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At least 631 records · Page 35Linked to original sources
PubMed1997

Comparison of topical anesthetics with lidocaine infiltration during laceration repair in children.

This study is a randomized, blinded trial that compares the effectiveness of a new topical anesthetic preparation of 2% mepivacaine and 1:100,000 norepinephrine (Mepivanor); a topical solution of 1% tetracaine, 1:4,000 adrenaline, and 4% cocaine (TAC); and 1% lidocaine infiltration during laceration repair in children. The study was conducted in the emergency department of a large academic children's hospital. Study participants were children 2 years of age or older with a laceration on the face or scalp, 5 cm or less in length, that required suturing. Patients were randomly assigned to receive Mepivanor topical solution, TAC topical solution, or lidocaine infiltration anesthesia prior to laceration repair. Seventy-one patients were enrolled in the study during a 2-month period. Outcome measures assessed pain perceptions using a Visual Analogue Scale (VAS) and a seven-point Likert scale. There was statistical power to detect differences of 1.2 to 1.7 units for the VAS outcome measures using alpha = 0.05 and beta = 0.20. There were no statistically significant (P > 0.05) differences between TAC and 1% lidocaine infiltration in providing effective anesthesia. Mepivanor was generally less effective in providing adequate anesthesia during laceration repair than TAC and lidocaine infiltration, with Tukey's post hoc test for ANOVA demonstrating statistically significant (P < 0.05) differences between Mepivanor and these agents for research assistant and suture technician VAS scores. Wound blanching was judged to be less with Mepivanor than with TAC, although this difference was not statistically significant. There were no adverse reactions, wound infections, or healing difficulties for any of the patients who received TAC or Mepivanor. It was concluded that non-cocaine-containing Mepivanor was generally less effective than TAC and lidocaine infiltration in providing adequate local anesthesia during laceration repair. TAC containing only 120 mg of cocaine (3 mL of 4% cocaine) was as effective as 1% lidocaine infiltration in providing local anesthesia during laceration repair. This will allow the amount of cocaine in TAC to be reduced, thereby decreasing costs and the likelihood of adverse reactions.

Adolescent↗
PubMed2006

An improved statistical method for detecting heterotachy in nucleotide sequences.

The principle of heterotachy states that the substitution rate of sites in a gene can change through time. In this article, we propose a powerful statistical test to detect sites that evolve according to the process of heterotachy. We apply this test to an alignment of 1289 eukaryotic rRNA molecules to 1) determine how widespread the phenomenon of heterotachy is in ribosomal RNA, 2) to test whether these heterotachous sites are nonrandomly distributed, that is, linked to secondary structure features of ribosomal RNA, and 3) to determine the impact of heterotachous sites on the bootstrap support of monophyletic groupings. Our study revealed that with 21 monophyletic taxa, approximately two-thirds of the sites in the considered set of sequences is heterotachous. Although the detected heterotachous sites do not appear bound to specific structural features of the small subunit rRNA, their presence is shown to have a large beneficial influence on the bootstrap support of monophyletic groups. Using extensive testing, we show that this may not be due to heterotachy itself but merely due to the increased substitution rate at the detected heterotachous sites.

Chi-Square Distribution↗
PubMed1985

Spontaneous abortions among women employed in the plastics industry.

A matched case-control study was done to analyze whether certain occupational exposures in the plastics industry were related to the risk of spontaneous abortions. Information on spontaneous abortions (cases) and births (controls) was obtained from the hospital discharge register; data on occupational exposures were obtained from the occupational health services of the workplaces. No increased risk of spontaneous abortions was observed among workers processing polymerized plastics or heated plastics made of vinyl chloride or of styrene. Owing to the low statistical power of the study, only strong effects can be ruled out. The odds ratio for workers actually processing polyurethane was increased (1.9, not statistically significant), and that for all workers in polyurethane-processing factories was significantly increased (3.0, p = 0.02). The finding needs to be investigated further in future studies.

Abortion, Spontaneous↗
PubMed2006

Relative risk of spinal cord injury in road crashes involving seriously injured occupants of light passenger vehicles.

