The DOI matches its Crossref record; 78 of the 80 references it cites were found in a registry or an index.
Glucose Variability; Does It Matter?
Abstract
Overall lowering of glucose is of pivotal importance in the treatment of diabetes, with proven beneficial effects on microvascular and macrovascular outcomes. Still, patients with similar glycosylated hemoglobin levels and mean glucose values can have markedly different daily glucose excursions. The role of this glucose variability in pathophysiological pathways is the subject of debate. It is strongly related to oxidative stress in in vitro, animal, and human studies in an experimental setting. However, in real-life human studies including type 1 and type 2 diabetes patients, there is neither a reproducible relation with oxidative stress nor a correlation between short-term glucose variability and retinopathy, nephropathy, or neuropathy. On the other hand, there is some evidence that long-term glycemic variability might be related to microvascular complications in type 1 and type 2 diabetes. Regarding mortality, a convincing relationship with short-term glucose variability has only been demonstrated in nondiabetic, critically ill patients. Also, glucose variability may have a role in the prediction of severe hypoglycemia. In this review, we first provide an overview of the various methods to measure glucose variability. Second, we review current literature regarding glucose variability and its relation to oxidative stress, long-term diabetic complications, and hypoglycemia. Finally, we make recommendations on whether and how to target glucose variability, concluding that at present we lack both the compelling evidence and the means to target glucose variability separately from all efforts to lower mean glucose while avoiding hypoglycemia.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Recent clinical data indicate that GV is associated with increased risk of hypoglycemia, microvascular and macrovascular complications, and mortality in patients with diabetes, independently of glycated hemoglobin level.”
From Glycemic variability and cardiovascular disease in patients with type 2 diabetes (2021) · cites this paper as [15]
Citations
Cites
(1993) · New England Journal of Medicine · doi:10.1056/nejm199309303291401 · Cited by 24,667
Intensive insulin therapy in critically ill patients.
Van den Berghe, G., Wouters, P., Weekers, F., Verwaest, C., Bruyninckx, F., Schetz, M., Vlasselaers, D., Ferdinande, P., Lauwers, P., & Bouillon, R. (2001) · New England Journal of Medicine · doi:10.1056/nejmoa011300 · Cited by 9,977
Biochemistry and molecular cell biology of diabetic complications
Brownlee, M. (2001) · Nature · doi:10.1038/414813a · Cited by 9,107
The Pathobiology of Diabetic Complications
Brownlee, M. (2005) · Diabetes · doi:10.2337/diabetes.54.6.1615 · Cited by 5,339
Intensive versus Conventional Glucose Control in Critically Ill Patients
(2009) · New England Journal of Medicine · doi:10.1056/nejmoa0810625 · Cited by 5,119
Intensive insulin therapy in the medical ICU
