Journal of Critical Care 29 (2014) 971–977
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Incidence and long-term outcomes of critically ill adult patients with moderate-to-severe diabetic ketoacidosis: Retrospective matched cohort study☆,☆☆ Luciano C.P. Azevedo, MD a, b, c, Heidi Choi, MD a, Kim Simmonds, PhD d, Jon Davidow, MD e, Sean M. Bagshaw, MD, MSc a,⁎ a
Division of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta, 2-124E Clinical Sciences Building, 8440-122 St, Edmonton, AB, T6G 2B7, Canada Research and Education Institute, Hospital Sírio–Libanês, São Paulo, Brazil c Emergency Medicine Department ICU, University of São Paulo, São Paulo, Brazil d Infectious Disease Epidemiology, Surveillance and Assessment Branch, Community and Population Health Division, Alberta Health & Wellness, 23rd Floor, Telus Plaza NT 10025 Jasper Ave, Edmonton, Alberta, T5J 1S6, Canada e Royal Alexandria Hospital, Division of Critical Care Medicine, Faculty of Medicine Dentistry, University of Alberta, 10240 Kingsway Ave NW, Edmonton, AB, T5H 3V9, Canada b
a r t i c l e
i n f o
Keywords: Diabetic ketoacidosis Diabetes mellitus Intensive care unit Resource utilization Insulin Mortality
a b s t r a c t Objective: The objective of this study was to describe the clinical outcomes and treatment intensity of adult intensive care unit (ICU) patients with moderate-to-severe diabetic ketoacidosis (DKA). We aimed also to compare their clinical course with matched non-DKA ICU controls and to identify prognostic factors for mortality and hospital readmission within 1 year. Design: This is a retrospective matched cohort study. Setting: The settings are 2 tertiary teaching hospitals in Edmonton, Canada. Patients: Patients were adults with moderate-to-severe DKA admitted from January 2002 to December 2009. Control patients were defined as randomly selected age, sex, and Acute Physiology and Chronic Health Evaluation II score–matched nondiabetic ICU patients (1:4.5 matching ratio). Diabetic patients were stratified according to severity of exacerbation. Interventions: None. Measurements and main results: From 2002 to 2009, the incidence of DKA per 1000 admissions was 4.59 (95% confidence interval [CI], 3.64-5.71). Severe DKA was associated with higher Acute Physiology and Chronic Health Evaluation II and Sequential Organ Failure Assessment scores in the first 3 days of ICU stay as compared with moderate DKA. Mechanical ventilation was received in 39%, vasopressors in 17%, and renal replacement therapy in 12% of DKA patients, respectively. One-year mortality and readmission rates were 9% and 36%. By logistic regression, death and/or readmission occurring in 1 year was independently associated with insulin use (odds ratio, 4.79; 95% CI, 1.14-20.05) and treatment noncompliance (odds ratio, 3.33; 95% CI, 1.04-10.64). Compared with matched non-DKA patients, those with DKA had lower mortality and were more likely to be discharged home. Conclusions: Diabetic ketoacidosis necessitating ICU admission is associated with considerable resource utilization and long-term risk for death. Interventions aimed to improve compliance with therapy may prevent readmissions and improve the long-term outcome. © 2014 Elsevier Inc. All rights reseved.
1. Introduction ☆ Conflicts or disclosures: All authors declare no support from any organization for the submitted work; no financial relationships with any organizations that might have an interest in the submitted work; and no other relationships or activities that could appear to have influenced the submitted work. ☆☆ This study was unfunded. Dr Bagshaw holds a Canada Research Chair in Critical Care Nephrology and is a clinical investigator supported by Alberta Innovates–Health Solutions. ⁎ Corresponding author at: Dr Sean M. Bagshaw, Division of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta, 2-124E Clinical Sciences Building, 8440-122 St NW, Edmonton, AB, T6G 2B7, Canada. Tel.: +1 780 491 8311; fax: +1 780 492 1500. E-mail address: [email protected] (S.M. Bagshaw). http://dx.doi.org/10.1016/j.jcrc.2014.07.034 0883-9441/© 2014 Elsevier Inc. All rights reseved.
