Öz
Amaç: Gestasyonel Diabetes Mellitus (GDM)’da gün içi glukoz dalgalanmaları ve bunun bebek üzerine etkisini belirlemek; ayrıca, glukozdaki dalgalanmaların HbA1c, fruktozamin (FRM) ve 1,5-Anhidroglucitol (1,5-AG) ile korelasyonunu saptamaktır. Gereç ve Yöntem: Sadece diyetle takip edilen GDM tanısı alan ve ≥35 gebelik haftasındaki 31 hastada devamlı glukoz ölçüm sistemi (CGMS) ile 72 saatlik glisemik değişkenlikler (ortalama mutlak değer %MAD ve ortalama glukoz değeri) ölçüldü, ayrıca hastalardan, CGMS takılı olduğu günler, kendi kendine glukoz ölçüm sistemi (SMBG) her öğün öncesinde ve birinci saat sonrasında parmak ucundan kan glukoz düzeylerini ölçmeleri istendi. 1,5 AG, Hba1c ve FRM düzeyleri CGMS çıkarıldığı üçüncü gün hastalardan alındı. Bulgular: Hastaların ortalama HbA1c, FRM ve 1,5-AG sırasıyla %5,0±0,3, 2,1±0,2 μmol/L, ve 17,0±4,9 ng/mL idi. Üç günlük izlemde maximum-minimum glukoz düzeyi ortalaması 131,1±22,5 ve 54,7±11,6 mg/dL iken %MAD değeri %6,7±3,1 idi. SMBG ve CGMS ile ölçülen ortalama glukoz değeri birbiri ile koreleyken (82,9±10,2 ve 86,1±10,3 mg/dL); glukoz dalgalanması ile FRM, HbA1c ve 1,5-AG arasında anlamlı korelasyon yoktu. Hastaların glikoz dalgalanmaları varsa doğumdaki bebek ağırlığının ve baş çevresinin düşük olduğu belirlendi. Sonuç: Çalışmamızda biyobelirteçlerin glisemik dalgalanmayı yansıtmadığı; istenilen glukoz seviyesinin sağlanması için, diyetle regüle GDM de bile, SMBG’un sık, düzenli olarak yapılmasının gerekliliği saptanmıştır; ancak glisemik dalgalanmaları fazla olan GDM’li annenin bebeğinde baş çevresi ve doğum kilosu daha düşük saptanmıştır ve glisemik dalgalanmayı daha yakından gösteren CGMS’ in her ne kadar maliyet ve uygulama zorluğu olsa da, SMBG’ ye alternatif yöntem olabileceği gösterilmiştir.
Anahtar Kelimeler
Gestasyonel diabetes 1.5 anhidroglucitol glisemik değişkenlik HbA1c fruktozamin
Destekleyen Kurum
İstanbul Üniversitesi Bilimsel Araştırmalar Proje Birimi
Proje Numarası
44800
Kaynakça
- 1. Saravanan P, Diabetes in Pregnancy Working G, Maternal Medicine Clinical Study G, Royal College of O, Gynaecologists UK. Gestational diabetes: opportunities for improving maternal and child health. Lancet Diabetes Endocrinol 2020;8(9):793-800. [CrossRef] google scholar
- 2. Catalano P.M BTA. Metabolic Changes during normal and diabetic pregnancies thrid edition ed. Reece A CDR, Gabbe S.G, editor. Lipincott Williams& Wilkins 2004. google scholar
- 3. Yamamoto JM, Kellett JE, Balsells M, Garcia-Patterson A, Hadar E, Sola I, et al. Gestational diabetes mellitus and diet: a systematic review and meta-analysis of randomized controlled trials examining the impact of modified dietary interventions on maternal glucose control and neonatal birth weight. Diabetes Care 2018;41(7):1346-61. [CrossRef] google scholar
- 4. Türkiye Endokrinoloji ve Metabolizma Derneği diabetes mellitus çalışma grubu TEMD diabetes mellitus ve komplikasyonlarının tanı, tedavi ve izlem kılavuzu 2022, 15.baskı, Bayt Bilimsel Araştırmalar Basın Yayın ve Tanıtım Ltd. Şti. Ankara, 2022 google scholar
