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PubMed1990

[Clinical reference values for laboratory hematology tests calculated using the iterative truncation method with correction: Part 1. Reference values for erythrocyte count, hemoglobin quantity, hematocrit and other erythrocyte parameters including MCV, MCH, MCHC and RDW].

Age and sex dependent differences in the clinical reference values for erythrocyte count (RBC), hemoglobin quantity (Hb), hematocrit (Ht) and other erythrocyte parameters including MCV (mean corpuscular volume), MCH (mean corpuscular hemoglobin), MCHC (mean corpuscular hemoglobin concentration) and RDW (red cell distribution width), were calculated by the iterative truncation method with correction (Usui's method) using the results from tests on 6,300 patients' specimens obtained at Kyoto University Hospital. For RBC, Hb and Ht, the data obtained from the individuals below 13 years old showed the normal or sometimes log-normal distribution, but adjustment by the Xn-type variable transformation was often necessary to obtain the normal distribution for the data taken from the populations containing individuals over the age of 14. For the clinical reference values of RBC, Hb and Ht, no sex difference was observed below the age of 12. The values for males were significantly higher than those of females in the age range 13-79, and the values showed no significant sex-dependent difference at ages above 80. In females, age-dependent change of values for RBC, Hb and Ht was less prominent than in males; especially the upper limit values for females were very stable for all ages. MCV and MCH gradually increased with age both in males and females, and the MCHC remained constant in all age populations of male and female. The reference value for RDW was generated by the percentile method instead of the iterative truncation method because of the strong deviation in the distribution pattern, and the RDW values showed a gradual increase with age in both males and females.

Age Factors↗
PubMed2002

Discovering subpopulation structure with latent class mixed models.

The linear mixed model is a well-known method for incorporating heterogeneity (for example, subject-to-subject variation) into a statistical analysis for continuous responses. However heterogeneity cannot always be fully captured by the usual assumptions of normally distributed random effects. Latent class mixed models offer a way of incorporating additional heterogeneity which can be used to uncover distinct subpopulations, to incorporate correlated non-normally distributed outcomes and to classify individuals. The methodology is motivated with examples in health care studies and a detailed illustration is drawn from the Nutritional Prevention of Cancer trials. Latent class models are used with longitudinal data on prostate specific antigen (PSA) as well as incidence of prostate cancer. The models are extended to accommodate prostate cancer as a survival endpoint; this is compared to treating it as a binary endpoint. Four subpopulations are identified which differ both with regard to their PSA trajectories and their incidence rates of prostate cancer.

Adolescent↗
PubMed1995

Phenylbutazone in racing greyhounds: plasma and urinary residues 24 and 48 hours after a single intravenous administration.

The concentrations of phenylbutazone (PBZ), oxyphenbutazone (OPBZ) and gammahydroxyphenylbutazone (OHPBZ) in plasma and urine from 50 Greyhounds 24 and 48 h after the intravenous administration of a single dose of PBZ (30 mg/kg) were measured. The 24 h plasma concentrations of OPBZ and OHPBZ, the 48 h plasma concentration of OHPBZ and the 24 h urinary concentration of PBZ were normally distributed, while log transformations were required before the 24 h plasma concentration of PBZ and the 24 and 48 h urinary concentrations of OPBZ and OHPBZ became normally distributed. The 95%, 99%, 99.9% and 99.99% upper predicted confidence intervals for both 24 h and 48 h plasma and urinary concentrations demonstrated wide potential variation in the concentration of the analytes should PBZ be administered to Greyhounds. The 24 h plasma and urinary concentrations of PBZ were weakly correlated, but no similar relationship existed for OPBZ or OHPBZ. The urinary concentrations of each analyte were not affected by the trainer or sex of the Greyhound or the urinary pH. We conclude that it would be impossible to predict the timing of the PBZ administration or the plasma concentration of PBZ from the measurement of the concentration of PBZ in a single sample of urine.

Animals↗
PubMed2006

An analysis of postoperative epidural analgesia failure by computed tomography epidurography.

