title: The glucogram: A new quantitative tool for glycemic analysis in the surgical intensive care unit.
abstract: BACKGROUND
  Glycemic control is an important aspect of patient care in the surgical intensive care unit (SICU). This is a pilot study of a novel glycemic analysis tool - the glucogram. We hypothesize that the glucogram may be helpful in quantifying the clinical significance of acute hyperglycemic states (AHS) and in describing glycemic variability (GV) in critically ill patients.
  
  
  METHODS
  Serial glucose measurements were analyzed in SICU patients with lengths of stay (LOS) >30 days. Glucose data were formatted into 12-hour epochs and graphically analyzed using stochastic and momentum indicators. Recorded clinical events were classified as major or minor (control). Examples of major events include cardiogenic shock, acute respiratory failure, major hemorrhage, infection/sepsis, etc. Examples of minor (control) events include non-emergent bedside procedures, blood transfusion given to a hemodynamically stable patient, etc. Positive/negative indicator status was then correlated with AHS and associated clinical events. The conjunction of positive indicator/major clinical event or negative indicator/minor clinical event was defined as clinical "match". GV was determined by averaging glucose fluctuations (maximal - minimal value within each 12-hour epoch) over time. In addition, event-specific glucose excursion (ESGE) associated with each positive indicator/AHS match (final minus initial value for each occurrence) was calculated. Descriptive statistics, sensitivity/specificity determination, and student's t-test were used in data analysis.
  
  
  RESULTS
  Glycemic and clinical data were reviewed for 11 patients (mean SICU LOS 74.5 days; 7 men/4 women; mean age 54.9 years; APACHE II of 17.7 ± 6.44; mortality 36%). A total of 4354 glucose data points (1254 epochs) were analyzed. There were 354 major clinical events and 93 minor (control) events. The glucogram identified AHS/indicator/clinical event "matches" with overall sensitivity of 84% and specificity of 65%. We noted that while the mean GV was greater for non-survivors than for survivors (19.3 mg/dL vs. 10.3 mg/dL, P = 0.02), there was no difference in mean ESGE between survivors (154.7) and non-survivors (160.8, P = 0.67).
  
  
  CONCLUSIONS
  The glucogram was able to quantify the correlation between AHS and major clinical events with a sensitivity of 84% and a specificity of 65%. In addition, mean GV was nearly two times higher for non-survivors. The glucogram may be useful both clinically (i.e., in the electronic ICU or other "early warning" systems) and as a research tool (i.e., in model development and standardization). Results of this study provide a foundation for further, larger-scale, multi-parametric, prospective evaluations of the glucogram.
authors.affiliation: Department of Surgery, Division of Critical Care, Trauma, and Burn, The Ohio State University Medical Center, Columbus, OH 43210, USA.
authors.forename: S P A
authors.initials: SP
authors.lastname: Stawicki
authors.forename: D
authors.initials: D
authors.lastname: Schuster
authors.forename: J F
authors.initials: JF
authors.lastname: Liu
authors.forename: J
authors.initials: J
authors.lastname: Kamal
authors.forename: S
authors.initials: S
authors.lastname: Erdal
authors.forename: A T
authors.initials: AT
authors.lastname: Gerlach
authors.forename: M l
authors.initials: Ml
authors.lastname: Whitmill
authors.forename: D E
authors.initials: DE
authors.lastname: Lindsey
authors.forename: C
authors.initials: C
authors.lastname: Murphy
authors.forename: S M
authors.initials: SM
authors.lastname: Steinberg
authors.forename: C H
authors.initials: CH
authors.lastname: Cook
references.citation: J Am Soc Nephrol. 2002 May;13(5):1350-7
references.pmid: 11961023
references.citation: Diabetes Care. 2005 Oct;28(10):2361-6
references.pmid: 16186263
references.citation: J Am Coll Surg. 2007 Feb;204(2):209-215
references.pmid: 17254924
references.citation: Ann Surg. 2006 Jun;243(6):845-51; discussion 851-3
references.pmid: 16772788
references.citation: J Trauma. 2005 May;58(5):921-4
references.pmid: 15920404
references.citation: Intensive Care Med. 2007 May;33(5):814-821
references.pmid: 17431584
references.citation: Diabet Med. 1998 Mar;15(3):188-93
references.pmid: 9545118
references.citation: JAMA. 2003 Oct 15;290(15):2041-7
references.pmid: 14559958
references.citation: Mayo Clin Proc. 2003 Dec;78(12):1471-8
references.pmid: 14661676
references.citation: Crit Care Med. 2008 Nov;36(11):3008-13
references.pmid: 18824908
references.citation: Crit Care Med. 2010 Mar;38(3):838-42
references.pmid: 20035218
references.citation: Anesthesiology. 2006 Aug;105(2):244-52
references.pmid: 16871057