Van den Berghe, G., Wilmer, A., Hermans, G., Meersseman, W., Wouters, P. J., Milants, I., Van Wijngaerden, E., Bobbaers, H., & Bouillon, R. (2006) · New England Journal of Medicine · doi:10.1056/nejmoa052521 · Cited by 3,639
Intensive insulin therapy and pentastarch resuscitation in severe sepsis
Brunkhorst, F. M., Engel, C., Bloos, F., Meier-Hellmann, A., Ragaller, M., Weiler, N., Moerer, O., Gruendling, M., Oppert, M., Grond, S., et al. (2008) · New England Journal of Medicine · doi:10.1056/nejmoa070716 · Cited by 2,921
Monnier, L., Mas, E., Ginet, C., Michel, F., Villon, L., Cristol, J.-P., & Colette, C. (2006) · JAMA · doi:10.1001/jama.295.14.1681 · Cited by 2,444
The PICO strategy for the research question construction and evidence search
Santos, C. M. D. C., Pimenta, C. A. D. M., & Nobre, M. R. C. (2007) · Revista Latino-Americana de Enfermagem · doi:10.1590/s0104-11692007000300023 · Cited by 2,342
Riddle (2003) · doi:10.2337/diacare.26.11.3080 · Cited by 1,479
Research works printed but not linked: 2
- Bugler J, Buell H 2008 Measuring glycemic variability—an estimation of data required based on a 90 day user study. Proc of 27th Workshop of the Artificial Insulin Delivery/Pancreas and Islet Transplantation study group of the European Association for the Study of Diabetes, Innsbruck, Austria, 2008 (Abstract S16)
- Devos, 2007, Impact of tight glucose control by intensive insulin therapy on ICU mortality and the rate of hypoglycemia: final results of the Glucontrol study, Intensive Care Med, 33, S189
Cited by
Sorted by citations
Items 201–300 of 410
Firouzabadi, M. D., Poopak, A., Sheikhy, A., Samimi, S., Nakhaei, P., Firouzabadi, F. D., Moosaie, F., Rabizadeh, S., Nakhjavani, M., & Esteghamati, A. (2022) · Primary care diabetes · doi:10.1016/j.pcd.2022.11.011 · Cited by 18
Paula, J. S., Braga, L. D. D. C., Moreira, R. O., & Kupfer, R. (2016) · Archives of Endocrinology and Metabolism · doi:10.1590/2359-3997000000222 · Cited by 18
Postoperative Glycemic Variability as a Predictor of Adverse Outcomes Following Lumbar Fusion
Canseco, J. A., Chang, M. P., Karamian, B. A., Nicholson, K. J., Patel, P. D., Shenoy, K., Hartman, J., Kurd, M. F., Rihn, J. A., Anderson, D. G., et al. (2021) · Spine · doi:10.1097/brs.0000000000004214 · Cited by 17
Wang, S., Tan, Z., Wu, T., Shen, Q., Huang, P., Wang, L., Liu, W., Song, H., Lin, M., Shi, X., et al. (2022) · Frontiers in Endocrinology · doi:10.3389/fendo.2022.858912 · Cited by 18
Han, H., Lai, J., Yan, C., Li, X., Hu, S., He, Y., & Li, H. (2022) · BMC Surgery · doi:10.1186/s12893-022-01601-3 · Cited by 17
Hatamoto, Y., Tanoue, Y., Yoshimura, E., Matsumoto, M., Hayashi, T., Ogata, H., Tanaka, S., Tanaka, H., & Higaki, Y. (2023) · Journal of Nutrition · doi:10.1016/j.tjnut.2022.12.024 · Cited by 18
Gad, H., Elgassim, E., Mohammed, I., Alhaddad, A. Y., Aly, H., Cabibihan, J., Al-Ali, A. K., Sadasivuni, K. K., Petropoulos, I. N., Ponirakis, G., et al. (2023) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2023.110670 · Cited by 16
Heart Failure in Type 1 Diabetes: A Complication of Concern? A Narrative Review
Gómez‐Pérez, A. M., Damas-Fuentes, M., Cornejo-Pareja, I. M., & Tinahones, F. J. (2021) · Journal of Clinical Medicine · doi:10.3390/jcm10194497 · Cited by 18
