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Pediatric deaths reported after vaccination: the utility of information obtained from parents.

BACKGROUND: The federally administered Vaccine Adverse Event Reporting System (VAERS) is a passive reporting system that receives domestic and foreign reports of adverse events that occur following immunization. This investigation explored whether routinely interviewing parents for follow-up of VAERS pediatric deaths would provide additional information important to vaccine safety. METHODS: The study was designed to follow up 100 consecutive pediatric deaths reported to VAERS by interviewing a parent and a healthcare provider (HCP) for each case. Several strategies contributed to successful follow-up. A standardized questionnaire was utilized to interview HCPs and parents. Overall and specific group frequencies (HCPs and parents) were calculated for each variable. McNemar's statistical tests of exact inference were calculated to assess whether there were statistically significant differences between HCP and parent knowledge by case for various variables. RESULTS: The median age of the cases was 4 months. Approximately half of the deaths were attributed to sudden infant death syndrome. In many instances, the information was equivalent in quality. For certain variables, such as knowledge of the child's position when found in distress, more parents than HCPs indicated that they knew the answer. CONCLUSIONS: Conducting parental and HCP follow-up for pediatric deaths reported to VAERS was resource intensive. In some instances, parents were more likely than HCPs to provide information regarding some important variables about the nature of the death. None of the additional information obtained from parents, however, provided a signal or confirmation of a causal link between the vaccine and death.

Adverse Drug Reaction Reporting Systems↗

Chloroplast phylogeny indicates that bryophytes are monophyletic.

Opinions on the basal relationship of land plants vary considerably and no phylogenetic tree with significant statistical support has been obtained. Here, we report phylogenetic analyses using 51 genes from the entire chloroplast genome sequences of 20 representative green plant species. The analyses, using translated amino acid sequences, indicated that extant bryophytes (mosses, liverworts, and hornworts) form a monophyletic group with high statistical confidence and that extant bryophytes are likely sisters to extant vascular plants, although the support for monophyletic vascular plants was not strong. Analyses at the nucleotide level could not resolve the basal relationship with statistical confidence. Bryophyte monophyly inferred using amino acid sequences has a good statistical foundation and is not rejected statistically by other data sets. We propose bryophyte monophyly as the currently best hypothesis.

Bryophyta↗

[L-arginine and immunity. Study of pediatric subjects].

BACKGROUND: Nitric oxide (NO) play a pivotal role in many biological processes, as in the vessel tone control, the atherogenesis, the platelets aggregation and the immune system modulation. The physiologic precursor of NO is the L-arginine. Evidence exists that the L-arginine administration can stimulate immune system in children with recurrent infections. This clinical trial was designed to evaluate the effects of oral administration of L-arginine on the number of infective events and on the lymphocytes subsets in children suffering from airways recurrent infections. METHODS: Forty outpatients, 21 male and 19 female, aging from 2 to 13 yrs. Two balanced groups, treated for 60 days with L-arginine or a placebo. Evaluation criteria: number of septic episodes; number of circulating white blood cells, % of the lymphocytes; lymphocytes subsets. STATISTICAL ANALYSIS: Descriptive analysis; inference tests: chi 2; "t" test; variance analysis. Statistical significance: p = 0.05. RESULTS: Fifteen patients treated with L-arginine and five treated with placebo (p < 0.01) were free from infections. The percentage of CD3 and CD4 subsets significantly (p < 0.05) increased in the L-arginine group than in the placebo group, while the CD8 subset significantly decreased. The CD4/CD8 ratio raised from 1.05 +/- 0.29 to 1.51 +/- 0.46 (p < 0.01) in the L-arginine group, from 1.12 +/- 0.16 to 1.27 +/- 0.24 in the placebo group. There were no side effects in both groups. CONCLUSIONS: L-arginine seems able to increase the immune system defences and to protect against the airway infections.

Adolescent↗

Truth and consequences of ordinal differences in statistical distributions: toward a theory of hierarchical inference.

