Exploratory Analysis of Methods for Automated Classification of Laboratory Test Orders into Syndromic Groups in Veterinary Medicine

Background

Recent focus on earlier detection of pathogen introduction in human and animal populations has led to the development of surveillance systems based on automated monitoring of health data. Real- or near real-time monitoring of pre-diagnostic data requires automated classification of records into syndromes–syndromic surveillance–using algorithms that incorporate medical knowledge in a reliable and efficient way, while remaining comprehensible to end users.

Methods

This paper describes the application of two of machine learning (Naïve Bayes and Decision Trees) and rule-based methods to extract syndromic information from laboratory test requests submitted to a veterinary diagnostic laboratory.

Results

High performance (F₁-macro = 0.9995) was achieved through the use of a rule-based syndrome classifier, based on rule induction followed by manual modification during the construction phase, which also resulted in clear interpretability of the resulting classification process. An unmodified rule induction algorithm achieved an F_1-micro score of 0.979 though this fell to 0.677 when performance for individual classes was averaged in an unweighted manner (F_1-macro), due to the fact that the algorithm failed to learn 3 of the 16 classes from the training set. Decision Trees showed equal interpretability to the rule-based approaches, but achieved an F_1-micro score of 0.923 (falling to 0.311 when classes are given equal weight). A Naïve Bayes classifier learned all classes and achieved high performance (F_1-micro = 0.994 and F_1-macro = .955), however the classification process is not transparent to the domain experts.

Conclusion

The use of a manually customised rule set allowed for the development of a system for classification of laboratory tests into syndromic groups with very high performance, and high interpretability by the domain experts. Further research is required to develop internal validation rules in order to establish automated methods to update model rules without user input.     

Modelling the cost-effectiveness of mass screening and treatment for reducing Plasmodium falciparum malaria burden

Background

Past experience and modelling suggest that, in most cases, mass treatment strategies are not likely to succeed in interrupting Plasmodium falciparum malaria transmission. However, this does not preclude their use to reduce disease burden. Mass screening and treatment (MSAT) is preferred to mass drug administration (MDA), as the latter involves massive over-use of drugs. This paper reports simulations of the incremental cost-effectiveness of well-conducted MSAT campaigns as a strategy for P. falciparum malaria disease-burden reduction in settings with varying receptivity (ability of the combined vector population in a setting to transmit disease) and access to case management.

Methods

MSAT incremental cost-effectiveness ratios (ICERs) were estimated in different sub-Saharan African settings using simulation models of the dynamics of malaria and a literature-based MSAT cost estimate. Imported infections were simulated at a rate of two per 1,000 population per annum. These estimates were compared to the ICERs of scaling up case management or insecticide-treated net (ITN) coverage in each baseline health system, in the absence of MSAT.

Results

MSAT averted most episodes, and resulted in the lowest ICERs, in settings with a moderate level of disease burden. At a low pre-intervention entomological inoculation rate (EIR) of two infectious bites per adult per annum (IBPAPA) MSAT was never more cost-effective than scaling up ITNs or case management coverage. However, at pre-intervention entomological inoculation rates (EIRs) of 20 and 50 IBPAPA and ITN coverage levels of 40 or 60%, respectively, the ICER of MSAT was similar to that of scaling up ITN coverage further.

Conclusions

In all the transmission settings considered, achieving a minimal level of ITN coverage is a “best buy”. At low transmission, MSAT probably is not worth considering. Instead, MSAT may be suitable at medium to high levels of transmission and at moderate ITN coverage. If undertaken as a burden-reducing intervention, MSAT should be continued indefinitely and should complement, not replace, case management and vector control interventions.     

Hybrid elementary flux analysis/nonparametric modeling: application for bioprocess control

Background  

The progress in the "-omic" sciences has allowed a deeper knowledge on many biological systems with industrial interest. This knowledge is still rarely used for advanced bioprocess monitoring and control at the bioreactor level. In this work, a bioprocess control method is presented, which is designed on the basis of the metabolic network of the organism under consideration. The bioprocess dynamics are formulated using hybrid rigorous/data driven systems and its inherent structure is defined by the metabolism elementary modes.     

SIRAC: Supervised Identification of Regions of Aberration in aCGH datasets

Background  

Array comparative genome hybridization (aCGH) provides information about genomic aberrations. Alterations in the DNA copy number may cause the cell to malfunction, leading to cancer. Therefore, the identification of DNA amplifications or deletions across tumors may reveal key genes involved in cancer and improve our understanding of the underlying biological processes associated with the disease.     