Takahara, S., Ikeda, K., Fujimoto, S., Asai, K., Oguri, Y., Harashima, S., Tsuji, H., Shide, K., & Inagaki, N. (2015) · Journal of Diabetes Investigation · doi:10.1111/jdi.12360 · Cited by 18
Riboldi, B. P., Luft, V. C., de Castilhos, C. D., de Cardoso, L. O., Schmidt, M. I., Barreto, S. M., de Sander, M. F., Matos, S. M. A., & Duncan, B. B. (2015) · Cardiovascular Diabetology · doi:10.1186/s12933-015-0181-8 · Cited by 17
Zhao, Y., Zheng, Y., Tian, Y., Yu, Q., Qin, L., Xu, K., Sun, B., Benedict, C., Chen, B., Wei, L., et al. (2022) · Diabetes Obesity and Metabolism · doi:10.1111/dom.14930 · Cited by 16
Goh, A. T., Yao, J., Chua, X. H., Whitton, C., van Dam, R. M., & Forde, C. G. (2023) · Food & Function · doi:10.1039/d2fo03060h · Cited by 16
Uncoupling Protein 2 Inhibition Exacerbates Glucose Fluctuation-Mediated Neuronal Effects
Cardoso, S., Seiça, R. M. F., & Moreira, P. I. (2017) · Neurotoxicity Research · doi:10.1007/s12640-017-9805-y · Cited by 16
Menting, J., Nikolaus, S., Wiborg, J. F., Bazelmans, E., Goedendorp, M. M., van Bon, A. C., van den Bergh, J. P., Mol, M. J. T. M., Tack, C. J., & Knoop, H. (2015) · Trials · doi:10.1186/s13063-015-0764-4 · Cited by 17
Rook, K. S., August, K. J., CHOI, S. E., Franks, M. M., & Stephens, M. A. P. (2015) · Journal of Health Psychology · doi:10.1177/1359105315581064 · Cited by 16
Lin, Y., Huang, Y., Chen, H., Hsieh, S., Sun, J., Chen, S., & Lin, C.-H. (2019) · Diabetes Therapy · doi:10.1007/s13300-019-00707-x · Cited by 18
Fuentes, B., Yvorra, S. P., Gutiérrez-Zúñiga, R., de Villar, N. G. P., de Celis, E., Rodríguez‐Pardo, J., Frutos, M. C. G.-D., Laso-García, F., Gutiérrez‐Fernández, M., Ortega-Casarrubios, M. D. L. Á., et al. (2020) · Journal of Translational Medicine · doi:10.1186/s12967-020-02586-4 · Cited by 16
Wang, C., Song, J., Ma, Z., Yang, W., Li, C., Zhang, X., Hou, X., Sun, Y. S., Lin, P., Liang, K., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0102941 · Cited by 15
Identifying subpopulations of septic patients: A temporal data-driven approach
Sharafoddini, A., Dubin, J. A., & Lee, J. (2020) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2020.104182 · Cited by 15
Kawaguchi, Y., Miyamoto, S., Hajika, Y., Ashida, N., Hirota, T., Masumoto, K., Sawa, J., Hamazaki, K., & Kumeda, Y. (2022) · Advances in Therapy · doi:10.1007/s12325-022-02138-w · Cited by 15
Lartey, A. H., Li, X., Li, Z., Zhang, Q., & Wang, J. (2021) · BMC Public Health · doi:10.1186/s12889-021-10367-x · Cited by 15
Kietsiriroje, N., Pearson, S. M., O’Mahoney, L. L., West, D. J., Ariëns, R. A. S., Ajjan, R., & Campbell, M. D. (2022) · Diabetes and Vascular Disease Research · doi:10.1177/14791641221103217 · Cited by 15
Tura, A., Farngren, J., Schweizer, A., Foley, J. E., Pacini, G., & Åhrén, B. (2015) · International Journal of Endocrinology · doi:10.1155/2015/484231 · Cited by 14
Cuesta–Frau, D., Novák, D., Burda, V., Molina, Á., Vargas, B., Mráz, M., Kaválková, P., Beneš, M., & Haluzı́k, M. (2018) · Entropy · doi:10.3390/e20110871 · Cited by 14
Kim, H. M., Lim, J. S., Lee, B., Kang, E. S., Lee, H. C., & Soo, B. (2015) · Endocrinology and Metabolism · doi:10.3803/enm.2015.30.1.84 · Cited by 14