Road crashes involving occupants of light passenger vehicles are the leading cause of traumatic spinal cord injury (SCI). Confirming the results of an earlier study, this study showed that: in single vehicle car crashes in the country, the odds of SCI were nearly five times higher (4.7) for occupants of non-sedan type light passenger vehicles compared with sedans; in single vehicle rollover crashes in the country, the odds of SCI were nearly three times higher (2.8) in non-sedans compared with sedans; the odds of SCI were nearly five times higher (4.8) for sports utility vehicles (SUVs) compared with sedans. When the data from the earlier study was included in order to increase statistical power, it was found that when compared to sedans that did not roll, occupants of all types of light passenger vehicles had a statistically significant substantially higher likelihood of SCI when involved in rollover (sedans 7.5 times, SUVs 5.9 times and others 8.4 times). In addition, SUVs had a higher likelihood of SCI even when not involved in rollover (5.4 times). Vehicle designers and regulators need to give more attention to the prevention of vehicle rollover and the means to improve occupant protection in the event of rollover. This study should be extended nationally to gain a larger case series so that the SCI risk of particular vehicle configurations, considering other crash factors, can be more precisely quantified and characteristics for low occurrence of SCI identified.

Accidents, Traffic↗
PubMedDate not supplied

Effects of high doses of toluene on color vision.

High exposure to toluene may cause optic neuropathy and retinopathy, both associated with dyschromatopsia. Another solvent, ethanol, is known to induce acute blue-yellow dyschromatopsia. This study investigated the acute effects of high doses of toluene on color vision. Eight male printshop workers were examined before and after cleaning printing containers with pure toluene. After cleaning, concentrations of toluene in blood were between 3.61 and 7.37 mg/l. Color vision was tested with the Farnsworth panel D-15 test, the Lanthony desaturated panel D-15 test, and the Standard Pseudoisochromatic Plates part 2. For control of possible acute effects, eight workers of a metal-working factory without any neurotoxic exposure were tested according to the same procedure. Acute exposure to toluene did not cause impairment of color vision. However, statistical power is limited due to the small number of exposed subjects. Color vision of the printshop workers tested before cleaning was slightly impaired (statistically not significant) when compared with unexposed subjects.

Adult↗
PubMed1998

Statistical methodology: IV. Analysis of variance, analysis of covariance, and multivariate analysis of variance.

Medical research frequently involves the statistical comparison of >2 groups, often using data obtained through the application of complex experimental designs. Fortunately, inferential statistical methodologies exist to address these situations. Analysis of variance (ANOVA) in its many forms is used to simultaneously test the equality of all groups in a study. One-way (with 1 independent variable), 2-way (with 2 independent variables), and repeated-measures (patients serve as their own controls) ANOVAs are forms of this technique. Each form has been developed to analyze data from a specific experimental design. Analysis of covariance (ANCOVA) allows the researcher to control for confounding variables that may influence the response of the dependent variable. Finally, multivariate analysis of variance (MANOVA) evaluates the simultaneous responses of multiple dependent variables to > or = 1 independent variable. Whereas ANOVA is the correct alternative to statistically inappropriate multiple t-tests, MANOVA is the correct alternative to statistically inappropriate multiple univariate ANOVA calculations. Use of each of these statistical methods requires an appropriate experimental design and data meeting a number of assumptions. When used properly, each of these methods provides a powerful statistical analysis technique.

Analysis of Variance↗
PubMed2001

Assessing the robustness of randomization tests: examples from behavioural studies.

Behavioural studies are commonly plagued with data that violate the assumptions of parametric statistics. Consequently, classic nonparametric methods (e.g. rank tests) and novel distribution-free methods (e.g. randomization tests) have been used to a great extent by behaviourists. However, the robustness of such methods in terms of statistical power and type I error have seldom been evaluated. This probably reflects the fact that empirical methods, such as Monte Carlo approaches, are required to assess these concerns. In this study we show that analytical methods cannot always be used to evaluate the robustness of statistical tests, but rather Monte Carlo approaches must be employed. We detail empirical protocols for estimating power and type I error rates for parametric, nonparametric and randomization methods, and demonstrate their application for an analysis of variance and a regression/correlation analysis design. Together, this study provides a framework from which behaviourists can compare the reliability of different methods for data analysis, serving as a basis for selecting the most appropriate statistical test given the characteristics of data at hand. Copyright 2001 The Association for the Study of Animal Behaviour.

Journal Article↗
PubMed2001

Regression calibration in studies with correlated variables measured with error.

