Multiple stressors produce differential transcriptomic patterns in a stream-dwelling salamander.

BACKGROUND: Global biodiversity is decreasing at an alarming rate and amphibians are at the forefront of this crisis. Understanding the factors that negatively impact amphibian populations and effectively monitoring their health are fundamental to addressing this epidemic. Plasma glucocorticoids are often used to assess stress in amphibians and other vertebrates, but these hormones can be extremely dynamic and impractical to quantify in small organisms. Transcriptomic responses to stress hormones in amphibians have been largely limited to laboratory models, and there have been few studies on vertebrates that have evaluated the impact of multiple stressors on patterns of gene expression. Here we examined the gene expression patterns in tail tissues of stream-dwelling salamanders (Eurycea tynerensis) chronically exposed to the stress hormone corticosterone under different temperature regimes. RESULTS: We found unique transcriptional signatures for chronic corticosterone exposure that were independent of temperature variation. Several of the corticosterone responsive genes are known to be involved in immune system response (LY-6E), oxidative stress (GSTM2 and TRX), and tissue repair (A2M and FX). We also found many genes to be influenced by temperature (CIRBP, HSC71, HSP40, HSP90, HSP70, ZNF593). Furthermore, the expression patterns of some genes (GSTM2, LY-6E, UMOD, ZNF593, CIRBP, HSP90) show interactive effects of temperature and corticosterone exposure, compared to each treatment alone. Through a series of experiments we also showed that stressor induced patterns of expression were largely consistent across ages, life cycle modes, and tissue regeneration. CONCLUSIONS: Outside of thermal stressors, the application of transcriptomes to monitor the health of non-human vertebrate systems has been vastly underinvestigated. Our study suggests that transcriptomic patterns harbor stressor specific signatures that can be highly informative for monitoring the diverse stressors of amphibian populations.

Integrating Multiple Distribution Models to Guide Conservation Efforts of an Endangered Toad.

Species distribution models are used for numerous purposes such as predicting changes in species' ranges and identifying biodiversity hotspots. Although implications of distribution models for conservation are often implicit, few studies use these tools explicitly to inform conservation efforts. Herein, we illustrate how multiple distribution models developed using distinct sets of environmental variables can be integrated to aid in identification sites for use in conservation. We focus on the endangered arroyo toad (Anaxyrus californicus), which relies on open, sandy streams and surrounding floodplains in southern California, USA, and northern Baja California, Mexico. Declines of the species are largely attributed to habitat degradation associated with vegetation encroachment, invasive predators, and altered hydrologic regimes. We had three main goals: 1) develop a model of potential habitat for arroyo toads, based on long-term environmental variables and all available locality data; 2) develop a model of the species' current habitat by incorporating recent remotely-sensed variables and only using recent locality data; and 3) integrate results of both models to identify sites that may be employed in conservation efforts. We used a machine learning technique, Random Forests, to develop the models, focused on riparian zones in southern California. We identified 14.37% and 10.50% of our study area as potential and current habitat for the arroyo toad, respectively. Generally, inclusion of remotely-sensed variables reduced modeled suitability of sites, thus many areas modeled as potential habitat were not modeled as current habitat. We propose such sites could be made suitable for arroyo toads through active management, increasing current habitat by up to 67.02%. Our general approach can be employed to guide conservation efforts of virtually any species with sufficient data necessary to develop appropriate distribution models.

Species distribution modelling for conservation of an endangered endemic orchid.

