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The American Journal of Managed Care April 2018
Delivering on the Value Proposition of Precision Medicine: The View From Healthcare Payers
Jane Null Kogan, PhD; Philip Empey, PharmD, PhD; Justin Kanter, MA; Donna J. Keyser, PhD, MBA; and William H. Shrank, MD, MSHS
Care Coordination for Children With Special Needs in Medicaid: Lessons From Medicare
Kate A. Stewart, PhD, MS; Katharine W.V. Bradley, PhD, MBA; Joseph S. Zickafoose, MD, MS; Rachel Hildrich, BS; Henry T. Ireys, PhD; and Randall S. Brown, PhD
Cost Sharing and Branded Antidepressant Initiation Among Patients Treated With Generics
Jason D. Buxbaum, MHSA; Michael E. Chernew, PhD; Machaon Bonafede, PhD; Anna Vlahiotis, MA; Deborah Walter, MPA; Lisa Mucha, PhD; and A. Mark Fendrick, MD
The Well-Being of Long-Term Cancer Survivors
Jeffrey Sullivan, MS; Julia Thornton Snider, PhD; Emma van Eijndhoven, MS, MA; Tony Okoro, PharmD, MPH; Katharine Batt, MD, MSc; and Thomas DeLeire, PhD
A Payer–Provider Partnership for Integrated Care of Patients Receiving Dialysis
Justin Kindy, FSA, MAAA; David Roer, MD; Robert Wanovich, PharmD; and Stephen McMurray, MD
Financial Burden of Healthcare Utilization in Consumer-Directed Health Plans
Xinke Zhang, PhD; Erin Trish, PhD; and Neeraj Sood, PhD
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Progress of Diabetes Severity Associated With Severe Hypoglycemia in Taiwan
Edy Kornelius, MD; Yi-Sun Yang, MD; Shih-Chang Lo, MD; Chiung-Huei Peng, DDS, PhD; Yung-Rung Lai, PharmD; Jeng-Yuan Chiou, PhD; and Chien-Ning Huang, MD, PhD
Limited Distribution Networks Stifle Competition in the Generic and Biosimilar Drug Industries
Laura Karas, MD, MPH; Kenneth M. Shermock, PharmD, PhD; Celia Proctor, PharmD, MBA; Mariana Socal, MD, PhD; and Gerard F. Anderson, PhD
Provider and Patient Burdens of Obtaining Oral Anticancer Medications
Daniel M. Geynisman, MD; Caitlin R. Meeker, MPH; Jamie L. Doyle, MPH; Elizabeth A. Handorf, PhD; Marijo Bilusic, MD, PhD; Elizabeth R. Plimack, MD, MS; and Yu-Ning Wong, MD, MSCE

Progress of Diabetes Severity Associated With Severe Hypoglycemia in Taiwan

Edy Kornelius, MD; Yi-Sun Yang, MD; Shih-Chang Lo, MD; Chiung-Huei Peng, DDS, PhD; Yung-Rung Lai, PharmD; Jeng-Yuan Chiou, PhD; and Chien-Ning Huang, MD, PhD
Rapid progression of diabetes complications was associated with higher risk of severe hypoglycemia.
Disease Variables

The date of diabetes diagnosis was defined as the index date. Patients were followed until the first event of severe hypoglycemia, which served as the event date, or the end date, which was designated asdisenrollment; mortality; or December 31, 2011. Severe hypoglycemia was defined as a diagnosis of patients who required hospitalization or a visit to an emergency department (ED) for treatment with an ICD-9-CM code of 250.3, 251.0, 251.1, 251.2, or 962.3. Because of the possibility of ambiguity with ICD-9-CM code 250.3 (diabetes with other coma) between diabetic ketoacidosis (DKA) or hyperosmolar hyperglycemic syndrome (HHS) with hypoglycemic coma,24 we manually identified and analyzed our data for patients who were diagnosed with ICD-9-CM code 250.3. However, none of the patients in our study population appeared to have DKA/HHS with hypoglycemic coma. Disease comorbidities that potentially increased the risk of severe hypoglycemia, such as hypertension (ICD-9-CM codes 401-405), coronary heart disease (ICD-9-CM codes 414, 429.2), chronic liver disease (ICD-9-CM code 571), chronic kidney disease (ICD-9-CM code 585), heart failure (ICD-9-CM code 428), cancer (ICD-9-CM codes 140-208), depression (ICD-9-CM codes 296.2, 296.3), chronic obstructive pulmonary disease (ICD-9-CM codes 490-492, 494, 496), and stroke (ICD-9-CM codes 430-437), were identified, as were prescriptions for antidiabetic drugs, such as biguanides, sulfonylureas, α-glucosidase inhibitors, thiazolidinediones, glinides, dipeptidyl peptidase-4 (DPP-4) inhibitors, and insulin. Antidiabetic medication prescription was defined as a prescription with a drug exposure window of at least 180 days during this study period. A cutoff of 180 days was applied to avoid an irregular pattern of drug use, which might be related to patients’ nonadherence or initial antidiabetic drug adverse effects. The primary end point of this study was the first hospitalization due to severe hypoglycemia.