Diabetic ketoacidosis (DKA) is characterized by a pathologic imbalance of insulin deficiency and catecholamine/glucagon excess. This imbalance results in the metabolic complications of hyperglycemia, metabolic acidosis, and ketoacidosis [1,2]. It is a common complication of patients with diabetes mellitus (DM), accounting for 9% to 28% of all diabetes-related hospital admissions [1]. More than 100 000 patients yearly are admitted with DKA to US hospitals, resulting in significant treatment costs [3]. In Canada, an estimated 5000 to 10 000 patients are hospitalized annually with a primary diagnosis of
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Table 1 Clinical characteristics of DKA patients stratified by severity at presentation Variable
All patients (n = 76)
Moderate DKA Severe DKA (n = 44) (n = 32)
Pa
Age, y Male sex, n (%) Charlson score, points APACHE II score, points SOFA score D1, points (n = 72) SOFA score D2, points (n = 70) SOFA score D3, points (n = 47) ΔSOFA D1-D2, points (n = 70) ΔSOFA D1-D3, points (n = 47) Origin, n (%) Emergency room Ward Transfer from another hospital DM diagnosis, n (%) (n = 63) Type I DM Type II DM New DM diagnosis, n (%) Time of diagnosis, y Medications before DKA episode, n (%) b Insulin use OHA use No therapy Any complications, n (%) b Nephropathy Retinopathy Neuropathy Peripheral vascular disease Gastroparesis Coronary artery disease Medications (prior), n (%) b Antihypertensives Statin Psychiatric medications Acetylsalicylic acid Precipitant for DKA, n (%) b Noncompliance Infection Ethanol abuse Pancreatitis New diagnosis Unknown Time-to-DKA resolution, d
38.6 ± 12.9 41 (54) 1 (1-3) 21.1 ± 8.4 5 (2-7)
38 ± 12.5 21 (48) 2 (1-3) 17 ± 6.1 3 (2-5)
40 ± 13.4 20 (62) 1 (1-3) 27 ± 7.4 7 (5-9)
.424 .202 .398 b.001 b.001
3 (1-5)
2 (1-4)
5 (2.5-8)
b.001
3 (1-5)
1 (0-4)
3.5 (2-7)
.006
1 (0-3)
1 (0-2)
2 (0-3)
.380
2 (1-5)
2 (1-4)
3.5 (0.5-6)
.207
55 (72) 4 (5) 17 (22)
32(73) 2 (5) 10 (23)
23 (72) 2 (6) 7 (22)
50 (79) 13 (21) 9 (13) 6 (1.5-19.5)
27 (61) 7 (16) 6 (14) 5.5 (0.5-19.5)
23 (72) 6 (19) 3 (10) 7.5 (2-19.5)
54 (71) 9 (12) 17 (22)
29 (66) 4 (9) 12 (27)
25 (78) 5 (16) 5 (16)
14 (18) 13 (17) 12 (16) 9 (12) 5 (7) 3 (4)
8 (18) 7 (16) 6 (14) 5 (11) 3 (7) 1 (2)
6 6 6 4 2 2
(19) (19) (19) (13) (6) (6)
.894 .891 .671 1.000 .836 .429
16 13 11 10
(21) (17) (14) (13)
12 (27) 8 (18) 8 (18) 7 (16)
4 5 3 3
(13) (16) (9) (9)
.076 .632 .213 .322
34 (45) 30 (39) 10 (13) 10 (13) 9 (12) 9 (12) 1 (1,2)
15 (34) 19 (43) 4 (9) 6 (14) 6 (14) 5 (11) 1 (1,2)
19 (59) 11 (34) 6 (18) 4 (13) 3 (9) 4 (13) 2 (1,2)
.065 .262 .286 .761 .473 1.000 .293
.936 – – – .996 – .455
.246 .384 .229
OHA indicates oral hypoglycemic agent. a Student t test for comparisons of continuous parametric data, Mann-Whitney U for continuous nonparametric data, and χ2 and Fisher exact tests for comparisons of categorical data. b More than one may apply.
Thus, we performed a retrospective cohort study to describe the incidence, clinical characteristics, acute physiology, and treatment intensity of adult ICU patients admitted with moderate-tosevere DKA. Moreover, we aimed to compare their course and outcome with matched non-DKA ICU controls. We further aimed to identify factors associated with mortality and hospital readmission within 1 year. 2. Methods This study was approved by the Health Research Ethics Board at the University of Alberta before commencement, and due to its retrospective observational design, the need for informed consent was waived. 2.1. Design, setting, and population This was a retrospective matched cohort study. All adult (age, ≥ 18 years) patients with a primary diagnosis of DKA admitted to the General Systems ICU at the University of Alberta Hospital and the General Medical/Surgical ICU at the Royal Alexandria Hospital (Edmonton, Canada) between January 1, 2002, and December 31, 2009 were retrieved. The decision to admit these patients to ICU was left at the discretion of emergency department physician or internist referral to the ICU as well as to the intensivist in charge of the ICU. Cases were defined as adult critically ill patients with a confirmed diagnosis of DKA. Patients with nonketotic hyperosmolar hyperglycemic state and ICU readmission within the index hospitalization were excluded. Controls were randomly selected age-, sex-, and Acute Physiology and Chronic Health Evaluation (APACHE) II score-matched patients admitted to the same ICU during the same interval (1:4.5 matching ratio). 2.2. Outcomes The primary outcome of interest was the incidence of ICU admissions with a primary diagnosis of DKA, defined as a proportion (no. of cases per number of individual admissions) and as the number of cases per 1000 ICU admissions. Secondary outcomes were shortterm (ICU/hospital) and long-term (90-day and 1-year) mortality, ICU/hospital lengths of stay, changes in Sequential Organ Failure Assessment (SOFA) scores during the first 3 days in the ICU, and measures of treatment intensity (ie, mechanical ventilation [MV], vasoactive therapy, and renal replacement therapy [RRT]). Because all ICUs in Edmonton are closed units, the decision on patients' admission and intensity of treatment during ICU stay is done at the discretion of intensive care–trained physicians. 2.3. Operational definitions
DKA [4]. Patients presenting with DKA are variably admitted to the intensive care unit (ICU) [5], in part, due to hospital-specific policies that prevent the use of intravenous insulin infusions on general medical wards [1,6]. Mortality attributable to DKA exceeded 90% before the discovery of insulin [7]. However, the implementation of standardized protocols for resuscitation and insulin replacement has contributed to near-universal survival [7,8]. Despite this marked improvement in survival, DKA remains a serious and often avoidable complication and contributor to major morbidity in diabetic patients [9]. Few studies have evaluated adult DKA admissions to the ICU, including precipitants, physiologic parameters, outcomes, and long-term follow-up. Comprehensive information about the clinical characteristics, treatment intensity, and long-term outcomes for these patients will have value for clinicians and decision makers regarding outcomes, policy, and resource use.