Regression calibration is a technique that corrects biases in regression results in situations where exposure variables are measured with error. The existence of a calibration substudy, where accurate and crude measurement methods are related by a second regression analysis, is assumed. The cost of measurement error in multivariate analyses is loss of statistical power. In this paper, calibration data from California Seventh-day Adventists are used to simulate study populations and new calibration studies. Applying regression calibration logistic analyses, the authors estimate power for pairs of nutritional variables. The results demonstrate substantial loss of power if variables measured with error are strongly correlated. Biases in estimated effects in cases where regression calibration is not performed can be large and are corrected by regression calibration. When the true coefficient has zero value, the corresponding coefficient in a crude analysis will usually have a nonzero expected value. Then type I error probabilities are not nominal, and the erroneous appearance of statistical significance can readily occur, particularly in large studies. Major determinants of power with use of regression calibration are collinearity between the variables measured with error and the size of correlations between crude and corresponding true variables. Where there is important collinearity, useful gains in power accrue with calibration study size up to 1,000 subjects.

Bias↗
PubMedDate not supplied

A k nearest neighbour test for space-time interaction.

This paper describes a k nearest neighbour statistic sensitive to the pattern of cases expected of space-time clusters of health events. The Knox and Mantel tests are frequently used for space-time clustering but have two disadvantages. First, the selection of critical space-time distances for the Knox test and of a data transformation for the Mantel test is subjective. Second, the Mantel statistic is the sum of the products of space and time distances, is linear in form, and is not sensitive to non-linear associations between small space and time distances expected of contagious processes. The k nearest neighbour statistic is the number of case pairs that are k nearest neighbours in both space and time, and is evaluated under the null hypothesis of independent space and time nearest neighbour relationships. The test was applied to simulated and real data and compared to the Knox and Mantel tests using statistical power comparisons. The k nearest neighbour test proved sensitive to the space-time interaction pattern expected of disease clusters, does not require parameters (such as critical distances) to be estimated from the data, and may be used to test hypotheses about the spatial and temporal scale of the cluster process. The method addresses significant weaknesses in existing space-time cluster tests and should prove useful in the quantification and evaluation of clusters of human health events. Additional research is needed to further document the power of the test under different cluster processes.

Censuses↗
PubMed2003

An examination of the genotyping error detection function of SIMWALK2.

This investigation was undertaken to assess the sensitivity and specificity of the genotyping error detection function of the computer program SIMWALK2. We chose to examine chromosome 22, which had 7 microsatellite markers, from a single simulated replicate (330 pedigrees with a pattern of missing genotype data similar to the Framingham families). We created genotype errors at five overall frequencies (0.0, 0.025, 0.050, 0.075, and 0.100) and applied SIMWALK2 to each of these five data sets, respectively assuming that the total error rate (specified in the program), was at each of these same five levels. In this data set, up to an assumed error rate of 10%, only 50% of the Mendelian-consistent mistypings were found under any level of true errors. And since as many as 70% of the errors detected were false-positives, blanking suspect genotypes (at any error probability) will result in a reduction of statistical power due to the concomitant blanking of correctly typed alleles. This work supports the conclusion that allowing for genotyping errors within likelihood calculations during statistical analysis may be preferable to choosing an arbitrary cut-off.

Adult Children↗
PubMed1990

New perspectives on Sanguinaria clinicals: individual toothpaste and oral rinse testing.

Clinical studies conducted since 1983 on oral care products containing sanguinaria extract have yielded a variety of results. A careful review of these trials suggests that the designs used to conduct many of these trials may have had affected the study outcomes. Review of these trials suggests that studies testing the efficacy of anti-plaque products exercise the following guidelines: 1) use parallel instead of crossover designs, 2) select appropriate study populations, 3) use sufficient numbers of subjects to ensure statistical power, 4) select appropriate controls, 5) ensure intra- or inter-rater reliability prior to the start of the study, and 6) use proper statistical methodology. This review was undertaken to provide perspective into the results of these early studies, and furnish the rationale for the planning of subsequent clinical testing of sanguinaria-containing products.

Alkaloids↗
PubMed2004

Increasing power for tests of genetic association in the presence of phenotype and/or genotype error by use of double-sampling.

