Regional variation in organ donation in Saudi Arabia.

INTRODUCTION: There is marked regional variation in organ donation among the different regions of Saudi Arabia. Our aim was to study the dominating factors for these variations to improve organ donation in low-donation areas. MATERIALS AND METHODS: This study was a retrospective review of the Saudi Center for Organ Transplantation data for cadaveric organ donation from 2006 to 2012, with the number of cases reported, documented, consented, and harvested in various regions (northern, southern, eastern, western, and central). The region, number, and size of contributing intensive care units (ICUs), overall donation rate, and transplanted rate (potential donor and those harvested, respectively) were also reviewed. RESULTS: Between 2006 and 2012, a total of 512 cases were procured and analyzed from Saudi Arabia. From the central region, 393 were acquired, representing 76.7% of the total consented cases. These 393 cases came from 30 of 97 contributing ICUs (31%). The eastern region was ranked second, followed by the western region. The conversion rate for all regions followed a similar trend. CONCLUSIONS: There is marked variation with regard to organ donation in different regions throughout Saudi Arabia, from 1.9% in the southern region to 76.7% in the central region. This finding is related to the presence of a Mobile Action Donor Team in the central region. The number of potential donors and the contributing ICUs were strong predictors of the number of actual donors. We suggest that having a mobile donor team in each region will increase the number of donors by at least 3 times within the next 3 to 5 years.

Bivariate models for co-aggregation of dichotomous traits in twins.

The study of twins is widely used for research into genetic and environmental influences on human traits. Study designs in which independent samples of monozygotic and dizygotic twins are compared with respect to their similarity have focused on single binary trait. However, the risk of co-occurrence of more than one disease in twins is a parameter of interest to genetic epidemiologists and other investigators. For example, they may be interested in assessing the genetic and environmental etiologies of reading deficits (RD) and attention deficit hyperactivity disorder (ADHD) and their co-morbidity. In this paper, we present statistical methodology for the estimation of twin similarity with respect to two dichotomous traits measured on each member of the twin pair. For two sample problems, several test procedures that account for the correlation between twins and the correlation between traits are presented. An example based on the Australian population-based twin registry published data is given to illustrate the methodology.

Air emissions from sour-gas processing plants and dairy-cattle reproduction in Alberta, Canada.

The dispersion of air pollutants from all 231 licensed sour-gas processing plants in Alberta, Canada, was modeled on a monthly basis over a 10-year period (1985-1994). Exposure estimates for sulfur dioxide (SO(2)-used as a surrogate for exposure to combusted emissions) then were assigned to 1382 provincial dairy farms using a geographical-information system. Individual average and peak exposure for periods prior to each of 15 months of age and conception (four exposure-averaging periods for each of two dispersion models) were estimated for 163,988 primiparous female dairy-cattle between 1986 and 1994. Monthly or annual average farm-site exposure estimates likewise were assigned to associated herd-level data sets for the biologically relevant period of interest for each of three additional reproductive outcomes: monthly herd-average calving interval, stillbirth risk, and twinning risk. In one of the main-effects models, the maximum (i.e., peak) monthly sour-gas exposure experienced by individual-animals from birth to conception was associated with an increased time to first-calving in the very-highest exposure category (hazard ratio=0.86, 95% CI=0.80, 0.92). This equates to a decreased hazard (lambda) of calving (in each month subsequent to 22 months of age) for the highest-exposure animals (lambda=0.170) versus the zero-exposure animals (lambda=0.198) in a model with referent values for agro-ecological region and season of birth. The dose-response was not consistent across the full range of exposure categories. There was significant (P=0.003) interaction of emissions with agro-ecological region. After accounting for the interaction, a more-consistent dose-response was evident for some (but not all) agro-ecological regions. This suggests that any effect of emissions on dairy-heifer reproduction is subject to modification by features of soil type, vegetative cover, and/or climate. The increase in monthly herd-average calving interval on farms exposed to the very-highest levels of emissions appeared quite small and of limited practical importance within the range of expected exposures. There was no association between exposure and the risk for twinning. Herds exposed to higher emissions exhibited a slight decrease in risk for stillbirth.