Interdependent MHC-DRB exon-plus-intron evolution in artiodactyls

Exon 2 sequences of an expressed MHC-DRB locus from sheep were examined for polymorphisms in both the antigen-binding regions and the adjacent intronic mixed simple tandem repeat. Twenty-one novel exon 2 Ovar-DRB alleles were identified. Short nucleotide motifs are extensively shared between certain exon 2 regions of Ovar-DRB alleles. The simple repeat variations, the number of different amino acids at usually polymorphic sites, and the number of silent substitutions were reduced in the intraspecies analyses of sheep DRB sequences, compared with those of cattle and goats. It was paradoxical that the abundance of different sheep alleles was similar to that of cattle and goats. This paradox may be explained by postulating a relatively small number of "ancient" alleles, with the present-day Ovar-DRB alleles being generated by reciprocal exchange of nucleotide motifs. At the antigen-binding sites, new combinations of amino acids were maintained in Ovar-DRB alleles by strong positive selection. In sheep--and less pronounced in goats and cattle--the DRB alleles can be divided into two groups. In one group, silent substitutions are increased when compared with the other. This suggests separate evolutionary pathways for certain groups of DRB alleles within a species. The simple repetitive sequences are also discussed with respect to the evolution of DRB alleles.      

Identification, Detection, and Spatial Resolution of Clostridium Populations Responsible for Cellulose Degradation in a Methanogenic Landfill Leachate Bioreactor

An anaerobic landfill leachate bioreactor was operated with crystalline cellulose and sterile landfill leachate until a steady state was reached. Cellulose hydrolysis, acidogenesis, and methanogenesis were measured. Microorganisms attached to the cellulose surfaces were hypothesized to be the cellulose hydrolyzers. 16S rRNA gene clone libraries were prepared from this attached fraction and also from the mixed fraction (biomass associated with cellulose particles and in the planktonic phase). Both clone libraries were dominated by Firmicutes phylum sequences (100% of the attached library and 90% of the mixed library), and the majority fell into one of five lineages of the clostridia. Clone group 1 (most closely related to Clostridium stercorarium), clone group 2 (most closely related to Clostridium thermocellum), and clone group 5 (most closely related to Bacteroides cellulosolvens) comprised sequences in Clostridium group III. Clone group 3 sequences were in Clostridium group XIVa (most closely related to Clostridium sp. strain XB90). Clone group 4 sequences were affiliated with a deeply branching clostridial lineage peripherally associated with Clostridium group VI. This monophyletic group comprises a new Clostridium cluster, designated cluster VIa. Specific fluorescence in situ hybridization (FISH) probes for the five groups were designed and synthesized, and it was demonstrated in FISH experiments that bacteria targeted by the probes for clone groups 1, 2, 4, and 5 were very abundant on the surfaces of the cellulose particles and likely the key cellulolytic microorganisms in the landfill bioreactor. The FISH probe for clone group 3 targeted cells in the planktonic phase, and these organisms were hypothesized to be glucose fermenters.     

The Association of Income with Health Behavior Change and Disease Monitoring among Patients with Chronic Disease

Background

Management of chronic diseases requires patients to adhere to recommended health behavior change and complete tests for monitoring. While studies have shown an association between low income and lack of adherence, the reasons why people with low income may be less likely to adhere are unclear. We sought to determine the association between household income and receipt of health behavior change advice, adherence to advice, receipt of recommended monitoring tests, and self-reported reasons for non-adherence/non-receipt.

Methods

We conducted a population-weighted survey, with 1849 respondents with cardiovascular-related chronic diseases (heart disease, hypertension, diabetes, stroke) from Western Canada (n = 1849). We used log-binomial regression to examine the association between household income and the outcome variables of interest: receipt of advice for and adherence to health behavior change (sodium reduction, dietary improvement, increased physical activity, smoking cessation, weight loss), reasons for non-adherence, receipt of recommended monitoring tests (cholesterol, blood glucose, blood pressure), and reasons for non-receipt of tests.

Results

Behavior change advice was received equally by both low and high income respondents. Low income respondents were more likely than those with high income to not adhere to recommendations regarding smoking cessation (adjusted prevalence rate ratio (PRR): 1.55, 95%CI: 1.09–2.20), and more likely to not receive measurements of blood cholesterol (PRR: 1.72, 95%CI 1.24–2.40) or glucose (PRR: 1.80, 95%CI: 1.26–2.58). Those with low income were less likely to state that non-adherence/non-receipt was due to personal choice, and more likely to state that it was due to an extrinsic factor, such as cost or lack of accessibility.

Conclusions

There are important income-related differences in the patterns of health behavior change and disease monitoring, as well as reasons for non-adherence or non-receipt. Among those with low income, adherence to health behavior change and monitoring may be improved by addressing modifiable barriers such as cost and access.