Thomsen, M. N., Skytte, M. J., Astrup, A. V., Deacon, C. F., Holst, J. J., Madsbad, S., Krarup, T., Haugaard, S. B., & Samkani, A. (2020) · Clinical Nutrition ESPEN · doi:10.1016/j.clnesp.2020.07.002 · Cited by 22
Batule, S., Ramos, A., Pérez-Montes de Oca, A., Fuentes, N., Martínez, S., Raga, J., Pena, X., Tural, C., Muñoz, P., Soldevila, B., et al. (2022) · Journal of Clinical Medicine · doi:10.3390/jcm11102813 · Cited by 13
Kawaguchi, Y., Sawa, J., & Kumeda, Y. (2020) · Diabetes Therapy · doi:10.1007/s13300-020-00940-9 · Cited by 13
Brancato, D., Saura, G., Fleres, M., Ferrara, L., Scorsone, A., Aiello, V., Noto, A. D., Spanò, L., & Provenzano, V. (2013) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2013.0030 · Cited by 13
Variability analysis and the diagnosis, management and treatment of sepsis
Buchan, C. A., Bravi, A., & SEELY, A. J. E. (2012) · Journal of Critical Care · doi:10.1016/j.jcrc.2012.10.060 · Cited by 13
Siegelaar, S. E., Hoekstra, J. B. L., & DeVries, J. H. (2011) · Best Practice & Research Clinical Endocrinology & Metabolism · doi:10.1016/j.beem.2011.03.004 · Cited by 13
Self-citationDevoting attention to glucose variability and hypoglycaemia in type 2 diabetes
Rutter, M. K. (2017) · Diabetologia · doi:10.1007/s00125-017-4421-1 · Cited by 14
Glycaemia dynamics in gestational diabetes mellitus
Valero, P., Salas, R., Pardo, F., Cornejo, M., Fuentes, G., Vega, S., Grismaldo, A., Hillebrands, J., van der Beek, E. M., van Goor, H., et al. (2022) · Biochimica et Biophysica Acta (BBA) - General Subjects · doi:10.1016/j.bbagen.2022.130134 · Cited by 12
Chan, N. B., Li, W., Aung, T., Bazuaye, E., & Montero, R. (2023) · JMIR AI · doi:10.2196/45450 · Cited by 13
Hulse, A., Rai, S., & KUMAR, K. M. P. (2016) · Indian Journal of Endocrinology and Metabolism · doi:10.4103/2230-8210.190546 · Cited by 12
Continuous glucose monitoring to assess glucose variability in type 3c diabetes
Lee, V. T. Y., Poynten, A. M., & Depczynski, B. (2022) · Diabetic Medicine · doi:10.1111/dme.14882 · Cited by 15
Biological variation of cardiovascular risk factors in patients with diabetes
Dawson, A. J., Sathyapalan, T., Atkin, S. L., & Kilpatrick, E. S. (2013) · Diabetic Medicine · doi:10.1111/dme.12160 · Cited by 12
Suzuki, R., Eiki, J., Moritoyo, T., Furihata, K., Wakana, A., Ohta, Y., Tokita, S., & Kadowaki, T. (2018) · Diabetes Obesity and Metabolism · doi:10.1111/dom.13364 · Cited by 12
Soriano, E. C., Lenhard, J. M., Gonzalez, J. S., Tennen, H. A., Chow, S., Otto, A. K., Perndorfer, C., Shen, B., Siegel, S. D., & Laurenceau, J. (2020) · Annals of Behavioral Medicine · doi:10.1093/abm/kaaa038 · Cited by 15
Saulnier, P., Briet, C., Gand, E., Chaillous, L., Dubois, S. G., Bonnet, F., Leguerrier, A.-M., Fradet, G., Crespin, I. D., Kerlan, V., et al. (2019) · Journal of Diabetes and its Complications · doi:10.1016/j.jdiacomp.2019.05.003 · Cited by 13
Hyperglycemia in-hospital management
Prieto, L. M. (2011) · Therapeutic Advances in Endocrinology and Metabolism · doi:10.1177/2042018810397083 · Cited by 12
