Literature DB >> 20068460

Differences in complexity of glycemic profile in survivors and nonsurvivors in an intensive care unit: a pilot study.

Krista Lundelin1, Luis Vigil, Susana Bua, Ivan Gomez-Mestre, Teresa Honrubia, Manuel Varela.   

Abstract

OBJECTIVE: To investigate glycemic dynamics and its relation with mortality in critically ill patients. We searched for differences in complexity of the glycemic profile between survivors and nonsurvivors in patients admitted to a multidisciplinary intensive care unit.
DESIGN: Prospective, observational study, convenience sample. SETTINGS: Multidisciplinary intensive care unit of a teaching hospital in Madrid, Spain. PATIENTS: A convenience sample of 42 patients, aged 29 to 86 yrs, admitted to an intensive care unit with an Acute Physiology and Chronic Health Evaluation II score of >or=14 and with an anticipated intensive care unit stay of >72 hrs.
INTERVENTIONS: A continuous glucose monitoring system was used to measure subcutaneous interstitial fluid glucose levels every 5 mins for 48 hrs during the first days of intensive care unit stay. A 24-hr period (n = 288 measurements) was used as time series for complexity analysis of the glycemic profile. MEASUREMENTS: Complexity of the glycemic profile was evaluated by means of detrended fluctuation analysis. Other conventional measurements of variability (range, sd, and Mean Amplitude of Glycemic Excursions) were also calculated. MAIN
RESULTS: Ten patients died during their intensive care unit stay. Glycemic profile was significantly more complex (lower detrended fluctuation analysis) in survivors (mean detrended fluctuation analysis, 1.49; 95% confidence interval, 1.44-1.53) than in nonsurvivors (1.60; 95% confidence interval, 1.52-1.68). This difference persisted after accounting for the presence of diabetes. In a logistic regression model, the odds ratio for death was 2.18 for every 0.1 change in detrended fluctuation analysis.Age, gender, Simplified Acute Physiologic Score 3 or Acute Physiologic and Chronic Health Evaluation II scores failed to explain differences in survivorship. Conventional variability measurements did not differ between survivors and nonsurvivors.
CONCLUSIONS: Complexity of the glycemic profile of critically ill patients varies significantly between survivors and nonsurvivors. Loss of complexity in glycemia time series, evaluated by detrended fluctuation analysis, is associated with higher mortality.

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Year:  2010        PMID: 20068460     DOI: 10.1097/CCM.0b013e3181ce49cf

Source DB:  PubMed          Journal:  Crit Care Med        ISSN: 0090-3493            Impact factor:   7.598


  20 in total

1.  Diabetes does not influence selected clinical outcomes in critically ill burn patients.

Authors:  Chaitanya K Dahagam; Alejandra Mora; Steven E Wolf; Charles E Wade
Journal:  J Burn Care Res       Date:  2011 Mar-Apr       Impact factor: 1.845

2.  Dynamic properties of glucose complexity during the course of critical illness: a pilot study.

Authors:  Emmanuel Godat; Jean-Charles Preiser; Jean-Christophe Aude; Pierre Kalfon
Journal:  J Clin Monit Comput       Date:  2019-03-19       Impact factor: 2.502

Review 3.  Management of critically ill patients with type 2 diabetes: The need for personalised therapy.

Authors:  Palash Kar; Karen L Jones; Michael Horowitz; Adam M Deane
Journal:  World J Diabetes       Date:  2015-06-10

4.  Glycemia management in critical care patients.

Authors:  Federico Bilotta; Giovanni Rosa
Journal:  World J Diabetes       Date:  2012-07-15

5.  Give me less sugar: how to manage glucose levels in post-anoxic injury?

Authors:  Fabio Silvio Taccone; Katia Donadello; Pierre Kalfon
Journal:  Intensive Care Med       Date:  2014-05-01       Impact factor: 17.440

6.  Complexity of continuous glucose monitoring data in critically ill patients: continuous glucose monitoring devices, sensor locations, and detrended fluctuation analysis methods.

Authors:  Matthew Signal; Felicity Thomas; Geoffrey M Shaw; J Geoffrey Chase
Journal:  J Diabetes Sci Technol       Date:  2013-11-01

Review 7.  Using Continuous Glucose Monitoring Data and Detrended Fluctuation Analysis to Determine Patient Condition: A Review.

Authors:  Felicity Thomas; Matthew Signal; J Geoffrey Chase
Journal:  J Diabetes Sci Technol       Date:  2015-06-30

8.  Increasing blood glucose variability heralds hypoglycemia in the critically ill.

Authors:  Rondi M Kauffmann; Rachel M Hayes; Brad D Buske; Patrick R Norris; Thomas R Campion; Marcus Dortch; Judith M Jenkins; Bryan R Collier; Addison K May
Journal:  J Surg Res       Date:  2011-03-31       Impact factor: 2.192

Review 9.  Glycemic variability in hospitalized patients: choosing metrics while awaiting the evidence.

Authors:  Susan S Braithwaite
Journal:  Curr Diab Rep       Date:  2013-02       Impact factor: 4.810

10.  [Glucose control in the critically ill. Innovations and contemporary strategies].

Authors:  U Holzinger
Journal:  Med Klin Intensivmed Notfmed       Date:  2013-05-19       Impact factor: 0.840

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