The criteria for DKA were adapted from the American Diabetes Association (ADA), which defines DKA as a blood glucose more than 13.9 mmol/L, moderate ketonuria or ketonemia, arterial pH less than 7.30, and serum bicarbonate less than 15 mmol/L. The definition for DKA resolution was also adapted from ADA guidelines, which included blood glucose less than 11.1 mmol/L, serum bicarbonate more than 18 mmol/L, and venous pH more than 7.30 [10]. The evaluation of DKA severity, in terms of metabolic complications, was adapted from ADA criteria grading for DKA severity (Table E1, Supplemental Digital Content) [11,12]. Acute kidney injury (AKI) was defined according to the Risk, Injury, Failure, Loss and End-Stage diagnostic classification scheme [13]. Treatment compliance (noncompliance) was defined by documentation in the medical record of non-adherence to prescribed diabetic therapy as the most likely contributing factor to DKA. During the period of data collection, there
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was no specific protocol for treatment of patients with DKA in the 2 ICUs that were evaluated in this study. 2.4. Data sources Data were captured from patients' medical records. Data collected included demographics, course of hospitalization, and clinical outcome measures. Demographic data included age, sex, prehospital medications, precipitating factors and complications related to DKA, measures of illness severity (APACHE), measures of organ failure (SOFA), acute physiology, acute laboratory parameters, dates of hospital/ICU admission, and dates of discharge or death. Follow-up up to 1 year after discharge was made by tracking provincial administrative data in Alberta for readmission and/or death. 2.5. Statistical analysis Analysis was carried out using Stata 12.0 (Stata Corp, College Station, TX). Normality was assessed using Kolmogorov-Smirnov test. Clinical variables and univariate comparison between groups were reported for normally or near-normally distributed variables as means with SDs and compared by Student t test. Non‐normally distributed continuous data were reported as medians and P25 to P75 and compared by Mann-Whitney U test. Categorical data were reported as proportions and compared using χ 2 or Fisher exact test. Univariate analyses of DKA cases were done to evaluate for clinical factors associated with DKA severity and long-term survival and/or rehospitalization. Logistic regression analysis for the composite
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end point of death and/or readmission associated with DKA for up to 1 year after index ICU admission, adjusting for age, sex, and APACHE II score was also performed. A P b .05 was considered statistically significant for all comparisons.
3. Results From 2002 to 2009, there were a total of 76 unique patients admitted to the study ICUs with a diagnosis of DKA. The total number of admissions to the 2 ICUs for the same period was 16 524 patients. Thus, the proportion of DKA per total admissions was 0.45% for an estimated incidence density of 4.59 (95% confidence interval [CI], 3.64-5.71) per 1000 admissions. The incidence rate of DKA patients admitted to ICU relative to all DKA patients presenting to the ED during the study period was 112.8 ICU admissions per 121 1,000 ED presentations (95% CI, 89.5-140.4).
3.1. Clinical characteristics Table 1 demonstrates clinical characteristics of DKA stratified by severity at admission. Those with severe DKA at presentation had higher admission APACHE II scores and SOFA scores over the first 3 days. There were no other significant differences by DKA severity including type of DM, duration of time from DM diagnosis, therapy for DM, non-DM medications, diabetic complications, or precipitating factors for DKA. Time-to-DKA resolution was similar between groups.