Branco, R. G., & Tasker, R. C. (2010) · Pediatric Critical Care Medicine · doi:10.1097/pcc.0b013e3181f4d606 · Cited by 12
Zhang, K., Fu, Y., Gou, W., Miao, Z., Tian, Y., Liang, Y., Liang, X., Shuai, M., Xiao, C., Wang, J., et al. (2025) · American Journal of Clinical Nutrition · doi:10.1016/j.ajcnut.2025.04.015 · Cited by 12
Liu, D., Fan, Y., Zhuang, Y., Hu, P. C., Gao, C., & Chen, Y. (2022) · Journal of Inflammation Research · doi:10.2147/jir.s383053 · Cited by 14
Oh, S., Purja, S., Shin, H., Kim, M., & Kim, E. Y. (2022) · Diabetes and Vascular Disease Research · doi:10.1177/14791641221106866 · Cited by 14
Ciechanowska, A., Góra, I. M., Sabalińska, S., & Ładyżyński, P. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23126704 · Cited by 11
Chiu, P., Wu, C., Huang, C.-H., Liou, H., Chang, C., Chang, H.-R., & Chang, C.-C. (2014) · PLoS ONE · doi:10.1371/journal.pone.0108531 · Cited by 11
Yano, Y., Hayakawa, M., Kuroki, K., Ueno, H., Yamagishi, S., Takeuchi, M., Eto, T., Nagata, N., Nakazato, M., Shimada, K., et al. (2013) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2012.12.006 · Cited by 11
VanDyke, R. D., Ren, Y., Sucharew, H. J., Miodovnik, M., Rosenn, B., & Khoury, J. C. (2011) · The Journal of Maternal-Fetal & Neonatal Medicine · doi:10.3109/14767058.2012.626922 · Cited by 11
Bessho, M., Murase‐Mishiba, Y., Tsutsumi, C., Haseda, F., Imagawa, A., Terasaki, J., & Hanafusa, T. (2013) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2013.09.003 · Cited by 11
Mohan, V., Pramodkumar, T. A., Jayashri, R., Gokulakrishnan, K., Velmurugan, K., Pradeepa, R., & Anjana, R. M. (2016) · Indian Journal of Endocrinology and Metabolism · doi:10.4103/2230-8210.190559 · Cited by 13
Urinary C-Peptide Excretion for Diabetic Treatment in Low Carbohydrate Diet (LCD)
Bando, H., Ebe, K., Muneta, T., Bando, M., & Yonei, Y. (2018) · Journal of Obesity and Diabetes · doi:10.33805/2638-812x.103 · Cited by 11
Liu, C.-S., Li, C., Wang, M., Yang, S.-Y., Li, T., & Lin, C. (2020) · Diabetes Obesity and Metabolism · doi:10.1111/dom.14240 · Cited by 12
Zucchini, S., Scipione, M., Balsamo, C., Maltoni, G., Rollo, A., Molinari, E., Mangoni, L., & Cicognani, A. (2011) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2011.0080 · Cited by 13
Control of Glycogen Content in Retina: Allosteric Regulation of Glycogen Synthase
Osorio-Paz, I., Sánchez‐Chávez, G., & Salceda, R. (2012) · PLoS ONE · doi:10.1371/journal.pone.0030822 · Cited by 11
Kawaguchi, Y., Sawa, J., Hamai, C., Nishimura, Y., & Kumeda, Y. (2019) · Journal of Diabetes Investigation · doi:10.1111/jdi.13038 · Cited by 10
Valente, T., Valente, F., Lucchesi, M. B. B., Punaro, G., Mouro, M. G., Gabbay, M. A. L., Higa, E. M. S., & Dib, S. A. (2021) · Archives of Endocrinology and Metabolism · doi:10.20945/2359-3997000000338 · Cited by 10
Yang, Y., Long, C., Li, T., & Chen, Q. (2022) · Frontiers in Endocrinology · doi:10.3389/fendo.2022.890090 · Cited by 11
Hypoglycemia and Blood Glucose Fluctuations in the Application of a Sensor-Augmented Insulin Pump
Luo, P., Cheng, Q., Chen, B., Li, Y., Wu, J., Zhang, X., Jiao, X., Zhao, J., & Lv, X. (2013) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2013.0078 · Cited by 10
