Tryptophan metabolism in vitamin B6-deficient mice

Vitamin B6 deficiency was induced in mice by maintenance for 4 weeks on a vitamin B6-free diet. Tryptophan metabolism was assessed by determining the urinary excretion of tryptophan metabolites, the metabolism of [14C]tryptophan in vivo and the formation of tryptophan and niacin metabolites by isolated hepatocytes. The vitamin B6-deficient animals excreted more xanthurenic acid and 3-hydroxykynurenine, and less of the niacin metabolites N1-methyl nicotinamide and methyl-2-pyridone-4-carboxamide, than did control animals maintained on the same diet supplemented with 5 mg vitamin B6/kg. After intraperitoneal injection of [14C]tryptophan, vitamin B6-deficient mice showed lower liberation of 14CO2 from [methylene-14C]tryptophan and [U-14C]tryptophan than did controls, indicating impairment of kynureninase (EC 3.7.1.3) activity. There was no difference between the two groups of animals in the metabolism of [ring-2-14C]tryptophan. Hepatocytes isolated from the vitamin B6-deficient animals formed more 3-hydroxykynurenine and xanthurenic acid than did cells from control animals, but also formed more NADP and free niacin

Environmental and occupational exposure to lead

Objective: To determine the status of environmental and occupational lead exposure in selected areas in Nairobi, Kenya. Design: Cross sectional study. Setting: Kariobangi North, Babadogo, Waithaka and Pumwani for assessment of environmental exposure to lead (Pb) and Ziwani Jua Kali works for assessment of occupational lead exposure. Olkalou in Nyandarua District was the covariate study area. Subjects: Three hundred and eight children and adults participated. Results: Blood lead levels (BLLs) obtained for the entire sample (n = 308) ranged from 0.4 to 65μg/ dl of blood. One hundred and sixty nine (55%) of the total sample had levels equal to or below 4.9μg/dl, while 62 (20%) of the sample had levels ranging from 5.0 to 9.9μg/dl. Blood lead levels above 10μg/dl were recorded in 77 (25%) of the total sample. Within Nairobi, 32 (15.3%) of the study subjects in areas meant for assessment of environmental lead exposure had levels above the WHO/CDC action levels of 10μg/dl of blood. The mean BLL for the occupationally exposed (Ziwani Jua kali) was 22.6 ± 13.4μg/dl. Among the workers, 89% had BLLs above 10μg/dl. In general, 15% of the entire sample (for both environmental and occupational groups) in Nairobi had BLLs above 15μg/dl. The covariate group at Olkalou had a mean BLL of 1.3 ± 0.9μg/dl. Conclusion: The prevalence of environmental lead exposure to the general public is high in Nairobi compared to Olkalou where non exposure was reported. Occupational lead exposure has been identified to be at alarming levels and urgent intervention measures are recommended. East African Medical Journla Vol. 85 (6) 2008: pp. 284-29

Data Representativeness: Issues and Solutions

In its control programmes on maximum residue level compliance and exposure assessments, EFSA requires the participating countries to submit results, from specific numbers of food item samples, analyzed in the countries. These data are used to obtain estimates such as the proportion of samples exceeding the maximum residue limits, and the mean and maximum residue concentration per food item to assess exposure. An important consideration is the design and analysis of the programmes. In this report, we combine elements of survey sampling methodology, and statistical modeling, as a benchmark framework for the programmes, starting from the translation of research questions into statistical problems, to the statistical analysis and interpretation. Particular focus is placed on the issues that could affect the representativeness of the data, and remedial procedures are proposed. For example, in the absence of information on the sampling design, a sensitivity analysis, across a range of designs, is proposed. On the other hand, weighted generalized linear mixed models, and generalized linear mixed models combining both conjugate and normal random effects, are proposed, to address selection bias. Likelihood-based analysis methods are also proposed to address missing and censored data problems. Suggestions for improvements in the design and analysis of the programmes are also identified and discussed. For instance, incorporation of stratified sampling methodology, in determining both the total number, and the allocation of samples to the participating countries, is proposed. All through the report, statistical analysis models which properly take into account the hierarchical (and thus correlated) structure in which the data are collected are proposed

Investigating the inequalities in route to diagnosis amongst patients with diffuse large B-cell or follicular lymphoma in England

Introduction: Diagnostic delay is associated with lower chances of cancer survival. Underlying comorbidities are known to affect the timely diagnosis of cancer. Diffuse large B-cell (DLBCL) and follicular lymphomas (FL) are primarily diagnosed amongst older patients, who are more likely to have comorbidities. Characteristics of clinical commissioning groups (CCG) are also known to impact diagnostic delay. We assess the association between comorbidities and diagnostic delay amongst patients with DLBCL or FL in England during 2005–2013. Methods: Multivariable generalised linear mixed-effect models were used to assess the main association. Empirical Bayes estimates of the random effects were used to explore between-cluster variation. The latent normal joint modelling multiple imputation approach was used to account for partially observed variables. Results: We included 30,078 and 15,551 patients diagnosed with DLBCL or FL, respectively. Amongst patients from the same CCG, having multimorbidity was strongly associated with the emergency route to diagnosis (DLBCL: odds ratio 1.56, CI 1.40–1.73; FL: odds ratio 1.80, CI 1.45–2.23). Amongst DLBCL patients, the diagnostic delay was possibly correlated with CCGs that had higher population densities. Conclusions: Underlying comorbidity is associated with diagnostic delay amongst patients with DLBCL or FL. Results suggest a possible correlation between CCGs with higher population densities and diagnostic delay of aggressive lymphomas