Table 2 Physiologic and laboratory characteristics of DKA patients at admission according to severity of presentation Variable
All patients (n = 76)
Moderate DKA (n = 44)
Severe DKA (n = 32)
Pa
Respiratory rate, breaths per minute Heart rate, beats per minute Mean arterial pressure, millimeters of mercury SOFA GCS score, points Hemoglobin level, grams per liter Platelets, 109 cells/mL White blood count, 109 cells/mL INR Serum albumin, grams per liter Serum ketones Quantity, millimolar Urine ketones Quantity Serum pH Lactate, millimolar PaCO2, millimeters of mercury PaO2, millimeters of mercury Serum anion gap, millimeters of mercury Serum osmolality, millimoles per kilogram Serum glucose, millimolar Serum bicarbonate, millimolar Serum sodium, millimolar Serum potassium, millimolar Serum chloride, millimolar Admission creatinine, millimolar Peak creatinine, millimolar Admission urea, millimolar Peak urea, millimolar AKI, n (%) AST, international unit per liter ALT, international unit per liter ALP, international unit per liter Total bilirubin, micromolar HbA1c (n = 21), (%) Elevated cTnI, n (%)
29.5 ± 6.8 122.9 ± 18.5 67.9 ± 11.2 1 (0-3) 130.2 ± 24.8 319.2 ± 132.5 20.8 ± 10.4 1.0 (1.0-1.1) 30.1 ± 6.2 n = 54 4.6 ± 1.4 n = 23 2.5 ± 0.8 7.11 ± 0.15 2.7 ± 2.2 18 ± 11 133 ± 66 25.4 ± 8.6 346.2 ± 39 44.1 ± 23.4 6.3 ± 4.3 135 ± 10 4.9 ± 1.5 101 ± 18 216 ± 154 209 ± 154 13.3 ± 8.6 13.3 ± 9 62 (82) 30 (17-62) 22.5 (17-43.5) 149 ± 63 24 ± 17 11.1 ± 2.6 11 (14)
29.0 ± 6.1 122.3 ± 19.1 72.1 ± 10.7 1 (0-1) 132.9 ± 27.7 322.2 ± 109.5 20.1 ± 7.51 1.0 (0.9-1.0) 30.8 ± 7.1 n = 31 4.5 ± 1.5 n = 12 2.7 ± 0.7 7.14 ± 0.13 2.2 ± 1.7 14 ± 7 122 ± 39 24 ± 7.7 331.3 ± 30.5 35.6 ± 18 5.7 ± 3.8 137 ± 9 4.6 ± 1.2 103 ± 13 183 ± 137 178 ± 140 10.6 ± 7.8 11.1 ± 9 32 (73) 21 (16-43) 20 (16-40.5) 144 ± 56 21 ± 17 10.9 ± 2.6 5 (11)
30.2 ± 7.3 123.6 ± 17.8 62.3 ± 9.4 3 (2,3) 126.9 ± 20.4 315.5 ± 158.4 21.7 ± 13.2 1.0 (1.0-1.1) 29.3 ± 4.7 n = 23 4.7 ± 1.4 n = 11 2.3 ± 0.9 7.07 ± 0.17 3.1 ± 2.6 24 ± 13 147 ± 87 27.1 ± 9.3 364.7 ± 41 56 ± 24.7 7.1 ± 5 133 ± 10 5.4 ± 1.8 99 ± 22 261 ± 166 251 ± 165 16.9 ± 8.5 16.3 ± 8.2 30 (94) 45 (27-86.5) 25.5 (17.5-44) 156 ± 71 26 ± 17 11.5 ± 9.1 6 (18)
.445 .767 b.001 b.001 .314 .831 .531 .067 .393 .588 .238 .052 .112 b.001 .108 .120 b.001 b.001 .166 .045 .039 .361 .028 .04 .001 .013 .094 b.001 .334 .430 .152 .631 .697
GCS indicates Glasgow Coma Scale; INR, international normalized ratio; AST, aspartate aminotransferase; ALT, alanine aminotransferase; ALP, alkaline phosphatase; HbA1c, glycated hemoglobin; cTnI, cardiac troponin I. a Student t test for comparisons of continuous parametric data, Mann-Whitney U for continuous nonparametric data, and χ2 and Fisher exact tests for comparisons of categorical data.
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Table 3 Treatment intensity and outcomes for DKA patients according to severity of presentation Variable
All patients Moderate Severe DKA (n = 76) DKA (n = 44) (n = 32)
MV, n (%) Vasopressors, n (%) RRT, n (%) ICU LOS, d Hospital LOS, d ICU death, n (%) Hospital death, n (%) Death in 90 d, n (%) Death in 1 y, n (%) Prior DKA admission, n (%) Readmission within 1 y, n (%) Discharge plan in chart, n (%) Follow-up with endocrinologist, n (%) Follow-up with GP, n (%) Follow-up for DM teaching/ outpatient clinic, n (%)
30 (39) 13 (17) 9 (12) 2 (1-4) 7 (4-11) 3 (4) 3 (4) 4 (5) 7 (9) 24 (32) 27 (36) 35 (46) 16 (21) 12 (16) 14 (18)
3 (7) 2 (4.5) 4 (9) 2 (1-2.5) 6 (3-10) 0 (0) 0 (0) 1 (2) 1 (2) 12 (27) 16 (36) 19 (43) 6 (14) 8 (18) 7 (16)
Pa
27 (84) b.001 11 (34) .001 5 (16) .473 3.5 (2-5) b.001 7.5 (4-12.5) .157 3 (9) .038 3 (9) .038 3 (9) .213 6 (19) .024 12 (37) .383 11 (34) .777 16 (50) .833 10 (31) .099 4 (13) 7 (22)
.396 .641
LOS indicates length of stay; GP, general practitioner. a Student t test for comparisons of continuous parametric data, Mann-Whitney U for continuous nonparametric data, and χ2 and Fisher exact tests for comparisons of categorical data.