Concerns regarding the long-term viability of threatened and endangered plant species are increasingly warranted given the potential impacts of climate change and habitat fragmentation on unstable and isolated populations. Orchidaceae is the largest and most diverse family of flowering plants, but it is currently facing unprecedented risks of extinction. Despite substantial conservation emphasis on rare orchids, populations continue to decline. Spiranthes parksii (Navasota ladies' tresses) is a federally and state-listed endangered terrestrial orchid endemic to central Texas. Hence, we aimed to identify potential factors influencing the distribution of the species, quantify the relative importance of each factor and determine suitable habitat for future surveys and targeted conservation efforts. We analysed several geo-referenced variables describing climatic conditions and landscape features to identify potential factors influencing the likelihood of occurrence of S. parksii using boosted regression trees. Our model classified 97 % of the cells correctly with regard to species presence and absence, and indicated that probability of existence was correlated with climatic conditions and landscape features. The most influential variables were mean annual precipitation, mean elevation, mean annual minimum temperature and mean annual maximum temperature. The most likely suitable range for S. parksii was the eastern portions of Leon and Madison Counties, the southern portion of Brazos County, a portion of northern Grimes County and along the borders between Burleson and Washington Counties. Our model can assist in the development of an integrated conservation strategy through: (i) focussing future survey and research efforts on areas with a high likelihood of occurrence, (ii) aiding in selection of areas for conservation and restoration and (iii) framing future research questions including those necessary for predicting responses to climate change. Our model could also incorporate new information on S. parksii as it becomes available to improve prediction accuracy, and our methodology could be adapted to develop distribution maps for other rare species of conservation concern.

Early discontinuation and restart of insulin in the treatment of type 2 diabetes mellitus.

INTRODUCTION: Although the largest improvement in glycemic control occurs within the first 90 days of insulin therapy, little is known about early persistence on insulin therapy. This research aimed to identify predictors of early discontinuation and of subsequent restart of basal or mixture insulin among patients with type 2 diabetes mellitus (T2DM) and to assess the economic cost associated with such behaviors over a 1-year period. METHODS: Truven's Health Analytics Commercial Claims and Encounters database was utilized for the study. Logistic regressions were used to examine factors associated with early discontinuation of insulin (basal or mixture) and, among patients who discontinued early, the factors associated with restarting. Cost regressions were estimated using generalized linear models with a gamma distribution and logistic link. Kaplan-Meier survival curves were used to examine time to discontinuation and time to restart among those who discontinued. RESULTS: Multivariate analyses revealed that patient characteristics, prior healthcare resource utilization, comorbid diagnoses, and type of initiated insulin were associated with early discontinuation of insulin and of restarting among patients who discontinued early. Acute care (hospitalization and emergency room) costs were 9.6% higher among patients who discontinued early (P < 0.001), although outpatient, drug, and total costs were significantly lower among individuals who discontinued early. Among the early discontinuation subgroup, restarting insulin was associated with higher costs. Specifically: 11.3% higher acute care costs (P < 0.001), 24.0% higher outpatient costs (P < 0.001), 80.2% higher drug costs (P < 0.001), and 30.3% higher total costs (P < 0.001), compared to patients who discontinued early but did not restart insulin therapy in the 1-year post-period. CONCLUSION: Among patients with T2DM who were initiated on insulin therapy, early discontinuation of insulin and its subsequent restart were associated with significantly higher acute care costs, which may signal a more complex and challenging subgroup of patients who tend to be less engaged in outpatient care and may have poorer long-term outcomes.

Change in healthcare utilization and costs following initiation of benzodiazepine therapy for long-term treatment of generalized anxiety disorder: a retrospective cohort study.

BACKGROUND: Selective serotonin reuptake inhibitors, serotonin-norepinephrine reuptake inhibitors, and benzodiazepine anxiolytics are used in the US to treat generalized anxiety disorder (GAD). While benzodiazepines typically provide rapid symptomatic relief, long-term use is not recommended due to risks of dependency, sedation, falls, and accidents. METHODS: Using a US health insurance database, we identified all persons with GAD (ICD-9-CM diagnosis code 300.02) who began a long-term course of treatment (≥ 90 days) with a benzodiazepine anxiolytic between 1/1/2003 and 12/31/2007, We compared healthcare utilization and costs over the six-month periods preceding and following the date of treatment initiation ("pretreatment" and "post-treatment", respectively), and focused attention on accident-related encounters (e.g., for treatment of fractures) and care received for other reasons possibly related benzodiazepine use (e.g., sedation, dizziness). RESULTS: A total of 866 patients met all study entry criteria; 25% of patients began treatment on an add-on basis (i.e., adjunctive to escitalopram, paroxetine, sertraline, or venlafaxine), while 75% of patients did not receive concomitant therapy. Mean total healthcare costs increased by $2334 between the pretreatment and post-treatment periods (from $4637 [SD=$9840] to $6971 [$17,002]; p<0.01); costs of accident-related encounters and other care that was possibly related to use of benzodiazepines increased by an average of $1099 ($1757 [$7656] vs $2856 [$14,836]; p=0.03). CONCLUSIONS: Healthcare costs increase in patients with GAD beginning long-term (≥ 90 days) treatment with a benzodiazepine anxiolytic; a substantial proportion of this increase is attributable to care associated with accidents and other known sequelae of long-term benzodiazepine use.

