- -

Influence of glucometric 'dynamical' variables on Duodenal-Jejunal Bypass Liner (DJBL) anthropometric and metabolic outcomes

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Influence of glucometric 'dynamical' variables on Duodenal-Jejunal Bypass Liner (DJBL) anthropometric and metabolic outcomes

Mostrar el registro sencillo del ítem

Ficheros en el ítem

dc.contributor.author Colás, Ana es_ES
dc.contributor.author Varela, Manuel es_ES
dc.contributor.author Mraz, Milos es_ES
dc.contributor.author Novak, Daniel es_ES
dc.contributor.author Cuesta Frau, David es_ES
dc.contributor.author Vigil, Luis es_ES
dc.contributor.author Benes, Marek es_ES
dc.contributor.author Pelikanova, Terezie es_ES
dc.contributor.author Haluzik, Martin es_ES
dc.contributor.author Burda, Vaclav es_ES
dc.contributor.author Vargas, Borja es_ES
dc.date.accessioned 2021-06-12T03:33:49Z
dc.date.available 2021-06-12T03:33:49Z
dc.date.issued 2020-05 es_ES
dc.identifier.issn 1520-7552 es_ES
dc.identifier.uri http://hdl.handle.net/10251/167868
dc.description.abstract [EN] Background The endoscopically implanted duodenal-jejunal bypass liner (DJBL) is an attractive alternative to bariatric surgery for obese diabetic patients. This article aims to study dynamical aspects of the glycaemic profile that may influence DJBL effects. Methods Thirty patients underwent DJBL implantation and were followed for 10 months. Continuous glucose monitoring (CGM) was performed before implantation and at month 10. Dynamical variables from CGM were measured: coefficient of variation of glycaemia, mean amplitude of glycaemic excursions (MAGE), detrended fluctuation analysis (DFA), % of time with glycaemia under 6.1 mmol/L (TU6.1), area over 7.8 mmol/L (AO7.8) and time in range. We analysed the correlation between changes in both anthropometric (body mass index, BMI and waist circumference) and metabolic (fasting blood glucose, FBG and HbA1c) variables and dynamical CGM-derived metrics and searched for variables in the basal CGM that could predict successful outcomes. Results There was a poor correlation between anthropometric and metabolic outcomes. There was a strong correlation between anthropometric changes and changes in glycaemic tonic control ( increment BMI- increment TU6.1: rho = - 0.67, P < .01) and between metabolic outcomes and glycaemic phasic control ( increment FBG- increment AO7.8: r = .60, P < .01). Basal AO7.8 was a powerful predictor of successful metabolic outcome (0.85 in patients with AO7.8 above the median vs 0.31 in patients with AO7.8 below the median: Chi-squared = 5.67, P = .02). Conclusions In our population, anthropometric outcomes of DJBL correlate with improvement in tonic control of glycaemia, while metabolic outcomes correlate preferentially with improvement in phasic control. Assessment of basal phasic control may help in candidate profiling for DJBL implantation. es_ES
dc.description.sponsorship Research Center for Informatics, Grant/Award Number: CZ.02.1.01/0.0/0.0/16_019/0000765; Biomedical data acquisition, processing and visualization, Grant/Award Number: SGS19/171/OHK3/3T/13; MH CZ - DRO ("IKEM, IN 00023001"); RVO VFN64165 es_ES
dc.language Inglés es_ES
dc.publisher John Wiley & Sons es_ES
dc.relation.ispartof Diabetes/Metabolism Research and Reviews es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Diabesity es_ES
dc.subject Type 2 diabetes mellitus es_ES