Phenotype and/or genotype misclassification can: significantly increase type II error probabilities for genetic case/control association, causing decrease in statistical power; and produce inaccurate estimates of population frequency parameters. We present a method, the likelihood ratio test allowing for errors (LRTae) that incorporates double-sample information for phenotypes and/or genotypes on a sub-sample of cases/controls. Population frequency parameters and misclassification probabilities are determined using a double-sample procedure as implemented in the Expectation-Maximization (EM) method. We perform null simulations assuming a SNP marker or a 4-allele (multi-allele) marker locus. To compare our method with the standard method that makes no adjustment for errors (LRTstd), we perform power simulations using a 2/k factorial design with high and low settings of: case/control samples, phenotype/genotype costs, double-sampled phenotypes/genotypes costs, phenotype/genotype error, and proportions of double-sampled individuals. All power simulations are performed fixing equal costs for the LRTstd and LRTae methods. We also consider case/control ApoE genotype data for an actual Alzheimer's study. The LRTae method maintains correct type I error proportions for all null simulations and all significance level thresholds (10%, 5%, 1%). LRTae average estimates of population frequencies and misclassification probabilities are equal to the true values, with variances of 10e-7 to 10e-8. For power simulations, the median power difference LRTae-LRTstd at the 5% significance level is 0.06 for multi-allele data and 0.01 for SNP data. For the ApoE data example, the LRTae and LRTstd p-values are 5.8 x 10e-5 and 1.6 x 10e-3, respectively. The increase in significance is due to adjustment in the LRTae for misclassification of the most commonly reported risk allele. We have developed freely available software that performs our LRTae statistic.

Journal Article↗
PubMed2006

A novel approach to characterise pathogen candidate genetic polymorphisms involved in clinical outcome.

Understanding the key factors influencing the clinical outcome of an infection is crucial for early diagnosis and optimised treatment. Despite widespread recognition of the importance of the genetics composition of pathogens, most efforts so far have focused on characterising disease and susceptibility genes in humans. Here, we propose a new flexible and powerful methodological framework to detect candidate genetic polymorphisms influencing clinical outcome from pathogen genomes. The rationale is to use well-supported clades in a phylogeny as statistical predictors for clinical outcomes rather than the individual polymorphisms themselves. This greatly increases the statistical power to detect candidate polymorphisms when analysing a large number of variable sites. In a second step, the candidate polymorphisms are recovered by characterising the polymorphisms that most strongly support the clades predicting the clinical outcome. The modelling approach further allows including host factors and testing for possible interactions between factors. We illustrate the approach by an application on a dataset of hepatitis B polymerase genes. The statistical model retains age at infection as well as six candidate polymorphisms as predictors for clinical outcome (acute, chronic and fulminant). The method is straightforward to apply and computationally effective. While the approach is focused on detecting candidate polymorphisms from pathogen genomes, the method might be more broadly applied for characterising the link between genotype and phenotype while statistically controlling for environmental factors.

Hepatitis B virus↗
PubMed2006

Clinical investigation on spontaneous otoacoustic emission (SOAE) in 447 ears.

OBJECTIVES: It is known that spontaneous otoacoustic emission (SOAE) is often observed in normal hearing ears, but concrete clinical application of SOAE test has been rarely reported, compared with transiently evoked otoacoustic emission (TEOAE) and distortion product otoacoustic emission (DPOAE) tests. In addition, there have been a variety of opinions concerning laterality of SOAE, and influence of gender and hearing on SOAE. The reason for this may be that each report has the small number of subjects and lacks in statistical power. Therefore, in the present study, SOAE, TEOAE and DPOAE were measured in 447 ears of subjects at various ages with different hearing level, and statistical analysis was performed to investigate the clinical significance of SOAE. MATERIALS AND METHODS: The subjects were 447 ears in 268 patients (268 ears in females, and 179 ears in males). The age of subjects ranged from 0 to 75 years (mean: 30.8 years), and there were 222 left and 225 right ears. The subjects of schoolchildren or older (414 ears) received pure-tone audiometry, and infants (33 ears) received auditory brain-stem response (ABR). SOAE and TEOAE were measured using ILO88 (Otodynamics, Version 4.20). DPOAE was measured using ILO92 (Otodynamics, Version 1.32). RESULTS: Incidence of SOAE and the number of SOAE per ear were high in the subjects at age of 50 years or younger, in those with hearing level of not more than 30 dB, in the right ear, and in females. Incidence of SOAE in the whole of normal hearing ears was approximately 38%, but the ears with SOAE had almost normal hearing of not more than 30 dB. CONCLUSIONS: SOAE is useful for objective hearing assessment. Moreover, SOAE sometimes appeared in the ears in which TEOAE or DPOAE could not be confirmed, and it might be useful for definite diagnosis of disease state to measure SOAE in addition to TEOAE or DPOAE.

Adolescent↗
PubMed2003

Advances in statistical methods for substance abuse prevention research.

