Purpose – The purpose of this paper is to present a bibliometric analysis of scientific output of the knowledge management (KM), the aim being to offer an overview of research activity in this field and characterize its most significant aspects. In addition, this study aims to quantitatively analyze KM research trends, forecasts, and citations from 1993 to 2012 in Web of Science (WOS). Design/methodology/approach – A total of 12,925 documents related to KM research were collected from following databases: Science Citation Index Expanded, Social Sciences Citation Index, Arts & Humanities Citation Index, Conference Proceedings Citation Index-Science, and Conference Proceedings Citation Index-Social Science & Humanities. These documents were carefully reviewed and subjected to bibliometric data analysis techniques. Findings – A number of research questions pertaining to patterns in scientific outputs, subject categories and major journals, author keywords frequencies, characteristics of the international collaboration, most cited papers and significant papers distribution of KM research were proposed and answered. In addition, there are five research sights on KM research are as follows: management science, computer science, information science, business, and engineering. Based on these findings, many implications emerged that improve one's understanding of the identity of KM as a distinct multi-discipline scientific field. Research limitations/implications – Comprehensiveness and inclusiveness of the analyzed KM-related data set in WOS because of some KM-centric journals are not indexed by Thomson Reuters. Originality/value – The paper offers an overview and evaluation of research activity into the KM viewed through the WOS during 1993-2012.

BackgroundGlycosylated hemoglobin A1C (HbA1c) has been widely recognized as a marker for predicting the severity of diabetes mellitus (DM) and several cardiovascular diseases. However, whether HbA1c could predict the severity and clinical outcomes in patients with stable coronary artery disease (CAD) remains largely unknown. We determine relationship of HbA1c with severity and outcome in patients with stable CAD.MethodsWe enrolled 1433 patients with stable angina who underwent coronary angiography and were followed up for an average 12 months. The patients were classified into three groups by tertiles of baseline HbA1c level (low group <5.7%, n = 483; intermediate group 5.7 - 6.3%, n = 512; high group >6.3%, n = 438). The relationships between the plasma HbA1c and severity of CAD and early clinical outcomes were evaluated.ResultsHigh HbA1c was associated with three-vessel disease. Area under the receivers operating characteristic curve (AUC = 0.67, 95% CI: 0.63-0.71, P < 0.001) and multivariate logistic regression analysis suggested that HbA1C was an independent predictor of severity of CAD (OR = 1.60, 95% CI: 1.29-1.99, P < 0.001) even after adjusting for gender, age, risk factor of CAD, lipid profile and fasting blood glucose. During follow-up, 133 patients underwent pre-specified outcomes. After adjusting for multiple variables in the Cox regression model, HbA1C remained to be an independent predictor of poor prognosis (HR = 1.28, 95% CI: 1.12-1.45, P < 0.001).ConclusionsWe concluded that high level of baseline HbA1c appeared to be an independent predictor for the severity of CAD and poor outcome in patients with stable CAD.