"Symptom-based insulin adjustment for glucose normalization" (SIGN) algorithm: a pilot study
Lack of self-monitoring of blood glucose (SMBG) records in actual practice settings continues to create therapeutic challenges for clinicians, especially in adjusting insulin therapy. In order to overcome this clinical obstacle, a "Symptom-based Insulin adjustment for Glucose Normalization"...
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| Published in: | Diabetes technology & therapeutics Vol. 14; no. 12; p. 1145 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
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United States
01.12.2012
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| ISSN: | 1557-8593, 1557-8593 |
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| Abstract | Lack of self-monitoring of blood glucose (SMBG) records in actual practice settings continues to create therapeutic challenges for clinicians, especially in adjusting insulin therapy. In order to overcome this clinical obstacle, a "Symptom-based Insulin adjustment for Glucose Normalization" (SIGN) algorithm was developed to guide clinicians in caring for patients with uncontrolled type 2 diabetes who have few to no SMBG records. This study examined the clinical outcome and safety of the SIGN algorithm.
Glycated hemoglobin (HbA1c), insulin usage, and insulin-related adverse effects of a total of 114 patients with uncontrolled type 2 diabetes who refused to use SMBG or performed SMBG once a day for less than three times per week were studied 3 months prior to the implementation of the algorithm and prospectively at every 3-month interval for a total of 6 months after the algorithm implementation. Patients with type 1 diabetes, nonadherence to diabetes medications, or who were not on insulin therapy at any time during the study period were excluded from this study.
Mean HbA1c improved by 0.29% at 3 months (P = 0.015) and 0.41% at 6 months (P = 0.006) after algorithm implementation. A slight increase in HbA1c was observed when the algorithm was not implemented. There were no major hypoglycemic episodes. The number of minor hypoglycemic episodes was minimal with the majority of the cases due to irregular meal habits.
The SIGN algorithm appeared to offer a viable and safe approach when managing uncontrolled patients with type 2 diabetes who have few to no SMBG records. |
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| AbstractList | Lack of self-monitoring of blood glucose (SMBG) records in actual practice settings continues to create therapeutic challenges for clinicians, especially in adjusting insulin therapy. In order to overcome this clinical obstacle, a "Symptom-based Insulin adjustment for Glucose Normalization" (SIGN) algorithm was developed to guide clinicians in caring for patients with uncontrolled type 2 diabetes who have few to no SMBG records. This study examined the clinical outcome and safety of the SIGN algorithm.BACKGROUNDLack of self-monitoring of blood glucose (SMBG) records in actual practice settings continues to create therapeutic challenges for clinicians, especially in adjusting insulin therapy. In order to overcome this clinical obstacle, a "Symptom-based Insulin adjustment for Glucose Normalization" (SIGN) algorithm was developed to guide clinicians in caring for patients with uncontrolled type 2 diabetes who have few to no SMBG records. This study examined the clinical outcome and safety of the SIGN algorithm.Glycated hemoglobin (HbA1c), insulin usage, and insulin-related adverse effects of a total of 114 patients with uncontrolled type 2 diabetes who refused to use SMBG or performed SMBG once a day for less than three times per week were studied 3 months prior to the implementation of the algorithm and prospectively at every 3-month interval for a total of 6 months after the algorithm implementation. Patients with type 1 diabetes, nonadherence to diabetes medications, or who were not on insulin therapy at any time during the study period were excluded from this study.SUBJECTS AND METHODSGlycated hemoglobin (HbA1c), insulin usage, and insulin-related adverse effects of a total of 114 patients with uncontrolled type 2 diabetes who refused to use SMBG or performed SMBG once a day for less than three times per week were studied 3 months prior to the implementation of the algorithm and prospectively at every 3-month interval for a total of 6 months after the algorithm implementation. Patients with type 1 