A theory is presented that establishes a dominance hierarchy of potential distinctions (order relations) between two distributions. It is proposed that it is worthwhile for researchers to ascertain the strongest possible distinction, because all weaker distinctions are logically implied. Implications of the theory for hypothesis testing, theory construction, and scales of measurement are considered. Open problems for future research are outlined.

Humans↗

Liver transplantation is associated with increased met-enkephalin levels in the pig.

BACKGROUND: It has been reported that less postoperative morphine is required following liver transplantation than is required following open cholecystectomy. This may be attributable to endogenous factors rather than to altered morphine pharmacokinetics. We measured the plasma concentrations of two endogenous neuropeptides associated with pain modulation, substance P (SP) and met-enkephalin (ME), in pigs undergoing liver transplantation and in control pigs undergoing laparotomy. METHODS: With the approval of the institutional Animal Care Committee, pigs were anesthetized with ketamine (30 mg/ kg,i.m.), atropine (0.05 mg/kg, i.m.) and acetylpromazine (0.1 mg/kg, i.m.). Anesthesia was maintained with isoflurane in oxygen. Pigs in the transplantation group (n = 10) underwent liver transplantation and control pigs (n = 10) underwent laparotomy. Blood samples for SP and ME measurement were collected pre-incision (Pre-In), pre-emergence (Pre-Em) from anesthesia, 6-12 hours, 18 hours, and 24 hours after surgery. SP and ME levels were determined by radioimmunoassay. Results are expressed as mean +/- SEM (in pg/ml of plasma for both peptides) and were compared by the non-parametric Mann-Whitney U test. Statistical significance was inferred if P < 0.05. RESULTS: Plasma ME levels were significantly increased in the transplanted pigs at Pre-Em, 6-12 hours and 18 hours after surgery. No statistically significant difference was observed for plasma SP level between the control and transplant pigs. CONCLUSIONS: Liver transplantation in the pig model is associated with increased concentrations of endogenous ME (but not SP) in plasma for at least 18 hours after surgery as compared to animals undergoing laparotomy.

Animals↗

Statistical distributions of optimal global alignment scores of random protein sequences.

BACKGROUND: The inference of homology from statistically significant sequence similarity is a central issue in sequence alignments. So far the statistical distribution function underlying the optimal global alignments has not been completely determined. RESULTS: In this study, random and real but unrelated sequences prepared in six different ways were selected as reference datasets to obtain their respective statistical distributions of global alignment scores. All alignments were carried out with the Needleman-Wunsch algorithm and optimal scores were fitted to the Gumbel, normal and gamma distributions respectively. The three-parameter gamma distribution performs the best as the theoretical distribution function of global alignment scores, as it agrees perfectly well with the distribution of alignment scores. The normal distribution also agrees well with the score distribution frequencies when the shape parameter of the gamma distribution is sufficiently large, for this is the scenario when the normal distribution can be viewed as an approximation of the gamma distribution. CONCLUSION: We have shown that the optimal global alignment scores of random protein sequences fit the three-parameter gamma distribution function. This would be useful for the inference of homology between sequences whose relationship is unknown, through the evaluation of gamma distribution significance between sequences.

Algorithms↗

Statistical tools for the analysis of nutrition effects on the survival of cohorts.

We discuss various methods which can be employed for the comparative analysis of samples of response curves. In the application discussed here, these curves are hazard functions, each generated by the survival data obtained for a cohort of experimental subjects which are fed a specific diet. It is demonstrated how comparisons of the effects of different diets on survival can be carried out by employing statistical techniques for inference on samples of curves. The methods are illustrated with data on the survival of large cohorts of male and female Mediterranean fruit flies under full diet and under protein deprivation. These statistical methods allow one to investigate differences between the samples of hazard functions generated by the four groups defined by combinations of sex and diet.

Analysis of Variance↗

Multiple testing to establish superiority/equivalence of a new treatment compared with k standard treatments for unbalanced designs.

