Patient Complexity: More Than Comorbidity. The Vector Model of Complexity

BACKGROUND: The conceptualization of patient complexity is just beginning in clinical medicine. OBJECTIVES: This study aims (1) to propose a conceptual approach to complex patients; (2) to demonstrate how this approach promotes achieving congruence between patient and provider, a critical step in the development of maximally effective treatment plans; and (3) to examine availability of evidence to guide trade-off decisions and assess healthcare quality for complex patients. METHODS/RESULTS: The Vector Model of Complexity portrays interactions between biological, socioeconomic, cultural, environmental and behavioral forces as health determinants. These forces are not easily discerned but exert profound influences on processes and outcomes of care for chronic medical conditions. Achieving congruence between patient, physician, and healthcare system is essential for effective, patient-centered care; requires assessment of all axes of the Vector Model; and, frequently, requires trade-off decisions to develop a tailored treatment plan. Most evidence-based guidelines rarely provide guidance for trade-off decisions. Quality measures often exclude complex patients and are not designed explicitly to assess their overall healthcare. CONCLUSIONS/RECOMMENDATIONS: We urgently need to expand the evidence base to inform the care of complex patients of all kinds, especially for the clinical trade-off decisions that are central to tailoring care. We offer long- and short-term strategies to begin to incorporate complexity into quality measurement and performance profiling, guided by the Vector Model. Interdisciplinary research should lay the foundation for a deeper understanding of the multiple sources of patient complexity and their interactions, and how provision of healthcare should be harmonized with complexity to optimize health

Molecular characterization and expression analysis of five different elongation factor 1 alpha genes in the flatfish Senegalese sole (Solea senegalensis Kaup): Differential gene expression and thyroid hormones dependence during metamorphosis

<p>Abstract</p> <p>Background</p> <p>Eukaryotic elongation factor 1 alpha (eEF1A) is one of the four subunits composing eukaryotic translation elongation factor 1. It catalyzes the binding of aminoacyl-tRNA to the A-site of the ribosome in a GTP-dependent manner during protein synthesis, although it also seems to play a role in other non-translational processes. Currently, little information is still available about its expression profile and regulation during flatfish metamorphosis. With regard to this, Senegalese sole (<it>Solea senegalensis</it>) is a commercially important flatfish in which <it>eEF1A </it>gene remains to be characterized.</p> <p>Results</p> <p>The development of large-scale genomics of Senegalese sole has facilitated the identification of five different <it>eEF1A </it>genes, referred to as <it>SseEF1A1</it>, <it>SseEF1A2</it>, <it>SseEF1A3</it>, <it>SseEF1A4</it>, and <it>Sse42Sp50</it>. Main characteristics and sequence identities with other fish and mammalian eEF1As are described. Phylogenetic and tissue expression analyses allowed for the identification of <it>SseEF1A1 </it>and <it>SseEF1A2 </it>as the Senegalese sole counterparts of mammalian <it>eEF1A1 </it>and <it>eEF1A2</it>, respectively, and of <it>Sse42Sp50 </it>as the ortholog of <it>Xenopus laevis </it>and teleost <it>42Sp50 </it>gene. The other two elongation factors, <it>SseEF1A3 </it>and <it>SseEF1A4</it>, represent novel genes that are mainly expressed in gills and skin. The expression profile of the five genes was also studied during larval development, revealing different behaviours. To study the possible regulation of <it>SseEF1A </it>gene expressions by thyroid hormones (THs), larvae were exposed to the goitrogen thiourea (TU). TU-treated larvae exhibited lower <it>SseEF1A4 </it>mRNA levels than untreated controls at both 11 and 15 days after treatment, whereas transcripts of the other four genes remained relatively unchanged. Moreover, addition of exogenous T4 hormone to TU-treated larvae increased significantly the steady-state levels of <it>SseEF1A4 </it>with respect to untreated controls, demonstrating that its expression is up-regulated by THs.</p> <p>Conclusion</p> <p>We have identified five different <it>eEF1A </it>genes in the Senegalese sole, referred to as <it>SseEF1A1</it>, <it>SseEF1A2</it>, <it>SseEF1A3</it>, <it>SseEF1A4</it>, and <it>Sse42Sp50</it>. The five genes exhibit different expression patterns in tissues and during larval development. TU and T4 treatments demonstrate that <it>SseEF1A4 </it>is up-regulated by THs, suggesting a role in the translational regulation of the factors involved in the dramatic changes that occurs during Senegalese sole metamorphosis.</p

Optimising monitoring efforts for secretive snakes: a comparison of occupancy and N-mixture models for assessment of population status

A fifth of reptiles are Data Deficient; many due to unknown population status. Monitoring snake populations can be demanding due to crypsis and low population densities, with insufficient recaptures for abundance estimation via Capture-Mark-Recapture. Alternatively, binomial N-mixture models enable abundance estimation from count data without individual identification, but have rarely been successfully applied to snake populations. We evaluated the suitability of occupancy and N-mixture methods for monitoring an insular population of grass snakes (Natrix helvetica) and considered covariates influencing detection, occupancy and abundance within remaining habitat. Snakes were elusive, with detectability increasing with survey effort (mean: 0.33 ± 0.06 s.e.m.). The probability of a transect being occupied was moderate (mean per kilometre: 0.44 ± 0.19 s.e.m.) and increased with transect length. Abundance estimates indicate a small threatened population associated to our transects (mean: 39, 95% CI: 20–169). Power analysis indicated that the survey effort required to detect occupancy declines would be prohibitive. Occupancy models fitted well, whereas N-mixture models showed poor fit, provided little extra information over occupancy models and were at greater risk of closure violation. Therefore we suggest occupancy models are more appropriate for monitoring snakes and other elusive species, but that population trends may go undetected

Biofluid Biomarkers in Huntington's Disease

Huntington's disease (HD) is a chronic progressive neurodegenerative condition where new markers of disease progression are needed. So far no disease-modifying interventions have been found, and few interventions have been proven to alleviate symptoms. This may be partially explained by the lack of reliable indicators of disease severity, progression, and phenotype.Biofluid biomarkers may bring advantages in addition to clinical measures, such as reliability, reproducibility, price, accuracy, and direct quantification of pathobiological processes at the molecular level; and in addition to empowering clinical trials, they have the potential to generate useful hypotheses for new drug development.In this chapter we review biofluid biomarker reports in HD, emphasizing those we feel are likely to be closest to clinical applicability