Issues of cost and efficiency in the design of reliability studies.

Reliability of continuous and dichotomous responses is usually assessed by means of the intraclass correlation coefficient (ICC). We derive the optimal allocation of the number of subjects k and the number of repeated measurements n that minimize the variance of the estimated ICC. Cost constraints are discussed for the case of normally distributed responses. Tables showing optimal choices of k and n are given, along with guidelines for the design of reliability studies in light of our results and those reported by others.

Caffeine metabolism in premature infants.

Caffeine has been used frequently in the treatment and prevention of apnea of prematurity. The metabolism of caffeine depends on the activities of the hepatic enzymes that vary from one infant to another. The objective of this study was to determine the influence of postnatal age (PNA), birth weight (BW), study weight (SW), gestational age (GA), postconceptual age (PCA), and gender on the maturation of caffeine metabolism in premature infants. The caffeine base was administered orally as a loading dose of 10 mg/kg, followed by a maintenance dose of 2 mg/kg every 24 hours. The steady-state concentration of caffeine and metabolites was measured in plasma taken on the 5th-day postloading dose. The molar concentration ratios for the N3 (N3-), N7 (N7-), N1 (N1-), and all methyl (Nall-) demethylation processes; clearance (CL); and the percentage of molar concentration of caffeine found in plasma to that of the total caffeine and metabolites (%CAF) were calculated from samples collected from 80 neonatal infants. The 48 male and 32 female premature infants had median (range) BW (g), GA (weeks), SW (g), PCA (weeks), and PNA (days) of 1300 (650-2260), 30 (24-34), 1630 (980-2670), 34 (29-40), and 28 (5-60), respectively. The median (range) of the ratios for the %CAF, CL, and the N3-, N7-, N1-, and Nall- were 86.9 (52.9-99.0), 0.127 (0.046-0.503) ml.kg-1.min-1, 0.032 (0-0.438), 0.070 (0.007-0.471), 0.026 (0-0.283), and 0.0463 (0.003-0.303), respectively. When the patients were stratified into four PNA age groups, each older group showed a consistently higher level of caffeine metabolic activity for the N3-, N7-, and Nall- pathways with a corresponding decrease in the %CAF, whereas no significant differences were seen for the N1-pathway or for CL. No pattern of significant differences between the demethylation process ratios, %CAF, or CL was seen between groups of infants when they were stratified according to BW, SW, PCA, or GA. The female infants were found to have significantly higher rates of caffeine metabolism as shown by %CAF, N1-, N3-, and Nall- processes but not the N7-. Multivariate linear regression analysis by two methods demonstrated that PNA is significantly related to %CAF and Nall-, whereas the female patients had higher levels of metabolic activity for the %CAF and N1- process. The authors conclude that the N7-demethy-lation process is the predominate caffeine metabolic process in premature infants. Furthermore, the maturation of the caffeine metabolism in premature infants with a PNA of less than 60 days increases with postnatal age, regardless of birth weight, gestational age, postconceptual age, and study weight. The female neonatal patients demonstrated a higher rate of caffeine metabolism than the males.

Efficiency considerations in the analysis of inter-observer agreement.

The reliability of binary assessments is often measured by the proportion of agreement above chance, as estimated by the kappa statistic. In this paper, we develop a model to estimate inter-rater and intra-rater reliability when each of the two observers has the opportunity to obtain a pair of replicate measurements on each subject. The model is analogous to the nested beta-binomial model proposed by Rosner (1989, 1992). We show that the gain in precision obtained from increasing the number of measurements per rater from one to two may allow fewer subjects to be included in the study with no net loss in efficiency for estimating the inter-rater reliability.

Testing the equality of two dependent kappa statistics.