In clinical studies, multiple superiority/equivalence testing procedures can be applied to classify a new treatment as superior, equivalent (same therapeutic effect), or inferior to each set of standard treatments. Previous stepwise approaches (Dunnett and Tamhane, 1997, Statistics in Medicine16, 2489-2506; Kwong, 2001, Journal of Statistical Planning and Inference 97, 359-366) are only appropriate for balanced designs. Unfortunately, the construction of similar tests for unbalanced designs is far more complex, with two major difficulties: (i) the ordering of test statistics for superiority may not be the same as the ordering of test statistics for equivalence; and (ii) the correlation structure of the test statistics is not equi-correlated but product-correlated. In this article, we seek to develop a two-stage testing procedure for unbalanced designs, which are very popular in clinical experiments. This procedure is a combination of step-up and single-step testing procedures, while the familywise error rate is proved to be controlled at a designated level. Furthermore, a simulation study is conducted to compare the average powers of the proposed procedure to those of the single-step procedure. In addition, a clinical example is provided to illustrate the application of the new procedure.

Analgesics↗

An innovative application of Bayesian disease mapping methods to patient safety research: a Canadian adverse medical event study.

Recently developed disease mapping and ecological regression methods have become important techniques in studies of disease epidemiology and in health services research. This increase in importance is partially a result of the development of Bayesian statistical methodologies that make it possible to study associations between health problems and risk factors at an aggregate (i.e. areal) level while taking into account such matters as unmeasured confounding and spatial relationships. In this paper we present a demonstration of the joint use of empirical Bayes (EB) and full Bayesian inferential techniques in a small area study of adverse medical events (also known as 'iatrogenic injury') in British Columbia, Canada. In particular, we illustrate a unified Bayesian hierarchical spatial modelling framework that enables simultaneous examinations of potential associations between adverse medical event occurrence and regional characteristics, age effects, residual variation and spatial autocorrelation. We propose an analytic strategy for complementary use of EB and FB inferential techniques for risk assessment and model selection, presenting an EB-FB combined approach that draws on the strengths of each method while minimizing inherent weaknesses. The work was motivated by the need to explore relatively efficient ways to analyse regional variations of health services outcomes and resource utilization when a considerable amount of statistical modelling and inference are required.

Adolescent↗

Bayesian inference for categorical traits with an application to variance component estimation.

We implemented statistical models of Bayesian inference that included direct and maternal genetic effects for genetic parameter estimation of categorical traits by Gibbs sampling. The estimation errors and variances of estimates of animal versus sire and maternal grandsire models, of linear versus threshold models, of single-trait versus multiple-trait models, and of treating herd-year-season as fixed versus random effects in the model were compared. The results indicated that linear models yielded biased estimates of genetic parameters for categorical traits. The animal model was improper for analysis of categorical traits using a threshold model and the Gibbs sampler. Moreover, linear versus threshold models and animal versus sire-maternal grandsire models resulted in larger Monte Carlo errors and increased auto-correlations among posterior samples. Treating herd-year-seasons as random effects in the threshold models decreased the Monte Carlo error, auto-correlations, and the variances of estimates. Efficiency of the single-trait threshold sire model, as measured by the variance of the estimates, was lower than for a multiple-trait model that included a correlated continuous trait, but both estimates were unbiased. Therefore, the threshold single-trait sire and maternal grandsire model is a feasible alternative to the multiple-trait model for analysis of variance components of categorical traits affected by direct and maternal genetic factors.

Animals↗

Inferring ideal amino acid interaction forms from statistical protein contact potentials.

We have analyzed 29 different published matrices of protein pairwise contact potentials (CPs) between amino acids derived from different sets of proteins, either crystallographic structures taken from the Protein Data Bank (PDB) or computer-generated decoys. Each of the CPs is similar to 1 of the 2 matrices derived in the work of Miyazawa and Jernigan (Proteins 1999;34:49-68). The CP matrices of the first class can be approximated with a correlation of order 0.9 by the formula e(ij) = h(i) + h(j), 1 <or= i, j <or= 20, where the residue-type dependent factor h is highly correlated with the frequency of occurrence of a given amino acid type inside proteins. Electrostatic interactions for the potentials of this class are almost negligible. In the potentials belonging to this class, the major contribution to the potentials is the one-body transfer energy of the amino acid from water to the protein environment. Potentials belonging to the second class can be approximated with a correlation of 0.9 by the formula e(ij) = c(0) - h(i)h(j) + q(i)q(j), where c(0) is a constant, h is highly correlated with the Kyte-Doolittle hydrophobicity scale, and a new, less dominant, residue-type dependent factor q is correlated ( approximately 0.9) with amino acid isoelectric points pI. Including electrostatic interactions significantly improves the approximation for this class of potentials. While, the high correlation between potentials of the first class and the hydrophobic transfer energies is well known, the fact that this approximation can work well also for the second class of potentials is a new finding. We interpret potentials of this class as representing energies of contact of amino acid pairs within an average protein environment.

