Response of Polynesian Arrowroot Tacca leontopetaloides to Fertilizer and Intra-Row Spacing at Garkawa

A field experiment was conducted at the Plateau State College of Agriculture, Garkawa to investigate the response of Polynesian arrowroot to fertilizer sources and intra-row spacing in 2011 and 2012 wet seasons.  Treatments consisted of three intra-row spacing (20, 25, 30cm) and five fertilizer sources (NPK, poultry manure, goat manure, cow dung and a control).These were factor ally combined and laid on a randomized complete block design with three replications. Polynesian arrowroot growth related characters (plant height, Leaf area) increased with decreased levels of intra-row spacing. Similarly, number of tillers/ha as well as fresh bulb weight kg/ha increased with decreased levels of intra-row spacing. The use of NPK fertilizer and poultry manure gave significant differences among all the fertilizer sources tried in both years. It is therefore concluded that among the intra-row spacing tried 20 and 25 cm were most appropriate, while among fertilizer sources tried NPK fertilizer and poultry manure were most appropriate. Keywords: Polynesian arrowroot, Fertilizer, Manure, Intra-row spacin

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