- 5. Wang Y, Zhang YL, Wang YP, Lei CH, Sun ZL. A study on the association of serum 1,5-anhydroglucitol levels and the hyperglycaemic excursions as measured by continuous glucose monitoring system among people with type 2 diabetes in China. Diabetes Metab Res Rev 2012;28(4):357-62. [CrossRef] google scholar
- 6. Butte NF. Carbohydrate and lipid metabolism in pregnancy: normal compared with gestational diabetes mellitus. Am J Clin Nutr 2000;71(5 Suppl):1256S-61S. [CrossRef] google scholar
- 7. Dalfra MG, Chilelli NC, Di Cianni G, Mello G, Lencioni C, Biagioni S, et al. Glucose fluctuations during gestation: An additional tool for monitoring pregnancy complicated by diabetes. Int J Endocrinol 2013;2013:279021. [CrossRef] google scholar
- 8. Zhou J, Mo Y, Li H, Ran X, Yang W, Li Q, et al. Relationship between HbA1c and continuous glucose monitoring in Chinese population: a multicenter study. PLoS One 2013;8(12):e83827. [CrossRef] google scholar
- 9. Czupryniak L, Barkai L, Bolgarska S, Bronisz A, Broz J, Cypryk K, et al. Self-monitoring of blood glucose in diabetes: from evidence to clinical reality in Central and Eastern Europe-recommendations from the international Central-Eastern European expert group. Diabetes Technol Ther 2014;16(7):460-75. [CrossRef] google scholar
- 10. Marling CR, Shubrook JH, Vernier SJ, Wiley MT, Schwartz FL. Characterizing blood glucose variability using new metrics with continuous glucose monitoring data. J Diabetes Sci Technol 2011;5(4):871-8. [CrossRef] google scholar
- 11. Chon S, Lee YJ, Fraterrigo G, Pozzilli P, Choi MC, Kwon MK, et al. Evaluation of glycemic variability in well-controlled type 2 diabetes mellitus. Diabetes Technol Ther 2013;15(6):455-60. [CrossRef] google scholar
- 12. Sacks DB. Hemoglobin variants and hemoglobin A1c analysis: problem solved? Clin Chem 2003;49(8):1245-7. [CrossRef] google scholar
- 13. Juraschek SP, Steffes MW, Miller ER, 3rd, Selvin E. Alternative markers of hyperglycemia and risk of diabetes. Diabetes Care 2012;35(11):2265-70. [CrossRef] google scholar
- 14. Dworacka M, Winiarska H, Szymanska M, Kuczynski S, Szczawinska K, Wierusz-Wysocka B. 1,5-anhydro-D-glucitol: a novel marker of glucose excursions. Int J Clin Practice Supp 2002;(129):40-4. google scholar
- 15. Rasmussen L, Christensen ML, Poulsen CW, Rud C, Christensen AS, Andersen JR, et al. Effect of high versus low carbohydrate intake in the morning on glycemic variability and glycemic control measured by continuous blood glucose monitoring in women with gestational diabetes mellitus:A randomized crossover study. Nutrients 2020;12(2):475. [CrossRef] google scholar
- 16. Yu W, Wu N, Li L, OuYang H, Qian M, Shen H. A review of research progress on glycemic variability and gestational diabetes. Diabetes Metab Syndr Obes 2020;13:2729-41. [CrossRef] google scholar
- 17. Kim MJ, Jung HS, Hwang-Bo Y, Cho SW, Jang HC, Kim SY, et al. Evaluation of 1, 5-anhydroglucitol as a marker for glycemic variability in patients with type 2 diabetes mellitus. Acta Diabetol 2013;50(4):505-10. [CrossRef] google scholar
- 18. Pramodkumar TA, Jayashri R, Gokulakrishnan K, Velmurugan K, Pradeepa R, Venkatesan U, et al. 1, 5 Anhydroglucitol in gestational diabetes mellitus. J Diabetes Complications 2019;33(3):231-5. [CrossRef] google scholar