dc.subject Continuous glucose monitoring es_ES
dc.subject Duodenal-jejunal bypass liner (DJBL) es_ES
dc.subject Metabolic surgery es_ES
dc.subject Detrended fluctuation analysis (DFA) es_ES
dc.subject.classification ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES es_ES
dc.title Influence of glucometric 'dynamical' variables on Duodenal-Jejunal Bypass Liner (DJBL) anthropometric and metabolic outcomes es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1002/dmrr.3287 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/CVUT//CZ.02.1.01%2F0.0%2F0.0%2F16-019%2F0000765/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MZCR//DRO IKEM 000023001/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MZCR//RVO VFN 64165/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/CVUT//SGS19%2F171%2FOHK3%2F3T%2F13/ es_ES
dc.rights.accessRights Cerrado es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors es_ES
dc.description.bibliographicCitation Colás, A.; Varela, M.; Mraz, M.; Novak, D.; Cuesta Frau, D.; Vigil, L.; Benes, M.... (2020). Influence of glucometric 'dynamical' variables on Duodenal-Jejunal Bypass Liner (DJBL) anthropometric and metabolic outcomes. Diabetes/Metabolism Research and Reviews. 36(4):1-9. https://doi.org/10.1002/dmrr.3287 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1002/dmrr.3287 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 9 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 36 es_ES
dc.description.issue 4 es_ES
dc.identifier.pmid 31916665 es_ES
dc.relation.pasarela S\401352 es_ES
dc.contributor.funder Czech Technical University in Prague es_ES
dc.contributor.funder Ministry of Health, República Checa es_ES
dc.description.references O’Rahilly, S., & Savill, J. (1997). Science, medicine, and the future Non-insulin dependent diabetes mellitus: the gathering storm. BMJ, 314(7085), 955-955. doi:10.1136/bmj.314.7085.955 es_ES
dc.description.references World Health Organization.Global Health Risks: Mortality and Burden of Disease Attributable to Selected Major Risks.Geneva:World Health Organization.2009; 62 p. es_ES
dc.description.references Hossain, P., Kawar, B., & El Nahas, M. (2007). Obesity and Diabetes in the Developing World — A Growing Challenge. New England Journal of Medicine, 356(3), 213-215. doi:10.1056/nejmp068177 es_ES
dc.description.references Ogurtsova, K., da Rocha Fernandes, J. D., Huang, Y., Linnenkamp, U., Guariguata, L., Cho, N. H., … Makaroff, L. E. (2017). IDF Diabetes Atlas: Global estimates for the prevalence of diabetes for 2015 and 2040. Diabetes Research and Clinical Practice, 128, 40-50. doi:10.1016/j.diabres.2017.03.024 es_ES
dc.description.references Beagley, J., Guariguata, L., Weil, C., & Motala, A. A. (2014). Global estimates of undiagnosed diabetes in adults. Diabetes Research and Clinical Practice, 103(2), 150-160. doi:10.1016/j.diabres.2013.11.001 es_ES
dc.description.references Zimmet, P., Alberti, K. G. M. M., & Shaw, J. (2001). Global and societal implications of the diabetes epidemic. Nature, 414(6865), 782-787. doi:10.1038/414782a es_ES
dc.description.references Chatterjee, S., Khunti, K., & Davies, M. J. (2017). Type 2 diabetes. The Lancet, 389(10085), 2239-2251. doi:10.1016/s0140-6736(17)30058-2 es_ES