In this prospective study involving 125 patients, we analyzed epidural analgesia failure after major abdominal surgery using computed tomography (CT) epidurographies to compare the incidence of dislodgement of epidural catheters and leakage of solution from the epidural space between two groups of patients: patients with successful or failed epidural analgesia. Our hypothesis was that the incidence of dislodgement and leakage should be low when epidural analgesia is successful. A thoracic epidural catheter was inserted before general anesthesia and secured by subcutaneous tunneling. Bupivacaine (0.25%) was administered during surgery followed by continuous epidural analgesia with 0.125% bupivacaine (10 mL/h) and morphine (0.25 mg/h) for 48 h. Failure was defined as a visual analog scale pain score at rest more than 30 mm and/or interruption of epidural analgesia before 48 h for any reason. When failure was not due to unintentionally withdrawn, kinked catheters or adverse events (n = 11), a CT scan with contrast injection was performed. Control CT scans were also performed in patients with adequate analgesia (i.e., the success group). The incidence of failure was 24.8% (n = 31). CT scans in the failure group (n = 20) showed seven patients with catheters outside the epidural space, nine with normal distribution, one with unilateral spread, and three with leakage of solution outside the epidural space. In the success group, CT scans (n = 19) showed 11 patients with normal distribution, five with unilateral spread, and three with leakage. We conclude that the major cause of epidural analgesia failure was dislodgment of the catheter. CT scans were mostly useful for detecting leakage of injectate, which may be the early phase of dislodgment.

Abdominal Neoplasms↗
PubMed2001

[Description of drinking water intake in French communities (E.MI.R.A. study)].

BACKGROUND: Assessment of risks associated with waterborne pollutants requires a good characterization of the exposure of individuals and populations. This characterization implies knowledge of pollutants' levels in water and their time variability, and also estimation of drinking water consumption. Several studies were conducted, mostly in North America, on levels of chemical contaminants or prevalence of pathogens. Few studies were conducted on drinking water intake of the general population. METHODS: This work, included within the E.MI.R.A study which was set up to assess waterborne infectious risks, describes in details daily drinking water consumption of 544 French volunteers. Data were collected by self-questionnaires. RESULTS: RESULTS differ according to the season. Tap water usage for food follows a normal distribution (arithmetic mean in winter=1.55 l/j, 95% CI [0.20-2.90]; arithmetic mean in spring=1.78 l/j, [0.13-3.43]). Total drinking water intake follows a log-normal distribution (geometric mean in winter=1.60 l/j, standard deviation=1.73 l/j; geometric mean in spring=1.92 l/j, standard deviation=1.70 l/j). Tap water intake amounts to more than 80% of total drinking water consumption, and pure tap water (i.e not added, modified nor boiled) amounts to 42% of total drinking water. RESULTS are also displayed by age, and compared to other data available in the literature. CONCLUSIONS: This work provides data that can be used to develop risk assessment and epidemiological studies in the field of chemical or infectious risks in the context of France.

Adolescent↗
PubMed1998

Differences in static balance and weight distribution between normal subjects and subjects with chronic unilateral low back pain.

Balance reactions are not routinely evaluated in patients with low back pain. The purpose of this study was to determine if there were differences in static balance and weight distribution between subjects with unilateral low back pain (N = 15) and pain-free controls (N = 15). Measurements included limits of stability (%LOS), target sway, weight distribution on each lower extremity in quiet standing, and center of gravity with measurements of maximal excursion in anterior/posterior and medial/lateral directions. Independent t tests were used to compare data between groups. Compared with control subjects, subjects with low back pain demonstrated greater anterior-posterior center of gravity excursion and total center of gravity excursion with eyes open and greater anterior-posterior, medial-lateral, and total center of gravity excursion, target sway, and %LOS with eyes closed. There was no difference in the weight-bearing distribution between groups. This study suggests that static balance in patients with chronic low back pain may be impaired and should be thoroughly evaluated and integrated into physical therapy treatment programs.

Adult↗
PubMedDate not supplied

Multivariate Bayesian analysis of Gaussian, right censored Gaussian, ordered categorical and binary traits using Gibbs sampling.