- 19. Nowak N, Skupien J, Cyganek K, Matejko B, Malecki M. 1, 5-Anhydroglucitol as a marker of maternal glycaemic control and predictor of neonatal birthweight in pregnancies complicated by type 1 diabetes mellitus. Diabetologia 2013;56(4):709-13. [CrossRef] google scholar
- 20. Sun J, Dou J-t, Wang X-l, Yang G-q, ZHENG H, MA F-l, et al. Correlation between 1, 5-anhydroglucitol and glycemic excursions in type 2 diabetic patients. Chin Med J (Enlg) 2011;124(22):3641-5. google scholar
- 21. Breyton A-E, Lambert-Porcheron S, Laville M, Vinoy S, Nazare J-A. CGMS and glycemic variability, relevance in clinical research to evaluate interventions in T2D, a literature review. Front Endocrinol (Lausanne) 2021;12:666008. doi: 10.3389/fendo.2021.666008. [CrossRef] google scholar
- 22. Care D. 6. Glycemic targets: standards of medical care in diabetes—2019. Diabetes Care 2019;42(Supplement 1):S61-70. [CrossRef] google scholar
- 23. Chircop J, Sheffield D, Kotera Y. Systematic review of self-monitoring of blood glucose in patients with type 2 diabetes. Nursing Research 2021;70(6):487-97. [CrossRef] google scholar
- 24. Pfoh ER, Linfield D, Speaker SL, Roufael JS, Yan C, Misra-Hebert AD, et al. Patient perspectives on self-monitoring of blood glucose when not using insulin: a cross-sectional survey. J Gen Intern Med 2022;37(7):1673-9. [CrossRef] google scholar
DETERMINING THE IMPORTANCE OF GLYCEMIC VARIABILITY IN GESTATIONAL DIABETES MELLITUS USING VARIOUS TECHNIQUES
Öz
Objective: The study aims to determine glycemic variation in patients with gestational diabetes mellitus (GDM) and to evaluate the effect on the fetal growth using a continuous glucose monitoring system (CGMS) and to investigate the correlation between glucose variation through biomarkers including HbA1c, fructosamine (FRM), and 1.5-Anhydroglucitol (1.5-AG). Materials and Methods: The study involves 31 women with GDM at gestational week ≥35 who’d only had diet therapy. Blood glucose levels were monitored for three consecutive days using CGMS to evaluate mean blood glucose levels and mean absolute difference (MAD). Self-monitoring of blood glucose (SMBG) was required from the patients while having the CMGS on their body. Blood samples were collected to measure serum 1.5-AG, HbA1c, and FRM. Results: The mean levels were HbA1c=5.0±0.3%, FRM=2.1±0.2 μmol/L, 1.5-AG=17.0±4.9 ng/ml, and 3-day average max-min glucose range=131.1±22.5 and 54.7±11.6 mg/dl (MAD=6.7±3.1%). The mean glucose levels measured using SMBG and CGMS were similar (82.9±10.2 vs 86.1±10.3 mg/dL). No correlation occurred between CMGS and biomarkers. The baby weight at birth and head circumference was determined to be lower for patients with glucose fluctuations. Conclusion: Biomarkers do not reflect glycemic fluctuation, and regular SMBG is required to achieve the desired glucose level, even in diet-regulated GDM. Lower head circumference and birth weight were determined in GDM mothers with high glycemic fluctuations, and CGMS may be an alternative method despite its cost and application difficulties.