dc.description.references Haffner, S. M., Lehto, S., Rönnemaa, T., Pyörälä, K., & Laakso, M. (1998). Mortality from Coronary Heart Disease in Subjects with Type 2 Diabetes and in Nondiabetic Subjects with and without Prior Myocardial Infarction. New England Journal of Medicine, 339(4), 229-234. doi:10.1056/nejm199807233390404 es_ES
dc.description.references Rubino, F., & Cummings, D. E. (2012). The coming of age of metabolic surgery. Nature Reviews Endocrinology, 8(12), 702-704. doi:10.1038/nrendo.2012.207 es_ES
dc.description.references Pournaras, D. J., Glicksman, C., Vincent, R. P., Kuganolipava, S., Alaghband-Zadeh, J., Mahon, D., … le Roux, C. W. (2012). The Role of Bile After Roux-en-Y Gastric Bypass in Promoting Weight Loss and Improving Glycaemic Control. Endocrinology, 153(8), 3613-3619. doi:10.1210/en.2011-2145 es_ES
dc.description.references Cummings, D. E. (2009). Endocrine mechanisms mediating remission of diabetes after gastric bypass surgery. International Journal of Obesity, 33(S1), S33-S40. doi:10.1038/ijo.2009.15 es_ES
dc.description.references Ribaric, G., Buchwald, J. N., & McGlennon, T. W. (2013). Diabetes and Weight in Comparative Studies of Bariatric Surgery vs Conventional Medical Therapy: A Systematic Review and Meta-Analysis. Obesity Surgery, 24(3), 437-455. doi:10.1007/s11695-013-1160-3 es_ES
dc.description.references Kwok, C. S., Pradhan, A., Khan, M. A., Anderson, S. G., Keavney, B. D., Myint, P. K., … Loke, Y. K. (2014). Bariatric surgery and its impact on cardiovascular disease and mortality: A systematic review and meta-analysis. International Journal of Cardiology, 173(1), 20-28. doi:10.1016/j.ijcard.2014.02.026 es_ES
dc.description.references Rubino, F., Nathan, D. M., Eckel, R. H., Schauer, P. R., Alberti, K. G. M. M., Zimmet, P. Z., … Cummings, D. E. (2016). Metabolic Surgery in the Treatment Algorithm for Type 2 Diabetes: A Joint Statement by International Diabetes Organizations. Diabetes Care, 39(6), 861-877. doi:10.2337/dc16-0236 es_ES
dc.description.references Afonso, B. B., Rosenthal, R., Li, K. M., Zapatier, J., & Szomstein, S. (2010). Perceived barriers to bariatric surgery among morbidly obese patients. Surgery for Obesity and Related Diseases, 6(1), 16-21. doi:10.1016/j.soard.2009.07.006 es_ES
dc.description.references Patel, S. R., Mason, J., & Hakim, N. (2012). The Duodenal-Jejunal Bypass Sleeve (EndoBarrier Gastrointestinal Liner) for Weight Loss and Treatment of Type II Diabetes. Indian Journal of Surgery, 74(4), 275-277. doi:10.1007/s12262-012-0721-3 es_ES
dc.description.references Kumar, N. (2016). Weight loss endoscopy: Development, applications, and current status. World Journal of Gastroenterology, 22(31), 7069. doi:10.3748/wjg.v22.i31.7069 es_ES
dc.description.references Sullivan, S., Edmundowicz, S. A., & Thompson, C. C. (2017). Endoscopic Bariatric and Metabolic Therapies: New and Emerging Technologies. Gastroenterology, 152(7), 1791-1801. doi:10.1053/j.gastro.2017.01.044 es_ES
dc.description.references Rohde, U., Hedbäck, N., Gluud, L. L., Vilsbøll, T., & Knop, F. K. (2016). Effect of the EndoBarrier Gastrointestinal Liner on obesity and type 2 diabetes: a systematic review and meta-analysis. Diabetes, Obesity and Metabolism, 18(3), 300-305. doi:10.1111/dom.12603 es_ES
dc.description.references Rodriguez-Grunert, L., Galvao Neto, M. P., Alamo, M., Ramos, A. C., Baez, P. B., & Tarnoff, M. (2008). First human experience with endoscopically delivered and retrieved duodenal-jejunal bypass sleeve. Surgery for Obesity and Related Diseases, 4(1), 55-59. doi:10.1016/j.soard.2007.07.012 es_ES