Procedures are developed and compared for testing the equality of two dependent kappa statistics in the case of two raters and a dichotomous outcome variable. Such problems may arise when each of a sample of subjects are rated under two distinct settings, and it is of interest to compare the observed levels of inter-observer and intra-observer agreement. The procedures compared are extensions of previously developed procedures for comparing kappa statistics computed from independent samples. The results of a Monte Carlo simulation show that adjusting for the dependency between samples tends to be worthwhile only if the between-setting correlation is comparable in magnitude to the within-setting correlations. In this case, a goodness-of-fit procedure that takes into account the dependency between samples is recommended.

An epidemiologic study of disease in 32 registered Holstein dairy herds in British Columbia.

Data recorded in a herd health management system were obtained from 32 registered Holstein dairy herds from British Columbia. Frequencies of disease were described, and the effect of herd, age, year, season, and the interrelationships between diseases within a lactation on the occurrence of disease were evaluated. Lactational incidence rates were computed for diseases with a short period of risk (ie, udder edema, milk fever, retained placenta, metritis, displaced abomasum, and ketosis), whereas for diseases with a longer period of risk (ie, cystic ovaries, mastitis and stable footrot), incidence densities were calculated. Overall, the disease incidence was low and showed an increase in frequency by year, which we attributed to more observing and complete recording by the owner, rather than an actual increase in disease incidence. Most diseases occurred early in lactation and their frequency increased with lactation number; the exception was udder edema, which occurred mainly during the first 2 lactations. An informal path model of disease interrelationships was made conditional on herd. Based on the results we inferred 2 independent pathways: one started by udder edema, and the other by milk fever. Udder edema was directly associated with mastitis occurrence from 0 to 30 d in lactation, metritis, and cystic ovaries. Mastitis from 0-30 d in lactation increased the risk of both mastitis from 31-150 d in lactation and cystic ovaries. Both of these increased the risk of late lactation mastitis. Milk fever was directly related with displaced abomasum, which increased the risk of footrot. In general, diseases that occurred in early lactation tended to increase the risk of other diseases later in lactation.

Investigating potential risk factors for seasonal variation: an example using graphical and spectral analysis methods based on the production of milk components in dairy cattle.

The objective of this study was to illustrate methods for investigating factors associated with seasonality, using milk-component production as an example. Milk-protein and fat percentages showed a seasonal pattern; percentages were lowest during June and July and highest in October and November. Graphical methods were used to compare herd calving patterns to seasonal production patterns and spectral analysis were used to compare seasonal production patterns between farm groups with different management practices. For the comparison of seasonality of production and herd calving patterns, data was obtained from archival records for all cows enrolled in Dairy Herd Improvement (DHI) milk recording in Ontario, Canada from 1990 to 1994. For comparisons of seasonality and management practices, monthly protein and fat percentages were obtained from the Dairy Farmers of Ontario from March 1985 to July 1994. Management information was obtained from responses to questionnaires completed by 364 dairy producers in Ontario. Graphical analyses provided a visualization of the relationship between herd calving patterns and seasonality of production-however, graphical methods alone did not allow statistical inferences to be made. Spectral analyses provided a formal statistical test of the null hypothesis of no association between an independent variable (farm management type) and seasonal production pattern in the data over time, provided that the outcome followed the same seasonal pattern regardless of covariate levels under the null hypothesis.

Repeatability of the Petrifilm HEC test and agreement with a hydrophobic grid membrane filtration method for the enumeration of Escherichia coli O157:H7 on beef carcasses.