A fully Bayesian analysis using Gibbs sampling and data augmentation in a multivariate model of Gaussian, right censored, and grouped Gaussian traits is described. The grouped Gaussian traits are either ordered categorical traits (with more than two categories) or binary traits, where the grouping is determined via thresholds on the underlying Gaussian scale, the liability scale. Allowances are made for unequal models, unknown covariance matrices and missing data. Having outlined the theory, strategies for implementation are reviewed. These include joint sampling of location parameters; efficient sampling from the fully conditional posterior distribution of augmented data, a multivariate truncated normal distribution; and sampling from the conditional inverse Wishart distribution, the fully conditional posterior distribution of the residual covariance matrix. Finally, a simulated dataset was analysed to illustrate the methodology. This paper concentrates on a model where residuals associated with liabilities of the binary traits are assumed to be independent. A Bayesian analysis using Gibbs sampling is outlined for the model where this assumption is relaxed.

Bayes Theorem↗
PubMed1977

[Metameters for the statistical treatment of data expressed in percentage values].

Medical or biochemical data are often expressed as percentages or proportions. Since the sampling error of percentage values does not usually follow a normal (Laplace-Gauss) model, statistical significance tests may give unsatisfactory results, when applied to the original data; however, the fitting to a normal distribution can be improved by choosing suitable metameters. The Author proposes the transformation of percentages to a hyperbolic function zp, based on Fisher's z, which is almost normally distributed. The performances of this transformation are checked, with special reference to medical laboratory problems.

Biochemical Phenomena↗
PubMed2002

Statistical approaches to estimating mean water quality concentrations with detection limits.

We review statistical methodology for estimating mean concentrations of potentially toxic pollutants in water, for small samples that are not normally distributed and often contain substantial numbers of nondetects, i.e. samples that are only known to be below some set of fixed thresholds. Maximum likelihood estimation (MLE) and regression on order statistics (ROS) are two main approaches that dominate the literature, with transformation bias under non-normality that increases with the severity of censoring being the main problem. We consider exact maximum likelihood estimators in conjunction with the Box-Cox transformation and propose the Quenouille-Tukey Jackknife as a method for bias reduction and variance estimation. Exact maximum likelihood estimators resulting from the expectation-maximization (EM) algorithm are exhibited in a simple heuristic form that also provides estimated values for the nondetects as subsidiary outputs. We show in simulationsthatthetwo main approaches perform well for the log-normal and gamma distributions as long as the jackknife is employed to reduce bias. Bias corrections to MLE used in the literature are shown to correct in the wrong direction under severe censoring. The jackknife is also used for estimating the variance of the both the MLE and ROS estimators. Robustness is improved by searching a class of power transformations (Box-Cox) for the best approximating normal distribution. We conclude that both the exact MLE and ROS procedures can be useful under varying experimental conditions. Limited simulations indicate that the ROS procedure is unbiased and has a smaller variance than the MLE under the log-normal distribution and is robust. The MLE performed better in simulations involving the gamma as the underlying distribution. We also compare the estimators for the mean and variance that one obtains from typical sets of water quality data, analyzing for copper, alumnium, arsenic, chromium, nickel, and lead.

Forecasting↗
PubMed2007

Analysis of the short form-36 (SF-36): the beta-binomial distribution approach.

Health-related quality of life (HRQoL) is an important indicator of health status and the Short Form-36 (SF-36) is a generic instrument to measure it. Multiple linear regression (MLR) is often used to study the relationship of HRQoL with patients' characteristics, though HRQoL outcomes tend to be not normally distributed, skewed and bounded (e.g. between 0 and 100). A sample of 193 patients with eating disorders has been analysed to assess the performance of the MLR under non-normality conditions. Normal distribution was rejected for seven out of the eight domains. A beta-binomial distribution is suggested to fit the SF-36 scores. The beta-binomial distribution is not rejected for five out of the eight domains. Thus, a beta-binomial regression (BBR) is suggested to analyse the SF-36 scores. Results using MLR and BBR have been compared for real and simulated data. Performance of the BBR is shown to be better than MLR in the HRQoL domains with few ordered categories and very similar to MLR in the more continuous domains. Moreover, the interpretation of the estimates obtained with BBR is clinically more meaningful. A common technique of statistical analysis is preferable for all the HRQoL dimensions. Therefore, the BBR approach is recommended not only to detect significant predictors of HRQoL when SF-36 is used, but also to analyse and interpret the effect of several explanatory variables on HRQoL. Further work is required to test the better performance of BBR against standard methods for other HRQoL outcomes, populations or interventions.