dc.description.references Rodriguez, L., Reyes, E., Fagalde, P., Oltra, M. S., Saba, J., Aylwin, C. G., … Sorli, C. (2009). Pilot Clinical Study of an Endoscopic, Removable Duodenal-Jejunal Bypass Liner for the Treatment of Type 2 Diabetes. Diabetes Technology & Therapeutics, 11(11), 725-732. doi:10.1089/dia.2009.0063 es_ES
dc.description.references Escalona, A., Pimentel, F., Sharp, A., Becerra, P., Slako, M., Turiel, D., … Gersin, K. (2012). Weight Loss and Metabolic Improvement in Morbidly Obese Subjects Implanted for 1 Year With an Endoscopic Duodenal-Jejunal Bypass Liner. Annals of Surgery, 255(6), 1080-1085. doi:10.1097/sla.0b013e31825498c4 es_ES
dc.description.references De Jonge, C., Rensen, S. S., Verdam, F. J., Vincent, R. P., Bloom, S. R., Buurman, W. A., … Greve, J. W. M. (2013). Endoscopic Duodenal–Jejunal Bypass Liner Rapidly Improves Type 2 Diabetes. Obesity Surgery, 23(9), 1354-1360. doi:10.1007/s11695-013-0921-3 es_ES
dc.description.references Cohen, R., le Roux, C. W., Papamargaritis, D., Salles, J. E., Petry, T., Correa, J. L., … Sorli, C. (2013). Role of proximal gut exclusion from food on glucose homeostasis in patients with Type 2 diabetes. Diabetic Medicine, 30(12), 1482-1486. doi:10.1111/dme.12268 es_ES
dc.description.references Haluzík, M., Kratochvílová, H., Haluzíková, D., & Mráz, M. (2018). Gut as an emerging organ for the treatment of diabetes: focus on mechanism of action of bariatric and endoscopic interventions. Journal of Endocrinology, 237(1), R1-R17. doi:10.1530/joe-17-0438 es_ES
dc.description.references El Khoury, L., Chouillard, E., Chahine, E., Saikaly, E., Debs, T., & Kassir, R. (2018). Metabolic Surgery and Diabesity: a Systematic Review. Obesity Surgery, 28(7), 2069-2077. doi:10.1007/s11695-018-3252-6 es_ES
dc.description.references Thaler, J. P., & Cummings, D. E. (2009). Hormonal and Metabolic Mechanisms of Diabetes Remission after Gastrointestinal Surgery. Endocrinology, 150(6), 2518-2525. doi:10.1210/en.2009-0367 es_ES
dc.description.references Kaválková, P., Mráz, M., Trachta, P., Kloučková, J., Cinkajzlová, A., Lacinová, Z., … Haluzík, M. (2016). Endocrine effects of duodenal–jejunal exclusion in obese patients with type 2 diabetes mellitus. Journal of Endocrinology, 231(1), 11-22. doi:10.1530/joe-16-0206 es_ES
dc.description.references Mingrone, G., Panunzi, S., De Gaetano, A., Guidone, C., Iaconelli, A., Leccesi, L., … Rubino, F. (2012). Bariatric Surgery versus Conventional Medical Therapy for Type 2 Diabetes. New England Journal of Medicine, 366(17), 1577-1585. doi:10.1056/nejmoa1200111 es_ES
dc.description.references Mingrone, G., Panunzi, S., De Gaetano, A., Guidone, C., Iaconelli, A., Nanni, G., … Rubino, F. (2015). Bariatric–metabolic surgery versus conventional medical treatment in obese patients with type 2 diabetes: 5 year follow-up of an open-label, single-centre, randomised controlled trial. The Lancet, 386(9997), 964-973. doi:10.1016/s0140-6736(15)00075-6 es_ES
dc.description.references Sjöström, L., Peltonen, M., Jacobson, P., Ahlin, S., Andersson-Assarsson, J., Anveden, Å., … Carlsson, L. M. S. (2014). Association of Bariatric Surgery With Long-term Remission of Type 2 Diabetes and With Microvascular and Macrovascular Complications. JAMA, 311(22), 2297. doi:10.1001/jama.2014.5988 es_ES
