Currently Viewing:
The American Journal of Managed Care January 2015
Disease-Modifying Therapy and Hospitalization Risk in Heart Failure Patients
Fadia T. Shaya, PhD, MPH; Ian M. Breunig, PhD; and Mandeep R. Mehra, MD, FACC, FACP, FRCP
Frequency and Costs of Hospital Transfers for Ambulatory Care-Sensitive Conditions
R. Neal Axon, MD, MSCR; Mulugeta Gebregziabher, PhD; Janet Craig, PhD, RN; Jingwen Zhang, MS; Patrick Mauldin, PhD; and William P. Moran, MD, MS
Celebrating Our 20th Anniversary
A. Mark Fendrick, MD, and Michael E. Chernew, PhD Co-Editors-in-Chief, The American Journal of Managed Care
Value-Based Insurance Design: Benefits Beyond Cost and Utilization
Teresa B. Gibson, PhD; J. Ross Maclean, MD; Michael E. Chernew, PhD; A. Mark Fendrick, MD; and Colin Baigel, MBChB
Changing Physician Behavior: What Works?
Fargol Mostofian, BHSc; Cynthiya Ruban, BSc; Nicole Simunovic, MSc; and Mohit Bhandari, MD, PhD, FRCSC
State of Emergency Preparedness for US Health Insurance Plans
Raina M. Merchant, MD, MSHP; Kristen Finne, BA; Barbara Lardy, MPH; German Veselovskiy, MPP; Casey Korba, MS; Gregg S. Margolis, NREMT-P, PhD; and Nicole Lurie, MD, MSPH
Relationship of Diabetes Complications Severity to Healthcare Utilization and Costs Among Medicare Advantage Beneficiaries
Leslie Hazel-Fernandez, PhD, MPH; Yong Li, PhD; Damion Nero, PhD; Chad Moretz, ScD; S. Lane Slabaugh, PharmD, MBA; Yunus Meah, PharmD; Jean Baltz, MMSc, MSW; Nick C. Patel, PharmD, PhD; and Jonathan R. Bouchard, MS, RPh
Revisiting Hospital Length of Stay: What Matters?
Mollie Shulan, MD; and Kelly Gao
Medical Homes: Cost Effects of Utilization by Chronically Ill Patients
Jason Neal, MA; Ravi Chawla, MBA; Christine M. Colombo, MBA; Richard L. Snyder, MD; and Somesh Nigam, PhD
Value-Based Insurance Design and Medication Adherence: Opportunities and Challenges
Kevin A. Look, PharmD, PhD
New Start Versus Continuing Users on Aripiprazole: Implications for Policy
Rashid Kazerooni, PharmD, BCPS; Joseph B. Nguyen, PharmD, BCPS; Mark Bounthavong, PharmD, MPH; Michael H. Tran, PharmD, BCPS; and Nermeen Madkour, PharmD, CSP
Multiple Chronic Conditions in Type 2 Diabetes Mellitus: Prevalence and Consequences
Pei-Jung Lin, PhD; David M. Kent, MD, MSc; Aaron Winn, MPP; Joshua T. Cohen, PhD; and Peter J. Neumann, ScD
Currently Reading
Prognostic Factors of Mortality Among Patients With Severe Hyperglycemia
Ya-Wun Guo, MD; Tzu-En Wu, MD, MS; and Harn-Shen Chen, MD, PhD
Using Financial Incentives to Improve the Care of Tuberculosis Patients
Cheng-Yi Lee, MS; Mei-Ju Chi, PhD; Shiang-Lin Yang, MS; Hsiu-Yun Lo, PhD; and Shou-Hsia Cheng, PhD

Prognostic Factors of Mortality Among Patients With Severe Hyperglycemia

Ya-Wun Guo, MD; Tzu-En Wu, MD, MS; and Harn-Shen Chen, MD, PhD
Sepsis, renal impairment with electrolyte imbalance, and low blood pressure were independent prognostic factors of mortality among patients with severe hyperglycemia in the emergency department.
ABSTRACT
Objectives
Severe hyperglycemia is associated with increased morbidity and mortality in a variety of patients. We undertook this study to identify prognostic factors of mortality among patients experiencing severe hyperglycemia in the emergency department (ED).