The Petrifilm HEC test (3M Canada Inc., London, Ontario), a quantitative microbiological test for Escherichia coli O157:H7, was evaluated for its performance as a beef-carcass monitoring test. Test repeatability and agreement and agreement with an E. coli O157:H7 detection method using a hydrophobic grid membrane filter (HGMF) overlaid onto cefixime-tellurite-sorbitol MacConkey agar (CT-SMAC) followed by a latex agglutination test for the O157 antigen were determined by using pure cultures of E. coli O157:H7, beef samples experimentally contaminated with bovine feces containing E. coli O157:H7, and naturally contaminated beef carcasses of unknown E. coli O157:H7 status from a local abattoir. The Petrifilm HEC test showed excellent repeatability and excellent agreement with the HGMF-CT-SMAC method when test samples were obtained from pure cultures and experimentally contaminated meat. All 125 naturally contaminated beef carcasses surveyed were negative for E. coli O157:H7 with both microbial methods. The Petrifilm HEC test, however, demonstrated a significantly lower proportion of cross-reactive organisms (false-positive reactions) than the HGMF-CT-SMAC method. Given the performance of this test coupled with its ease of use and compact size, it shows considerable promise for carcass testing where abattoir laboratory facilities are limited and as a substitute for more complex laboratory testing methods used in established laboratories.

The association between the bovine tuberculosis status of herds in the East Offaly Project Area, and the distance to badger setts, 1988-1993.

The proximity of farms to badger setts was compared between farms that had experienced a tuberculosis breakdown and those that had not, over the 6 year period from 1988 to 1993. The data were derived from a badger removal study conducted in East Offaly County in the Republic of Ireland. Badger removal began in 1989 and continued through 1993; by the end of 1990, approximately 80% of all badgers caught in the 6 year period had been removed. All badgers were examined, grossly, for evidence of tuberculosis. Tuberculosis status of the approximately 900 study herds was based on the results of the single intradermal comparative skin test and/or lesions of bovine tuberculosis. All herds were tested at least once annually. The number of herds experiencing bovine tuberculosis declined over the period, particularly in the years 1992 and 1993. The data on farm and badger sett location were stored and analysed, initially, in a geographical information system. Owing to the badger removal programme, the distance between the barn yard of a typical farm and the nearest occupied badger sett increased, by about 300 m year-1, and by about 600 m year-1 to the closest infected sett. In bivariate analyses, in the years 1988 and 1989, the risk of tuberculosis declined with increasing distance to a badger sett containing one or more tuberculous badgers. In multivariable logistic regression analyses, year and the average number of cattle tested per farm per year were controlled. A second identical analysis was conducted to control for the repeated observations on the same herds using generalised estimating equations. In both analyses, the risk of a multiple reactor tuberculosis breakdown decreased for herds at least 1000 m away from an infected badger sett, and increased as the number of infected badgers per infected sett increased. Despite the significantly reduced risk of a breakdown with increasing distance to infected badger setts, the relationship was not strong (sensitivity and specificity of the model in the low 70% range) and explained only 9-19% of tuberculosis breakdowns.

Statistical analysis of intraclass correlations from multiple samples with applications to arterial blood pressure data.

We consider inference procedures on intraclass correlations for unbalanced data from several multivariate normal populations. We derive several tests, including ones based on Fisher's variance stabilizing transformation and Neyman's score functions, to test the homogeneity of intraclass correlations. We illustrate the methodology with an example that uses arterial blood pressure data collected by Miall and Oldham and we compare the procedures in terms of their empirical levels and powers with a Monte Carlo simulation study. We recommend the use of Neyman's C(alpha) test and a test based on the ANOVA estimators of the intraclass correlations as they hold their significance levels and give consistently higher powers.

Calf health in cow-calf herds in Switzerland.