Anahtar Kelimeler
Gestastional diabetes 1.5 anhydroglucitol glycemic variability HbA1c fructosamine
Proje Numarası
44800
Kaynakça
- 1. Saravanan P, Diabetes in Pregnancy Working G, Maternal Medicine Clinical Study G, Royal College of O, Gynaecologists UK. Gestational diabetes: opportunities for improving maternal and child health. Lancet Diabetes Endocrinol 2020;8(9):793-800. [CrossRef] google scholar
- 2. Catalano P.M BTA. Metabolic Changes during normal and diabetic pregnancies thrid edition ed. Reece A CDR, Gabbe S.G, editor. Lipincott Williams& Wilkins 2004. google scholar
- 3. Yamamoto JM, Kellett JE, Balsells M, Garcia-Patterson A, Hadar E, Sola I, et al. Gestational diabetes mellitus and diet: a systematic review and meta-analysis of randomized controlled trials examining the impact of modified dietary interventions on maternal glucose control and neonatal birth weight. Diabetes Care 2018;41(7):1346-61. [CrossRef] google scholar
- 4. Türkiye Endokrinoloji ve Metabolizma Derneği diabetes mellitus çalışma grubu TEMD diabetes mellitus ve komplikasyonlarının tanı, tedavi ve izlem kılavuzu 2022, 15.baskı, Bayt Bilimsel Araştırmalar Basın Yayın ve Tanıtım Ltd. Şti. Ankara, 2022 google scholar
- 5. Wang Y, Zhang YL, Wang YP, Lei CH, Sun ZL. A study on the association of serum 1,5-anhydroglucitol levels and the hyperglycaemic excursions as measured by continuous glucose monitoring system among people with type 2 diabetes in China. Diabetes Metab Res Rev 2012;28(4):357-62. [CrossRef] google scholar
- 6. Butte NF. Carbohydrate and lipid metabolism in pregnancy: normal compared with gestational diabetes mellitus. Am J Clin Nutr 2000;71(5 Suppl):1256S-61S. [CrossRef] google scholar
- 7. Dalfra MG, Chilelli NC, Di Cianni G, Mello G, Lencioni C, Biagioni S, et al. Glucose fluctuations during gestation: An additional tool for monitoring pregnancy complicated by diabetes. Int J Endocrinol 2013;2013:279021. [CrossRef] google scholar
- 8. Zhou J, Mo Y, Li H, Ran X, Yang W, Li Q, et al. Relationship between HbA1c and continuous glucose monitoring in Chinese population: a multicenter study. PLoS One 2013;8(12):e83827. [CrossRef] google scholar
- 9. Czupryniak L, Barkai L, Bolgarska S, Bronisz A, Broz J, Cypryk K, et al. Self-monitoring of blood glucose in diabetes: from evidence to clinical reality in Central and Eastern Europe-recommendations from the international Central-Eastern European expert group. Diabetes Technol Ther 2014;16(7):460-75. [CrossRef] google scholar
- 10. Marling CR, Shubrook JH, Vernier SJ, Wiley MT, Schwartz FL. Characterizing blood glucose variability using new metrics with continuous glucose monitoring data. J Diabetes Sci Technol 2011;5(4):871-8. [CrossRef] google scholar
- 11. Chon S, Lee YJ, Fraterrigo G, Pozzilli P, Choi MC, Kwon MK, et al. Evaluation of glycemic variability in well-controlled type 2 diabetes mellitus. Diabetes Technol Ther 2013;15(6):455-60. [CrossRef] google scholar
- 12. Sacks DB. Hemoglobin variants and hemoglobin A1c analysis: problem solved? Clin Chem 2003;49(8):1245-7. [CrossRef] google scholar
- 13. Juraschek SP, Steffes MW, Miller ER, 3rd, Selvin E. Alternative markers of hyperglycemia and risk of diabetes. Diabetes Care 2012;35(11):2265-70. [CrossRef] google scholar
