5 research outputs found
Are the Asian Equity Markets more Interdependent after the Financial Crisis?
This paper examines the impact of the 1997 Asian Financial Crisis on the linkages between the Singapore and five Asian-Pacific stock markets. We show that the interdependence between these markets has intensified after the crisis. Before the crisis, only the Malaysian stock market is found to be cointegrated with Singapore. However, after the onset of the crisis, the stock markets of Hong Kong, Japan, Malaysia and the US are found to be cointegrated with the Singapore stock market.
Applying non-linear dynamics in the Singapore stock market using Chaos theory
The question of whether the Stock Exchange of Singapore (SES) is weak-form efficient under the Efficient Market Hypothesis (EMH) has been a topic of much debate. Although various tests have been conducted to verify its efficiency, they have yielded inconclusive and mixed results. The problem may lie in the fault of the models used and their simplifying assumptions. All the current tests for weak form efficiency are based on the linear model, which we will show may be invalid to be used for analysing the capital markets, since capital markets are non-linear in nature.BUSINES
Pioneering Arterial Hypertension Phenotyping on Nationally Aggregated Electronic Health Records
Background: Hypertension is frequently studied in epidemiological studies that have been conducted using retrospective observational data, either as an outcome or a variable. However, there are few validation studies investigating the accuracy of hypertension phenotyping algorithms in aggregated electronic health record (EHR) data. Methods: Utilizing a centralized repository of inpatient EHR data from Singapore for the period of 2019–2020, a new algorithm that incorporates both diagnostic codes and medication details (Diag+Med) was devised. This algorithm was intended to supplement and improve the diagnostic code-only model (Diag-Only) for the classification of hypertension. We computed various metrics (sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV)) to assess the algorithm’s effectiveness in identifying hypertension on 2813 chart-reviewed records. This pool was composed of two patient cohorts: a random sampling of all inpatient admissions (Random Cohort) and a targeted group with atrial fibrillation diagnoses (AF Cohort). Results: The Diag+Med algorithm was more sensitive at detecting hypertension patients in both cohorts compared to the Diag-Only algorithm (83.8 and 87.6% vs. 68.2 and 66.5% in the Random and AF Cohorts, respectively). These improvements in sensitivity came at minimal costs in terms of PPV reductions (88.2 and 90.3% vs. 91.4 and 94.2%, respectively). Conclusion: The combined use of diagnosis codes and specific antihypertension medication exposure patterns facilitates a more accurate capture of patients with hypertension in a database of aggregated EHRs from diverse healthcare institutions in Singapore. The results presented here allow for the bias correction of risk estimates derived from observational studies involving hypertension
Phenotyping Diabetes Mellitus on Aggregated Electronic Health Records from Disparate Health Systems
Background: Identifying patients with diabetes mellitus (DM) is often performed in epidemiological studies using electronic health records (EHR), but currently available algorithms have features that limit their generalizability. Methods: We developed a rule-based algorithm to determine DM status using the nationally aggregated EHR database. The algorithm was validated on two chart-reviewed samples (n = 2813) of (a) patients with atrial fibrillation (AF, n = 1194) and (b) randomly sampled hospitalized patients (n = 1619). Results: DM diagnosis codes alone resulted in a sensitivity of 77.0% and 83.4% in the AF and random hospitalized samples, respectively. The proposed algorithm combines blood glucose values and DM medication usage with diagnostic codes and exhibits sensitivities between 96.9% and 98.0%, while positive predictive values (PPV) ranged between 61.1% and 75.6%. Performances were comparable across sexes, but a lower specificity was observed in younger patients (below 65 versus 65 and above) in both validation samples (75.8% vs. 90.8% and 60.6% vs. 88.8%). The algorithm was robust for missing laboratory data but not for missing medication data. Conclusions: In this nationwide EHR database analysis, an algorithm for identifying patients with DM has been developed and validated. The algorithm supports quantitative bias analyses in future studies involving EHR-based DM studies
Effects of once-weekly exenatide on cardiovascular outcomes in type 2 diabetes
BACKGROUND: The cardiovascular effects of adding once-weekly treatment with exenatide to usual care in patients with type 2 diabetes are unknown. METHODS: We randomly assigned patients with type 2 diabetes, with or without previous cardiovascular disease, to receive subcutaneous injections of extended-release exenatide at a dose of 2 mg or matching placebo once weekly. The primary composite outcome was the first occurrence of death from cardiovascular causes, nonfatal myocardial infarction, or nonfatal stroke. The coprimary hypotheses were that exenatide, administered once weekly, would be noninferior to placebo with respect to safety and superior to placebo with respect to efficacy. RESULTS: In all, 14,752 patients (of whom 10,782 [73.1%] had previous cardiovascular disease) were followed for a median of 3.2 years (interquartile range, 2.2 to 4.4). A primary composite outcome event occurred in 839 of 7356 patients (11.4%; 3.7 events per 100 person-years) in the exenatide group and in 905 of 7396 patients (12.2%; 4.0 events per 100 person-years) in the placebo group (hazard ratio, 0.91; 95% confidence interval [CI], 0.83 to 1.00), with the intention-to-treat analysis indicating that exenatide, administered once weekly, was noninferior to placebo with respect to safety (P<0.001 for noninferiority) but was not superior to placebo with respect to efficacy (P=0.06 for superiority). The rates of death from cardiovascular causes, fatal or nonfatal myocardial infarction, fatal or nonfatal stroke, hospitalization for heart failure, and hospitalization for acute coronary syndrome, and the incidence of acute pancreatitis, pancreatic cancer, medullary thyroid carcinoma, and serious adverse events did not differ significantly between the two groups. CONCLUSIONS: Among patients with type 2 diabetes with or without previous cardiovascular disease, the incidence of major adverse cardiovascular events did not differ significantly between patients who received exenatide and those who received placebo