dc.description.references Monnier, L., Mas, E., Ginet, C., Michel, F., Villon, L., Cristol, J.-P., & Colette, C. (2006). Activation of Oxidative Stress by Acute Glucose Fluctuations Compared With Sustained Chronic Hyperglycemia in Patients With Type 2 Diabetes. JAMA, 295(14), 1681. doi:10.1001/jama.295.14.1681 es_ES
dc.description.references Ceriello, A., Esposito, K., Piconi, L., Ihnat, M. A., Thorpe, J. E., Testa, R., … Giugliano, D. (2008). Oscillating Glucose Is More Deleterious to Endothelial Function and Oxidative Stress Than Mean Glucose in Normal and Type 2 Diabetic Patients. Diabetes, 57(5), 1349-1354. doi:10.2337/db08-0063 es_ES
dc.description.references Di Flaviani, A., Picconi, F., Di Stefano, P., Giordani, I., Malandrucco, I., Maggio, P., … Frontoni, S. (2011). Impact of Glycemic and Blood Pressure Variability on Surrogate Measures of Cardiovascular Outcomes in Type 2 Diabetic Patients. Diabetes Care, 34(7), 1605-1609. doi:10.2337/dc11-0034 es_ES
dc.description.references Nusca, A., Tuccinardi, D., Albano, M., Cavallaro, C., Ricottini, E., Manfrini, S., … Di Sciascio, G. (2018). Glycemic variability in the development of cardiovascular complications in diabetes. Diabetes/Metabolism Research and Reviews, 34(8), e3047. doi:10.1002/dmrr.3047 es_ES
dc.description.references Dungan, K. M., Binkley, P., Nagaraja, H. N., Schuster, D., & Osei, K. (2011). The effect of glycaemic control and glycaemic variability on mortality in patients hospitalized with congestive heart failure. Diabetes/Metabolism Research and Reviews, 27(1), 85-93. doi:10.1002/dmrr.1155 es_ES
dc.description.references Monnier, L., Colette, C., & Owens, D. R. (2009). Integrating glycaemic variability in the glycaemic disorders of type 2 diabetes: a move towards a unified glucose tetrad concept. Diabetes/Metabolism Research and Reviews, 25(5), 393-402. doi:10.1002/dmrr.962 es_ES
dc.description.references Zaccardi, F., Pitocco, D., & Ghirlanda, G. (2009). Glycemic risk factors of diabetic vascular complications: the role of glycemic variability. Diabetes/Metabolism Research and Reviews, 25(3), 199-207. doi:10.1002/dmrr.938 es_ES
dc.description.references Frontoni, S., Di Bartolo, P., Avogaro, A., Bosi, E., Paolisso, G., & Ceriello, A. (2013). Glucose variability: An emerging target for the treatment of diabetes mellitus. Diabetes Research and Clinical Practice, 102(2), 86-95. doi:10.1016/j.diabres.2013.09.007 es_ES
dc.description.references Service, F. J., Molnar, G. D., Rosevear, J. W., Ackerman, E., Gatewood, L. C., & Taylor, W. F. (1970). Mean Amplitude of Glycemic Excursions, a Measure of Diabetic Instability. Diabetes, 19(9), 644-655. doi:10.2337/diab.19.9.644 es_ES
dc.description.references Freire, A. X., & Murillo, L. C. (2010). How «sweet» complexity is and how «bitter» variability can be; the new aspect of intensive care unit hyperglycemia*. Critical Care Medicine, 38(3), 996-997. doi:10.1097/ccm.0b013e3181ce217e es_ES
dc.description.references Lundelin, K., Vigil, L., Bua, S., Gomez-Mestre, I., Honrubia, T., & Varela, M. (2010). Differences in complexity of glycemic profile in survivors and nonsurvivors in an intensive care unit: A pilot study*. Critical Care Medicine, 38(3), 849-854. doi:10.1097/ccm.0b013e3181ce49cf es_ES
dc.description.references Varela, M. (2008). The route to diabetes: Loss of complexity in the glycemic profile from health through the metabolic syndrome to type 2 diabetes. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy, Volume 1, 3-11. doi:10.2147/dmso.s3812 es_ES