Study Design
Longitudinal observation study.

Methods
We recruited patients who visited the ED with blood glucose levels higher than 500 mg/dL between July 2008 and September 2010. The primary outcome was death from any cause within 90 days. Outcome analysis was first performed with Pearson’s χ2 test. Any characteristic with suspected significance (P <.1) was then used in a univariate Cox regression model. The variables found to be statistically significant were then subjected to multivariate analysis for further investigation.

Results
Among 733 patients with severe hyperglycemia, the 90-day mortality rate was 14.6% (n = 107). Independent prognostic factors for increasing 90-day mortality included elevated absolute neutrophil count (hazard ratio [HR], 7.34), elevated C-reactive protein (HR, 4.48), elevated blood urea nitrogen (HR, 3.04), elevated respiratory rate (HR, 2.91), decreasing body temperature (HR, 2.68), decreasing systolic blood pressure (HR, 2.65), elevated potassium (HR, 2.54), decreasing blood glucose (HR, 2.46), elevated creatinine (HR, 2.40), elevated white blood cell count (HR, 2.30), and elevated ratio of blood urea nitrogen to creatinine (HR, 2.23).

Conclusions
The 90-day mortality rate among patients with severe hyperglycemia in the ED was 14.6%. Sepsis, renal impairment with electrolyte imbalance, and lower blood pressure were independent prognostic factors.

Am J Manag Care. 2015;21(1):e9-e22
Severe hyperglycemia is associated with increased morbidity and mortality in a variety of patients. We recruited patients who visited the emergency department (ED) with blood glucose levels higher than 500 mg/dL to identify prognostic factors of mortality.
  • Our study found the 90-day mortality rate associated with severe hyperglycemia in the ED was 14.6%.
  • Patients in the mortality group were older and more likely to have an electrolyte imbalance. Both low and high body temperature indicated increased mortality rates.
  • However, higher blood glucose levels did not indicate higher mortality rates among these extremely hyperglycemic patients.
Severe hyperglycemia is associated with increased morbidity and mortality in a variety of groups of patients.1-3 The numerous precipitating factors in the development of severe hyperglycemia include infection, 4-8 poor compliance with antidiabetes therapy,4,7,9 myocardial infarction (MI),6,9 cerebrovascular accidents,6,9 other medical conditions,7 and medication side effects. Many observational studies have shown a consistent relationship between blood glucose levels and adverse clinical outcomes, even in patients without established diabetes. 1,2,10 Hyperglycemia is associated with many undesirable effects, including worse outcomes for strokes,11 increased likelihood of death or severe disability from subarachnoid hemorrhage,12 adverse events such as ST segment elevation MI,10 and morbidity after colectomy for cancer.13

The death rates from severe hyperglycemia for adults in the United States and Taiwan have gradually declined.6,7 The prognostic concomitant factors for mortality include altered mental status on admission,14 pneumonia, older age, stroke, MI,6 and high urea plasma levels.15 The cause of death is often related to concomitant life-threatening illnesses, rather than directly due to metabolic complications of hyperglycemia or ketoacidosis.4,5 Successful treatment of these serious complications requires improving tissue perfusion; correcting hyperglycemia, hyperosmolality, and electrolyte imbalances; and identifying and treating comorbid precipitating events.4,5

The association between hyperglycemia and worse outcomes often reflects the severity of an illness, but hyperglycemia itself may also contribute to the burden of the disease. To our knowledge, few studies have addressed the presentation of and prognostic factors associated with hyperglycemia in the emergency department (ED). We executed this study to identify prognostic factors for mortality among patients with severe hyperglycemia in the ED.

METHODS

Study Participants


We reviewed charts and selected patients who visited the ED in Taipei Veterans General Hospital between July 1, 2008, and September 30, 2010, enrolling patients who had blood glucose levels higher than 500 mg/dL. Exclusion criteria included being aged less than 30 years or more than 99 years, and surviving less than 24 hours after arrival. We reviewed the charts and analyzed data from routine examinations in the ED, including vital signs, a complete blood count, and serum biochemical analysis. A total of 781 patients came to the ED with blood glucose higher than 500 mg/dL; twenty-five patients were excluded due to the age restrictions, and 23 patients were excluded due to a survival time of less than 24 hours. A total of 733 patients were thus enrolled for analysis (Figure 1).

