Biomedical subjects

L D Epstein

Publications and source records attributed to L D Epstein.

8 recordsLinked to original sources

PubMed2000

Effect of El Niño and ambient temperature on hospital admissions for diarrhoeal diseases in Peruvian children.

INTRODUCTION: To investigate whether the El Niño phenomenon and ambient temperature had an effect on the epidemiology of childhood diarrhoea, we analysed data on daily number of admissions of children with diarrhoea to the Oral Rehydration Unit of the Instituto de Salud del Niño in Lima, Peru, between January, 1993, and November, 1998. METHODS: We obtained daily data on hospital admissions from the Oral Rehydration Unit, and meteorological data from the Peruvian Weather Service, and used time-series linear regression models to assess the effects of the 1997-98 El Niño event on admissions for diarrhoea. FINDINGS: 57,331 children under 10 years old were admitted to the unit during the study. During the 1997-98 El Niño episode, mean ambient temperature in Lima increased up to 5 degrees C above normal, and the number of daily admissions for diarrhoea increased to 200% of the previous rate. 6225 excess admissions were attributable to El Niño, and these cost US$277,000. During the period before the El Niño episode, admissions for diarrhoea increased by 8% per 1 degree C increase in mean ambient temperature. The effects of El Niño and ambient temperature on the number of admissions for diarrhoea were greatest during the winter months. INTERPRETATION: El Niño had an effect on hospital admissions greater than that explained by the regular seasonal variability in ambient temperature. The excess increase in ambient temperature was the main environmental variable affecting admissions. If our findings are reproducible in other regions, diarrhoeal diseases may increase by millions of cases worldwide with each degree of increase in ambient temperature above normal.

Child↗

PubMed1998

Effects of Cryptosporidium parvum infection in Peruvian children: growth faltering and subsequent catch-up growth.

The authors conducted a 2-year (1989-1991) community-based longitudinal study in a shantytown in Lima, Peru, to examine the effect of Cryptosporidium parvum infection on child growth during the year following the onset of infection. A cohort of children, aged 0-3 months at recruitment, was followed monthly for anthropometrics, weekly for stool samples, and daily for diarrheal status. Data from 185 children in the cohort permitted a comparison of growth in C. parvum-infected and noninfected children. The analyses fitted smooth, flexible curves with a linear random-effects model to estimate growth differences between C. parvum-infected and noninfected children. Children infected with C. parvum experienced growth faltering, both in weight and in height, for several months after the onset of infection, followed by a period of catch-up growth. Younger children took longer to catch up in weight than did older children. Catch-up growth, however, did not occur in children infected between ages 0 and 5 months. These children did not catch up in height, and one year after infection they exhibited an average deficit of 0.95 cm (95% confidence interval (CI) 0.38-1.53) relative to noninfected children of similar age. Stunted children who became infected also did not catch up in either weight or height, and one year after infection they exhibited a height deficit of 1.05 cm (95% CI 0.46-1.66) relative to noninfected, stunted children of similar age. These results indicate that Cryptosporidium parvum has a lasting adverse effect on linear (height) growth, especially when acquired during infancy and when children are stunted before they become infected.

Animals↗

PubMed1997

Asymptomatic and symptomatic cryptosporidiosis: their acute effect on weight gain in Peruvian children.

This study investigated whether a child's first infection with Cryptosporidium parvum had an acute effect on weight gain. Specifically, the authors compared monthly rates of weight gain between C. parvum-infected and noninfected children. Over a 2-year period (1989-1991), a cohort of Peruvian children aged 0-3 months at recruitment were followed twice weekly for assessment of daily diarrheal status, weekly for C. parvum stool examinations, and monthly for anthropometric measurements. Data on 207 children permitted the authors to examine the effect of C. parvum infection on weight gain. During the 2-year study period, 45% (94/207) of the children became infected with C. parvum for the first time. Weight gain intervals in 57 of the 94 infected children met criteria for analysis. Of these, 63 percent (36/57) were asymptomatic (i.e., had no diarrhea). On average, children with symptomatic cryptosporidiosis gained (i.e., grew) 342 g less (95% confidence interval 167-517) during the first month of infection than did children without diarrhea who were not yet infected. The effect of asymptomatic cryptosporidiosis was less severe: On average, children with asymptomatic infection gained 162 g less (95% confidence interval 27-297) during the first month of infection than did children without diarrhea who were not yet infected. Symptomatic cryptosporidiosis retarded weight gain more than did asymptomatic cryptosporidiosis, but the latter was twice as common. Since asymptomatic cryptosporidiosis is more prevalent, it may have more of an overall adverse effect on child growth in the community than symptomatic cryptosporidiosis.

Acute Disease↗

PubMed1997

Use of generalized regression tree models to characterize vegetation favoring Anopheles albimanus breeding.

