Investigation into the potential shortfall of skilled and experienced test and power technicians across the generation industry

The New Zealand Generation Industry is concerned there is going to be a potential shortage of Power Technicians whose skills are critical to the functioning of generation assets. The systemic nature of the situation is recognised in the development of a framework that is used as both a diagnostic of the current situation and as a platform for future management. The framework is a synthesis of the Perpetual Inventory Model, Total Quality Management, Manpower Planning best practice and Capability Maturity Assessment, with the associated governance considerations being further addressed through the Viable Systems Model and the responsibility alignment tool RASCI. The demographics of the current working population of Power Technicians were identified through the use of surveys and interviews. The results showed that there is an ageing cohort of Power Technicians in the South Island, especially within the Hydro-specific Power Technician resource pool. Recommendations have been made from both a short-term response to the current situation, as well as a long-t erm strategic response to ensure that management systems and business processes are in place to achieve the necessary and sustainable levels of Power Technicians across the industry

Interactions among genes in the ErbB-Neuregulin signalling network are associated with increased susceptibility to schizophrenia

<p>Abstract</p> <p>Background</p> <p>Evidence of genetic association between the NRG1 (Neuregulin-1) gene and schizophrenia is now well-documented. Furthermore, several recent reports suggest association between schizophrenia and single-nucleotide polymorphisms (SNPs) in ERBB4, one of the receptors for Neuregulin-1. In this study, we have extended the previously published associations by investigating the involvement of all eight genes from the ERBB and NRG families for association with schizophrenia.</p> <p>Methods</p> <p>Eight genes from the ERBB and NRG families were tested for association to schizophrenia using a collection of 396 cases and 1,342 blood bank controls ascertained from Aberdeen, UK. A total of 365 SNPs were tested. Association testing of both alleles and genotypes was carried out using the fast Fisher's Exact Test (FET). To understand better the nature of the associations, all pairs of SNPs separated by ≥ 0.5 cM with at least nominal evidence of association (<it>P </it>< 0.10) were tested for evidence of pairwise interaction by logistic regression analysis.</p> <p>Results</p> <p>42 out of 365 tested SNPs in the eight genes from the ERBB and NRG gene families were significantly associated with schizophrenia (<it>P </it>< 0.05). Associated SNPs were located in ERBB4 and NRG1, confirming earlier reports. However, novel associations were also seen in NRG2, NRG3 and EGFR. In pairwise interaction tests, clear evidence of gene-gene interaction was detected for NRG1-NRG2, NRG1-NRG3 and EGFR-NRG2, and suggestive evidence was also seen for ERBB4-NRG1, ERBB4-NRG2, ERBB4-NRG3 and ERBB4-ERBB2. Evidence of intragenic interaction was seen for SNPs in ERBB4.</p> <p>Conclusion</p> <p>These new findings suggest that observed associations between NRG1 and schizophrenia may be mediated through functional interaction not just with ERBB4, but with other members of the NRG and ERBB families. There is evidence that genetic interaction among these loci may increase susceptibility to schizophrenia.</p

Factors influencing longitudinal changes of circulating liver enzyme concentrations in subjects randomized to placebo in four clinical trials

Liver enzyme concentrations are measured as safety end points in clinical trials to detect drug-related hepatotoxicity, but little is known about the epidemiology of these biomarkers in subjects without hepatic dysfunction who are enrolled in drug trials. We studied alanine and aspartate aminotransferase (ALT and AST) in subjects randomized to placebo who completed assessments over 36 mo in a cardiovascular outcome trial [the Stabilisation of Atherosclerotic Plaque by Initiation of Darapladib Therapy ("STABILITY") trial; n = 4,264; mean age: 64.2 yr] or over 12 mo in three trials that enrolled only subjects with type 2 diabetes (T2D) [the DIA trials; n = 308; mean age: 62.4 yr] to investigate time-dependent relationships and the factors that might affect ALT and AST, including body mass index (BMI), T2D, and renal function. Multivariate linear mixed models examined time-dependent relationships between liver enzyme concentrations as response variables and BMI, baseline T2D status, hemoglobin A1clevels, and renal function, as explanatory variables. At baseline, ALT was higher in individuals who were men, 60 ml·min−1·1.73 m−2. ALT was not significantly associated with T2D at baseline, although it was positively associated with HbA1c. GFR had a greater impact on ALT than T2D. ALT concentrations decreased over time in subjects who lost weight but remained stable in individuals with increasing BMI. Weight change did not alter AST concentrations. We provide new insights on the influence of time, GFR, and HbA1con ALT and AST concentrations and confirm the effect of sex, age, T2D, BMI, and BMI change in subjects receiving placebo in clinical trials.NEW & NOTEWORTHY Clinical trials provide high-quality data on liver enzyme concentrations from subjects randomized to placebo that can be used to investigate the epidemiology of these biomarkers. The adjusted models show the influence of sex, age, time, renal function, type 2 diabetes, HbA1c, and body mass index on alanine aminotransferase and aspartate aminotransferase concentrations and their relative importance. These factors need to be considered when assessing potential signals of hepatotoxicity in trials of new drugs and in clinical trials investigating subjects with nonalcoholic fatty liver disease

Overcoming Time-Varying Confounding in Self-Controlled Case Series with Active Comparators: Application and Recommendations.

