APACHE II Predicts Long-term Survival in COPD Patients Admitted to a General Medical Ward

OBJECTIVE: The Acute Physiology and Chronic Health Evaluation II (APACHE II) was developed to predict intensive-care unit (ICU) resource utilization. This study tested APACHE II's ability to predict long-term survival of patients with chronic obstructive pulmonary disease (COPD) admitted to general medical floors. DESIGN: We performed a retrospective cohort study of patients admitted for COPD exacerbation outside the ICU. APACHE II scores were calculated by chart review. Mortality was determined by the Social Security Death Index. We tested the association between APACHE II scores and long-term mortality with Cox regression and logistic regression. PATIENTS: The analysis included 92 patients admitted for COPD exacerbation in two Burlington, Vermont hospitals between January 1995 and June 1996. MEASUREMENTS AND MAIN RESULTS: In Cox regression, APACHE II score (hazard ratio [HR] 1.76 for each increase in a 3-level categorization, 95% confidence interval [CI] 1.16 to 2.65) and comorbidity (HR 2.58; 95% CI, 1.36 to 4.88) were associated with long-term mortality (P < .05) in the univariate analysis. After controlling for smoking history, comorbidity, and admission pCO(2), APACHE II score was independently associated with long-term mortality (HR 2.19; 95% CI, 1.27 to 3.80). In univariate logistic regression, APACHE II score (odds ratio [OR] 2.31; 95% confidence internal [CI] 1.24 to 4.30) and admission pCO(2) (OR 4.18; 95% CI, 1.15 to 15.21) were associated with death at 3 years. After controlling for smoking history, comorbidity, and admission pCO(2), APACHE II score was independently associated with death at 3 years (OR 2.62; 95% CI, 1.12 to 6.16). CONCLUSION: APACHE II score may be useful in predicting long-term mortality for COPD patients admitted outside the ICU

Molecular insights into a dinoflagellate bloom

In coastal waters worldwide, an increase in frequency and intensity of algal blooms has been attributed to eutrophication, with further increases predicted because of climate change. Yet, the cellular-level changes that occur in blooming algae remain largely unknown. Comparative metatranscriptomics was used to investigate the underlying molecular mechanisms associated with a dinoflagellate bloom in a eutrophied estuary. Here we show that under bloom conditions, there is increased expression of metabolic pathways indicative of rapidly growing cells, including energy production, carbon metabolism, transporters and synthesis of cellular membrane components. In addition, there is a prominence of highly expressed genes involved in the synthesis of membrane-associated molecules, including those for the production of glycosaminoglycans (GAGs), which may serve roles in nutrient acquisition and/or cell surface adhesion. Biotin and thiamine synthesis genes also increased expression along with several cobalamin biosynthesis-associated genes, suggesting processing of B(12) intermediates by dinoflagellates. The patterns in gene expression observed are consistent with bloom-forming dinoflagellates eliciting a cellular response to elevated nutrient demands and to promote interactions with their surrounding bacterial consortia, possibly in an effort to cultivate for enhancement of vitamin and nutrient exchanges and/or direct consumption. Our findings provide potential molecular targets for bloom characterization and management efforts

The effect of sampling effort on spatial autocorrelation in macrobenthic intertidal invertebrates

The importance of sampling effort in the statistical exploration of spatial autocorrelation is demonstrated for benthic macroinvertebrate assemblages within the intertidal warm-temperate Knysna estuary, South Africa. While the role of spatial scale in determining autocorrelation patterns in ecological populations has been noted, the effects of changing sampling effort (e.g., sample size) have rarely been explored; neither have the nature of any changes with sample size. Invertebrate assemblages were sampled from a single grid lattice comprised of 48 sampling stations at four sample sizes (0.0015, 0.0026, 0.0054 and 0.01 m ). Four metrics were investigated: assemblage abundance, frequency (species density), and numbers of the two most abundant species in the area Simplisetia erythraeensis and Prionospio sexoculata. Spatial autocorrelation was estimated for each sample size from the global Moran’s I. For a range of distance classes, Moran’s I correlograms were constructed, these plotted autocorrelation estimates as a function of the separation distance between point samples. Spatial autocorrelation was present in three of the metrics (assemblage abundance frequency and Prionospio abundance), but not for Simplisetia abundance. The estimated magnitude of spatial autocorrelation varied across sampling units for all four assemblage and species metrics (global Moran’s I ranged from 0.5 to − 0.07). Correlograms indicated that optimal sampling interval distances fell in the region of 8 m for Simplisetia and 19 m for the remaining three metrics. These distances indicate the dimensions of the processes (both biotic and abiotic) that determine spatial patterning in the microbenthic intertidal invertebrates sampled.