METHODS: We conducted a prospective study of consecutive patients with acute stroke who were admitted to 36 participating hospitals in China, India, Indonesia, Korea, Malaysia, the Philippines, Singapore, Taiwan, Thailand, and Vietnam. With the use of a simple identical data sheet, we recorded the demographics and cardiovascular risk factors of each patient. Early death was defined as death on discharge from the acute hospital.
RESULTS: We enrolled 2403 patients with ischemic stroke and 783 patients with intracerebral hemorrhage. Among patients with ischemic stroke, previous use of antiplatelet drugs (adjusted odds ratio [OR] 0.53; 95% confidence interval [CI] 0. 30 to 0.95) and relatively young age group 56 to 75 years (OR 0.65; 95% CI 0.42 to 1.00) were protective factors; atrial fibrillation (OR 2.23; 95% CI 1.40 to 3.57), ischemic heart disease (OR 2.03; 95% CI 1.37 to 3.05), diabetes (OR 1.52; 95% CI 1.04 to 2.22), and ex-smoker status (OR 2.18; 95% CI 1.18 to 4.05) were risk factors for early death. Among patients with intracerebral hemorrhage, hypertension (OR 0.56; 95% CI 0.38 to 0.82) and young age group 56 to 75 years old (OR 0.55; 95% CI 0.34 to 0.87) were associated with lower death rate, whereas diabetes (OR 1.74; 95% CI 1.01 to 2.98) was a risk factor for early death.
CONCLUSIONS: In Asian patients with stroke, previous use of antiplatelet drugs nearly halved the risk of early death in patients with ischemic stroke, whereas atrial fibrillation, ischemic heart disease, diabetes, and ex-smoker status were risk factors for early death. Among patients with intracerebral hemorrhage, diabetes was associated with early death, whereas young age group and hypertension were associated with lower death rates, though no clear explanation for the hypertension association could be discerned from the data available.
METHODS: This was a retrospective, non-interventional, cohort study using data from a Japanese medical claims database. Patients with glaucoma aged ≥20 years with a first drug claim for glaucoma treatment between 01 July 2005 and 30 October 2014 and with data for > 6 months before and after this first prescription were included. The primary endpoint was duration of drug persistence among glaucoma patients with and without the use of fixed combination drugs in the year following initiation of second-line combination treatment.
RESULTS: Of 1403 patients included in the analysis, 364 (25.94%) received fixed combination drugs and 1039 (74.06%) received unfixed combination drugs as second-line treatment. Baseline characteristics were generally comparable between the groups. A total of 39.01% of patients on fixed combination drugs, compared with 41.67% of patients on unfixed combination drugs, persisted on their glaucoma drugs 12 months post second-index date. Median persistence durations for the fixed combination drugs and unfixed combination drugs groups were 6 (95% confidence interval [CI]: 5-8) and 7 months (95% CI 6-9), respectively. Patients who received prostaglandin analogs (PGAs) were the most persistent with their treatment (n = 99, 12.84%). Patients diagnosed with primary open-angle glaucoma were less likely to experience treatment modification (hazard ratio [HR]: 0.800, 95% CI 0.649-0.986, P = 0.036), while those diagnosed with secondary glaucoma were more likely to experience treatment modification (HR: 1.678, 95% CI 1.231-2.288, P = 0.001) compared with glaucoma suspects.
CONCLUSIONS: In this retrospective claims database study, the persistence rate of second-line glaucoma combination treatment was low, with no difference in persistence between glaucoma patients receiving unfixed combination drugs compared with fixed combination drugs. Patients on PGA showed greater persistence rates compared with other treatments.
METHODS: This nested case-control study was performed by collecting data from 1 January 2015 to 30 June 2017. Univariable and multivariable logistic regressions were used to identify potential risk factors. The regression coefficients were converted into item scores by dividing each regression coefficient with the minimum coefficient in the model and rounding to the nearest integer. This value was then summed to the total score. The prediction power of the model was determined by the area under the receiver operating characteristic curve (AuROC).
RESULTS AND DISCUSSION: Six clinical risk factors, namely age ≥65 years, benzodiazepine use, history of a cerebrovascular accident, dose of hydrochlorothiazide ≥25 mg, female sex and statin use, were included in our ABCDF-S score. The model showed good power of prediction (AuROC 81.53%, 95% confidence interval [CI]: 78%-84%) and good calibration (Hosmer-Lemeshow X2 = 23.20; P = .39). The positive likelihood ratios of hyponatremia in patients with low risk (score ≤ 6) and high risk (score ≥ 8) were 0.26 (95% CI: 0.21-0.32) and 3.89 (95% CI: 3.11-4.86), respectively.
WHAT IS NEW AND CONCLUSION: The screening tool with six risk predictors provided a useful prediction index for thiazide-associated hyponatremia. However, further validation of the tool is warranted prior to its utilization in routine clinical practice.