Literature DB >> 2209307

Controlled study in diabetic children comparing insulin-dosage adjustment by manual and computer algorithms.

F Chiarelli1, S Tumini, G Morgese, A M Albisser.   

Abstract

A controlled trial of a new microprocessor device for insulin-dosage adjustment was undertaken in two matched groups of a priori well-controlled diabetic children. A prospective study design with three equal 8-wk periods was used. In the first period, both groups used manual methods for insulin-dosage adjustment after manual criteria. In the second period, one group of children adjusted insulin dosage by computer algorithms, whereas the other continued to use manual methods. In the third period, both groups again adjusted insulin by traditional methods. Mean premeal glycemia and glycosylated hemoglobin levels did not change in either group throughout the study. During the second period, episodes of hypoglycemia were more frequent in children without the computer than in those who used the device. In keeping with the latter outcome, the group that used the microprocessor device was given less insulin in the second period than the first (0.88 +/- 0.02 vs. 0.94 +/- 0.02 U.kg-1.day-1, P less than 0.0001) and in comparison to the control group of patients who concurrently were given an increased insulin dose in the second period compared with the first. This study showed that insulin treatment through specific computer-mediated dosage-adjusting algorithms was safe and minimized hypoglycemia by effectively accommodating seasonally changing insulin requirements. We recommend the device to help diabetic children and their families in the care of insulin-dependent diabetes.

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Year:  1990        PMID: 2209307     DOI: 10.2337/diacare.13.10.1080

Source DB:  PubMed          Journal:  Diabetes Care        ISSN: 0149-5992            Impact factor:   19.112


  8 in total

1.  Parameters affecting postprandial blood glucose: effects of blood glucose measurement errors.

Authors:  Theodor Koschinsky; Sascha Heckermann; Lutz Heinemann
Journal:  J Diabetes Sci Technol       Date:  2008-01

2.  Development of the Likelihood of Low Glucose (LLG) algorithm for evaluating risk of hypoglycemia: a new approach for using continuous glucose data to guide therapeutic decision making.

Authors:  Timothy C Dunn; Gary A Hayter; Ken J Doniger; Howard A Wolpert
Journal:  J Diabetes Sci Technol       Date:  2014-04-17

3.  Automatic data processing to achieve a safe telemedical artificial pancreas.

Authors:  M Elena Hernando; Gema García-Sáez; Iñaki Martínez-Sarriegui; Agustín Rodríguez-Herrero; Carmen Pérez-Gandía; Mercedes Rigla; Alberto de Leiva; Ismael Capel; Belén Pons; Enrique J Gómez
Journal:  J Diabetes Sci Technol       Date:  2009-09-01

4.  Design of a decision support system to help clinicians manage glycemia in patients with type 2 diabetes mellitus.

Authors:  David Rodbard; Robert A Vigersky
Journal:  J Diabetes Sci Technol       Date:  2011-03-01

5.  A Run-to-Run Control Strategy to Adjust Basal Insulin Infusion Rates in Type 1 Diabetes.

Authors:  Cesar C Palerm; Howard Zisser; Lois Jovanovič; Francis J Doyle
Journal:  J Process Control       Date:  2008       Impact factor: 3.666

6.  Computerized management of diabetes: a synthesis of controlled trials.

Authors:  E A Balas; S A Boren; G Griffing
Journal:  Proc AMIA Symp       Date:  1998

7.  The Columbia Registry of Information and Utilization Management Trials.

Authors:  E A Balas; M G Stockham; M A Mitchell; S M Austin; D A West; B G Ewigman
Journal:  J Am Med Inform Assoc       Date:  1995 Sep-Oct       Impact factor: 4.497

Review 8.  Artificial Intelligence in Decision Support Systems for Type 1 Diabetes.

Authors:  Nichole S Tyler; Peter G Jacobs
Journal:  Sensors (Basel)       Date:  2020-06-05       Impact factor: 3.576

  8 in total

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