dc.description.references Peng, C. ‐K., Havlin, S., Stanley, H. E., & Goldberger, A. L. (1995). Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series. Chaos: An Interdisciplinary Journal of Nonlinear Science, 5(1), 82-87. doi:10.1063/1.166141 es_ES
dc.description.references Ogata, H., Tokuyama, K., Nagasaka, S., Tsuchita, T., Kusaka, I., Ishibashi, S., … Yamamoto, Y. (2012). The lack of long-range negative correlations in glucose dynamics is associated with worse glucose control in patients with diabetes mellitus. Metabolism, 61(7), 1041-1050. doi:10.1016/j.metabol.2011.12.007 es_ES
dc.description.references Rodríguez de Castro, C., Vigil, L., Vargas, B., García Delgado, E., García Carretero, R., Ruiz-Galiana, J., & Varela, M. (2016). Glucose time series complexity as a predictor of type 2 diabetes. Diabetes/Metabolism Research and Reviews, 33(2), e2831. doi:10.1002/dmrr.2831 es_ES
dc.description.references Abdul-Ghani, M. A., Williams, K., DeFronzo, R., & Stern, M. (2006). Risk of Progression to Type 2 Diabetes Based on Relationship Between Postload Plasma Glucose and Fasting Plasma Glucose. Diabetes Care, 29(7), 1613-1618. doi:10.2337/dc05-1711 es_ES
dc.description.references Nathan, D. M., Davidson, M. B., DeFronzo, R. A., Heine, R. J., Henry, R. R., Pratley, R., & Zinman, B. (2007). Impaired Fasting Glucose and Impaired Glucose Tolerance: Implications for care. Diabetes Care, 30(3), 753-759. doi:10.2337/dc07-9920 es_ES
dc.description.references Abdul-Ghani, M. A., Tripathy, D., & DeFronzo, R. A. (2006). Contributions of  -Cell Dysfunction and Insulin Resistance to the Pathogenesis of Impaired Glucose Tolerance and Impaired Fasting Glucose. Diabetes Care, 29(5), 1130-1139. doi:10.2337/dc05-2179 es_ES
dc.description.references Colas, A., Vigil, L., Rodríguez de Castro, C., Vargas, B., & Varela, M. (2018). New insights from continuous glucose monitoring into the route to diabetes. Diabetes/Metabolism Research and Reviews, 34(5), e3002. doi:10.1002/dmrr.3002 es_ES
dc.description.references Meyer, C., Pimenta, W., Woerle, H. J., Van Haeften, T., Szoke, E., Mitrakou, A., & Gerich, J. (2006). Different Mechanisms for Impaired Fasting Glucose and Impaired Postprandial Glucose Tolerance in Humans. Diabetes Care, 29(8), 1909-1914. doi:10.2337/dc06-0438 es_ES
dc.description.references Charles, M. A., Fontbonne, A., Thibult, N., Warnet, J.-M., Rosselin, G. E., & Eschwege, E. (1991). Risk Factors for NIDDM in White Population: Paris Prospective Study. Diabetes, 40(7), 796-799. doi:10.2337/diab.40.7.796 es_ES
dc.description.references Staimez, L. R., Weber, M. B., Ranjani, H., Ali, M. K., Echouffo-Tcheugui, J. B., Phillips, L. S., … Narayan, K. M. V. (2013). Evidence of Reduced β-Cell Function in Asian Indians With Mild Dysglycemia. Diabetes Care, 36(9), 2772-2778. doi:10.2337/dc12-2290 es_ES
dc.description.references Danne, T., Nimri, R., Battelino, T., Bergenstal, R. M., Close, K. L., DeVries, J. H., … Phillip, M. (2017). International Consensus on Use of Continuous Glucose Monitoring. Diabetes Care, 40(12), 1631-1640. doi:10.2337/dc17-1600 es_ES
dc.description.references (2018). 7. Diabetes Technology: Standards of Medical Care in Diabetes—2019. Diabetes Care, 42(Supplement 1), S71-S80. doi:10.2337/dc19-s007 es_ES
