Predicting the optimal basal insulin infusion pattern in children and adolescents on insulin pumps

Diabetes Care

Volumn 36, Issue 6, 2013, Pages 1507-1511

  Holterhus, Paul Martin ^a   Bokelmann, Jessica ^a   Riepe, Felix ^a   Heidtmann, Bettina ^b   Wagner, Verena ^c   Rami Merhar, Birgit ^d   Kapellen, Thomas ^e   Raile, Klemens ^f   Quester, Wulf ^g   Holl, Reinhard W ^h  

^a UNIVERSITY OF KIEL   (Germany)

^b Catholic Children's Hospital Wilhelmstift   (Germany)

^c UNIVERSITY OF LÜBECK   (Germany)

^d MEDICAL UNIVERSITY OF VIENNA   (Austria)

^e UNIVERSITY OF LEIPZIG   (Germany)

^f Experimental and Clinical Research Center   (Germany)

^g RUHR UNIVERSITY BOCHUM   (Germany)

^h UNIVERSITY OF ULM   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

INSULIN;

ADOLESCENT; AGE; ARTICLE; AUSTRALIA; CHILD; DATA BASE; DISEASE DURATION; FEMALE; GENDER; GERMANY; HUMAN; INSULIN DEPENDENT DIABETES MELLITUS; INSULIN INFUSION; INSULIN PUMP; INSULIN TREATMENT; MAJOR CLINICAL STUDY; MALE; MATHEMATICAL MODEL; PREDICTION; PRESCHOOL CHILD; PROBABILITY; QUALITY CONTROL; SCHOOL CHILD; VALIDATION STUDY;

ADOLESCENT; CHILD; DIABETES MELLITUS, TYPE 1; FEMALE; HUMANS; INSULIN; INSULIN INFUSION SYSTEMS; MALE; MODELS, THEORETICAL; REGRESSION ANALYSIS;

EID: 84878263498     PISSN: 01495992     EISSN: 19355548     Source Type: Journal    
DOI: 10.2337/dc12-1705     Document Type: Article

References (24)