We propose the use of generalized tree models (GTMs) to analyze data from entomological field studies. Generalized tree models can be used to characterize environments with different mosquito breeding capacity. A GTM simultaneously analyzes a set of predictor variables (e.g., vegetation coverage) in relation to a response variable (e.g., counts of Anopheles albimanus larvae), and how it varies with respect to a set of criterion variables (e.g., presence of predators). The algorithm produces a treelike graphical display with its root at the top and 2 branches stemming down from each node. At each node, conditions on the value of predictors partition the observations into subgroups (environments) in which the relation between response and criterion variables is most homogeneous.

Animals↗

PubMed1996

A bivariate parametric model for survival and intermediate event times.

In diseases such as acquired immune deficiency syndrome (AIDS), there is great interest in describing the frequency of secondary diagnoses that occur during the course of the disease and their effect on survival. Casting this situation in a more general framework, one distinguishes a terminal event (TE) and an intermediate event (IE) that may or may not occur. In epidemiologic applications the TE is usually death. Earlier studies of IE and TE times have used the latter to censor the IE time for individuals who do not present it. For such cases, we argue that more appropriately the TE removes the individual from the risk set for the IE. With this view, one distinguishes observations of four types, each with a different formula for its likelihood contribution. We propose an approach that uses separate parametric models for the marginal distribution of the survival time D and for the conditional distribution of the time R to the IE given D = d and R < or = D. A central quantity is the probability of presenting the IE given the occurrence of the TE at time d. This function of d can reveal important connections between the two events. We suggest a model derived from Weibull distributions where the parameters control the shape of this function. One can obtain inferences about other probabilities of interest such as the proportion of individuals who present the IE, P(R < or = D), the marginal distribution of R among the IE cases, P(R > r [symbol: see text] R < or = D) and the residual survival after the IE occurs, P(D - R > v [symbol: see text] R < or = D, R = r). We apply the model to the analysis of time to secondary Kaposi's sarcoma (KS) diagnosis and time to death in a large cohort study of homosexual men infected with the human immunodeficiency virus type 1 (HIV) and who had an initial non-KS AIDS diagnosis.

Acquired Immunodeficiency Syndrome↗

PubMed1996

Bayesian imputation of predictive values when covariate information is available and gold standard diagnosis is unavailable.

We suggest a conceptually simple Bayesian approach to inferences about the conditional probability of a specimen being infection-free given the outcome of a diagnostic test and covariate information. The approach assumes that the infection state of a specimen is not observable but uses the outcomes of a second test in conjunction with those of the first, that is, dual testing data. Dual testing procedures are often employed in clinical laboratories to assure that samples are not contaminated or to increase the likelihood of correct diagnoses. Using the CD4 count and a proxy for risk behavior as covariates, we apply the method to obtain inferences about the conditional probability of an individual being HIV-1 infection-free given the individual's covariates and a negative outcome with the standard enzyme-linked immunoad-sorbent assay/Western blotting test for HIV-1 detection. Inferences combine data from two studies where specimens were tested with the standard and with the more sensitive polymerase chain reaction test.

Algorithms↗

PubMed1994

The IgG2a antibody response to thyroglobulin is linked to the Igh locus in mouse.

The IgG-subclass usage by several strains of mice in the response to immunization with mouse thyroglobulin (mTg) was examined in the experimental autoimmune thyroiditis model. While the subclass usage by most mouse strains was similar, the Ighb allotype-bearing mice consistently produced lower IgG2a levels to mTg. Using CBA-Ighb congenic and recombinant inbred strains of mice, the lower level of IgG2a in the Ighb mouse was mapped to the Igh locus. The regulation of IgG2a appeared to be cis controlled, as the CBA x C57BL/6F1 mouse also produced reduced IgG2a of the Ighb (B6) allotype but not of the Ighj (CBA) allotype.

Animals↗

PubMedDate not supplied

A new model for category-scaling data with an application to the development of health-status measures.

Category rating is used to assess patient, family-member, provider, and societal preferences for health outcomes. Often, it is of interest to compare ratings obtained from different groups. Standard methods for making comparisons, such as regressions, correlations, and multiple t-tests, do not account for the dependency among ratings. The authors propose a new model for category ratings that does consider their relative dependency. This model provides a profile of ratings for a single group and facilitates comparisons across groups. It was applied to category ratings for four levels of Bending and Lifting function as defined by the recently developed Functional Capacity Index (FCI). Differences in ratings were observed across groups with different personal experiences of functional limitations and across groups with different degrees of clinical knowledge. These differences were not observed when standard methods were used. Thus, ignoring the relative nature of category ratings can lead to different conclusions about group preferences for health outcomes. When the ratings are being used to scale a health-status measure, this discrepancy has implications for the application of the measure in resource allocation.

Activities of Daily Living↗