SummaryBackgroundSurgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world.MethodsThis international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231.FindingsBetween Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p<0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p<0·001).InterpretationCountries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication.FundingDFID-MRC-Wellcome Trust Joint Global Health Trial Development Grant,...
Purpose – The purpose of present study is to explore the linkages among Intellectual Capital (IC), Corporate Governance (CG) and Corporate Social Responsibility (CSR) through direct and indirect empirical inquiry. Design/methodology/approach – The main setting is designed for exploring the relationship among IC, CG and CSR. Therefore, these three constructs are examined directly in which their statistical relation is evaluated among themselves and indirectly in which their possible effects are examined onto firms’ unsystematic factors such as cash flow, short-term solvency, long-term solvency, profitability and asset utilization. Findings – Empirical investigation is conducted on manufacturing firms listed in Istanbul Stock Exchange from 2007 to 2011. Empirical results do support a positive relationship among these important constructs. Research limitations/implications – The empirical research is carried out in manufacturing firms only. Originality/value – IC, CG and CSR are three demanding research areas to study. This is the first attempt here to examine their possible linkages based on so-called direct and indirect empirical inquiries. The primary reason behind this attempt is that these concepts are assumed to be important for all stakeholders.
The devastating Japan earthquake (magnitude 9.0) and tsunami (39-metre high) of 2011, also called the Great Tohoku or Sendai earthquake, was a record-breaker natural disaster causing enormous damage and a nuclear meltdown at Fukushima nuclear power plant. This paper attempts to analyse the long and short run effects of this record-breaking natural disaster on the Japanese equity, debt and FX markets as well as Gold as one of the most popular metals and investment options, using daily data. A variance bound test proposed by Fakhry & Richter (2018) underpinned by the C-GARCH-t model of volatility is adopted. The results seem to indicate that the natural disaster influenced the efficiency of the market in the immediate terms more than the long term. In a global financial market where the key is competitiveness, it is essential to analyse the efficiency and therefore stability of the Japanese financial market. Therefore, analysing the impact of the natural disaster on the competitiveness of the Japanese financial market.
SUMMARY Default modelling is a general term used for several interrelated fields of risk management. Bond defaults, credit (loan) defaults, firm defaults and country defaults are examples of this kind. The scope and reason for existence of this study is to focus mainly on firm default. The purpose of this review is to shed light on the development and evaluation of the models proposed for predicting bankruptcy in terms of conceptualization, country distribution, sector specification, time dimension, variables used and findings reported. The current review includes firm default studies published in business fields such as accounting, economics, finance and management science. This review is distinct in that it seeks (i) to give a comprehensive examination of the models, (ii) to compare and contrast the features of the models and (iii) to show with a solid argument where future research should be focused. Copyright © 2013 John Wiley & Sons, Ltd.
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