- 14. Dworacka M, Winiarska H, Szymanska M, Kuczynski S, Szczawinska K, Wierusz-Wysocka B. 1,5-anhydro-D-glucitol: a novel marker of glucose excursions. Int J Clin Practice Supp 2002;(129):40-4. google scholar
- 15. Rasmussen L, Christensen ML, Poulsen CW, Rud C, Christensen AS, Andersen JR, et al. Effect of high versus low carbohydrate intake in the morning on glycemic variability and glycemic control measured by continuous blood glucose monitoring in women with gestational diabetes mellitus:A randomized crossover study. Nutrients 2020;12(2):475. [CrossRef] google scholar
- 16. Yu W, Wu N, Li L, OuYang H, Qian M, Shen H. A review of research progress on glycemic variability and gestational diabetes. Diabetes Metab Syndr Obes 2020;13:2729-41. [CrossRef] google scholar
- 17. Kim MJ, Jung HS, Hwang-Bo Y, Cho SW, Jang HC, Kim SY, et al. Evaluation of 1, 5-anhydroglucitol as a marker for glycemic variability in patients with type 2 diabetes mellitus. Acta Diabetol 2013;50(4):505-10. [CrossRef] google scholar
- 18. Pramodkumar TA, Jayashri R, Gokulakrishnan K, Velmurugan K, Pradeepa R, Venkatesan U, et al. 1, 5 Anhydroglucitol in gestational diabetes mellitus. J Diabetes Complications 2019;33(3):231-5. [CrossRef] google scholar
- 19. Nowak N, Skupien J, Cyganek K, Matejko B, Malecki M. 1, 5-Anhydroglucitol as a marker of maternal glycaemic control and predictor of neonatal birthweight in pregnancies complicated by type 1 diabetes mellitus. Diabetologia 2013;56(4):709-13. [CrossRef] google scholar
- 20. Sun J, Dou J-t, Wang X-l, Yang G-q, ZHENG H, MA F-l, et al. Correlation between 1, 5-anhydroglucitol and glycemic excursions in type 2 diabetic patients. Chin Med J (Enlg) 2011;124(22):3641-5. google scholar
- 21. Breyton A-E, Lambert-Porcheron S, Laville M, Vinoy S, Nazare J-A. CGMS and glycemic variability, relevance in clinical research to evaluate interventions in T2D, a literature review. Front Endocrinol (Lausanne) 2021;12:666008. doi: 10.3389/fendo.2021.666008. [CrossRef] google scholar
- 22. Care D. 6. Glycemic targets: standards of medical care in diabetes—2019. Diabetes Care 2019;42(Supplement 1):S61-70. [CrossRef] google scholar
- 23. Chircop J, Sheffield D, Kotera Y. Systematic review of self-monitoring of blood glucose in patients with type 2 diabetes. Nursing Research 2021;70(6):487-97. [CrossRef] google scholar
- 24. Pfoh ER, Linfield D, Speaker SL, Roufael JS, Yan C, Misra-Hebert AD, et al. Patient perspectives on self-monitoring of blood glucose when not using insulin: a cross-sectional survey. J Gen Intern Med 2022;37(7):1673-9. [CrossRef] google scholar
Ayrıntılar
| Birincil Dil | İngilizce |
|---|---|
| Konular | Sağlık Kurumları Yönetimi |
| Bölüm | ARAŞTIRMA |
| Yazarlar | |
| Proje Numarası | 44800 |
| Yayımlanma Tarihi | 31 Ocak 2023 |
| Gönderilme Tarihi | 24 Ekim 2022 |
| Yayımlandığı Sayı | Yıl 2023 Cilt: 86 Sayı: 1 |
Kaynak Göster
Contact information and address
Addressi: İ.Ü. İstanbul Tıp Fakültesi Dekanlığı, Turgut Özal Cad. 34093 Çapa, Fatih, İstanbul, TÜRKİYE
Email: itfdergisi@istanbul.edu.tr
Phone: +90 212 414 21 61