Adolescent↗
PubMed2006

Atomic force microscopy characterization of Xenopus laevis oocyte plasma membrane.

We used atomic force microscopy (AFM) to characterize the plasma membrane of Xenopus laevis oocytes. The samples were prepared according to novel protocols, which allowed the investigation of the extra- and intracellular sides of the membrane, both of which showed sparsely distributed spherical-like protrusions. Regions with comparably sized and densely packed structures arranged in an orderly manner were visualized and dimensionally characterized. In particular, two different arrangements, hexagonal and square packing, were recognizable in ordered regions. The lateral dimension of structures visualized on the external side had a normal distribution centered on 25.5 +/- 0.3 nm (mean value +/- SE), whereas that on the intracellular side showed a normal distribution centered on 30.2 +/- 0.8 nm. The height of the protrusions was 2-5 nm on the external side and 1-3 nm on the intracellular side. The mean number of structures on the external and intracellular sides of the plasma membrane was about 1000 microm(-2) and 850 microm(-2) respectively. Trypsin treatment greatly decreased the size of the membrane protrusions, thus confirming the proteic nature of the structures. These results show that AFM is a useful tool for structural characterization of proteins in a native eukaryotic membrane.

Animals↗
PubMed2006

Semiparametric variance-component models for linkage and association analyses of censored trait data.

Variance-component (VC) models are widely used for linkage and association mapping of quantitative trait loci in general human pedigrees. Traditional VC methods assume that the trait values within a family follow a multivariate normal distribution and are fully observed. These assumptions are violated if the trait data contain censored observations. When the trait pertains to age at onset of disease, censoring is inevitable because of loss to follow-up and limited study duration. Censoring also arises when the trait assay cannot detect values below (or above) certain thresholds. The latent trait values tend to have a complex distribution. Applying traditional VC methods to censored trait data would inflate type I error and reduce power. We present valid and powerful methods for the linkage and association analyses of censored trait data. Our methods are based on a novel class of semiparametric VC models, which allows an arbitrary distribution for the latent trait values. We construct appropriate likelihood for the observed data, which may contain left or right censored observations. The maximum likelihood estimators are approximately unbiased, normally distributed, and statistically efficient. We develop stable and efficient numerical algorithms to implement the corresponding inference procedures. Extensive simulation studies demonstrate that the proposed methods outperform the existing ones in practical situations. We provide an application to the age at onset of alcohol dependence data from the Collaborative Study on the Genetics of Alcoholism. A computer program is freely available.

Age of Onset↗
PubMed2002

Time-effect profile of antihypertensive agents assessed with trough/peak ratio, smoothness index and dose omission: an ambulatory blood pressure monitoring study with trandolapril vs. quinapril.

The duration of action of antihypertensive drugs may be assessed by several methods using ambulatory blood pressure monitoring (ABPM). The aim of this double-blind, randomized study was to compare the time-effect profile of once daily Trandolapril (Tra) 2 mg vs. Quinapril (Qui) 20 mg in 92 patients with mild-to-moderate hypertension. All patients received placebo during a 30-day run-in period followed by 2 months of active therapy and 1-day medication omission. ABPM was conducted on each period. 24 h antihypertensive coverage was assessed by trough:peak ratio (T/P) and smoothness index (SI) methods. Residual lowering of blood pressure after single-blind, 1 day medication omission was investigated as the SBP/DBP 48-h trough effect. There were no statistically significant differences between treatment groups in the mean SBP/DBP peak or trough effect. Individual T/P were not normally distributed and had very large variations explained by BP random- and activity-related fluctuations. Group T/P were 0.85 for Tra and 0.62 for Qui. The SI values were normally distributed and not statistically different between the two treatment groups. After dose omission, Qui was ineffective at 48-h trough while Tra retained a significant effect (SBP/DBP = -3.4/-4.3 mmHg) and this difference was even greater in ABPM-responders. Comparison of the trough:peak ratios and smoothness indexes of Tra and Qui failed to show any statistically significant difference on 24-h antihypertensive coverage. Nevertheless, residual lowering of blood pressure at 48-h trough suggests that Tra had a longer duration of action than Qui.