Baseline Examination

Through medical records, we obtained the following data: age, gender, day arrived at ED, blood glucose, body temperature, systolic blood pressure (SBP), pulse rate, white blood cell count, absolute neutrophil count, hemoglobin, hematocrit, platelets, C-reactive protein, blood urea nitrogen, creatinine, sodium, potassium, and alanine aminotransferase. We also evaluated the ratio of blood urea nitrogen to creatinine, and effective serum osmolality, which we calculated with the following formula: 2[measured Na+ (mEq/l)]+ glucose (mg/dL)/18.4 The participants were divided into 5 equal-sized groups (quintiles) for each parameter in order to evaluate its impact on prognosis. Baseline characteristics were expressed as mean ± SD, median, and the 20th to 80th percentile interquintile (range). Admission rates and intensive care unit (ICU) hospitalization rates were also recorded.

Main Outcome Measures

The main outcome measure was death from any cause within 90 days.16 Information on date of death was obtained from the Department of Health, Executive Yuan, ROC (Taiwan).

Statistical Analysis

To compare clinical characteristics among groups by mortality, we performed independent unpaired t tests or the Mann-Whitney U test for continuous variables, based on whether the variables had a normal distribution. Pearson’s χ2 test was used for categorical data. We used independent t tests to compare age, blood glucose levels, body temperature, respiratory rate, SBP, pulse rate, hemoglobin, hematocrit, creatinine, ratio of blood urea nitrogen to creatinine, effective serum osmolarity, and sodium and potassium levels; then we presented the results as mean ± SD. We used the Mann-Whitney U test to compare white blood cell counts, absolute neutrophil counts, platelets, C-reactive protein, blood urea nitrogen, and alanine aminotransferase, and we expressed the results as medians with interquintile ranges due to their nonnormal distribution.

We calculated 90-day mortality rates associated with each parameter by dividing patients into 5 groups according to a basic characteristics scale, as mentioned above. Outcome analysis was performed with the Pearson’s χ2 test, and if significance (P <.1) was suspected, a univariable Cox regression model was then used. We presumed every group was compared with the group with the lowest mortality rate. The results were expressed as hazard ratios with 95% CI. The data were all shown as forest plots. The variables that were statistically significant were then subjected to multivariate analysis to investigate whether they still had statistical significance.

The following models were used to identify potential confounders of the relationship between mortality and the parameter in question: 1) unadjusted, 2) adjusted for gender and age, and 3) adjusted for all other parameters, including age, sex, blood glucose, body temperature, respiratory rate, SBP, pulse rate, white blood cell count, absolute neutrophil count, hemoglobin, hematocrit, platelets, C-reactive protein, blood urea nitrogen, creatinine, sodium, potassium, and alanine aminotransferase. The ratio of blood urea nitrogen to creatinine was not adjusted for when considering blood urea nitrogen and creatinine as separate variables in Model 3. Similarly, effective osmolality was not adjusted for sodium and blood glucose in Model 3. We performed analyses with SPSS for Windows version 18.0 (SPSS, Inc, Chicago, Illinois). Statistical significance was considered as P <.05. The study had approval from the institutional review board of Taipei Veterans General Hospital.

RESULTS

Study Participants and Baseline Characteristics

We enrolled 733 patients for analysis, of which 494 (67.4%) were men. The mean age at baseline was 68.5 ± 15.4 years, mean blood glucose level was 691.5 ± 204.5 mg/dL, C-reactive protein level was 7.0 ± 9.6 mg/dL, blood urea nitrogen level was 46.2 ± 34.1 mg/dL, creatinine level was 2.6 ± 2.1 mg/dL, sodium level was 132.3 ± 8.7 mmol/L, and potassium level was 4.6 ± 1.0 mmol/L. The baseline clinical characteristics of our study subjects are shown in the eAppendix Table (available at www.ajmc.com).