Confounding by indication is a key challenge for pharmacoepidemiologists. Although self-controlled study designs address time-invariant confounding, indications sometimes vary over time. For example, infection might act as a time-varying confounder in a study of antibiotics and uveitis, because it is time-limited and a direct cause both of receiving antibiotics and uveitis. Methods for incorporating active comparators in self-controlled studies to address such time-varying confounding by indication have only recently been developed. In this paper we formalize these methods, and provide a detailed description for how the active comparator rate ratio can be derived in a self-controlled case series (SCCS): either by explicitly comparing the regression coefficients for a drug of interest and an active comparator under certain circumstances using a simple ratio approach, or through the use of a nested regression model. The approaches are compared in two case studies, one examining the association between thiazolidinediones and fractures, and one examining the association between fluoroquinolones and uveitis using the UK Clinical Practice Research DataLink. Finally, we provide recommendations for the use of these methods, which we hope will support the design, execution and interpretation of SCCS using active comparators and thereby increase the robustness of pharmacoepidemiological studies

Pathway and network-based analysis of genome-wide association studies in multiple sclerosis

Genome-wide association studies (GWAS) testing several hundred thousand SNPs have been performed in multiple sclerosis (MS) and other complex diseases. Typically, the number of markers in which the evidence for association exceeds the genome-wide significance threshold is very small, and markers that do not exceed this threshold are generally neglected. Classical statistical analysis of these datasets in MS revealed genes with known immunological functions. However, many of the markers showing modest association may represent false negatives. We hypothesize that certain combinations of genes flagged by these markers can be identified if they belong to a common biological pathway. Here we conduct a pathway-oriented analysis of two GWAS in MS that takes into account all SNPs with nominal evidence of association (P < 0.05). Gene-wise P-values were superimposed on a human protein interaction network and searches were conducted to identify sub-networks containing a higher proportion of genes associated with MS than expected by chance. These sub-networks, and others generated at random as a control, were categorized for membership of biological pathways. GWAS from eight other diseases were analyzed to assess the specificity of the pathways identified. In the MS datasets, we identified sub-networks of genes from several immunological pathways including cell adhesion, communication and signaling. Remarkably, neural pathways, namely axon-guidance and synaptic potentiation, were also over-represented in MS. In addition to the immunological pathways previously identified, we report here for the first time the potential involvement of neural pathways in MS susceptibilit

Pathway and network-based analysis of genome-wide association studies in multiple sclerosis

Genome-wide association studies (GWAS) testing several hundred thousand SNPs have been performed in multiple sclerosis (MS) and other complex diseases. Typically, the number of markers in which the evidence for association exceeds the genome-wide significance threshold is very small, and markers that do not exceed this threshold are generally neglected. Classical statistical analysis of these datasets in MS revealed genes with known immunological functions. However, many of the markers showing modest association may represent false negatives. We hypothesize that certain combinations of genes flagged by these markers can be identified if they belong to a common biological pathway. Here we conduct a pathway-oriented analysis of two GWAS in MS that takes into account all SNPs with nominal evidence of association (P < 0.05). Gene-wise P-values were superimposed on a human protein interaction network and searches were conducted to identify sub-networks containing a higher proportion of genes associated with MS than expected by chance. These sub-networks, and others generated at random as a control, were categorized for membership of biological pathways. GWAS from eight other diseases were analyzed to assess the specificity of the pathways identified. In the MS datasets, we identified sub-networks of genes from several immunological pathways including cell adhesion, communication and signaling. Remarkably, neural pathways, namely axon-guidance and synaptic potentiation, were also over-represented in MS. In addition to the immunological pathways previously identified, we report here for the first time the potential involvement of neural pathways in MS susceptibility

An exploration of cognitive subgroups in Alzheimer's disease

Heterogeneity is observed in the patterns of cognition in Alzheimer's disease (AD). Such heterogeneity might suggest the involvement of different etiological pathways or different host responses to pathology. A total of 627 subjects with mild/moderate AD underwent cognitive assessment with the Mini-Mental State Examination (MMSE) and the Dementia Rating Scale-2 (DRS-2). Latent class analysis (LCA) was performed on cognition subscale data to identify and characterize cognitive subgroups. Clinical, demographic, and genetic factors were explored for association with class membership. LCA suggested the existence of four subgroups; one group with mild and another with severe global impairment across the cognitive domains, one group with primary impairments in attention and construction, and another group with primary deficits in memory and orientation. Education, disease duration, age, Apolipoprotein E-ε4 (APOE ε4) status, gender, presence of grasp reflex, white matter changes, and early or prominent visuospatial impairment were all associated with class membership. Our results support the existence of heterogeneity in patterns of cognitive impairment in AD. Our observation of classes characterized by predominant deficits in attention/construction and memory respectively deserves further exploration as does the association between membership in the attention/construction class and APOE ε4 negative status. (JINS, 2010, 16, 233-243.

