CoChat
Sign Up
Cited by 52Diabetes Management and ResearchDiabetes Management and EducationDiabetes and associated disorders

ISPAD Clinical Practice Consensus Guidelines 2024: Glycemic Targets

Open access
de Bock, Martin, Agwu, Juliana Chizo, Deabreu, Matt, Dovc, Klemen, Maahs, David M., Marcovecchio, M. Loredana, Mahmud, Farid H., Nóvoa-Medina, Yeray +3 more·2024·Hormone Research in Paediatrics
DOI 10.1159/000543266PMC PMC11854972
Open this paper in CoChat — free accountOpen PDF

Abstract

Summary of what is New or Different 1. This chapter recommends a target HbA1c of ≤6.5% (48mmol/mol) for those who have access to advanced diabetes technologies like continuous glucose monitoring (CGM) and automated insulin delivery (AID). This target should be encouraged for all children and adolescents living with diabetes when safely achievable. In other settings, the HbA1c target is ≤7.0% (53mmol/mol). The emphasis on the lower HbA1c target is deliberate, based on the growing evidence that achieving HbA1c levels below previous targets can significantly reduce the risk of developing diabetes complications and that when adequate technology and healthcare professional support are available, these lower glycemic targets can be safely achieved without increasing the risk of hypoglycemia or adding to the care burdens. 2. These glycemic goals may be individualized based on an assessment of the potential challenges for the person with diabetes and their caregivers. 3. The relationship between glycemic targets and rates of excess body weight are discussed. 4. The glycemic target chapter is also more succinct compared to previous iterations. This chapter is meant to provide updated guidance on overall glycaemic management alongside other ISPAD consensus guidelines that provide further context and information, including specific populations (e.g. pre-schooler children, limited care settings), or situations (e.g. exercise).

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1159/000543266

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

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?

  • The improvement in time in range and the reduction in HbA1c with AID systems were found with no increase (and in some cases, a reduction) in hypoglycaemia across all age groups.

    “This improvement in time in range and the reduction in HbA₁ c were found with no increase (and in some cases, a reduction) in hypoglycaemia across all age groups. 100”

    From The future of type 1 diabetes therapy (2025) · cites this paper as [100]

    The Abstract says that lower HbA1c targets can be achieved without increasing hypoglycemia risk when adequate technology and professional support are available. The Continuous Glucose Monitoring section sets time-in-range targets, but our copy does not report that AID improved time in range, reduced hypoglycemia in some cases, or produced these outcomes across all age groups. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • Clinical trials and real-world data have shown that AID systems effectively reduce HbA1c, time above range, and time below range, and increase time in range by an average of 10-15 percentage points when compared with standard care.

    “Clinical trials and realworld data have shown that AID systems effectively reduce HbA₁ c , time above range, and time below range, and increase time in range by an average of 10-15 percentage points when compared with standard care.”

    From The future of type 1 diabetes therapy (2025) · cites this paper as [100]

    In The Purpose of Setting Glycemic Targets (page not provided), the guideline identifies AID implementation as one contributor to improved population glycemic metrics. It does not report the claimed reductions in HbA1c, time above range, or time below range versus standard care, or a 10–15-percentage-point increase in time in range. The Glycated Hemoglobin section instead directs readers to a separate guideline for evidence on the efficacy of advanced technologies. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • Although no TITR goal has been universally established, a TITR of higher than 50% is considered a reasonable target.

    “Although no TITR goal has been universally established, a TITR of higher than 50% is considered a reasonable target (figure 3B). 100”

    From The future of type 1 diabetes therapy (2025) · cites this paper as [100]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

No citation lists for this paper

No citation lists for this paper yet — checked again daily.