Amino Acids↗

Variety and volatility in financial markets

We study the price dynamics of stocks traded in a financial market by considering the statistical properties of both a single time series and an ensemble of stocks traded simultaneously. We use the n stocks traded on the New York Stock Exchange to form a statistical ensemble of daily stock returns. For each trading day of our database, we study the ensemble return distribution. We find that a typical ensemble return distribution exists in most of the trading days with the exception of crash and rally days and of the days following these extreme events. We analyze each ensemble return distribution by extracting its first two central moments. We observe that these moments fluctuate in time and are stochastic processes, themselves. We characterize the statistical properties of ensemble return distribution central moments by investigating their probability density functions and temporal correlation properties. In general, time-averaged and portfolio-averaged price returns have different statistical properties. We infer from these differences information about the relative strength of correlation between stocks and between different trading days. Last, we compare our empirical results with those predicted by the single-index model and we conclude that this simple model cannot explain the statistical properties of the second moment of the ensemble return distribution.

Journal Article↗

Modeling the effects of genetic factors on late-onset diseases in cohort studies.

Many late-onset diseases are caused by what appears to be a combination of a genetic predisposition to disease and environmental factors. The use of existing cohort studies provides an opportunity to infer genetic predisposition to disease on a representative sample of a study population, now that many such studies are gathering genetic information on the participants. One feature to using existing cohorts is that subjects may be censored due to death prior to genetic sampling, thereby adding a layer of complexity to the analysis. We develop a statistical framework to infer parameters of a latent variables model for disease onset. The latent variables model describes the role of genetic and modifiable risk factors on the onset ages of multiple diseases, and accounts for right-censoring of disease onset ages. The framework also allows for missing genetic information by inferring a subject's unknown genotype through appropriately incorporated covariate information. The model is applied to data gathered in the Framingham Heart Study for measuring the effect of different Apo-E genotypes on the occurrence of various cardiovascular disease events.

Adult↗

Mating patterns in a hybrid zone of fire-bellied toads (Bombina): inferences from adult and full-sib genotypes.

We present two novel methods to infer mating patterns from genetic data. They differ from existing statistical methods of parentage inference in that they apply to populations that deviate from Hardy-Weinberg and linkage equilibrium, and so are suited for the study of assortative mating in hybrid zones. The core data set consists of genotypes at several loci for a number of full-sib clutches of unknown parentage. Our inference is based throughout on estimates of allelic associations within and across loci, such as heterozygote deficit and pairwise linkage disequilibrium. In the first method, the most likely parents of a given clutch are determined from the genotypic distribution of the associated adult population, given an explicit model of nonrandom mating. This leads to estimates of the strength of assortment. The second approach is based solely on the offspring genotypes and relies on the fact that a linear relation exists between associations among the offspring and those in the population of breeding pairs. We apply both methods to a sample from the hybrid zone between the fire-bellied toads Bombina bombina and B. variegata (Anura: Disco glossidae) in Croatia. Consistently, both approaches provide no evidence for a departure from random mating, despite adequate statistical power. Instead, B. variegata-like individuals among the adults contributed disproportionately to the offspring cohort, consistent with their preference for the type of breeding habitat in which this study was conducted.

Animals↗

Requirements for demonstrating clinical efficacy: statistical aspects.

Usual statistical practice in inference on the comparison of two treatment effects is based on significance tests. In the positive case, it is unlikely that the observed difference is based only on random variation, and a decision is made that there is a real superiority. In the negative case, no conclusion on a missing difference is possible. In both cases, statistical tests fail to describe the magnitude of the underlying effect. Confidence intervals are more suitable for demonstrating clinical efficacy. Their advantages and applications are discussed.