Association Between Fluoroquinolone Use and Hospitalization With Aortic Aneurysm or Aortic Dissection.

IMPORTANCE: Fluoroquinolone use has been associated with increased hospitalization with aortic aneurysm or dissection in noninterventional studies, but the reason for this observed association is unclear. OBJECTIVE: To determine the association between fluoroquinolone use and aortic aneurysm or dissection using multiple study designs and multiple databases to increase the robustness of findings. DESIGN, SETTING, AND PARTICIPANTS: Cohort and case-crossover studies were conducted separately in 2 databases of UK primary care records. Clinical Practice Research Datalink Aurum and GOLD primary care records were linked to hospital admissions data. Adults with a systemic fluoroquinolone or cephalosporin prescription between April 1997 and December 2019 were included in the cohort study. Adults hospitalized with aortic aneurysm or dissection within the eligibility period were included in the case-crossover study. Individuals meeting inclusion criteria in the case-crossover study were matched 1:3 to control individuals on age, sex, index date, and clinical practice to adjust for calendar trends in prescribing. Data were analyzed from January to July 2022. EXPOSURES: Systemic fluoroquinolone or comparator antibiotic. MAIN OUTCOMES AND MEASURES: Hazard ratios (HRs) were estimated in the cohort study for the association between prescription of fluoroquinolones and hospitalization with aortic aneurysm or dissection using stabilized inverse probability of treatment-weighted Cox regression. Odds ratios (OR) were estimated in the case-crossover study for the association between systemic fluoroquinolone use and hospitalization with aortic aneurysm or dissection using a conditional logistic regression model. Estimates were pooled across databases using fixed-effects meta-analysis. RESULTS: In the cohort study, we identified 3 134 121 adults in Aurum (mean [SD] age, 52.5 [20.3] years; 1 969 257 [62.8%] female) and 452 086 in GOLD (mean [SD] age, 53.9 [20.2] years; 286 502 [63.4%] female) who were prescribed fluoroquinolones or cephalosporins. In crude analyses, fluoroquinolone relative to cephalosporin use was associated with increased hospitalization with aortic aneurysm or dissection (pooled HR, 1.28; 95% CI, 1.13-1.44; P < .001) but after adjustment for potential confounders, this association disappeared (pooled adjusted HR, 1.03; 95% CI, 0.91-1.17; P = .65). In the case-crossover study, we identified 84 841 individuals hospitalized with aortic aneurysm or dissection in Aurum (mean [SD] age, 75.5 [10.9]; 23 551 [27.8%] female) and 10 357 in GOLD (mean [SD] age, 75.6 [10.5]; 2809 [27.1%] female). Relative to nonuse, fluoroquinolone use was associated with an increase in hospitalization with aortic aneurysm or dissection, but no association was found relative to other antibiotics (vs cephalosporin pooled OR, 1.05; 95% CI, 0.87-1.27; vs trimethoprim, 0.89; 95% CI, 0.75-1.06; vs co-amoxiclav, 0.98; 95% CI, 0.82-1.18). CONCLUSIONS AND RELEVANCE: The results in this study suggest that estimates of association of fluoroquinolones with aortic aneurysm or dissection may be affected by confounding. When such confounding is accounted for, no association was evident, providing reassurance on the safety of fluoroquinolones with respect to aortic aneurysm or dissection

Quantifying possible bias in clinical and epidemiological studies with quantitative bias analysis: common approaches and limitations

Bias in epidemiological studies can adversely affect the validity of study findings. Sensitivity analyses, known as quantitative bias analyses, are available to quantify potential residual bias arising from measurement error, confounding, and selection into the study. Effective application of these methods benefits from the input of multiple parties including clinicians, epidemiologists, and statisticians. This article provides an overview of a few common methods to facilitate both the use of these methods and critical interpretation of applications in the published literature. Examples are given to describe and illustrate methods of quantitative bias analysis. This article also outlines considerations to be made when choosing between methods and discusses the limitations of quantitative bias analysis

Core Concepts in Pharmacoepidemiology: Quantitative Bias Analysis.

Pharmacoepidemiological studies provide important information on the safety and effectiveness of medications, but the validity of study findings can be threatened by residual bias. Ideally, biases would be minimized through appropriate study design and statistical analysis methods. However, residual biases can remain, for example, due to unmeasured confounders, measurement error, or selection into the study. A group of sensitivity analysis methods, termed quantitative bias analyses, are available to assess, quantitatively and transparently, the robustness of study results to these residual biases. These approaches include methods to quantify how the estimated effect would be altered under specified assumptions about the potential bias, and methods to calculate bounds on effect estimates. This article introduces quantitative bias analyses for unmeasured confounding, misclassification, and selection bias, with a focus on their relevance and application to pharmacoepidemiological studies