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Articles by J. Chan
Total Records ( 3 ) for J. Chan
  G. Ko , W. So , P. Tong , R. Ma , A. Kong , R. Ozaki , C. Chow , C. Cockram and J. Chan
  Aims To develop a simple scoring system for identifying Southern Chinese at risk of diabetes.
Methods The score was derived from a risk factor matching cohort for Type 2 diabetes in Hong Kong Chinese (cohort 1, 2448 subjects without a history of diabetes; age, mean ±  sd 37.2 ± 8.9 years, median 36.0 years; 1649 had risk factors for diabetes and 799 were age-matched control subjects from the community). Two other cohorts were used to validate the risk score (cohort 2, 3734 subjects with risk factors for diabetes; and cohort 3, 1513 participants of a community diabetes survey). All subjects had a 75 g oral glucose tolerance test (OGTT).
Results In cohort 1, 270 (11%) of the subjects were found to have diabetes on OGTT. A risk score system was derived using the β values of the corresponding predictors in the logistic regression analysis. The area under the curve (95% confidence intervals) of the score system was 0.735 (0.705, 0.765). The application of a risk score of ≥ 16 increased the detection rate 2.5–4 times in all three cohorts. A high post-test probability of diabetes of > 60% was derived from a risk score of ≥ 20. Only 10–20 and ∼5% with a score of ≥ 12 and ≥ 16, respectively, are indicated for OGTT. This will considerably improve the yield of OGTT screening.
Conclusions A simple risk score identifies young-to-middle-aged Southern Chinese at high risk for diabetes. Subjects with a score of 16 or above (out of 30) should undergo OGTT for definitive diagnosis of diabetes.
  J. Chan , W. So , G. Ko , P. Tong , X. Yang , R. Ma , A. Kong , R. Wong , F. Le Coguiec , B. Tamesis , T. Wolthers , G. Lyubomirsky and P. Chow
  Aims  The Joint Asia Diabetes Evaluation (JADE) Program is the first web-based program incorporating a comprehensive risk engine, care protocols, clinical decision and self-management support to improve ambulatory diabetes care. The aim was to validate the risk stratification system of the JADE Program using a large prospective cohort.

Methods  The JADE interactive risk engine stratifies patients into different risk levels using results from an annual comprehensive assessment of complications and risk factors. We used a prospective registry consisting of 7534 Type 2 diabetic patients [45.6% men, median (range) age 57 years (13-92)] to perform internal validation of the risk engine.

Results  The JADE Risk Engine categorized patients into four risk levels (from low to high): level 1, n = 4520 (6%); level 2, n = 1468 (19.5%); level 3, n = 4476 (59.4%); and level 4, n = 1138 (15.1%). After a median follow-up period of 5.5 years (mean ± sd 5.4 ± 2.81 years), 763 (10.1%) died, 1129 (14.9%) developed cardiovascular disease (CVD), 282 (3.7%) developed end-stage renal disease and 1400 (18.6%) had at least one of these events. Compared with risk level 1, levels 2, 3 and 4 were associated with 2.8-, 4.7- and 8.6-fold increased risk of clinical end-points. Risk levels 3 and 4 were, respectively, associated with 2.2- and 3.9-fold increased risk for all-cause death and 4.8- and 12.1-fold increased CVD risks.

Conclusion  Based on results from a comprehensive assessment, the JADE Risk Engine successfully categorizes patients into different risk levels to guide clinical management.

  A. R. Chacra , M. Kipnes , L. L. Ilag , S. Sarwat , J. Giaconia and J. Chan
  Aims  The efficacy of two basal insulins, insulin lispro protamine suspension (ILPS) and insulin detemir, was compared in basal-bolus regimens in Type 1 diabetes.

Methods  In this 32-week, multinational, parallel-group, randomized, controlled trial, adult patients with Type 1 diabetes received ILPS or insulin detemir, injected twice daily (before breakfast and bedtime) and prandial insulin lispro three times daily. The primary outcome was change in glycated haemoglobin (HbA1c) from baseline to endpoint.

Results  Least squares mean (±se) changes in HbA1c were similar between groups, meeting non-inferiority (margin, 0.4%): −0.69 ± 0.07% for ILPS and −0.59 ± 0.07% for insulin detemir [between-treatment difference −0.10%; 95% confidence interval (CI) −0.29, 0.10]. Standard deviation of fasting blood glucose was similar (non-inferiority margin 0.8 mmol/l): 2.74 ± 0.14 mmol/l for ILPS and 2.38 ± 0.14 mmol/l for insulin detemir (CI −0.03, 0.75). Patients on ILPS gained more weight (1.59 ± 0.23 kg vs. 0.62 ± 0.24 kg; CI 0.34, 1.60; margin 1.5 kg). Weight-adjusted daily total and prandial insulin doses were lower for ILPS (prandial insulin, 0.38 ± 0.01 U/kg/day for ILPS, 0.44 ± 0.01 U/kg/day for insulin detemir; P = 0.004); daily basal insulin dose was similar. All hypoglycaemia incidence and rate and nocturnal hypoglycaemia incidence were similar between groups; nocturnal hypoglycaemia rate was lower for insulin detemir (mean ± sd 0.79 ± 1.23 for ILPS, 0.49 ± 0.85 for insulin detemir; P = 0.001). Severe hypoglycaemia rate was 0.03 ± 0.11 for ILPS and 0.02 ± 0.10 for insulin detemir (P = 0.37).

Conclusions  ILPS-treated patients with Type 1 diabetes achieved similar glycaemic control as insulin detemir-treated patients after 32 weeks. Glucose variability was similar. While weight gain and nocturnal hypoglycaemia rate were statistically higher with ILPS, the clinical relevance is unclear.

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