Reference Ranges for Some Biochemical Parameters in Adult Kenyans

PURPOSE: To establish the reference ranges of some biochemical parameters for adult Kenyan population. METHODS: In a prospective involving 1100 healthy blood donors (age: 18-55 yr) in Kenyatta National Hospital, Kenya reference ranges of some biochemical analytes were constructed by using the parametric methods to estimate 2.5 and 97.5 percentiles of distribution. RESULTS: The reference ranges of the analytes were: alanine aminotransferase (ALT) [males (0-39) U/L, females (0-34) U/L]; aspartate aminotransferase (AST) [males (6-40) U/L, females (3-37) U/L]; alkaline phosphatase (ALP) [males (13-201) U/L, females (5-227) U/L]; albumin (ALB) [males (29-52) g/L, females (28-50) g/L]; protein (PROT) [males (57-89) g/L, females (56-88) g/L]; creatinine (CREAT) [males (59-127) μmol/L, females (54-122) μmol/L]; glucose (GLU) [males (2.8-6.8) mmol/L, females (2.6-7) mmol/L]; phosphorus (PHOS) [males (0.5-2.0) mmol/L, females (0.2-2.4) mmo/L]; potassium (POT) [males (3-5.3), females (3.1-5.1) mmo/L]; sodium (SOD) [males (111-153) mmol/L, females (117-151) mmol/L]; Blood urea nitrogen BUN [males (1.5-5.9) mmol/L, females (1.2-6.0) mmol/L] and Uric acid (UA) [males (120-458) μmol/L, females (89-415) μmol/L]. Age differences in the established reference ranges were observed in ALT, ALB, CREAT, ALP and UA in males and in ALT, ALB, and CREAT in females. Gender differences were observed in ALT, AST, ALB, CREAT and UA in the 18-28 yr old, ALT, AST, ALB, SOD and UA in 29-39 yr old and AST, ALB, and UA in 40-50 yr old. CONCLUSION: Age and sex specific reference ranges of some biochemical parameters were established some of which were different from those reported in literature. There therefore the need for each clinical chemistry laboratory to establish its own ranges. Keywords: Reference range, Biochemical parameter, Adult Kenyan, Kenyatta National Hospital

Analysis of hierarchical routine data with covariate missingness: effects of audit and feedback on clinicians' prescribed pediatric pneumonia care in Kenyan hospitals

Background: Routine clinical data are widely used in many countries to monitor quality of care. A limitation of routine data is missing information which occurs due to lack of documentation of care processes by health care providers, poor record keeping, or limited health care technology at facility level. Our objective was to address missing covariates while properly accounting for hierarchical structure in routine pediatric pneumonia care. Methods: We analyzed routine data collected during a cluster randomized trial to investigating the effect of audit and feedback (A&amp;F) over time on inpatient pneumonia care among children admitted in 12 Kenyan hospitals between March and November 2016. Six hospitals in the intervention arm received enhance A&amp;F on classification and treatment of pneumonia cases in addition to a standard A&amp;F report on general inpatient pediatric care. The remaining six in control arm received standard A&amp;F alone. We derived and analyzed a composite outcome known as Pediatric Admission Quality of Care (PAQC) score. In our analysis, we adjusted for patients, clinician and hospital level factors. Missing data occurred in patient and clinician level variables. We did multiple imputation of missing covariates within the joint model imputation framework. We fitted proportion odds random effects model and generalized estimating equation (GEE) models to the data before and after multilevel multiple imputation. Results: Overall, 2,299 children aged 2 to 59 months were admitted with childhood pneumonia in 12 hospitals during the trial period. 2,127 (92%) of the children (level 1) were admitted by 378 clinicians across the 12 hospitals. Enhanced A&amp;F led to improved inpatient pediatric pneumonia care over time compared to standard A&amp;F. Female clinicians and hospitals with low admission workload were associated with higher uptake of the new pneumonia guidelines during the trial period. In both random effects and marginal model, parameter estimates were biased and inefficient under complete case analysis. Conclusions: Enhanced A&amp;F improved the uptake of WHO recommended pediatric pneumonia guidelines over time compared to standard audit and feedback. When imputing missing data, it is important to account for the hierarchical structure to ensure compatibility with analysis models of interest to alleviate bias.</p

A characterization of missingness at random in a generalized shared-parameter joint modeling framework for longitudinal and time-to-event data, and sensitivity analysis

We consider a conceptual correspondence between the missing data setting, and joint modeling of longitudinal and time-to-event outcomes. Based on this, we formulate an extended shared random effects joint model. Based on this, we provide a characterization of missing at random, which is in line with that in the missing data setting. The ideas are illustrated using data from a study on liver cirrhosis, contrasting the new framework with conventional joint models

Handling missing data in modelling quality of clinician-prescribed routine care: sensitivity analysis of departure from missing at random assumption

Missing information is a major drawback in analyzing data collected in many routine health care settings. Multiple imputation assuming a missing at random mechanism is a popular method to handle missing data. The missing at random assumption cannot be confirmed from the observed data alone, hence the need for sensitivity analysis to assess robustness of inference. However, sensitivity analysis is rarely conducted and reported in practice. We analyzed routine paediatric data collected during a cluster randomized trial conducted in Kenyan hospitals. We imputed missing patient and clinician-level variables assuming the missing at random mechanism. We also imputed missing clinician-level variables assuming a missing not at random mechanism. We incorporated opinions from 15 clinical experts in the form of prior distributions and shift parameters in the delta adjustment method. An interaction between trial intervention arm and follow-up time, hospital, clinician and patient-level factors were included in a proportional odds random-effects analysis model. We performed these analyses using R functions derived from the jomo package. Parameter estimates from multiple imputation under the missing at random mechanism were similar to multiple imputation estimates assuming the missing not at random mechanism. Our inferences were insensitive to departures from the missing at random assumption using either the prior distributions or shift parameters sensitivity analysis approach