Wolahan, S. M., Prins, M. L., McArthur, D. L., Real, C. R., Hovda, D. A., Martin, N. A., Vespa, P. M., & Glenn, T. C. (2016) · Neurocritical Care · doi:10.1007/s12028-016-0313-3 · Cited by 10
Blood Glucose Variability and Outcomes in Critically III Children
Lal, R., Baronia, A. K., Naranje, K., Poddar, B., Bhriguvanshi, A., & Singh, R. K. (2017) · Indian Journal of Critical Care Medicine · doi:10.4103/ijccm.ijccm_364_16 · Cited by 10
Beyond hyperglycemia: glycaemic variability as a prognostic factor after acute ischemic stroke
Gutiérrez-Zúñiga, R., de Leciñana, M. A., Delgado‐Mederos, R., Gállego-Culleré, J., Rodríguez‐Yáñez, M., Martínez-Zabaleta, M., Freijo, M. M., Portilla-Cuenca, J. C., Gil-Núñez, A., Sebastián, J. D., et al. (2023) · Neurología (English Edition) · doi:10.1016/j.nrleng.2020.06.017 · Cited by 10
González-Heredia, T., Hernández-Corona, D. M., González-Ortı́z, M., & Martínez‐Abundis, E. (2017) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2017.0020 · Cited by 10
Spanakis, E. K., Singh, L. G., Siddiqui, T., Sorkin, J. D., Notas, G., Magee, M. F., Fink, J. C., Zhan, M., & Umpierrez, G. E. (2020) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2019-000990 · Cited by 10
Hatamoto, Y., Yoshimura, E., Tomiga-Takae, R., Komiyama, T., Matsumoto, M., Higaki, Y., & Tanaka, H. (2021) · Nutrition Metabolism and Cardiovascular Diseases · doi:10.1016/j.numecd.2021.03.006 · Cited by 9
Tros, F., Meirhaeghe, A., Hadjadj, S., Amouyel, P., Bougneres, P. F., & Fradin, D. (2014) · Physiological Reports · doi:10.14814/phy2.12076 · Cited by 10
Catalogna, M., Doenyas‐Barak, K., Sagi, R., Hamad, R. A., Nevo, U., Ben‐Jacob, E., & Efrati, S. (2016) · PLoS ONE · doi:10.1371/journal.pone.0168805 · Cited by 9
Current insulin analogues in the treatment of diabetes: emphasis on type 2 diabetes
Esposito, K., & Giugliano, D. (2012) · Expert Opinion on Biological Therapy · doi:10.1517/14712598.2012.648181 · Cited by 9
Strilka, R. J., Stull, M. C., Clemens, M. S., McCaver, S. C., & Armen, S. B. (2016) · Theoretical Biology and Medical Modelling · doi:10.1186/s12976-016-0029-2 · Cited by 9
Inzucchi, S. E., Umpierrez, G. E., DIGENIO, A. G., Zhou, R., & Kovatchev, B. P. (2015) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2015.09.002 · Cited by 9
Continuous Glucose Monitoring during Critical Care
Inzucchi, S. E., & Kosiborod, M. (2010) · Anesthesiology · doi:10.1097/aln.0b013e3181ff419e · Cited by 9
Zhu, Q., Zong, Q., Guo, S., Ye, H., Ma, Z., Zhang, R., Zou, H., & Ba, Y. (2025) · Diabetes Obesity and Metabolism · doi:10.1111/dom.16410 · Cited by 8
Lin, C.-H., Huang, C., Tsai, J.-S., Hsieh, S., Sun, J., Huang, B.-Y., Mj, H., & Huang, Y. (2011) · Endocrine Journal · doi:10.1507/endocrj.ej11-0036 · Cited by 8
Effect of Low Carbohydrate Diet (LCD) for Diabetic Patients withHypertriglycemia
Ebe, K., Bando, H., Muneta, T., Bando, M., & Yonei, Y. (2017) · Institutional Repositories DataBase (IRDB) · Cited by 7
Kawaguchi, Y., Hajika, Y., Rinka, M., Masumoto, K., Sawa, J., Hamazaki, K., & Kumeda, Y. (2024) · Journal of Diabetes Investigation · doi:10.1111/jdi.14151 · Cited by 12