3.2. Laboratory variables Table 2 describes the physiologic and laboratorial parameters of DKA patients stratified by severity at ICU admission. Patients with severe DKA had lower mean arterial pressure and serum pH, higher anion gap, serum lactate, sodium, potassium, and creatinine. As anticipated, severe DKA was associated with greater increases in serum osmolality and blood glucose compared with moderate DKA. Although blood PaCO2 levels were higher in those with severe compared with moderate DKA, this was confounded by a higher proportion of severe DKA patients receiving MV (PaCO2 MV 26.4 mmol/L [13.5] vs no MV 13.5 [6.1]; P b .001). Patients with severe DKA more often reduced level of consciousness as demonstrated by increased median of neurologic SOFA as compared with moderate DKA patients. This may partially explain the higher need for ventilatory support in this group (Table 3). 3.3. Resource utilization and clinical outcomes Table 3 shows ICU utilization and outcomes for DKA patients admitted to ICU. Advanced life support was not uncommonly used among DKA patients, with 39%, 17%, and 12% receiving MV, vasopressor therapy, and RRT, respectively. Median ICU length of stay was longer for those with severe compared with moderate DKA. In-hospital death was uncommon, occurring exclusively in those with severe DKA. Hospital readmission was common, occurring in 36% by 1 year. Documentation of a discharge plan in the medical record was poor, occurring in only 46%. Follow-up with an endocrinologist, general practitioner, and/or DM clinic was relatively uncommon (Table 3). When compared with matched non-DM ICU patients, DKA patients had lower ICU and in-hospital mortality and lower overall ICU and hospital lengths of stay (Table 4). 3.4. Analysis of patients with unfavourable outcomes Table 5 describes DKA patients stratified by death and/or hospital readmission at 1 year. No patient with a new diagnosis of DM died or was readmitted. However, death/readmission was more common among DKA patients with noncompliance and sepsis as precipitants.
Table 4 Comparison of clinical characteristics and outcomes of DKA patients and matched controls Variable
Overall DKA patients (n = 76)
Matched controls (n = 356)
Pa
Age, y Male sex, n (%) APACHE II, points Diagnostic category, n (%) Medical, n (%) Surgical, n (%) Major diagnosis, n (%) Pneumonia/sepsis Gastrointestinal diseases Trauma (excluding TBI) TBI Drug overdose Other ICU LOS, d Hospital LOS, d ICU mortality, n (%) Hospital mortality, n (%) Discharge disposition, n (%) Home Acute care Chronic care Other b
38.6 ± 12.9 41 (54) 21.1 ± 8.4
38.3 ± 13 198 (56) 21.0 ± 8.3
74 (97) 2 (3)
268 (75) 87 (25)
.847 .790 .781 b.001 – –
– – – – – – 2 (1-4) 7 (4-11) 3 (4) 3 (4) n = 73 59 (80) 7 (10) 3 (4) 4 (6)
72 (20) 45 (13) 35 (10) 32 (9) 34 (9) 138 (39) 3 (2-9) 14.5 (7-31) 53 (15) 67 (19) n = 289 195 (67) 55 (19) 31 (11) 8 (3)
– – – – – – b.001 b.001 .001 .001 .036 – – – –
TBI indicates traumatic brain injury. a Student t test for comparisons of continuous parametric data, Mann-Whitney U for continuous nonparametric data, and χ2 and Fisher exact tests for comparisons of categorical data. b Left without authorization or unknown.
By logistic regression analysis, after adjusting for age, sex, and APACHE II score, the use of insulin (odds ratio, 4.79; 95% CI, 1.1420.05; P = .032) and noncompliance as a precipitant (odds ratio, 3.33; 95% CI, 1.04-10.64; P = .042) were independently associated with death and/or readmission within 1 year (Fig. 1.). 3.5. Sensitivity analysis of noncompliant patients Tables E1 and E2 (Supplemental Digital Content) describe the clinical characteristics, resource use, and outcomes of DKA patients stratified by noncompliance as the major precipitant for DKA. Noncompliant patients were younger, were more likely to have had a prior hospitalization for DKA, were more likely to have severe DKA at presentation, were more likely admitted from the emergency department, and were more likely users of insulin. Noncompliant patients also had higher mortality at 1 year (19% vs 2%; P = .024) as compared with those with adequate treatment. 4. Discussion We performed a 2-center retrospective matched cohort study of all adult patients admitted to intensive care with DKA to describe the incidence, clinical characteristics, resource utilization, and long-term outcomes. We found that DKA was an uncommon diagnosis associated with ICU admission, representing only 0.45% of total admissions. However, we showed that these patients often receive substantial advanced life support, including MV, vasoactive drugs, and RRT, to treat complications associated with DKA and its precipitants. We also identified noncompliance with DM treatment and sepsis as the predominant precipitants for DKA, in particular, for those presenting with more severe illness. As expected, the mortality associated with DKA was low, however, was not insignificant. Approximately 1 in 10 DKA patients admitted to ICU were dead at 1 year. Moreover, rehospitalization among patients admitted to ICU with DKA was common, occurring in 36% by 1 year. Noncompliance with prescribed diabetic therapy and insulin use were both found to be independent risk factors for mortality or rehospitalization. When compared with matched ICU controls, DKA patients generally
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Table 5 Clinical characteristics, resource intensity, and outcomes of DKA patients according to death or readmission in 1 year after index DKA admission Variable
All patients (n = 76)
Alive/not-readmitted (n = 44)
Death/ readmission (n = 32)
Pa
