). As expected, subjects with normal glucose tolerance (NGT) were significantly younger than IGT and NIDDM subjects. The relatives with IGT and NIDDM display more features of syndrome-X when compared to NGT. Likewise, NGT relatives were less insulin sensitive and their basal insulin levels were higher when compared with a control group of subjects without familial history of NIDDM (log %S, 3.6 +/- 0.4 vs. 3.9 +/- 0.4; P = 0.000; log-insulin 2.4 +/- 0.4 vs. 2.1 +/- 0.6 mU/l; P < 0.02). In comparison with the general population, of any age group, NIDDM and IGT were more common in those subjects with a family history of NIDDM. Interestingly, the rates, of abnormal glucose tolerance in the 55-64 and > 64 year groups in the general population were similar to those seen in relatives two decades younger. Our study not only confirms a high prevalence of impaired glucose tolerance (IGT and NIDDM) in subjects with a family history of NIDDM, but also that these abnormalities can be detected at a very early age. Globally, this piece of information corroborates that special attention and precocious detection programs should be addressed to relatives of NIDDM patients.

Effects of a short prednisone regime at clinical onset of type 1 diabetes

The effect of corticosteroids on beta cell function and humoral immune response in type 1 diabetes was tested in a 2-month trial conducted on 32 newly diagnosed patients (age 22.8 +/- 1.4 years, mean +/- S.E.M.). Prednisone was administered at immunosuppressive dosage (1 mg.kg-1.day-1) during the initial 10 days and at a maintenance dosage (0.3 mg.kg-1.day-1) for 50 days. Patients (n = 32) were enrolled within 6 weeks after diagnosis and matched in pairs for age, sex, presence of islet cell antibodies (ICA) and glucagon stimulated C-peptide levels. Insulin discontinuation was not contemplated. All the patients who received prednisone became ICA during treatment but in some (4 out of 10) this effect was only transient. Insulin antibodies (IA) were significantly lower in the prednisone group at second and third month (P < 0.05). No patient experienced complete remission but in 10 prednisone and 4 control patients the insulin requirements were below 0.3 IU/kg (P < 0.05). With similar glycemia the fasting C-peptide levels were higher in the treated patients. The profile of the insulin requirements during the follow-up was different in the two groups and at 9 months the prednisone group needed less insulin than the control (P < 0.05). Interestingly, within the prednisone-treated group and after 6 months, the levels of stimulated C-peptide improved significantly among the ICA+ patients while they were steady or declined in ICA- (P < 0.01). The analysis of variance covariance confirmed a positive interaction between ICA and the administration of prednisone on the outcome of beta cell function.(ABSTRACT TRUNCATED AT 250 WORDS)

A graphical study of tuberculosis incidence and trends in the WHO's European region (1980-2006).

A graphical output was obtained using classical principal component analysis techniques in order to analyse tuberculosis trends in Europe over a 27-year period (1980–2006). Taxonomic methods were used to better define the interrelationship between the data in the 52 countries studied. Data were provided by the World Health Organization. Differences in the overall incidence and trends were identified during the 1980–2006 period. The highest rates of incidence were reported in Kazakhstan, Bosnia and Herzegovina, Romania and Kyrgyzstan. High and moderately high rates were reported in the former Soviet Union, the former Yugoslavia, some countries from the former Eastern Bloc, Turkey and Portugal. The lowest rates were reported in the eastern Mediterranean, Scandinavia and Iceland. Risk of infection was determined by social conditions, intravenous drug use, HIV infection and immigration from countries where tuberculosis is endemic. As regards development of tuberculosis in Europe, 1992 represents the change in the decreasing trend in the incidence observed from 1980, when the incidence presented a minimum general trend and started to increase. The linear model calculated to project the rate of increase from 2006 to 2015, reveals the tuberculosis rates observed during the 1980s.

Cyclin-Dependent Kinase 4 Hyperactivity Promotes Autoreactivity in the Immune System but Protects Pancreatic β Cell Mass from Autoimmune Destruction in the Nonobese Diabetic Mouse Model

Cyclin-dependent kinase 4 (Cdk4) plays a central role in perinatal pancreatic β cell replication, thus becoming a potential target for therapeutics in autoimmune diabetes. Its hyperactive form, Cdk4R24C, causes β cell hyperplasia without promoting hypoglycemia in a nonautoimmune-prone mouse strain. In this study, we explore whether β cell hyperproliferation induced by the Cdk4R24C mutation balances the autoimmune attack against β cells inherent to the NOD genetic background. To this end, we backcrossed the Cdk4R24C knockin mice, which have the Cdk4 gene replaced by the Cdk4R24C mutated form, onto the NOD genetic background. In this study, we show that NOD/Cdk4R24C knockin mice exhibit exacerbated diabetes and insulitis, and that this exacerbated diabetic phenotype is solely due to the hyperactivity of the NOD/Cdk4R24C immune repertoire. Thus, NOD/Cdk4R24C splenocytes confer exacerbated diabetes when adoptively transferred into NOD/SCID recipients, compared with NOD/wild-type (WT) donor splenocytes. Accordingly, NOD/Cdk4R24C splenocytes show increased basal proliferation and higher activation markers expression compared with NOD/WT splenocytes. However, to eliminate the effect of the Cdk4R24C mutation specifically in the lymphocyte compartment, we introduced this mutation into NOD/SCID mice. NOD/SCID/Cdk4R24C knockin mice develop β cell hyperplasia spontaneously. Furthermore, NOD/SCID/Cdk4R24C knockin females that have been adoptively transferred with NOD/WT splenocytes are more resistant to autoimmunity than NOD/SCID WT female. Thus, the Cdk4R24C mutation opens two avenues in the NOD model: when expressed specifically in β cells, it provides a new potential strategy for β cell regeneration in autoimmune diabetes, but its expression in the immune repertoire exacerbates autoimmunity.

