An Overview of Chitosan Nanofibers and their Applications in the Drug Delivery Process

Chitosan is a polycationic natural polymer which is abundant in nature. Chitosan has gained much attention as natural polymer in the biomedical field. The up to date drug delivery as well as the nanotechnology in controlled release of drugs from chitosan nanofibers are focused in this review. Electrospinning is one of the most established and widely used techniques for preparing nanofibers. This method is versatile and efficient for the production of continuous nanofibers. The chitosan-based nanofibers are emerging materials in the arena of biomaterials. Recent studies revealed that various drugs such as antibiotics, chemotherapeutic agents, proteins and anti-inflammatory analgesic drugs were successfully loaded onto electrospun nanofibers. Chitosan nanofibers have several outstanding properties for different significant pharmaceutical applications such as wound dressing, tissue engineering, enzyme immobilization, and drug delivery systems. This review highlights different issues of chitosan nanofibers in drug delivery applications, starting from the preparation of chitosan nanofibers, followed by giving an idea about the biocompatibility and degradation of chitosan nanofibers, then describing how to load the drug into the nanofibers. Finally, the major applications of chitosan nanofibers in drug delivery systems

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