Age, y Male Sex, n (%) Charlson score, points APACHE II, points SOFA score D1, points DM diagnosis, (n = 63) Type I DM, n (%) Type II DM, n (%) New DM diagnosis, n (%) Time of diagnosis, y Medications before DKA episode, n (%) b Insulin use OHA use No therapy Precipitant for DKA, n (%)b Noncompliance Infection Ethanol abuse Pancreatitis New diagnosis Unknown DKA severe at presentation, n (%) Time-to-DKA resolution, d MV, n (%) Vasopressors, n (%) RRT, n (%) AKI, n (%) ICU LOS, d Hospital LOS, d Prior DKA admission, n (%) Discharge plan in chart, n (%) Follow-up with endocrinologist, n (%) Follow-up with general practitioner, n (%) Follow-up for DM teaching/outpatient clinic, n (%)
38.6 ± 12.9 41 (54) 1 (1-3) 21.1 ± 8.4 5 (2-7)
38.6 ± 12.6 24 (55) 1(1-2.5) 20.5 ± 7.2 5 (3-7)
38.6 ± 13.3 17 (53) 1 (1-3) 21.8 ± 9.7 4.5 (2-8)
.991 .902 .748 .505 .745
50 (79) 112 (21) 9 (13) 6 (1.5-19.5)
24 (55) 7 (16) 9 (20) 6.5 (0-20.5)
26 (81) 5 (16) 0 (0) 5.5 (3-19.5)
.707 – .004 .623
54 (71) 9 (12) 17 (22)
25 (57) 6 (14) 15 (34)
29 (91) 3 (9) 2 (6)
.001 .570 .004
34 (45) 30 (39) 10 (13) 10 (13) 9 (12) 9 (12) 32 (42) 1 (1,2) 30 (39) 13 (17) 9 (12) 62 (82) 2 (1-4) 7 (4-11) 24 (32) 35 (46) 16 (21) 12 (16) 14 (18)
13 (30) 21 (48) 6 (14) 6 (14) 8 (18) 4 (9) 17 (38) 1 (1,2) 18 (41) 8 (18) 3 (7) 36 (82) 2 (1-5) 8 (4.5-12.5) 10 (23) 23 (52) 10 (23) 10 (23) 9 (20)
21 (66) 9 (28) 4 (13) 4 (13) 1 (3) 5 (16) 15 (46) 1 (1,2) 12 (38) 5 (16) 6 (19) 26 (81) 2 (1-3) 6 (3-9) 14 (44) 12 (38) 6 (18) 2 (6) 5 (16)
.005 .037 .761 .761 .031 .473 .473 .639 .521 .632 .151 .286 .208 .056 .087 .092 .526 .034 .464
a b
Student t test for comparisons of continuous parametric data, Mann-Whitney U for continuous nonparametric data, and χ2 and Fisher exact tests for comparisons of categorical data. More than one may apply.
remained in the ICU and hospital for fewer days and had lower mortality. However, our data suggest that many of these deaths and readmissions associated with DKA may have been avoidable. These observations would imply that there are likely missed opportunities for reducing complications, improving outcomes, and reducing unnecessary resource use among patients with DM. 4.1. Interpretation and context with prior literature Few data have specifically evaluated the characteristics, outcomes, and resource use among adult patients with DKA admitted to ICU [1,6,14]. Studies not focused solely in pediatric populations to date have been limited by study design, small sample size, and variable case mix (ie, inclusion of both ICU and non-ICU patients) [15,16]. Likewise, prior studies have limited generalizability due to variation in policy for management of DKA and in critical care service delivery. A previous large study of DKA admissions in the United States found wide variability on the utilization of ICU for DKA patients (range, 2.1%87.7%). Hospitals with greater volume of DKA admissions were less likely to admit these patients to the ICU. Although this observed variation was not associated with significant differences in lengths of stay or mortality, these data suggest that institutional practice patterns appear to impact ICU utilization for DKA patients [6]. Furthermore, among patients admitted to hospital with DKA, prior data have suggested that only 8% to 23% had received MV [14,15], implying the decision to triage to ICU may not have centered solely on patient illness severity but rather determined by policy for DKA management (ie, insulin infusion). In contrast, DKA patients in our cohort were significantly more likely to be supported with MV (39% overall and 84% among severe DKA subgroup). Likewise, in a cohort
study of a single-center medical ICU in the United States, DKA was the primary admission diagnosis in 7.6% with an average APACHE II score of 12 [1]. In contrast, in our data, DKA represented less than 1% of admissions, and our cohort was characterized by markedly higher APACHE II score, in particular, among those with severe DKA. Prior studies have shown the development of severe AKI associated with DKA, and initiation of RRT is a relatively uncommon complication [17]. In contrast, 82% of the DKA patients in our cohort presented with AKI and 12% were temporarily supported with RRT. This trend is likely related to both the severity of underlying and precipitating conditions (ie, sepsis) and severity of DKA, whereas patients with milder DKA likely had less severe AKI that resolved rapidly with resuscitation and were more likely triaged to non-ICU settings (ie, hospital ward or high-dependency unit). Noncompliance in our study was found to be the most common precipitant for moderate-to-severe DKA requiring ICU admission, occurring more commonly among younger patients and insulin users. These patients also had trends for higher illness severity at presentation and worse long-term glycemic control (ie, as measured by hemoglobin A1C levels). Moreover, noncompliance was also shown to predict with higher health resource use, in particular, rehospitalization and less favorable outcomes. Noncompliance has repeatedly been identified as an important and potentially avoidable precipitant for DKA across all age groups [18-20]. Indeed, in the diabetes audit and research in Tayside Scotland (DARTS) study, adherence to prescribed diabetic therapy in young patients was inversely related to episodes of DKA, hospitalizations, and poor long-term glycemic control [21]. Similar to our data, Hjort and Christensen [18] found that noncompliance was the major precipitant among mainly young diabetic patients hospitalized with DKA. Psychosocial factors may
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Fig. 1. Interaction of independent risk factors for DKA readmission and/or death in the 1 year after a DKA episode.