The paper describes advances in statistical methods for prevention research with a particular focus on substance abuse prevention. Standard analysis methods are extended to the typical research designs and characteristics of the data collected in prevention research. Prevention research often includes longitudinal measurement, clustering of data in units such as schools or clinics, missing data, and categorical as well as continuous outcome variables. Statistical methods to handle these features of prevention data are outlined. Developments in mediation, moderation, and implementation analysis allow for the extraction of more detailed information from a prevention study. Advancements in the interpretation of prevention research results include more widespread calculation of effect size and statistical power, the use of confidence intervals as well as hypothesis testing, detailed causal analysis of research findings, and meta-analysis. The increased availability of statistical software has contributed greatly to the use of new methods in prevention research. It is likely that the Internet will continue to stimulate the development and application of new methods.

Humans↗
PubMed1998

Further investigation on the regression method of mapping quantitative trait loci.

The simple regression method of mapping quantitative trait loci (QTL) is further investigated in comparison with the mixture model maximum likelihood method under high heritabilities, dominant and missing markers. No significant difference between the two methods is detected in terms of errors of parameter estimation and statistical powers, with the exception that the estimation of residual variance provided by the regression method is confounded with part of the QTL variance. The test statistic profiles show some difference between the two methods, but the difference is only detectable at the micro level. An alternative method, referred to as iteratively reweighted least squares, is proposed, which can correct the deficiency of parameter confounding in the regression method yet retains the properties of simplicity and rapidity of the ordinary regression method. Like the existing regression method, the weighted least squares method can be useful in QTL mapping in conjunction with the permutation tests and construction of confidence intervals by bootstrapping.

Chromosome Mapping↗
PubMed2004

Model-based inference of haplotype block variation.

The haplotype block structure of SNP variation in human DNA has been demonstrated by several recent studies. The presence of haplotype blocks can be used to dramatically increase the statistical power of genetic mapping. Several criteria have already been proposed for identifying these blocks, all of which require haplotypes as input. We propose a comprehensive statistical model of haplotype block variation and show how the parameters of this model can be learned from haplotypes and/or unphased genotype data. Using real-world SNP data, we demonstrate that our approach can be used to resolve genotypes into their constituent haplotypes with greater accuracy than previously known methods.

Algorithms↗
PubMed1999

Diet and waist-to-hip ratio: important predictors of lipoprotein levels in sedentary and active young men with no evidence of cardiovascular disease.

OBJECTIVE: Healthy, young men were studied to determine the relationship of energy and nutrient intake and physical activity to concentrations of plasma lipoprotein and cholesteryl ester transfer protein. DESIGN: A cross-sectional study compared active and sedentary male subjects (17 to 35 years old) with no personal or family history of coronary heart disease. Participants kept 20-day food and activity journals. Individual intakes of energy, protein, carbohydrate, fat, saturated fat, monounsaturated fatty acids, polyunsaturated fatty acids, dietary fiber, and alcohol were evaluated. Measurements of blood lipids (total cholesterol and triglycerides, high- and low-density lipoprotein cholesterol); apolipoproteins; cholesteryl ester transfer protein; anthropometric variables (body mass index, waist-to-hip ratio, percentage of body fat); and aerobic capacity were taken during fall and spring data collection periods. SUBJECT SELECTION: Subjects were selected on the basis of normal blood lipid levels, absence of underlying disease, and willingness to comply with their current level of physical activity for the duration of the study. Minimal sample size for statistical power was 12 men per group: 12 of 15 subjects who exercised and 13 of 15 subjects who were sedentary completed all phases of the study. STATISTICAL ANALYSES: Statistical analyses consisted of 2-way analysis of variance (activity level and season). Pearson product moment correlations and multiple regression analyses were conducted to assess whether energy and nutrient intakes, physical activity status, and/or anthropometric variables predicted plasma concentrations of lipids and apolipoproteins. RESULTS: Lower waist-to-hip ratio, and not specifically activity level, was associated with higher levels of high-density lipoprotein cholesterol (HDL-C) and lower levels of low-density lipoprotein cholesterol (LDL-C). Dietary intake of saturated and monounsaturated fats and alcohol predicted changes in some apolipoprotein and lipoprotein levels. APPLICATIONS: Use of waist-to-hip ratio in the primary prevention of coronary heart disease is a simple and cost-effective measure to predict development of abnormal lipoprotein profiles in young men. Specific dietary recommendations include adoption of a heart-healthy diet with emphasis on monounsaturated fatty acids (10% to 12% of energy or one third of total fat intake) and the suggestion that small amounts of alcohol (< 3 drinks per week) may, indeed, be beneficial. Because alcohol and waist-to-hip ratio were both important predictors of LDL-C level, even in active young men, the consumption of low levels of alcohol may be beneficial only if waist-to-hip ratio is maintained within the healthful range by achieving an appropriate balance of physical activity and macronutrient intake.

Adolescent↗