High-frequency variability of bacterioplankton in response to environmental drivers in Red Sea coastal waters

Autotrophic and heterotrophic bacterioplankton are essential to the biogeochemistry of tropical ecosystems. However, the processes that govern their dynamics are not well known. We provide here a high-frequency assessment of bacterial community dynamics and concurrent environmental factors in Red Sea coastal waters. Weekly sampling of surface samples during a full annual cycle at an enclosed station revealed high variability in ecological conditions, which reflected in changes of major bacterioplankton communities. Temperature varied between 23 and 34°C during the sampling period. Autotrophic (Synechococcus, 1.7–16.2 × 104 cells mL−1) and heterotrophic bacteria (1.6–4.3 × 105 cells mL−1) showed two maxima in abundance in spring and summer, while minima were found in winter and autumn. Heterotrophic cells with high nucleic acid content (HNA) peaked in July, but their contribution to the total cell counts (35–60%) did not show a clear seasonal pattern. Actively respiring cells (CTC+) contributed between 4 and 51% of the total number of heterotrophic bacteria, while live cells (with intact membrane) consistently accounted for over 90%. Sequenced 16S rRNA amplicons revealed a predominance of Proteobacteria in summer and autumn (>40%) and a smaller contribution in winter (21–24%), with members of the Alphaproteobacteria class dominating throughout the year. The contribution of the Flavobacteriaceae family was highest in winter (21%), while the Rhodobacteraceae contribution was lowest (6%). Temperature, chlorophyll-a, and dissolved organic carbon concentration were the environmental variables with the greatest effects on bacterial abundance and diversity patterns

The ASOS Surgical Risk Calculator: development and validation of a tool for identifying African surgical patients at risk of severe postoperative complications

Background: The African Surgical Outcomes Study (ASOS) showed that surgical patients in Africa have a mortality twice the global average. Existing risk assessment tools are not valid for use in this population because the pattern of risk for poor outcomes differs from high-income countries. The objective of this study was to derive and validate a simple, preoperative risk stratification tool to identify African surgical patients at risk for in-hospital postoperative mortality and severe complications. Methods: ASOS was a 7-day prospective cohort study of adult patients undergoing surgery in Africa. The ASOS Surgical Risk Calculator was constructed with a multivariable logistic regression model for the outcome of in-hospital mortality and severe postoperative complications. The following preoperative risk factors were entered into the model; age, sex, smoking status, ASA physical status, preoperative chronic comorbid conditions, indication for surgery, urgency, severity, and type of surgery. Results: The model was derived from 8799 patients from 168 African hospitals. The composite outcome of severe postoperative complications and death occurred in 423/8799 (4.8%) patients. The ASOS Surgical Risk Calculator includes the following risk factors: age, ASA physical status, indication for surgery, urgency, severity, and type of surgery. The model showed good discrimination with an area under the receiver operating characteristic curve of 0.805 and good calibration with c-statistic corrected for optimism of 0.784. Conclusions: This simple preoperative risk calculator could be used to identify high-risk surgical patients in African hospitals and facilitate increased postoperative surveillance. © 2018 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.Medical Research Council of South Africa gran