contribute to noncompliance, including lower socioeconomic status (ie, social welfare or unemployment) and self-reported treatment error (ie, incorrect management of insulin during illness) [22]. 4.2. Implications for health policy Episodes of DKA among patients known to have DM should be avoidable, in particular, for those with noncompliance as a primary precipitant. The observation that noncompliance remains the most common precipitant for moderate-to-severe DKA prompting ICU admission would imply an important gap in health services delivery. Importantly, we observed that a relatively low proportion of these DKA patients had documented discharge care plans or scheduled follow-up, in particular, among those with noncompliance as a precipitant. These at-risk patients would appear to benefit from patient-centered strategies focused on simplifying access, education (ie, insulin management during illness), and treatment of concomitant illness (ie, mental illness) [19,23]. Prior data have supported the implementation of multidisciplinary programs to address barriers to communication, access to care, and treatment. From an economics perspective, based on US data of an average 100 000 annual hospitalizations for DKA, with an estimated average cost of $13 000 United States Dollars per patient, the annual attributable acute hospitalization costs for episodes of DKA may exceed $1 billion United States Dollars per year [24]. Moreover, the costs associated with admission to ICU may exceed 20% of these estimated expenditures [20,25]. Accordingly, these observations and our study would highlight the importance of additional research to investigate the most cost-effective strategies, whether in the inpatient or outpatient setting, to improve diabetes self-management and prevent unnecessary health resource use for avoidable episodes of DKA. 4.3. Limitations Our study has a number of limitations to consider. First, it was retrospective in design with a relatively small sample size and few
events, limiting the statistical power. Second, our study was focused on DKA patients admitted to ICU. As such, we have no data on those DKA patients admitted directly to hospital wards or managed in the emergency department. Third, DKA patients in this study were admitted to the 2 tertiary level teaching hospitals in a large urban health region in Canada. Accordingly, our results may have limited generalizability to other health jurisdictions with differing health insurance models. Fourth, we were unable to perform a more detailed matching of DKA and non-DKA patients for additional variables such as Charlson comorbidity score and SOFA score, which may have reduced the risk of residual confounding. Finally, we did not have data available on the long-term outcomes for matched controls that limited comparison of health resource utilization after index hospitalization. 5. Conclusions Diabetic ketoacidosis in adult patients necessitating ICU admission is associated with considerable resource utilization and long-term risk for death. Insulin use and noncompliance are independent risk factors for death or readmission. Interventions aimed to increase compliance with therapy may prevent avoidable readmissions and improve the long-term outcome. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.jcrc.2014.07.034. References [1] Freire AX, Umpierrez GE, Afessa B, et al. Predictors of intensive care unit and hospital length of stay in diabetic ketoacidosis. J Crit Care 2002;17(4):207–11. [2] Magee MF, Bhatt BA. Management of decompensated diabetes. Diabetic ketoacidosis and hyperglycemic hyperosmolar syndrome. Crit Care Clin 2001;17 (1):75–106. [3] Bull SV, Douglas IS, Foster M, et al. Mandatory protocol for treating adult patients with diabetic ketoacidosis decreases intensive care unit and hospital lengths of stay: results of a nonrandomized trial. Crit Care Med 2007;35(1):41–6. [4] Chiasson JL, Aris-Jilwan N, Belanger R, et al. Diagnosis and treatment of diabetic ketoacidosis and the hyperglycemic hyperosmolar state. CMAJ 2003;168(7):859–66. [5] Marinac JS, Mesa L. Using a severity of illness scoring system to assess intensive care unit admissions for diabetic ketoacidosis. Crit Care Med 2000;28(7):2238–41.
L.CP. Azevedo et al. / Journal of Critical Care 29 (2014) 971–977 [6] Gershengorn HB, Iwashyna TJ, Cooke CR, et al. Variation in use of intensive care for adults with diabetic ketoacidosis⁎. Crit Care Med 2012;40(7):2009–15. [7] Kitabchi AE, Umpierrez GE, Fisher JN, et al. Thirty years of personal experience in hyperglycemic crises: diabetic ketoacidosis and hyperglycemic hyperosmolar state. J Clin Endocrinol Metab 2008;93(5):1541–52. [8] Waller SL, Delaney S, Strachan MW. Does an integrated care pathway enhance the management of diabetic ketoacidosis? Diabet Med 2007;24(4):359–63. [9] Strachan MW, Nimmo GR, Noyes K, et al. Management of cerebral oedema in diabetes. Diabetes Metab Res Rev 2003;19(3):241–7. [10] Casteels K, Mathieu C. Diabetic ketoacidosis. Rev Endocr Metab Disord 2003;4(2): 159–66. [11] Kitabchi AE, Nyenwe EA. Hyperglycemic crises in diabetes mellitus: diabetic ketoacidosis and hyperglycemic hyperosmolar state. Endocrinol Metab Clin North Am 2006;35(4):725–51. [12] Kitabchi AE, Umpierrez GE, Murphy MB, et al. Hyperglycemic crises in adult patients with diabetes: a consensus statement from the American Diabetes Association. Diabetes Care 2006;29(12):2739–48. [13] Bellomo R, Ronco C, Kellum JA, et al. Acute renal failure—definition, outcome measures, animal models, fluid therapy and information technology needs: the Second International Consensus Conference of the Acute Dialysis Quality Initiative (ADQI) Group. Crit Care 2004;8(4):R204–12. [14] Azoulay E, Chevret S, Didier J, et al. Infection as a trigger of diabetic ketoacidosis in intensive care-unit patients. Clin Infect Dis 2001;32(1):30–5. [15] Barski L, Nevzorov R, Rabaev E, et al. Diabetic ketoacidosis: clinical characteristics, precipitating factors and outcomes of care. Isr Med Assoc J 2012;14(5):299–303.