Cited by 52

Research works printed but not linked: 71

  1. [1]White NH, Cleary PA, Dahms W, Goldstein D, Malone J, Tamborlane WV,. Beneficial effects of intensive therapy of diabetes during adolescence: outcomes after the conclusion of the Diabetes Control and Complications Trial (DCCT). J Pediatr. 2001; 139(6): 804– 12. 11743505
  2. [2]Diabetes Control and Complications Trial Research Group. Effect of intensive diabetes treatment on the development and progression of long-term complications in adolescents with insulin-dependent diabetes mellitus: diabetes control and complications trial. J Pediatr. 1994; 125(2): 177– 88. 8040759
  3. [3]Arnqvist HJ, Ludvigsson J, Nordwall M. Early increase in HbA1c trajectory predicts development of severe microangiopathy in patients with type 1 diabetes: the VISS study. BMJ Open Diabetes Res Care. 2024; 12(3): e003917. PMC11085680 38719508
  4. [4]Arnqvist HJ, Westerlund MC, Fredrikson M, Ludvigsson J, Nordwall M. Impact of HbA1c followed 32 years from diagnosis of type 1 diabetes on development of severe retinopathy and nephropathy: the VISS study. Diabetes Care. 2022; 45(11): 2675– 82. 36094113
  5. [5]Tienhaara E, Falck AAK, Pokka TML, Tossavainen PH. The natural history of emerging diabetic retinopathy and microalbuminuria from prepuberty to early adulthood in type 1 diabetes: a 19-year prospective clinical follow-up study. Diabet Med. 2022; 39(1): e14732. 34687245
  6. [6]Miller RG, Orchard TJ, Costacou T. 30-year cardiovascular disease in type 1 diabetes: risk and risk factors differ by long-term patterns of glycemic control. Diabetes Care. 2022; 45(1): 142– 50. 34782353 PMC8753768
  7. [7]Miller RG, Orchard TJ. Understanding metabolic memory: a tale of two studies. Diabetes. 2020; 69(3): 291– 9. 32079705 PMC7034186
  8. [8]McEwan P, Bennett H, Bolin K, Evans M, Bergenheim K. Assessing the economic value of maintained improvements in type 1 diabetes management, in terms of HbA1c, weight and hypoglycaemic event incidence. Diabet Med. 2018; 35(5): 557– 66. 29377320 PMC5947585
  9. [9]Bak JC, Serné EH, Kramer MHH, Nieuwdorp M, Verheugt CL. National diabetes registries: do they make a difference? Acta Diabetol. 2021; 58(3): 267– 78. 32770407 PMC7907019
  10. [10]Foster NC, Beck RW, Miller KM, Clements MA, Rickels MR, DiMeglio LA,. State of type 1 diabetes management and outcomes from the T1D exchange in 2016–2018. Diabetes Technol Ther. 2019; 21(2): 66– 72. 30657336 PMC7061293
  11. [11]National Institute for Health and Care Excllence (NICE) (published 2015, updated 2023). Diabetes (type 1 and type 2) in children and young people: diagnosis and management. [cited August 21, 2024]; Available from: https://www.nice.org.uk/guidance/ng18 32200593
  12. [12]Holmes-Walker DJ, Abraham MB, Chee M, Jones TW; Australasian Diabetes Data Network ADDN Study Group. Glycaemic outcomes in Australasian children and adults with type 1 diabetes: failure to meet targets across the age spectrum. Intern Med J. 2023; 53(1): 61– 7. 34142758 PMC10286755
  13. [13]Al-Shehaili SM, Al-Johani SS, Al-Sarhan NT, Al-Anazi AA, Al-Mijmaj FF, Al-Qhatani WN,. The effect of poor glycemic control on cognitive function in children and adolescents with type 1 diabetes mellitus: a single-center cross-sectional study (2019–2020). Saudi Med J. 2023; 44(10): 1006– 12. 37777276 PMC10541988
  14. [14]Prahalad P, Rioles N, Noor N, Rapaport R, Weinstock RS, Ebekozien O,. T1D exchange quality improvement collaborative: accelerating change through benchmarking and improvement science for people with type 1 diabetes. J Diabetes. 2022; 14(1): 83– 7. 34854232 PMC9060055
  15. [15]Gerhardsson P, Schwandt A, Witsch M, Kordonouri O, Svensson J, Forsander G,. The SWEET project 10-year benchmarking in 19 countries worldwide is associated with improved HbA1c and increased use of diabetes technology in youth with type 1 diabetes. Diabetes Technol Ther. 2021; 23(7): 491– 9. 33566729
  16. [16]Alonso GT, Corathers S, Shah A, Clements M, Kamboj M, Sonabend R,. Establishment of the T1D exchange quality improvement collaborative (T1DX-QI). Clin Diabetes. 2020; 38(2): 141– 51. 32327886 PMC7164986
  17. [17]Samuelsson U, Åkesson K, Peterson A, Hanas R, Hanberger L. Continued improvement of metabolic control in Swedish pediatric diabetes care. Pediatr Diabetes. 2018; 19(1): 150– 7. 27807917
  18. [18]Addala A, Auzanneau M, Miller K, Maier W, Foster N, Kapellen T,. A decade of disparities in diabetes technology use and HbA1c in pediatric type 1 diabetes: a transatlantic comparison. Diabetes Care. 2021; 44(1): 133– 40. 32938745 PMC8162452
  19. [19]Burnside MJ, Williman JA, Davies HM, Jefferies CA, Paul RG, Wheeler BJ,. Inequity in access to continuous glucose monitoring and health outcomes in paediatric diabetes, a case for national continuous glucose monitoring funding: a cross-sectional population study of children with type 1 diabetes in New Zealand. Lancet Reg Health West Pac. 2023; 31: 100644. 36419466 PMC9676142
  20. [20]Virmani A, Brink SJ, Middlehurst A, Mohsin F, Giraudo F, Sarda A,. ISPAD Clinical Practice Consensus Guidelines 2022: management of the child, adolescent, and young adult with diabetes in limited resource settings. Pediatr Diabetes. 2022; 23(8): 1529– 51. 36537524
  21. [21]Van Loocke M, Battelino T, Tittel SR, Prahalad P, Goksen D, Davis E,. Lower HbA1c targets are associated with better metabolic control. Eur J Pediatr. 2021; 180(5): 1513– 20. 33415466
  22. [22]de Bock M, Codner E, Craig ME, Huynh T, Maahs DM, Mahmud FH,. ISPAD Clinical Practice Consensus Guidelines 2022: glycemic targets and glucose monitoring for children, adolescents, and young people with diabetes. Pediatr Diabetes. 2022; 23(8): 1270– 6. 36537523 PMC10107615
  23. [24]Sundberg F, deBeaufort C, Krogvold L, Patton S, Piloya T, Smart C,. ISPAD clinical practice consensus guidelines 2022: managing diabetes in preschoolers. Pediatr Diabetes. 2022; 23(8): 1496– 511. 36537520 PMC10108244
  24. [25]American Diabetes Association Professional Practice Committee. 14. Children and adolescents: standards of care in diabetes-2024. Diabetes Care. 2024; 47(Suppl 1): S258– 81. 38078582 PMC10725814
  25. [26]Diabetes Control, and Complications Trial Research Group, Nathan DM, Genuth S, Lachin J, Cleary P, Crofford O,. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med. 1993; 329(14): 977– 86. 8366922
  26. [27]Biester T, Berget C, Boughton C, Cudizio L, Ekhlaspour L, Hilliard ME,. ISPAD clinical practice consensus guidelines 2024: diabetes technologies: insulin delivery. Horm Res Paediatr. 2024: 1– 34. In preparation. PMC11854989 39657603
  27. [28]Mathieu C, Ahmed W, Gillard P, Cohen O, Vigersky R, de Portu S,. The health economics of automated insulin delivery systems and the potential use of time in range in diabetes modeling: a narrative review. Diabetes Technol Ther. 2024; 26(S3): 66– 75. 38377319
  28. [29]Biskupiak JE, Ramos M, Levy CJ, Forlenza G, Hopley C, Boyd J,. Cost-effectiveness of the tubeless automated insulin delivery system vs standard of care in the management of type 1 diabetes in the United States. J Manag Care Spec Pharm. 2023; 29(7): 807– 17. 37133431 PMC10394185
  29. [30]Hautala N, Hannula V, Palosaari T, Ebeling T, Falck A. Prevalence of diabetic retinopathy in young adults with type 1 diabetes since childhood: the O ulu cohort study of diabetic retinopathy. Acta Ophthalmol. 2014; 92(8): 749– 52. 24862935
  30. [31]Schreur V, van Asten F, Ng H, Weeda J, Groenewoud JMM, Tack CJ,. Risk factors for development and progression of diabetic retinopathy in Dutch patients with type 1 diabetes mellitus. Acta Ophthalmol. 2018; 96(5): 459– 64. 30188024 PMC6174939
  31. [32]Sherif EM, Matter RM, Salah NY, Abozeid NEH, Atif HM, Tantawy NM. Changes in early optical coherence tomography angiography among children and adolescents with type 1 diabetes: relation to fibroblast growth factor 21. Diabetes Metab Res Rev. 2023; 39(2): e3598. 36494875
  32. [33]Samuelsson U, Anderzen J, Åkesson K, Hanberger L. The importance of low HbA1c during childhood on glycaemic control in adulthood and the risk of late complications. Acta Paediatr. 2021; 110(4): 1264– 72. 32978990
  33. [34]Spanakis EK, Golden SH. Race/ethnic difference in diabetes and diabetic complications. Curr Diab Rep. 2013; 13(6): 814– 23. 24037313 PMC3830901
  34. [35]Rossing P, Groop PH, Singh R, Lawatscheck R, Tuttle KR. Prevalence of chronic kidney disease in type 1 diabetes among adults in the US. Diabetes Care. 2024; 47(8): 1395– 99. 38857124 PMC11272963
  35. [36]Vazquez L, Vazquez Arreola E, Hanson RL, Sinha M. Glycemic measures in childhood as predictors of future diabetes-related microvascular complications in an indigenous american population. Diabetes Care. 2023; 46(9): 1659– 67. 37433116 PMC10465819
  36. [37]Rasmussen VF, Thrysøe M, Nyengaard JR, Tankisi H, Karlsson P, Hansen J,. Neuropathy in adolescents with type 1 diabetes: confirmatory diagnostic tests, bedside tests, and risk factors. Diabetes Res Clin Pract. 2023; 201: 110736. 37276985
  37. [38]Ibrahim BA, Hussein SA, Abdullah WH. Cognitive functions in children with type I diabetes. Wiad Lek. 2023; 76(5 pt 1): 944– 50. 37326074
  38. [39]Kar Ş, Er E, Ata A, İnal-Kaleli İ, Özcan T, Köse S,. Effect of metabolic control on cognitive functions in children and adolescents with type 1 diabetes mellitus. J Pediatr Endocrinol Metab. 2023; 36(7): 636– 42. 37146253
  39. [40]Mauras N, Buckingham B, White NH, Tsalikian E, Weinzimer SA, Jo B,. Impact of type 1 diabetes in the developing brain in children: a longitudinal study. Diabetes Care. 2021; 44(4): 983– 92. 33568403 PMC7985430
  40. [41]Liu S, Kuja-Halkola R, Larsson H, Lichtenstein P, Ludvigsson JF, Svensson AM,. Neurodevelopmental disorders, glycemic control, and diabetic complications in type 1 diabetes: a nationwide cohort study. J Clin Endocrinol Metab. 2021; 106(11): e4459– 70. 34171098 PMC8530713
  41. [42]Papadakis JL, Anderson LM, Garza K, Feldman MA, Shapiro JB, Evans M,. Psychosocial aspects of diabetes technology use: the child and family perspective. Endocrinol Metab Clin North Am. 2020; 49(1): 127– 41. 31980113
  42. [43]Lukács A, Mayer K, Sasvári P, Barkai L. Health-related quality of life of adolescents with type 1 diabetes in the context of resilience. Pediatr Diabetes. 2018; 19(8): 1481– 6. 30203556
  43. [44]Chen CW, Tinsley LJ, Volkening LK, Anderson BJ, Laffel LM. Observed characteristics associated with diabetes device use among teens with type 1 diabetes. J Diabetes Sci Technol. 2023; 17(1): 186– 94. 34652236 PMC9846387
  44. [45]Rosner B, Roman-Urrestarazu A. Health-related quality of life in paediatric patients with type 1 diabetes mellitus using insulin infusion systems. A systematic review and meta-analysis. PLoS One. 2019; 14(6): e0217655. 31237873 PMC6592525
  45. [46]Edqvist J, Rawshani A, Adiels M, Björck L, Lind M, Svensson AM,. BMI, mortality, and cardiovascular outcomes in type 1 diabetes: findings against an obesity paradox. Diabetes Care. 2019; 42(7): 1297– 304. 31048408
  46. [47]DuBose SN, Hermann JM, Tamborlane WV, Beck RW, Dost A, DiMeglio LA,. Obesity in youth with type 1 diabetes in Germany, Austria, and the United States. J Pediatr. 2015; 167(3): 627– 32.e324. 26164381
  47. [48]Maffeis C, Birkebaek NH, Konstantinova M, Schwandt A, Vazeou A, Casteels K,. Prevalence of underweight, overweight, and obesity in children and adolescents with type 1 diabetes: data from the international SWEET registry. Pediatr Diabetes. 2018; 19(7): 1211– 20. 30033651
  48. [49]Birkebaek N, Kahlert J, Bjarnason R, Drivvoll AK, Johansen A, Konradsdottir E,. Body mass index standard deviation score and obesity in children with type 1 diabetes in the Nordic countries. HbA1c and other predictors of increasing BMISDS. Pediatr Diabetes. 2018; 19(7): 1198– 205. 29781227
  49. [50]Nansel T, Lipsky L, Iannotti R. Cross-sectional and longitudinal relationships of body mass index with glycemic control in children and adolescents with type 1 diabetes mellitus. Diabetes Res Clin Pract. 2013; 100(1): 126– 32. 23339757 PMC3634913
  50. [51]Minges KE, Whittemore R, Weinzimer SA, Irwin ML, Redeker NS, Grey M. Correlates of overweight and obesity in 5529 adolescents with type 1 diabetes: the T1D Exchange Clinic Registry. Diabetes Res Clin Pract. 2017; 126: 68– 78. 28214669 PMC5401652
  51. [52]Phelan H, Foster NC, Schwandt A, Couper JJ, Willi S, Kroschwald P,. Longitudinal trajectories of BMI z-score: an international comparison of 11,513 Australian, American and German/Austrian/Luxembourgian youth with type 1 diabetes. Pediatr Obes. 2020; 15(2): e12582. 31691541