1. Weinzimer SA, Ahern JH, Doyle EA, et al. Persistence of benefits of continuous subcutaneous insulin infusion in very young children with type 1 diabetes: a follow-up report. Pediatrics 2004;114:1601-1605 (Pubitemid 41754924)
2. Danne T, Battelino T, Kordonouri O, et al. A cross-sectional international survey of continuous subcutaneous insulin infusion in 377 children and adolescents with type 1 diabetes mellitus from 10 countries. Pediatr Diabetes 2005;6:193-198 (Pubitemid 43013626)
3. Grabert M, Schweiggert F, Holl RW. A framework for diabetes documentation and quality management in Germany: 10 years of experience with DPV. Comput Methods Programs Biomed 2002;69:115-121 (Pubitemid 34722933)
4. Holterhus PM, Odendahl R, Oesingmann S, et al.; German/Austrian DPV Initiative; German Pediatric CSII Working Group. Classification of distinct baseline insulin infusion patterns in children and adolescents with type 1 diabetes on continuous subcutaneous insulin infusion therapy. Diabetes Care 2007;30:568-573 (Pubitemid 46354335)
5. Klinkert C, Bachran R, Heidtmann B, Grabert M, Holl RW; DPV-Initiative. Age-specific characteristics of the basal insulin-rate for pediatric patients on CSII. Exp Clin Endocrinol Diabetes 2008;116:118-122 (Pubitemid 351363382)
6. Bachran R, Beyer P, Klinkert C, Heidtmann B, Rosenbauer J, Holl RW; German/Austrian DPV Initiative; German Pediatric CSII Working Group; BMBF Competence Network Diabetes. Basal rates and circadian profiles in continuous subcutaneous insulin infusion (CSII) differ for preschool children, prepubertal children, adolescents and young adults. Pediatr Diabetes 2012;13:1-5
7. Eisen MB, Spellman PT, Brown PO, Botstein D. Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci USA 1998;95:14863-14868 (Pubitemid 29003722)
8. Dunger DB, Matthews DR, Edge JA, Jones J, Preece MA. Evidence for temporal coupling of growth hormone, prolactin, LH and FSH pulsatility overnight during normal puberty. J Endocrinol 1991;130:141-149
9. Löfqvist C, Andersson E, Gelander L, Rosberg S, Blum WF, Albertsson Wikland K. Reference values for IGF-I throughout childhood and adolescence: a model that accounts simultaneously for the effect of gender, age, and puberty. J Clin Endocrinol Metab 2001;86:5870-5876 (Pubitemid 33152637)
10. Redwine L, Hauger RL, Gillin JC, Irwin M. Effects of sleep and sleep deprivation on interleukin-6, growth hormone, cortisol, and melatonin levels in humans. J Clin Endocrinol Metab 2000;85:3597-3603
11. Roffwarg HP, Muzio JN, Dement WC. Ontogenetic development of the human sleep-dream cycle. Science 1966;152:604-619
12. Löhr B, Siegmund R. Ultradian and circadian rhythms of sleep-wake and food-intake behavior during early infancy. Chronobiol Int 1999;16:129-148 (Pubitemid 29186433)
13. Howard BJ, Wong J. Sleep disorders. Pediatr Rev 2001;22:327-342 (Pubitemid 34075748)
14. Zucchini S, Scipione M, Balsamo C, et al. Comparison between sensor-augmented insulin therapy with continuous subcutaneous insulin infusion or multiple daily injections in everyday life: 3-day analysis of glucose patterns and sensor accuracy in children. Diabetes Technol Ther 2011;13:1187-1193
15. Davis SN, Horton ES, Battelino T, Rubin RR, Schulman KA, Tamborlane WV. STAR 3 randomized controlled trial to compare sensor-augmented insulin pump therapy with multiple daily injections in the treatment of type 1 diabetes: research design, methods, and baseline characteristics of enrolled subjects. Diabetes Technol Ther 2010;12:249-255
16. Bergenstal RM, Tamborlane WV, Ahmann A, et al.; STAR 3 Study Group. Effectiveness of sensor-augmented insulin-pump therapy in type 1 diabetes. N Engl J Med 2010;363:311-320
17. Conget I, Battelino T, Giménez M, Gough H, Castañeda J, Bolinder J; SWITCH Study Group. The SWITCH study (sensing with insulin pump therapy to control HbA(1c)): design and methods of a randomized controlled crossover trial on sensor-augmented insulin pump efficacy in type 1 diabetes suboptimally controlled with pump therapy. Diabetes Technol Ther 2011;13:49-54
18. Elleri D, Allen JM, Nodale M, et al. Automated overnight closed-loop glucose control in young children with type 1 diabetes. Diabetes Technol Ther 2011;13:419-424
19. Weinzimer SA, Steil GM, Swan KL, Dziura J, Kurtz N, Tamborlane WV. Fully automated closed-loop insulin delivery versus semiautomated hybrid control in pediatric patients with type 1 diabetes using an artificial pancreas. Diabetes Care 2008;31:934-939
20. Atlas E, Nimri R, Miller S, Grunberg EA, Phillip M. MD-logic artificial pancreas system: a pilot study in adults with type 1 diabetes. Diabetes Care 2010;33:1072-1076
21. van Heusden K, Dassau E, Zisser HC, Seborg DE, Doyle FJ 3rd. Control-relevant models for glucose control using a priori patient characteristics. IEEE Trans Biomed Eng 2012;59:1839-1849
22. Kanderian SS, Weinzimer SA, Steil GM. The identifiable virtual patient model: comparison of simulation and clinical closed-loop study results. J Diabetes Sci Tech 2012;6:371-379
23. Miller S, Nimri R, Atlas E, Grunberg EA, Phillip M. Automatic learning algorithm for the MD-logic artificial pancreas system. Diabetes Technol Ther 2011;13:983-990
24. Mauseth R, Wang Y, Dassau E, et al. Proposed clinical application for tuning fuzzy logic controller of artificial pancreas utilizing a personalization factor. J Diabetes Sci Tech 2010;4:913-922