In 1993, an observational study was initiated to provide general information on animal health in extensive beef farms, to estimate disease frequency and the economic impact of calf diseases and to identify risk factors related to health and weight gain. The longitudinal study was conducted from fall 1993 until winter 94/95 and included 100 farms in western Switzerland. The basic concept was to follow one generation of calves on these farms and record all events concerning animal health from birth to weaning. The study population included 1270 calves (most were Angus crossbreds). Farm-management data were collected with a questionnaire conducted on the farm. Birth and weaning weights were obtained from the beef cattle breeding association. Clinical diagnoses and treatment costs were provided by the farm veterinarians. Two thirds of the dead calves were submitted to a complete postmortem examination. Fifty-three percent of the farms in the study were primary type income farms while 47% were secondary type income farms. Thirty-eight percent of the farms were situated in the lower areas of Switzerland, 14% in the prealpine foothills, the remaining 48% were located in mountain areas. Preweaning calf mortality was 5%. The main causes of calf deaths were respiratory diseases and digestive disorders. Twenty-two percent of the calves were treated at least once by a veterinarian; 36% of the treatments administered by the veterinarian were applied because of diarrhea, 27% because of respiratory diseases. Disease incidence was highest during the months of November, December and January. The association of disease and potential farm-level risk factors was analysed using chi 2-statistics and multivariable regression methods including generalized estimating equations to adjusted for herd effects. Specific risk factors for disease were not identified. Treatment for disease was not associated with 250-day standardized weight gain.

Variations in the prevalence of antibody to brucella infection in cattle by farm, area and district in Kenya.

Variations in the sero-prevalence of antibody to brucella infection by cow, farm and area factors were investigated for three contrasting districts in Kenya: Samburu, an arid and pastoral area: Kiambu, a tropical highland area; and Kilifi, a typical tropical coastal area. Cattle were selected by a two-stage cluster sampling procedure and visited once between August 1991 and 1992. Schall's algorithm, a statistical model suitable for multi-level analysis was used. Using this model, older age, free grazing and large herd size (> or = 31) were associated with higher seroprevalence. Also, significant farm-to-farm, area-to-area and district-to-district variations were estimated. The patterns of high risk districts and areas seen were consistent with known animal husbandry and movement risk factors, but the larger than expected farm-to-farm variation within high risk areas and districts could not be explained. Thus, a multi-level method provided additional information beyond conventional analyses of sero-prevalence data.

Assessing infections at multiple levels of aggregation.

The patterns of sero-prevalence of antibodies to four infectious diseases, representing a broad range of pathogens (bacteria: brucellosis; mycoplasma: contagious bovine pleuropneumonia; viruses: infectious bovine rhinotracheitis; protozoa: trypanosomosis) were investigated at three levels of organization (farm, area and district). Three contrasting districts in Kenya were compared: an arid and pastoral area (Samburu); a tropical highland area (Kiambu), and a tropical coastal area (Kilifi). Cattle in three districts were selected by two-stage cluster sampling between August 1991 and 1992. Schall's algorithm, a generalized linear mixed model suitable for multi-level analysis, was compared to ordinary logistic regression (OLR), which ignores clustering of responses; generalized estimating equations (GEE) or Jacknife, to account for clustering at the farm level; SAS VARCOMP, which provides normal-theory random-effects models. Schall's algorithm provided similar estimates to GEE (regression effects) and Jackknife (standard errors) for farm-level clustered data. Extending Schall's procedure for additional district and area-within-district random effects usually provided additional information. In general, models that included only a farm-level random effect consistently provided larger estimates of farms' variance components than did models with additional district and area random effects. The four type diseases exhibited various amounts of clustering. Brucellosis had moderate farm clustering plus some area and district clustering. Contagious bovine pleuropneumonia had only a small amount of clustering, mostly by area. Infectious bovine rhinotracheitis exhibited a large amount of clustering, primarily at the farm level. Trypanosomiasis antibody prevalence varied by district, area and farm. We believe that patterns of disease clustering identified by multi-level analysis can be used to better target high-risk units for disease control and guide research to understand disease transmission factors.

A comparison of different models for assessing variations in the sero-prevalence of infectious bovine rhinotracheitis by farm, area and district in Kenya.