  52. [53]Grönberg A, Carlsson PO. Good glycemic control without exceeding the BMI trajectory during the first 5 years of treatment in children and adolescents with type 1 diabetes. Pediatr Diabetes. 2022; 23(3): 341– 50. 34981619 PMC9305211
  53. [54]Marlow AL, King BR, Phelan HT, Smart CE. Adolescents with type 1 diabetes can achieve glycemic targets on intensive insulin therapy without excessive weight gain. Endocrinol Diabetes Metab. 2022; 5(4): e352. 35715954 PMC9258989
  54. [55]Seget S, Jarosz-Chobot P, Ochab A, Polanska J, Rusak E, Witoszek P,. Body mass index, basal insulin and glycemic control in children with type 1 diabetes treated with the advanced hybrid closed loop system remain stable-1-year prospective, observational, two-center study. Front Endocrinol. 2022; 13: 1036808. PMC9592809 36303875
  55. [56]Piccini B, Felicioni M, Pessina B, Bertini M, Casalini E, Ceccotti C,. Glycemic control, basal/bolus distribution, BMI and meal management in children and adolescents with type 1 diabetes and advanced hybrid closed loop. Nutrients. 2023; 15(23): 4875. 38068733 PMC10707798
  56. [57]Beck RW, Bergenstal RM, Riddlesworth TD, Kollman C, Li Z, Brown AS,. Validation of time in range as an outcome measure for diabetes clinical trials. Diabetes Care. 2019; 42(3): 400– 5. 30352896 PMC6905478
  57. [58]Chehregosha H, Khamseh ME, Malek M, Hosseinpanah F, Ismail-Beigi F. A view beyond HbA1c: role of continuous glucose monitoring. Diabetes Ther. 2019; 10(3): 853– 63. 31037553 PMC6531520
  58. [59]Beck RW. Is it time to replace time-in-range with time-in-tight-range? Maybe not. Diabetes Technol Ther. 2024; 26(3): 147– 50. 38156959
  59. [60]Petersson J, Åkesson K, Sundberg F, Särnblad S. Translating glycated hemoglobin A1c into time spent in glucose target range: a multicenter study. Pediatr Diabetes. 2019; 20(3): 339– 44. 30652407
  60. [61]Sundberg F, deBeaufort C, Krogvold L, Patton S, Piloya T, Smart C,. ISPAD clinical practice consensus guidelines 2022: managing diabetes in preschoolers. Pediatr Diabetes. 2022; 23(8): 1496– 511. 36537520 PMC10108244
  61. [62]Dunn TC, Ajjan RA, Bergenstal RM, Xu Y. Is it time to move beyond TIR to TITR? Real-world data from over 20,000 users of continuous glucose monitoring in patients with type 1 and type 2 diabetes. Diabetes Technol Ther. 2024; 26(3): 203– 10. 38444315 PMC10877396
  62. [63]Castañeda J, Arrieta A, van den Heuvel T, Battelino T, Cohen O. Time in tight glucose range in type 1 diabetes: predictive factors and achievable targets in real-world users of the MiniMed 780G system. Diabetes Care. 2024; 47(5): 790– 7. 38113453 PMC11043222
  63. [64]Hamidi V, Pettus JH. Time in tight range for patients with type 1 diabetes: the time is now, or is it too soon? Diabetes Care. 2024; 47(5): 782– 4. 38640413
  64. [65]Beck RW, Connor CG, Mullen DM, Wesley DM, Bergenstal RM. The fallacy of average: how using HbA1c alone to assess glycemic control can be misleading. Diabetes Care. 2017; 40(8): 994– 9. 28733374 PMC5521971
  65. [66]Bergenstal RM, Gal RL, Connor CG, Gubitosi-Klug R, Kruger D, Olson BA,. Racial differences in the relationship of glucose concentrations and hemoglobin A1c levels. Ann Intern Med. 2017; 167(2): 95– 102. 28605777
  66. [67]Basu A, Slama MQ, Nicholson WT, Langman L, Peyser T, Carter R,. Continuous glucose monitor interference with commonly prescribed medications: a pilot study. J Diabetes Sci Technol. 2017; 11(5): 936– 41. 28332406 PMC5950984
  67. [68]Almurashi AM, Rodriguez E, Garg SK. Emerging diabetes technologies: continuous glucose monitors/artificial pancreases. J Indian Inst Sci. 2023; 103(1): 205– 30. PMC10043869 37362851
  68. [69]Garg SK, Kipnes M, Castorino K, Bailey TS, Akturk HK, Welsh JB,. Accuracy and safety of Dexcom G7 continuous glucose monitoring in adults with diabetes. Diabetes Technol Ther. 2022; 24(6): 373– 80. 35157505 PMC9208857
  69. [70]Nguyen A, White JR. FreeStyle libre 3. Clin Diabetes. 2022; 41(1): 127– 8. 36714257 PMC9845075
  70. [71]Patton SR. Adherence to glycemic monitoring in diabetes. J Diabetes Sci Technol. 2015; 9(3): 668– 75. 25591853 PMC4604539
  71. [72]American Diabetes Association. 16. Diabetes advocacy: Standards of medical care in diabetes-2019. Diabetes Care. 2019; 42(Suppl 1): S182– 3. 30559242