dc.description.references Lu, J., Ma, X., Zhou, J., Zhang, L., Mo, Y., Ying, L., … Jia, W. (2018). Association of Time in Range, as Assessed by Continuous Glucose Monitoring, With Diabetic Retinopathy in Type 2 Diabetes. Diabetes Care, 41(11), 2370-2376. doi:10.2337/dc18-1131 es_ES
dc.description.references Dixon, J. B., & O’Brien, P. E. (2002). Health Outcomes of Severely Obese Type 2 Diabetic Subjects 1 Year After Laparoscopic Adjustable Gastric Banding. Diabetes Care, 25(2), 358-363. doi:10.2337/diacare.25.2.358 es_ES
dc.description.references Beck, R. W., Bergenstal, R. M., Riddlesworth, T. D., Kollman, C., Li, Z., Brown, A. S., & Close, K. L. (2018). Validation of Time in Range as an Outcome Measure for Diabetes Clinical Trials. Diabetes Care, 42(3), 400-405. doi:10.2337/dc18-1444 es_ES
dc.description.references (2018). Need for Regulatory Change to Incorporate Beyond A1C Glycemic Metrics. Diabetes Care, 41(6), e92-e94. doi:10.2337/dci18-0010 es_ES
dc.description.references Advani, A. (2019). Positioning time in range in diabetes management. Diabetologia, 63(2), 242-252. doi:10.1007/s00125-019-05027-0 es_ES
dc.description.references Kovatchev, B. P. (2017). Metrics for glycaemic control — from HbA1c to continuous glucose monitoring. Nature Reviews Endocrinology, 13(7), 425-436. doi:10.1038/nrendo.2017.3 es_ES
dc.description.references Narayan, K. M. V. (2016). Type 2 Diabetes: Why We Are Winning the Battle but Losing the War? 2015 Kelly West Award Lecture. Diabetes Care, 39(5), 653-663. doi:10.2337/dc16-0205 es_ES
dc.description.references Bonora, E., Targher, G., Alberiche, M., Bonadonna, R. C., Saggiani, F., Zenere, M. B., … Muggeo, M. (2000). Homeostasis model assessment closely mirrors the glucose clamp technique in the assessment of insulin sensitivity: studies in subjects with various degrees of glucose tolerance and insulin sensitivity. Diabetes Care, 23(1), 57-63. doi:10.2337/diacare.23.1.57 es_ES
dc.description.references Schouten, R., Rijs, C. S., Bouvy, N. D., Hameeteman, W., Koek, G. H., Janssen, I. M. C., & Greve, J.-W. M. (2010). A Multicenter, Randomized Efficacy Study of the EndoBarrier Gastrointestinal Liner for Presurgical Weight Loss Prior to Bariatric Surgery. Annals of Surgery, 251(2), 236-243. doi:10.1097/sla.0b013e3181bdfbff es_ES
dc.description.references Wood, G. C., Mirshahi, T., Still, C. D., & Hirsch, A. G. (2016). Association of DiaRem Score With Cure of Type 2 Diabetes Following Bariatric Surgery. JAMA Surgery, 151(8), 779. doi:10.1001/jamasurg.2016.0251 es_ES
dc.description.references Klonoff, D. C. (2005). Continuous Glucose Monitoring: Roadmap for 21st century diabetes therapy. Diabetes Care, 28(5), 1231-1239. doi:10.2337/diacare.28.5.1231 es_ES
dc.description.references Rodbard, D. (2016). Continuous Glucose Monitoring: A Review of Successes, Challenges, and Opportunities. Diabetes Technology & Therapeutics, 18(S2), S2-3-S2-13. doi:10.1089/dia.2015.0417 es_ES
dc.description.references Buchwald, H., Avidor, Y., Braunwald, E., Jensen, M. D., Pories, W., Fahrbach, K., & Schoelles, K. (2004). Bariatric Surgery. JAMA, 292(14), 1724. doi:10.1001/jama.292.14.1724 es_ES
dc.description.references Koehestanie, P., Betzel, B., Aarts, E. O., Janssen, I. M. C., Wahab, P., & Berends, F. J. (2015). Is reimplantation of the duodenal-jejunal bypass liner feasible? Surgery for Obesity and Related Diseases, 11(5), 1099-1104. doi:10.1016/j.soard.2015.01.016 es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem