Biomedical subjects

C Montomoli

Publications and source records attributed to C Montomoli.

8 recordsLinked to original sources

PubMed1996

Estimating reliability of evoked potential measures from residual scores: an example using tibial SSEPs.

A normative study of tibial SSEPs was performed in 74 healthy subjects, and the effects of the variables sex, age and height on SSEP parameters were assessed. In a subgroup of 20 subjects a test-retest study was also performed, which allowed us to estimate the reliability of the different parameters by means of the intraclass correlation coefficient. We demonstrated that the intraclass correlation coefficient may be biased by predictable effects of subject-related variables (such as age, height and sex), if it is computed from raw original values. This bias can be eliminated by estimating reliability indices on residual scores calculated as the differences between observed values and those predicted by subject's age, height and sex.

Adolescent↗

PubMed1995

[Bayesian analysis of ecological studies].

Studying the space-time variation of risk for a given disease may give etiological clues and suggestions for planning further studies to investigate the underlying causes. When the observed events are rare, approaches based on maximum likelihood may lead to unstable and largely uninformative estimates of risk and of its time trend due to Poisson sampling variation. In this paper we propose a general Bayesian model for analyzing the variation of risk in space and time. We applied the Bayesian model to the analysis of the geographical variation of breast cancer mortality, to an ecological study on the correlation between lung cancer mortality and degree of urbanization and industrialization and to the analysis of the space-time variation of cumulative prevalence of Insulin Dependent Diabetes Mellitus (IDDM) as observed in military examinations between 1954 and 1989.

Bayes Theorem↗

PubMed1994

Coffee induced thermogenesis and skin temperature.

The purpose of this study was to investigate the relationship between the changes in mean skin temperature and the energy expenditure induced by drinking coffee containing 4 mg of caffeine/kg body weight. Twelve healthy, weight-stable subjects were studied (five males, seven females; mean age +/- s.d., 25.3 +/- 3.3 years; BMI 22.5 +/- 3.1). Energy expenditure (EE) was measured by open-circuit indirect calorimetry, and skin temperature was determined with thermometric probes applied to the four body regions indicated by Ramanathan (chest, arm, thigh, calf). The calorimetric and thermometric measurements were carried out for 120 min with the participants lying down quietly. A significant correlation was found between the total thermogenic responses (net responses) and the temperature changes between 90 and 120 min from the coffee intake. Multiple regression analysis using mean EE after coffee intake as the dependent variable, and mean skin temperature and body weight as the independent variables yields the following equation: EE (kcal/min/m2) = -1.44 + 0.052 (mean skin temperature) + 0.004 (body weight). (r = 0.71 and P = 0.01) Our results indicate that small interindividual differences in mean skin temperature could explain energy expenditure differences in subjects with the same body weight, body composition and physical activity. This, in turn, could help explain variations in proneness to obesity.

Adult↗

PubMed1993

Childhood leukemia in south-west Sardinia (Italy).

AIM AND BACKGROUND: Public concern on an increased incidence of childhood leukemia in SW Sardinia prompted the authors to an epidemiological investigation. METHODS: Incident childhood neoplasms observed in the Cagliari province (Sardinia--Italy) in 1974-1989 were registered. Expected cases of the most frequent childhood cancers were calculated for each town, based on the sex-and age-specific incidence rates in the province. RESULTS: An excess risk of childhood acute lymphoblastic leukemia (ALL) was observed in Carbonia, a town located in the SW part of the province. The risk was highest in 1983-85, when 7 cases occurred versus 0.8 expected (RR = 8.7; 95% C.I. = 4.6, 16.3). No spatial clustering of ALL cases was observed within the town. CONCLUSIONS: A significantly higher than expected incidence of childhood ALL was observed in the town of Carbonia in 1983-85. In alternative to chance, possible exposure to environmental pollutants from a near industrial settlement is discussed as the cause of the observed excess, but it is far to be proven. Other hypotheses, including a viral infection in a population with increased susceptibility, as suggested for new urban settlements, cannot be discarded.

Adolescent↗

PubMed1993

Spatial correlation in ecological analysis.

This paper presents a statistical approach, originally developed for mapping disease risk, to ecological regression analysis in the presence of spatial autocorrelated extra-Poisson variation. An insight into the effect of allowing for spatial autocorrelation on the relationship between disease rates and explanatory variables is given. Examples based on cancer frequency in Scotland and Sardinia are used to illustrate the interpretation of regression coefficient and further methodological issues.

Analysis of Variance↗

PubMed1992

Empirical Bayes versus fully Bayesian analysis of geographical variation in disease risk.

This paper reviews methods for mapping geographical variation in disease incidence and mortality. Recent results in Bayesian hierarchical modelling of relative risk are discussed. Two approaches to relative risk estimation, along with the related computational procedures, are described and compared. The first is an empirical Bayes approach that uses a technique of penalized log-likelihood maximization; the second approach is fully Bayesian, and uses an innovative stochastic simulation technique called the Gibbs sampler. We chose to map geographical variation in breast cancer and Hodgkin's disease mortality as observed in all the health care districts of Sardinia, to illustrate relevant problems, methods and techniques.

Bayes Theorem↗

PubMedDate not supplied

Bayesian estimates of disease maps: how important are priors?

In the fully Bayesian (FB) approach to disease mapping the choice of the hyperprior distribution of the dispersion parameter is a key issue. In this context we investigated the sensitivity of the rate ratio estimates to the choice of the hyperprior via a simulation study. We also compared the performance of the FB approach to mapping disease risk to the conventional approach of mapping maximum likelihood (ML) estimates and p-values. The study was modelled on the incidence data of insulin dependent diabetes mellitus (IDDM) as observed in the communes of Sardinia.

Bayes Theorem↗

PubMedDate not supplied

Bayesian analysis of space-time variation in disease risk.

The analysis of variation of risk for a given disease in space and time is a key issue in descriptive epidemiology. When the data are scarce, maximum likelihood estimates of the area-specific risk and of its linear time-trend can be seriously affected by random variation. In this paper, we propose a Bayesian model in which both area-specific intercept and trend are modelled as random effects and correlation between them is allowed for. This model is an extension of that originally proposed for disease mapping. It is illustrated by the analysis of the cumulative prevalence of insulin dependent diabetes mellitus as observed at the military examination of 18-year-old conscripts born in Sardinia during the period 1936-1971. Data concerning the genetic differentiation of the Sardinian population are used to interpret the results.

Adolescent↗