Authors
de Bock, M., Agwu, J. C., Deabreu, M., Dovc, K., Maahs, D. M., Marcovecchio, M. L., Mahmud, F. H., Nóvoa-Medina, Y., Priyambada, L., Smart, C. E., & DiMeglio, L. A.
Affiliations
  • Wye Valley NHS Trust (GB)
  • Stanford Medicine (US)
  • University of Cambridge (GB)
  • University of Toronto (CA)
  • Rainbow Children's Hospital (IN)
  • John Hunter Children's Hospital (AU)
  • Riley Hospital for Children (US)
Corresponding author
Maahs, David M.
ORCID
Venue
Hormone Research in Paediatrics
Publisher
S. Karger AG
Published
2024-12-19
Volume
97
Issue
6
Pages
1-13
ISSN
  • 1663-2818 (ISSN-L)
  • 1663-2826
DOI
10.1159/000543266
PMC
PMC11854972
OpenAlex
W4405614560
Cited by
52
References
0
Citations by year
2026: 37 · 2025: 15
FWCI
17.13
Type
journal article
Language
en
Open access
Licence
Locations
  • Hormone Research in Paediatrics (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • IUScholarWorks (Indiana University) (submittedVersion, cc-by-nc)
  • Apollo (University of Cambridge) (submittedVersion, cc-by-nc)
  • Acceda (Universidad de Las Palmas de Gran Canaria) (submittedVersion)
Funders
  • Sanofi
  • Dexcom
  • Abbott Diabetes Care
Topics
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Diabetes and associated disorders
Keywords
glycemic targets, HbA1c, pediatric diabetes, adolescent diabetes, continuous glucose monitoring, artificial pancreas, diabetes technology, ISPAD guidelines, glycemic control
MeSH terms
Glycemic Control, Adolescent, Blood Glucose, Child, Diabetes Mellitus, Type 1, Female, Glycated Hemoglobin, Humans, Hypoglycemic Agents, Insulin, Male, Societies, Medical, Blood Glucose Self-Monitoring, Practice Guidelines as Topic, Consensus, Young Adult

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