Statistical Analysis

Hazard ratios (HRs) and 95% CIs for the Cox proportional hazards model were used to analyze the data and determine the risk of severe hypoglycemia. One-way analysis of variance was used to compare data among the 3 groups. The Kaplan-Meier method was used to estimate severe hypoglycemia cumulative incidences. A 2-sided value <.05 was considered to be statistically significant. All statistical analyses were performed using the SPSS Statistical Package, version 18 (SPSS; Chicago, Illinois).


Table 1 shows the baseline demographic characteristics of the patients in this study. A total of 330,831 patients were included in this cohort from January 1, 1999, through December 31, 2011. The mean age was 56.8 years, and mean follow-up duration was 9.3 years. The mean initial aDCSI score was 0.7, whereas the mean aDCSI score at the event date or end date was 2.9. Patients with rapid increase in aDSCI score per year generally were older, were more likely to be male, and had more disease comorbidities and complications and a shorter follow-up duration.

Table 2 shows that the risks of severe hypoglycemia were associated with progression in aDCSI score. Compared with the patients with diabetes with slow progression of diabetes severity (increase in aDCSI score of <0.1 per year), the HRs of patients with moderate progression (increase of 0.1-0.3) and rapid progression (increase of >0.3) increased in proportion to diabetic progression, with HRs of 1.08 (95% CI, 1.02-1.14) and 4.91 (95% CI, 4.65-5.18), respectively. The incidence densities of severe hypoglycemia (per 1000 person-years) for slow, moderate, and rapid increase in aDCSI score were 2.3, 2.5, and 11.4, respectively.

Table 3 shows the risk of severe hypoglycemia with different diabetes complications. Before adjustment for potential confounders, all diabetes complications were associated with higher risk of severe hypoglycemia. However, after adjustment for age, gender, and antidiabetic medication, patients with metabolic complications showed the highest risk of severe hypoglycemia (HR, 1.96; 95% CI, 1.87-2.06). Retinopathy (HR, 1.11; 95% CI, 1.07-1.15), nephropathy (HR, 1.33; 95% CI, 1.28-1.37), and stroke (HR, 1.21; 95% CI, 1.17-1.25) were also associated with severe hypoglycemia. Meanwhile, cardiovascular disease (HR, 0.90; 95% CI, 0.87-0.93) was associated with lower risk of severe hypoglycemia.

The eAppendix Figure shows the Kaplan-Meier curves of the cumulative incidence of severe hypoglycemia in the 3 groups of aDCSI score increase per year. The Kaplan-Meier curves showed that the risk of severe hypoglycemia seemed to emerge in the first year, and it can be seen that there was marked divergence of aDCSI score increase among the 3 groups over the 13-year follow-up period.

Table 4 [part A and part Bshows various model adjustments that were performed to evaluate the risk of severe hypoglycemia according to the progression of diabetes complications. Despite adjustment for age, gender, disease comorbidities, and prescriptions for antidiabetic drugs, the progression of diabetes complications still had a significant effect on the risk of developing severe hypoglycemia.


This study found that progression of diabetes severity was associated with an increased incidence of severe hypoglycemia. To the best of our knowledge, this is the first study to examine the association between progression of diabetes severity and risk of severe hypoglycemia. An increase in aDCSI score per year was positively related to risk of severe hypoglycemia. Furthermore, we found that being older than 45 years or having a prescription for insulin or a sulfonylurea was associated with increased risk of severe hypoglycemia, whereas having a prescription for biguanides, α-glucosidase inhibitors, thiazolidinediones, or DPP-4 inhibitors was associated with a lower risk of hypoglycemia.

The progression of diabetes complications is difficult to quantify. The severity of diabetes complications increases with time after diabetes onset, and patients with diabetes often exhibit different patterns of progression and complications. Previous study findings have demonstrated that patients with older age,16 previous hypoglycemia,13,14 history of chronic kidney disease,15 retinopathy,13 and antidiabetic drug prescriptions11-13 have a higher risk of hypoglycemia. In this study, we further explored the importance of timing and severity of these complications. We used increase in aDCSI score per year to measure the progression of diabetes complications. Compared with patients with slow progression of diabetes complications, severe hypoglycemia occurred more frequently in patients with complications that progressed rapidly within a short period of time. Furthermore, we demonstrated that severe hypoglycemia risk increased in proportion to the progression of diabetes complications (Table 4).

Surprisingly, patients with metabolic complications, such as DKA or HHS, had the highest risk of developing severe hypoglycemia. In these patients, a high degree of glucose variability might contribute to the mechanism of severe hypoglycemia.25,26 The potential mechanism of hypoglycemia might be characterized by deficient counterregulatory hormone release, especially in older patients, and a diminished autonomic response.27 Regarding antidiabetic medications, our findings showed that sulfonylurea prescription (HR, 2.50; 95% CI, 2.39-2.61) was associated with the highest risk of hypoglycemia, whereas DPP-4 inhibitor prescription was correlated with the lowest risk of hypoglycemia (HR, 0.22; 95% CI, 0.22-0.25). This finding was consistent with results reported in a previous study.11-13

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