Yuan, S., & Shen, J. (2020) · Current Medical Science · doi:10.1007/s11596-020-2209-x · Cited by 8
Postoperative Glycemic Variability and Adverse Outcomes After Posterior Cervical Fusion
Patel, P. D., Canseco, J. A., Wilt, Z. T., Okroj, K. T., Chang, M. P., Reyes, A. A., Bowles, D. R., Kurd, M. F., Rihn, J. A., Anderson, D. G., et al. (2020) · Journal of the American Academy of Orthopaedic Surgeons · doi:10.5435/jaaos-d-20-00126 · Cited by 8
Glucose forecasting using genetic programming and latent glucose variability features
Contador, S., Velasco, J. M., Garnica, Ó., & Hidalgo, J. I. (2021) · Applied Soft Computing · doi:10.1016/j.asoc.2021.107609 · Cited by 8
Kawaguchi, Y., Miyamoto, S., Hajika, Y., Ashida, N., Masumoto, K., Sawa, J., Hamazaki, K., & Kumeda, Y. (2021) · Journal of Diabetes Investigation · doi:10.1111/jdi.13677 · Cited by 8
Ashkenazi, I., Morgan, S. B., Graif, N., Shaked, O., Shohat, N., Khoury, A., Snir, N., & Warschawski, Y. (2022) · Archives of Orthopaedic and Trauma Surgery · doi:10.1007/s00402-022-04558-3 · Cited by 8
Gottfried, S., Pontiggia, L., Newberg, A. B., Laynor, G., & Monti, D. (2022) · BMJ Open · doi:10.1136/bmjopen-2022-061756 · Cited by 8
Dungan, K. M., Osei, K., Gaillard, T. R., Moore, J., & Binkley, P. F. (2014) · Diabetes/Metabolism Research and Reviews · doi:10.1002/dmrr.2569 · Cited by 8
Behavior monitoring under uncertainty using Bayesian surprise and optimal action selection
Ávila, L. O., & Martinez, E. C. (2014) · Expert Systems with Applications · doi:10.1016/j.eswa.2014.04.031 · Cited by 8
Walker, G. S., Cunningham, S. G., Sainsbury, C. A. R., & Jones, G. C. (2017) · Diabetic Medicine · doi:10.1111/dme.13455 · Cited by 8
Ye, Y., Pan, B., Gu, M., Xian, G., Chen, W., Zheng, L., Zhang, Z., & Sheng, P. (2020) · Journal of Orthopaedic Surgery and Research · doi:10.1186/s13018-020-02029-2 · Cited by 8
Zhang, X., Zhang, J., Li, J., Gao, Y., Li, R., Jin, X., Wang, X., Huang, Y., & Wang, G. (2021) · Scientific Reports · doi:10.1038/s41598-021-87409-2 · Cited by 7
Strilka, R. J., Armen, S. B., & INDECK, M. C. (2014) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2014.04.023 · Cited by 8
Mahin, D., Lavasani, S. M., Cristobal, L., Patel, N. T., Sedrak, M. S., Stewart, D. B., Waisman, J. R., Yuan, Y., Yu, W., Samoa, R. A., et al. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12051906 · Cited by 7
Investigation of Uric Acid and Cystatin C on Low-Carbohydrate Diet (LCD)
Bando, H., Ebe, K., Muneta, T., Bando, M., & Yonei, Y. (2017) · Diabetes Research - Open Journal · doi:10.17140/droj-3-133 · Cited by 7
Time-dependent glycemic variability and mortality in critically ill patients with diabetes*
Umpierrez, G. E., & Smiley, D. D. (2010) · Critical Care Medicine · doi:10.1097/ccm.0b013e318202e7c0 · Cited by 7
Guilmin‐Crépon, S., Carel, J., Schroedt, J., Scornet, E., Alberti, C., Tubiana‐Rufi, N., & on behalf of the Start-In! Study Group (2018) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2017.0404 · Cited by 8
Antsiferov, M. B., Galstyan, G. R., Zilov, A. V., Mayorov, A. Y., Markova, T. N., Demidov, N. A. D., Koteshkova, O. M. K., Лаптев, Д. Н., & Vitebskaya, A. V. (2019) · Diabetes Mellitus · doi:10.14341/dm10227 · Cited by 8