Mortality

With 107 patients dying within 90 days of visiting the ED, the 90-day mortality rate was 14.6%. The causes of death are shown in Table 1. Causes of death among these patients with severe hyperglycemia were broadly similar to those expected in Taiwan; however, the proportion of patients in our study dying from pneumonia, infections, and diabetes was higher compared with expected values. Table 2 reveals the baseline clinical characteristics of our study subjects according to their survival status. Deceased subjects had higher admission rates (95.3% vs 85.9%) and more ICU admissions (58.9% vs 24.4%). The deceased subjects also tended to be older (72.2 ± 13.7 years vs 67.9 ± 15.6 years) and to have higher respiratory rates (22.5 ± 5.5 breaths per minute vs 20.4 ± 3.6 breaths per minute), white blood cell counts (12,700/ cumm vs 9900/cumm), C-reactive protein (8.0 mg/dL vs 1.51 mg/dL), blood urea nitrogen (48.0 mg/dL vs 34.0 mg/dL), serum creatinine (3.05 ± 2.02 mg/dL vs 2.50 ± 2.12 mg/dL), and serum sodium (134.7 ± 11.5 mmol/L vs 131.9 ± 8.1 mmol/L). However, the subjects who died had lower blood glucose levels (651.8 ± 151.7 mg/dL vs 698.3 ± 211.6 mg/dL), lower systolic BP (128.2 ± 38.9 mm Hg vs 141.4 ± 35.4 mm Hg), and lower hemoglobin levels (11.6 ± 2.9 g/dL vs 12.6 ± 2.7 g/dL).

Dividing the patients into 5 equal groups for each parameter, we compared those who survived with those who did not, using Pearson’s χ2 test. The baseline characteristics, including blood glucose, body temperature, respiratory rate, SBP, pulse rate, white blood cell count, absolute neutrophil count, hemoglobin, C-reactive protein, blood urea nitrogen, creatinine, ratio of blood urea nitrogen to creatinine, effective osmolality, and sodium and potassium levels, were entered in the survival analysis, with the exception of platelet and alanine aminotransferase due to their nonsignificance (P = .111 and .609, respectively).

Survival Analysis

The parameters entered for survival analysis were first used in univariable Cox regression models. The results are expressed as hazard ratios with 95% CI and all are shown in the forest plot (Figure 2). We found significantly higher mortality rates among patients with blood glucose either between 542 mg/dL and 595 mg/dL or between 595 mg/dL and 677 mg/dL; body temperature lower than 36°C or higher than 37.4°C; respiratory rates exceeding 22 breaths per minute; SBP of lower than 110 mm Hg or between 110 mm Hg and 128 mm Hg; white blood cell count between 11,800/cumm and 15,900/cumm, or more than 15,900/cumm; absolute neutrophil count between 9721/cumm and 13,846/cumm, or more than 13,846/cumm; C-reactive protein between 4.20 mg/dL and 13.20 mg/dL, or more than 13.20 mg/dL; blood urea nitrogen between 43 mg/dL and 68 mg/dL or more than 68 mg/dL; creatinine between 2.27 mg/dL and 3.31 mg/dL, or more than 3.31 mg/dL; sodium levels above 137 mg/dL; and potassium levels above 5.2 mg/dL.

We subjected the statistically significant variables to multivariate analysis, adjusting for age and sex in Model 2, and then adjusted for the other parameters in Model 3. Finally, factors that were independent prognostic factors of 90-day mortality included blood glucose between 542 mg/dL and 677 mg/dL; body temperature lower than 36°C; respiratory rate greater than 22 breaths per minute; SBP lower than 110 mm Hg; white blood cell counts between 11,800/cumm and 15,900/cumm; absolute neutrophil counts of 9721/cumm or higher; C-reactive protein of 4.20 mg/dL or higher; blood urea nitrogen of 43 mg/dL or higher; creatinine of 2.27 mg/dL or higher; and potassium of more than 5.2 mg/dL (Table 3).

DISCUSSION

 
Copyright AJMC 2006-2019 Clinical Care Targeted Communications Group, LLC. All Rights Reserved.
x
Welcome the the new and improved AJMC.com, the premier managed market network. Tell us about yourself so that we can serve you better.
Sign Up