The relative variability of the sero-prevalence of antibodies to infectious bovine rhinotracheitis (IBR) due to cow, farm, and agroecological area levels were investigated for three contrasting districts in Kenya: Samburu, an arid and pastoral area; Kiambu, a tropical highland area; and Kilifi, a typical tropical coastal area. Cattle were selected by two-stage cluster sampling and visited once between August 1991 and 1992. Data on animal, farm, and area factors were analyzed using Schall's algorithm and MLn (multi-level, n-level), two generalized mixed-model programs suitable for multi-level analysis. Most variation in IBR sero-prevalence was from farm-to-farm. This was reflected by the many farm-level fixed effects (farm size, disease control measures and type of breeding) significant in models both ignoring and accounting for single variance components (clustering) at farm, area, and district levels. Area-to-area and district-to-district variations were noted but the area and district variance components were one-third and one-fifth the size of the farm variance components for both methods. As farm-to-farm variation differed markedly by farm size and district, models in MLn were extended to allow for multiple farm-level variance components by these categories. For each, sero-prevalence of IBR increased with age and was significantly decreased on small-sized zero-grazing farms. These models, particularly the model with different farm variance components by districts, fit the data better and highlighted well that there was considerable farm-to-farm variation--differing by district--and that the available farm-level fixed effects did not predict IBR sero-prevalence well.

Maximum likelihood estimation of the kappa coefficient from bivariate logistic regression.

We propose a maximum likelihood estimator (MLE) of the kappa coefficient from a 2 x 2 table when the binary ratings depend on patient and/or clinician effects. We achieve this by expressing the logit of the probability of positive rating as a linear function of the subject-specific and the rater-specific covariates. We investigate the bias and variance of the MLE in small and moderate size samples through Monte Carlo simulation and we provide the sample size calculation to detect departure from the null hypothesis H0: kappa = kappa 0 in the direction of H1: kappa > kappa 0.

Maximum likelihood estimation of the kappa coefficient from models of matched binary responses.

We present an estimate of the kappa-coefficient of agreement between two methods of rating based on matched pairs of binary responses and show that the estimate depends on the common intraclass correlation coefficient between the pairs. Via Monte Carlo simulation, we investigate power of the test of significance on kappa, and the large sample bias and variance of its maximum likelihood estimator.

Parametric estimation in a genetic mixture model with application to nuclear family data.

The apparent conflict between the biometrician and Mendelian genetics has been recently resolved by the introduction of a genetic mixed model to analyze continuous traits measured on human families and to elucidate the mechanism of underlying major genes. The mixed model formulated by Elston and Stewart (1971, Human Heredity 21, 523-542), extended by Morton and MacLean (1974, American Journal of Human Genetics 26, 489-503), and reviewed, with further extensions, by Boyle and Elston (1979, Biometrics 35, 55-68) has become an extremely useful tool of wide applicability in the field of genetic epidemiology. This model allows for segregation at a major locus, a polygenic effect, and a sibling environmental variation. The main concern of this paper is with estimating the model parameters by the method of maximum likelihood. The expectation-maximization (EM) algorithm is developed to derive the estimates iteratively. An approximation of the information matrix when using the EM algorithm is given. We illustrate the methodology by fitting the model to the arterial blood pressure data collected by Miall and Oldham (1955, Clinical Science 14, 459-487).

Statistical testing of genetic linkage under heterogeneity.

Recent advances in human genetics have led to a renewed interest in statistical methods for the detection of linkage from family data--for example, between marker loci and disease traits. Statistical analysis of linkage between two loci is carried out almost exclusively by means of the lod (log-odds) score test, equivalent to a likelihood ratio test. The current practice is to declare genetic linkage between loci when the maximum lod score exceeds 3. As will be discussed here, the lod-score approach is not appropriate for the detection of linkage from heterogeneous data, e.g., when families consist of a mixture of linked and unlinked types. Heterogeneity may arise, for example, when rare mutations at different genetic loci are responsible for the same disease trait. As an alternative approach to account for possible heterogeneity in the detection of linkage, we propose the application of large-sample test statistics that are members of Neyman's class of C(alpha), or partial score tests. The convergence of the proposed test statistics to their asymptotic distributions is investigated via Monte Carlo simulation for typical study designs applicable in human genetics.