Abrupt vegetation change after the Late Quaternary megafaunal extinction in southeastern Australia

A substantial extinction of megafauna occurred in Australia between 50 and 45 kyr ago(1,2), a period that coincides with human colonization of Australia(3). Large shifts in vegetation also occurred around this time, but it is unclear whether the vegetation changes were driven by the human use of fire(4)-and thus contributed to the extinction event-or were a consequence of the loss of megafaunal grazers(5,6). Here we reconstruct past vegetation changes in southeastern Australia using the stable carbon isotopic composition of higher plant wax n-alkanes and levels of biomass burning from the accumulation rates of the biomarker levoglucosan from a well-dated sediment core offshore from the Murray-Darling Basin. We find that from 58 to 44 kyr ago, the abundance of plants with the C-4 carbon fixation pathway was generally high-between 60 and 70%. By 43 kyr ago, the abundance of C-4 plants dropped to 30% and biomass burning increased. This transient shift lasted for about 3,000 years and came after the period of human arrival and directly followed megafauna extinction at 48.9-43.6 kyr ago(1). We conclude that the vegetation shift was not the cause of the megafaunal extinction in this region. Instead, our data are consistent with the hypothesis that vegetation change was the consequence of the extinction of large browsers and led to the build-up of fire-prone vegetation in the Australian landscape

Prediction of hospitalization due to adverse drug reactions in elderly community-dwelling patients (The PADR-EC score)

© 2016 Parameswaran Nair et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Background Adverse drug reactions (ADRs) are the major cause of medication-related hospital admissions in older patients living in the community. This study aimed to develop and validate a score to predict ADR-related hospitalization in people aged =65 years. Methods ADR-related hospitalization and its risk factors were determined using a prospective, cross-sectional study in patients aged =65 years admitted to two hospitals. A predictive model was developed in the derivation cohort (n = 768) and the model was applied in the validation cohort (n = 240). ADR-related hospital admission was determined through expert consensus from comprehensive reviews of medical records and patient interviews. The causality and preventability of the ADR were assessed based on the Naranjo algorithm and modified Schumock and Thornton criteria, respectively. Results In the derivation sample (mean [±SD] age, 80.1±7.7 years), 115 (15%) patients were admitted due to a definite or probable ADR; 92.2% of these admissions were deemed preventable. The number of antihypertensives was the strongest predictor of an ADR followed by presence of dementia, renal failure, drug changes in the preceding 3 months and use of anticholinergic medications; these variables were used to derive the ADR prediction score. The predictive ability of the score, assessed from calculation of the area under the receiver operator characteristic (ROC) curve, was 0.70 (95% confidence interval (CI) 0.65-0.75). In the validation sample (mean [±SD] age, 79.6±7.6 years), 30 (12.5%) patients' admissions were related to definite or probable ADRs; 80% of these admissions were deemed preventable. The area under the ROC curve in this sample was 0.67 (95% CI 0.56-0.78). Conclusions This study proposes a practical and simple tool to identify elderly patients who are at an increased risk of preventable ADR-related hospital admission. Further refinement and testing of this tool is necessary to implement the score in clinical practice