Investigation of Area under the Curves for Insulin Secretion in Diabetes
Bando, H., Ebe, K., Muneta, T., Bando, M., & Yonei, Y. (2018) · International Journal of Biotechnology and Recent Advances · doi:10.18689/ijbr-1000105 · Cited by 6
Dupas, B., Feldman-Billard, S., Quoc, E. B., Erginay, A., Guillausseau, P.-J., & Massin, P. (2014) · Acta Ophthalmologica · doi:10.1111/aos.12369 · Cited by 6
Different antihyperglycaemic drug effects on glycaemic variability in Type 2 diabetic patients
Babenko, A. Y., Krasilnikova, E. I., Lykhonosov, M. P., Likhonosova, A. P., & Grineva, E. N. (2014) · Diabetes Mellitus · doi:10.14341/dm2014472-80 · Cited by 6
Prídavková, D., Samoš, M., Kazimierová, I., Šutarík, Ľ., Fraňová, S., Galajda, P., & Mokáň, M. (2018) · Obesity Facts · doi:10.1159/000493734 · Cited by 6
CHANDRAN, S. R., Tan, H. C., Chen, Q., Lee, P. C., Gardner, D. S.-L., Chin, Y. A., Lam, A. Y. R., Teh, M. M., & Bee, Y. M. (2023) · Journal of Diabetes Science and Technology · doi:10.1177/19322968231157387 · Cited by 5
Lee, W., Kim, N., Jung, I., Park, S. Y., Yu, J. H., Seo, J. A., Kim, J., Kim, K. J., Kim, N. H., Yoo, H. J., et al. (2023) · Diabetes & Metabolism Journal · doi:10.4093/dmj.2022.0273 · Cited by 6
Gutiérrez-Zúñiga, R., de Leciñana, M. A., Delgado‐Mederos, R., Gállego-Culleré, J., Rodríguez‐Yáñez, M., Martínez-Zabaleta, M., Freijo, M. M., Portilla-Cuenca, J. C., Gil-Núñez, A., Sebastián, J. D., et al. (2020) · Neurología · doi:10.1016/j.nrl.2020.06.018 · Cited by 6
Strilka, R., Sjulin, T., Huprikar, N., Cameron, L., Woody, P. W., & Armen, S. B. (2020) · International Journal of Critical Illness and Injury Science · doi:10.4103/ijciis.ijciis_112_19 · Cited by 7
Metadata
- Authors
- Siegelaar, S. E., Holleman, F., Hoekstra, J. B. L., & DeVries, J. H.
- Affiliations
- Amsterdam UMC Location University of Amsterdam (NL)
- Corresponding author
- Siegelaar, Sarah E.
- Venue
- Endocrine Reviews
- Publisher
- The Endocrine Society
- Published
- 2010-04-01
- Volume
- 31
- Issue
- 2
- Pages
- 171-182
- ISSN
- 0163-769X (ISSN-L)
- 1945-7189
- OpenAlex
- W2100202103
- Cited by
- 409
- References
- 80
- Citations by year
- 2026: 6 · 2025: 10 · 2024: 11 · 2023: 13 · 2022: 28 · 2021: 25 · 2020: 25 · 2019: 30 · 2018: 30 · 2017: 25 · 2016: 26 · 2015: 33 · 2014: 40 · 2013: 37 · 2012: 30
- FWCI
- 4.79
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Endocrine Reviews (publishedVersion)
- PubMed (publishedVersion)
- Pure Amsterdam UMC (publishedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Hyperglycemia and glycemic control in critically ill and hospitalized patients
- Keywords
- glycemic variability, type 1 diabetes, type 2 diabetes, oxidative stress, microvascular complications, diabetic retinopathy, diabetic nephropathy, diabetic neuropathy, hypoglycemia, glycemic control, HbA1c, glycemic excursions, mortality
- MeSH terms
- Animals, Blood Glucose, Diabetes Mellitus, Humans, Hypoglycemia, Insulin, Blood Glucose Self-Monitoring, Oxidative Stress, Diabetes Complications
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review