Clinical Trials as Topic↗

TREEFINDER: a powerful graphical analysis environment for molecular phylogenetics.

BACKGROUND: Most analysis programs for inferring molecular phylogenies are difficult to use, in particular for researchers with little programming experience. RESULTS: TREEFINDER is an easy-to-use integrative platform-independent analysis environment for molecular phylogenetics. In this paper the main features of TREEFINDER (version of April 2004) are described. TREEFINDER is written in ANSI C and Java and implements powerful statistical approaches for inferring gene tree and related analyzes. In addition, it provides a user-friendly graphical interface and a phylogenetic programming language. CONCLUSIONS: TREEFINDER is a versatile framework for analyzing phylogenetic data across different platforms that is suited both for exploratory as well as advanced studies.

Computational Biology↗

Regression models for clustered binary responses: implications of ignoring the intracluster correlation in an analysis of perinatal mortality in twin gestations.

PURPOSE: Dependent binary responses, such as health outcomes in twin pairs or siblings, frequently arise in perinatal epidemiologic research. This gives rise to correlated data, which must be taken into account during analysis to avoid erroneous statistical and biological inferences. METHODS: An analysis of perinatal mortality (fetal deaths plus deaths within the first 28 days) in twins in relation to cluster-varying (those that are unique to each fetus within a twin pregnancy such as birthweight) and cluster-constant (those that are identical for both twins within a sibship such as maternal smoking status) risk factors is presented. Marginal (ordinary logistic regression [OLR] and logistic regression using generalized estimating equations [GEE]) and cluster-specific (conditional and random-intercept logistic regression models) regression models are fit and their results contrasted. The United States "matched multiple data" file of twin births (1995-1997), which includes 285,226 twins from 142,613 pregnancies, was used to examine the implications of ignoring of clustering on regression inferences. RESULTS: The OLR models provide variance estimates for cluster constant covariates that ranged from 7% to 71% smaller than those from GEE-based models. This underestimation is even more pronounced for some cluster-varying covariates, ranging from 21% to 198%. CONCLUSIONS: Ignoring the cluster dependency is likely to affect the precision of covariate effects and consequently interpretation of results. With widespread availability of appropriate software, statistical methods for taking the intracluster dependency into account are easily implemented and necessary.

Cluster Analysis↗

Are molecular haplotypes worth the time and expense? A cost-effective method for applying molecular haplotypes.

Because current molecular haplotyping methods are expensive and not amenable to automation, many researchers rely on statistical methods to infer haplotype pairs from multilocus genotypes, and subsequently treat these inferred haplotype pairs as observations. These procedures are prone to haplotype misclassification. We examine the effect of these misclassification errors on the false-positive rate and power for two association tests. These tests include the standard likelihood ratio test (LRTstd) and a likelihood ratio test that employs a double-sampling approach to allow for the misclassification inherent in the haplotype inference procedure (LRTae). We aim to determine the cost-benefit relationship of increasing the proportion of individuals with molecular haplotype measurements in addition to genotypes to raise the power gain of the LRTae over the LRTstd. This analysis should provide a guideline for determining the minimum number of molecular haplotypes required for desired power. Our simulations under the null hypothesis of equal haplotype frequencies in cases and controls indicate that (1) for each statistic, permutation methods maintain the correct type I error; (2) specific multilocus genotypes that are misclassified as the incorrect haplotype pair are consistently misclassified throughout each entire dataset; and (3) our simulations under the alternative hypothesis showed a significant power gain for the LRTae over the LRTstd for a subset of the parameter settings. Permutation methods should be used exclusively to determine significance for each statistic. For fixed cost, the power gain of the LRTae over the LRTstd varied depending on the relative costs of genotyping, molecular haplotyping, and phenotyping. The LRTae showed the greatest benefit over the LRTstd when the cost of phenotyping was very high relative to the cost of genotyping. This situation is likely to occur in a replication study as opposed to a whole-genome association study.

Cost-Benefit Analysis↗