Road to the nursing home: costs and disease progression among medicare beneficiaries with ADRD.

OBJECTIVES: To estimate long-term care costs and disease progression among Medicare beneficiaries aged 65+ with ADRD. METHODS: Retrospective analysis of Medicare Part A claims and nursing home (NH) Minimum Data Set (MDS) records among beneficiaries 1999-2007. Expenditures were grouped into 3 periods; PRE, events occurring between date of ADRD diagnosis, before first NH admission; PERI, from first NH admission to at least 100 days; and, PERM, after 120 days. Utilization and reimbursements were computed for each period. RESULTS: Demographics of the3,681,702 ADRD beneficiaries showed average age of 83 (+/-7), female (67.7%) and white (87.4%). Medicare reimbursements per person increased by 58% from the PRE ($47,912) to PERM period ($75,654). Age, ethnicity, gender (male), and comorbidities were significantly related to total reimbursements in each phase. CONCLUSIONS: Applying a taxonomy of NH phases, Medicare expenditures per person year are higher among patients in their terminal phase and higher still with comorbidities.

Development of a next day functioning measure to assess the impact of sleep disturbance due to restless legs syndrome: the restless legs syndrome-next day impact questionnaire.

OBJECTIVES: Symptoms of Restless Legs Syndrome (RLS) affect patients' quality and duration of sleep, which can have next day sequelae detrimental to daytime performance. To date, no measure sufficiently assesses such sequelae. This study aimed to develop a new self-reported outcome measure to assess the impact of disturbed sleep due to RLS on next day functioning and to support its content validity. METHODS: The development of the Restless Legs Syndrome-Next Day Impact (RLS-NDI) questionnaire included concept elicitation interviews with RLS patients in the United States (n=20); grounded theory data collection and analysis methods; and review by clinical and measurement experts to generate items, responses, and instructions. Cognitive interviews (n=15) were conducted to ensure understanding of the RLS-NDI, concept comprehensiveness, and identification of any necessary item revisions. RESULTS: Impacts on next day functioning attributed to disturbed sleep due to RLS symptoms included activities of daily living (i.e., work, household chores), cognitive functioning (i.e., concentration, forgetfulness, mental tiredness, alertness), emotional functioning (i.e., irritability, depressed mood), physical functioning (i.e., physical tiredness, active leisure activities), energy, daytime sleepiness, and social functioning (i.e., relationships, social activities/situations). The final measure consists of 14 items assessed "today" and rated on a numeric rating scale. CONCLUSIONS: The RLS-NDI is an evaluative tool with demonstrated content validity.

Measurement of non-restorative sleep in insomnia: A review of the literature.

OBJECTIVE: Non-restorative sleep (NRS) is a core symptom of insomnia, typically defined as a subjective feeling of being unrefreshed upon awakening. NRS symptoms have been less consistently studied than other symptoms of insomnia, and there is no consensus regarding measurement of NRS. Given its subjective nature, patient-reported outcome (PRO) instruments are important for evaluating NRS symptom severity and treatment-related changes. The objective of this literature review was to identify PROs used in insomnia populations that purport to measure NRS, and to evaluate their psychometric characteristics. METHODS: A comprehensive review of PRO instruments used in insomnia was conducted; instruments were reviewed for NRS content by two independent reviewers; a total of 26 instruments identified to contain NRS content were retained for further review. RESULTS: Of the 26 instruments reviewed, 23 contained at least one item evaluating subjective nighttime aspects of NRS; 17 contained at least one item evaluating daytime aspects of NRS. Only the Sleep Assessment Questionnaire contained a specific NRS domain score. However, little published evidence was available regarding measurement properties of the NRS domain in insomnia populations. CONCLUSIONS: There is currently no reliable and well-validated PRO instrument available for specifically evaluating NRS symptom severity and response to interventions in insomnia populations. Reliable and valid measurement tools are needed to measure the symptom of NRS in insomnia.