Adolescent↗
PubMedDate not supplied

[Estimation of reproducibility and repeatability in microbiological ring trials--robust versus conservative methods].

During the last years there was a lot of progress to be seen in the development of standardized methods for microbiological ring trials. The statistical analyzing strategies, in particular the calculation of estimations for the parameters repeatability and reproducibility, will be considered in this paper. Apart from the conservative method of the variance analysis robust methods are increasingly discussed. We will compare and discuss these methods using data of recently realized ring trials. If we can assume a normal distribution of our data, then all estimations are theoretically precise and efficient. But up to now, we know very little about the character of the robust estimations, if the normal distribution cannot be assumed. In addition to this, we have to mention once more, that the use of robust estimators is unreasonable without taking a critical look on the data themselves. Thus, we will show the possibilities of graphical presentation of all data to identify laboratories with critical results.

Animals↗
PubMedDate not supplied

Clinical trials in psychosocial medicine: methodologic and statistical considerations. Part II. Assessing reliability with equal-appearing interval scales.

The usual statistical procedures for assessing reliability among several raters do not apply to scales of the equal-appearing interval type. This is so primarily because the set of possible responses on such scales, namely the nonnegative integers 0,1,...(M-1), contains so few points that normal distribution theory cannot be invoked. Traditional analyses of such data, which include the one-way analysis of variance intraclass correlation, produce a reliability coefficient based on an assumed normally distributed response variable, and must therefore be interpreted with great caution. This paper discusses a statistical approach which exploits the discrete nature of the response variable and hence is more appropriate for such data.

Clinical Trials as Topic↗
PubMed1997

[Determination of caffeine metabolite for the evaluation of N-acetyltransferase, CYP1A2 and xanthine oxidase activities].

Caffeine was used as a metabolic probe to measure, in 120 healthy volunteers, the activities of three enzymes, deduced to be N-acetyltransferase(NAT2), CYP1A2 and xanthine oxidase (XO). The caffeine metabolites of 5-acetylamino-6-formylamino-3-methyluracil (AFMU), 1-methylxanthine(1X), 1-methyluric acid(1U), 1, 7-dimethylxanthine(17X), and 1, 7-dimethyluric acid(17U) in urine were determined with HPLC after 4-5 hours of caffeine drink. The ratios of AFMU/1X or AFMU/(AFMU + 1X + 1U), (AFMU + 1X + 1U)/17X or (AFMU + 1X + 1U)/17U, and 1U/1X or 1U/(1X + 1U) were used as the index of NAT2, CYP1A2, and XO activities respectively. Frequency distribution analysis of the metabolic ratios of NAT2 indicated two distinct group with 20 slow acetylators and 100 rapid acetylators. Similar CYP1A2 activity was found in Chinese compared with European volunteers. Frequency analysis of CYP1A2 indicated the log normal distribution in 120 Chinese. The CYP1A2 index was much higher in smokers than that in nonsmokers. But no obvious difference was observed between young and old volunteers. The XO index also showed log normal distribution and has the similar value compared with European volunteers. The concentration variations of 1X and 1U in young volunteers were much lower than that in old volunteers.

Adolescent↗
PubMed1989

Multivariate measures of similarity and niche overlap.

Niche overlap measures are used to assess the similarity in resource use by two species. Recently researchers have used niche overlap measures as summary measures and for making inferences, typically about competition for resources. The problem of estimating niche overlap when the niches are multivariate normal distributions with equal covariance matrices has previously been studied. In this work, the assumption of equal covariance matrices is relaxed. Two general measures of similarity are evaluated assuming general multivariate normal distributions. Commonly used measures of overlap are given as special cases of these two general measures. The question of bias in estimating these measures is discussed and shown to be a potential problem, especially when there are many redundant variables or if sample sizes are small.

Animals↗