diabetes, nonadherence to diabetes medications, or who were not on insulin therapy at any time during the study period were excluded from this study.Mean HbA1c improved by 0.29% at 3 months (P = 0.015) and 0.41% at 6 months (P = 0.006) after algorithm implementation. A slight increase in HbA1c was observed when the algorithm was not implemented. There were no major hypoglycemic episodes. The number of minor hypoglycemic episodes was minimal with the majority of the cases due to irregular meal habits.RESULTSMean HbA1c improved by 0.29% at 3 months (P = 0.015) and 0.41% at 6 months (P = 0.006) after algorithm implementation. A slight increase in HbA1c was observed when the algorithm was not implemented. There were no major hypoglycemic episodes. The number of minor hypoglycemic episodes was minimal with the majority of the cases due to irregular meal habits.The SIGN algorithm appeared to offer a viable and safe approach when managing uncontrolled patients with type 2 diabetes who have few to no SMBG records.CONCLUSIONSThe SIGN algorithm appeared to offer a viable and safe approach when managing uncontrolled patients with type 2 diabetes who have few to no SMBG records. Lack of self-monitoring of blood glucose (SMBG) records in actual practice settings continues to create therapeutic challenges for clinicians, especially in adjusting insulin therapy. In order to overcome this clinical obstacle, a "Symptom-based Insulin adjustment for Glucose Normalization" (SIGN) algorithm was developed to guide clinicians in caring for patients with uncontrolled type 2 diabetes who have few to no SMBG records. This study examined the clinical outcome and safety of the SIGN algorithm. Glycated hemoglobin (HbA1c), insulin usage, and insulin-related adverse effects of a total of 114 patients with uncontrolled type 2 diabetes who refused to use SMBG or performed SMBG once a day for less than three times per week were studied 3 months prior to the implementation of the algorithm and prospectively at every 3-month interval for a total of 6 months after the algorithm implementation. Patients with type 1 diabetes, nonadherence to diabetes medications, or who were not on insulin therapy at any time during the study period were excluded from this study. Mean HbA1c improved by 0.29% at 3 months (P = 0.015) and 0.41% at 6 months (P = 0.006) after algorithm implementation. A slight increase in HbA1c was observed when the algorithm was not implemented. There were no major hypoglycemic episodes. The number of minor hypoglycemic episodes was minimal with the majority of the cases due to irregular meal habits. The SIGN algorithm appeared to offer a viable and safe approach when managing uncontrolled patients with type 2 diabetes who have few to no SMBG records. |
| Author | Lim, Jiahui Tsou, Keith Lee, Joyce Yu-Chia Wong, Sabrina Koh, Feaizen Ong, Sooim |
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| References_xml | – reference: 7587846 - Diabetes Care. 1995 Aug;18(8):1113-23 – reference: 10857938 - Diabetes Care. 2000 Apr;23(4):477-83 – reference: 2289639 - Fam Pract. 1990 Dec;7(4):273-8 – reference: 20811025 - Am J Health Syst Pharm. 2010 Sep 15;67(18):1503-6 – reference: 17102152 - Diabetes Educ. 2006 Nov-Dec;32(6):835-6, 844-7 – reference: 12766106 - Diabetes Care. 2003 Jun;26(6):1759-63 – reference: 12659642 - BMC Health Serv Res. 2003 Mar 19;3(1):6 – reference: 15920048 - Diabetes Care. 2005 Jun;28(6):1333-8 – reference: 19267710 - Diabetes Obes Metab. 2009 Apr;11(4):323-9 – reference: 11375356 - Diabetes Care. 2001 Jun;24(6):979-82 – reference: 17259518 - Diabetes Care. 2007 Feb;30(2):389-94 – reference: 17599428 - Am J Cardiol. 2007 Jun 18;99(12A):80i-89i |
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| SubjectTerms | Algorithms Blood Glucose Self-Monitoring Diabetes Mellitus, Type 2 - blood Diabetes Mellitus, Type 2 - drug therapy Diabetes Mellitus, Type 2 - physiopathology Drug Administration Schedule Female Glycated Hemoglobin A - drug effects Glycated Hemoglobin A - metabolism Guidelines as Topic Humans Hypoglycemia - blood Hypoglycemia - drug therapy Hypoglycemic Agents - administration & dosage Hypoglycemic Agents - pharmacology Insulin - administration & dosage Insulin - pharmacology Male Medication Adherence Middle Aged Pilot Projects Prospective Studies Severity of Illness Index |
| Title | "Symptom-based insulin adjustment for glucose normalization" (SIGN) algorithm: a pilot study |
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