What do we know about quality of life in dementia? A review of the emerging evidence on the predictive and explanatory value of disease specific measures of health related quality of life in people with dementia.

OBJECTIVE: Given its complexity, there is growing consensus on the need to measure patient-rated broad outcomes like health-related quality of life (HRQL) as well as discrete functions like cognition and behaviour in dementia. This review brings together current data on the distribution, determinants and course of HRQL in dementia to investigate the predictive and explanatory value of measures of HRQL in people with dementia. DESIGN: A systematic review of papers in English published up to October 2007 to identify data on the use of disease-specific measures of HRQL in dementia. RESULTS: There are no clear or consistent associations between socio-demographic variables and HRQL. There is no convincing evidence that lower cognition or greater activity limitation is associated with lower HRQL. There is a strong suggestion that depression is consistently associated with decreased HRQL in dementia. However, the magnitude of the associations observed is moderate only and the proportion of variance explained is low suggesting that depression and HRQL are different constructs. We currently know almost nothing about the natural history of HRQL in dementia or what attributes or interventions promote or inhibit HRQL life for people with dementia. CONCLUSIONS: While in other illnesses there may be simple association between HRQL and an easily measurable clinical variable, in dementia this is not so. There are now instruments available with which to measure disease-specific HRQL directly in clinical trials and other studies that can yield informative data.

Depression status, medical comorbidity and resource costs. Evidence from an international study of major depression in primary care (LIDO).

BACKGROUND: Despite the burden of depression, there remain few data on its economic consequences in an international context. AIMS: To explore the relationship between depression status (with and without medical comorbidity), work loss and health care costs, using cross-sectional data from a multi-national study of depression in primary care. METHOD: Primary care attendees were screened for depression. Those meeting eligibility criteria were categorised according to DSM-IV criteria for major depressive disorder and comorbid status. Unit costs were attached to self-reported days absent from work and uptake of health care services. RESULTS: Medical comorbidity was associated with a 17-46% increase in health care costs in five of the six sites, but a clear positive association between costs and clinical depression status was identified in only one site. CONCLUSIONS: The economic consequences of depression are influenced to a greater (and considerable) extent by the presence of medical comorbidity than by symptom severity alone.

Course of depression, health services costs, and work productivity in an international primary care study.

The Longitudinal Investigation of Depression Outcomes (LIDO) Study examined the outcomes and economic correlates of previously untreated depression among primary care patients in Barcelona, Spain; Be'er Sheva, Israel; Melbourne, Australia; Porto Alegre, Brazil; St. Petersburg, Russia; and Seattle, USA. Across all sites, 968 patients with current depressive disorder completed assessments of depression severity (Composite International Diagnostic Interview and Center for Epidemiologic Studies Depression Scale) at baseline and 9 months, and assessments of health services utilization and work days missed at baseline, 9 months, and 12 months. Follow-up depression status was characterized as persistent depression (n=345), partial remission (n=283), or full remission (n=340). At each site, patients with more favorable depression outcomes had fewer days missed from work; however, this relationship did not reach the 5% level of statistical significance at any site, and reached the 10% significance level only at Porto Alegre. Patients with more favorable depression outcomes also had lower health services costs, but this relationship reached the 5% significance level only in St. Petersburg. While the lack of statistical precision does not permit definitive conclusions, our findings are consistent with recent studies showing that recovery from depression is associated with lower health services costs and less time missed from work due to illness.