DISCRIMINANT ANALYSIS ALGORITHM BASED ON A DISTANCE FUNCTION AND ON A BAYESIAN DECISION

We propose a new algorithm for the allocation of an individual to one of several possible groups or populations. The algorithm enables us to define a finite partition over the sample space, based on distance function. This partition is used, jointly with the application of a standard Bayesian decision rule, to allocate individuals to the populations. The algorithm also provides a measure of the allocation confidence for each individual, in a similar manner to that of logistic regression. The error rates for classification are also computed using the leave-one-out method. Results are compared with those obtained with other discriminant analysis techniques previously reported: Fishers linear discriminant function, the quadratic discriminant function, logistic discrimination, and others.

Graphical study of reasons for engagement in physical activity in European Union

We collect data on 15 reasons why people in the 27 EU countries engage in physical activity, from the European Commission’s Special Eurobarometer. A graphical output was obtained using classical Principal Component Analysis techniques in order to analyse types of motivation in the EU. Cluster Analysis method were used to define the interrelationship between the data in the 27 countries. People in Sweden, Denmark and Finland were the most highly motivated. High rates were detected in Austria, Germany, Slovenia, Estonia, Luxembourg and Latvia while low rates were found in Bulgaria, Romania, Czech Republic, Greece, Spain, Hungary, Italy, Lithuania, Poland, Portugal and Slovakia. The lowest motivation rates were in the Netherlands. Regarding the reasons for engaging in exercise (a sport or physical activity), we observed two motivation types. The first group was related to health and physical appearance while the second was associated with social reasons: to be with friends, to better integrate into society, to meet people from other cultures. For citizens of Latvia, Bulgaria and Romania, health and physical appearance carried greater importance than the European average while for citizens of Germany, Finland and Sweden the second motivation type was higher than the European average.

Comparative efficiency research (COMER): meta-analysis of cost-effectiveness studies.

BackgroundThe aim of this study was to create a new meta-analysis method for cost-effectiveness studies using comparative efficiency research (COMER).MethodsWe built a new score named total incremental net benefit (TINB), with inverse variance weighting of incremental net benefits (INB). This permits determination of whether an alternative is cost-effective, given a specific threshold (TINB > 0 test). Before validation of the model, the structure of dependence between costs and quality-adjusted life years (QoL) was analysed using copula distributions. The goodness-of-fit of a Spanish prospective observational study (n = 498) was analysed using the Independent, Gaussian, T, Gumbel, Clayton, Frank and Placket copulas. Validation was carried out by simulating a copula distribution with log-normal distribution for costs and gamma distribution for disutilities. Hypothetical cohorts were created by varying the sample size (n: 15–500) and assuming three scenarios (1-cost-effective; 2-non-cost-effective; 3-dominant). The COMER result was compared to the theoretical result according to the incremental cost-effectiveness ratio (ICER) and the INB, assuming a margin of error of 2,000 and 500 monetary units, respectively.ResultsThe Frank copula with positive dependence (−0.4279) showed a goodness-of-fit sufficient to represent costs and QoL (p-values 0.524 and 0.808). The theoretical INB was within the 95% confidence interval of the TINB, based on 15 individuals with a probability > 80% for scenarios 1 and 2, and > 90% for scenario 3. The TINB > 0 test with 15 individuals showed p-values of 0.0105 (SD: 0.0411) for scenario 1, 0.613 (SD: 0.265) for scenario 2 and < 0.0001 for scenario 3.ConclusionsCOMER is a valid tool for combining cost-effectiveness studies and may be of use to health decision makers.

Application of a Markovian process to the calculation of mean time equilibrium in a genetic drift model

The most common phenomena in the evolution process are natural selection and genetic drift. In this article, we propose a probabilistic method to calculate the mean and variance time for random genetic drift equilibrium, measured as number of generations, based on Markov process and a complex probabilistic model. We studied the case of a constant, panmictic population of diploid organisms, which had a demonstrated lack of mutation, selection or migration for a determined autonomic locus, and two possible alleles, H and h. The calculations presented in this article were based on a Markov process. They explain how genetic and genotypic frequencies changed in different generations and how the heterozygote alleles became extinguished after many generations. This calculation could be used in more evolutionary applications. Finally, some simulations are presented to illustrate the theoretical calculations presented using different basal situations.

Rao distance between multivariate linear normal models and their application to the classification of response curves

Abstract In this paper we have defined and obtained algebraic expressions for a distance between multivariate linear normal models, with identical covariance matrix, through the Fisher information matrix. Explicit algebraic expressions have been obtained of the estimator of the distance which is used to design a test of hypothesis concerning the comparison of various multivariate linear normal models of equal covariance matrices, establishing their relation with the classic Multivariate Variance Analysis hypotheses test. This distance has also been used to obtain a classification by means of Discriminant Analysis. The advantages have also been emphasized of the use of distances in the carrying out of hypotheses testing as this enables us to make graphic representations of the results, either by representing the linear models compared on a graph, dendogram or additive tree, or in a Euclidean space of low dimension (usually a plane). A method of classifying response curves is proposed for a classification of children subjected to an oral glucose tolerance test, showing the practical use of the distance obtained. Such classification enables us to detect groups of individuals which, without having appreciable clinical differences, do present significantly different responses to oral glucose tolerance test.