Literature DB >> 28974470

Diabetes Alert Dogs (DADs): An assessment of accuracy and implications.

Linda A Gonder-Frederick1, Jesse H Grabman2, Jaclyn A Shepard2.   

Abstract

AIMS: To test the accuracy of Diabetes Alert Dogs (DADs) by comparing recorded alerts to continuous glucose monitoring (CGM) device readings during waking and sleeping hours.
METHODS: 14 individuals (7 adults with type 1 diabetes and 7 youth with type 1 diabetes/parents) who owned DADs for ≥6 mos wore masked CGM devices over a several-week period while recording DAD alerts electronically and in paper diaries.
RESULTS: During waking hours, sensitivity scores across participants were 35.9% for low BG events and 26.2% for high BG events. DAD accuracy was highly variable with 3/14 individual dogs performing statistically higher than chance. Sensitivity scores were lower during sleep hours of the person with diabetes (22.2% for low BG events and 8.4% for high BG events). DAD accuracy during sleeping hours was also highly variable, with 1/11 individual dogs performing statistically better than chance. Rate of change analyses indicated that DADs were responding to absolute BG level, rather than rapid shifts in glucose levels.
CONCLUSIONS: In this study the majority of DADs did not demonstrate accurate detection of low and high BG events. However, performance varied greatly across DADs and additional studies are needed to examine factors contributing to this variability. Additionally, more research is needed to investigate the significant gap between the positive experiences and clinical outcomes reported by DAD owners and the mixed research findings on DAD accuracy.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Blood glucose monitoring; CGM; Dogs; Observational study; Severe hypoglycemia; Type 1

Mesh:

Substances:

Year:  2017        PMID: 28974470      PMCID: PMC5723560          DOI: 10.1016/j.diabres.2017.09.009

Source DB:  PubMed          Journal:  Diabetes Res Clin Pract        ISSN: 0168-8227            Impact factor:   5.602


  11 in total

1.  Calculation of signal detection theory measures.

Authors:  H Stanislaw; N Todorov
Journal:  Behav Res Methods Instrum Comput       Date:  1999-02

2.  Statistical tools to analyze continuous glucose monitor data.

Authors:  William Clarke; Boris Kovatchev
Journal:  Diabetes Technol Ther       Date:  2009-06       Impact factor: 6.118

3.  Perceptions about professionally and non-professionally trained hypoglycemia detection dogs.

Authors:  N M Petry; J A Wagner; C J Rash; K K Hood
Journal:  Diabetes Res Clin Pract       Date:  2015-05-15       Impact factor: 5.602

4.  Psychology, technology, and diabetes management.

Authors:  Linda A Gonder-Frederick; Jaclyn A Shepard; Jesse H Grabman; Lee M Ritterband
Journal:  Am Psychol       Date:  2016-10

5.  Is the frequency of self-monitoring of blood glucose related to long-term metabolic control? Multicenter analysis including 24,500 patients from 191 centers in Germany and Austria.

Authors:  M Schütt; W Kern; U Krause; P Busch; A Dapp; R Grziwotz; I Mayer; J Rosenbauer; C Wagner; A Zimmermann; W Kerner; R W Holl
Journal:  Exp Clin Endocrinol Diabetes       Date:  2006-07       Impact factor: 2.949

6.  Variability of Diabetes Alert Dog Accuracy in a Real-World Setting.

Authors:  Linda A Gonder-Frederick; Jesse H Grabman; Jaclyn A Shepard; Anand V Tripathi; Dallas M Ducar; Zachary R McElgunn
Journal:  J Diabetes Sci Technol       Date:  2017-01-09

7.  Reliability of Trained Dogs to Alert to Hypoglycemia in Patients With Type 1 Diabetes.

Authors:  Evan A Los; Katrina L Ramsey; Ines Guttmann-Bauman; Andrew J Ahmann
Journal:  J Diabetes Sci Technol       Date:  2016-08-28

8.  Can trained dogs detect a hypoglycemic scent in patients with type 1 diabetes?

Authors:  Ky Dehlinger; Kristin Tarnowski; Jody L House; Evan Los; Kathryn Hanavan; Bryan Bustamante; Andrew J Ahmann; W Kenneth Ward
Journal:  Diabetes Care       Date:  2013-07       Impact factor: 19.112

9.  Evidence of a strong association between frequency of self-monitoring of blood glucose and hemoglobin A1c levels in T1D exchange clinic registry participants.

Authors:  Kellee M Miller; Roy W Beck; Richard M Bergenstal; Robin S Goland; Michael J Haller; Janet B McGill; Henry Rodriguez; Jill H Simmons; Irl B Hirsch
Journal:  Diabetes Care       Date:  2013-02-01       Impact factor: 19.112

10.  Dogs Can Be Successfully Trained to Alert to Hypoglycemia Samples from Patients with Type 1 Diabetes.

Authors:  Dana S Hardin; Wesley Anderson; Jennifer Cattet
Journal:  Diabetes Ther       Date:  2015-10-06       Impact factor: 2.945

View more
  3 in total

1.  Technological Ecological Momentary Assessment Tools to Study Type 1 Diabetes in Youth: Viewpoint of Methodologies.

Authors:  Mary Katherine Ray; Alana McMichael; Maria Rivera-Santana; Jacob Noel; Tamara Hershey
Journal:  JMIR Diabetes       Date:  2021-06-03

2.  Dogs demonstrate the existence of an epileptic seizure odour in humans.

Authors:  Amélie Catala; Marine Grandgeorge; Jean-Luc Schaff; Hugo Cousillas; Martine Hausberger; Jennifer Cattet
Journal:  Sci Rep       Date:  2019-03-28       Impact factor: 4.379

Review 3.  Hypoglycaemia detection and prediction techniques: A systematic review on the latest developments.

Authors:  Omar Diouri; Monika Cigler; Martina Vettoretti; Julia K Mader; Pratik Choudhary; Eric Renard
Journal:  Diabetes Metab Res Rev       Date:  2021-03-24       Impact factor: 4.876

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.