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[16] Efstathiou SP, Tsiakou AG, Tsioulos DI, et al. A mortality prediction model in diabetic ketoacidosis. Clin Endocrinol 2002;57(5):595–601. [17] Woodrow G, Brownjohn AM, Turney JH. Acute renal failure in patients with type 1 diabetes mellitus. Postgrad Med J 1994;70(821):192–4. [18] Hjort U, Christensen JH. Diabetic ketoacidosis and compliance. Lancet 1998;351 (9103):674–5. [19] Bismuth E, Laffel L. Can we prevent diabetic ketoacidosis in children? Pediatr Diabetes 2007;8(Suppl. 6):24–33. [20] Maldonado MR, Chong ER, Oehl MA, et al. Economic impact of diabetic ketoacidosis in a multiethnic indigent population: analysis of costs based on the precipitating cause. Diabetes Care 2003;26(4):1265–9. [21] Morris AD, Boyle DI, McMahon AD, et al. Adherence to insulin treatment, glycaemic control, and ketoacidosis in insulin-dependent diabetes mellitus. The DARTS/MEMO Collaboration. Diabetes Audit and Research in Tayside Scotland. Medicines Monitoring Unit. Lancet 1997;350(9090):1505–10. [22] Randall L, Begovic J, Hudson M, et al. Recurrent diabetic ketoacidosis in inner-city minority patients: behavioral, socioeconomic, and psychosocial factors. Diabetes Care 2011;34(9):1891–6. [23] Kitabchi AE, Umpierrez GE, Miles JM, et al. Hyperglycemic crises in adult patients with diabetes. Diabetes Care 2009;32(7):1335–43. [24] Kitabchi AE, Umpierrez GE, Murphy MB, et al. Hyperglycemic crises in diabetes. Diabetes Care 2004;27(Suppl. 1):S94–S102. [25] Javor KA, Kotsanos JG, McDonald RC, et al. Diabetic ketoacidosis charges relative to medical charges of adult patients with type I diabetes. Diabetes Care 1997;20(3): 349–54.
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Incidence and long-term outcomes of critically ill adult patients with moderate-to-severe diabetic ketoacidosis: Retrospective matched cohort study☆,☆☆ Luciano C.P. Azevedo, MD a, b, c, Heidi Choi, MD a, Kim Simmonds, PhD d, Jon Davidow, MD e, Sean M. Bagshaw, MD, MSc a,⁎ a
Division of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta, 2-124E Clinical Sciences Building, 8440-122 St, Edmonton, AB, T6G 2B7, Canada Research and Education Institute, Hospital Sírio–Libanês, São Paulo, Brazil c Emergency Medicine Department ICU, University of São Paulo, São Paulo, Brazil d Infectious Disease Epidemiology, Surveillance and Assessment Branch, Community and Population Health Division, Alberta Health & Wellness, 23rd Floor, Telus Plaza NT 10025 Jasper Ave, Edmonton, Alberta, T5J 1S6, Canada e Royal Alexandria Hospital, Division of Critical Care Medicine, Faculty of Medicine Dentistry, University of Alberta, 10240 Kingsway Ave NW, Edmonton, AB, T5H 3V9, Canada b
a r t i c l e
i n f o
Keywords: Diabetic ketoacidosis Diabetes mellitus Intensive care unit Resource utilization Insulin Mortality
a b s t r a c t Objective: The objective of this study was to describe the clinical outcomes and treatment intensity of adult intensive care unit (ICU) patients with moderate-to-severe diabetic ketoacidosis (DKA). We aimed also to compare their clinical course with matched non-DKA ICU controls and to identify prognostic factors for mortality and hospital readmission within 1 year. Design: This is a retrospective matched cohort study. Setting: The settings are 2 tertiary teaching hospitals in Edmonton, Canada. Patients: Patients were adults with moderate-to-severe DKA admitted from January 2002 to December 2009. Control patients were defined as randomly selected age, sex, and Acute Physiology and Chronic Health Evaluation II score–matched nondiabetic ICU patients (1:4.5 matching ratio). Diabetic patients were stratified according to severity of exacerbation. Interventions: None. Measurements and main results: From 2002 to 2009, the incidence of DKA per 1000 admissions was 4.59 (95% confidence interval [CI], 3.64-5.71). Severe DKA was associated with higher Acute Physiology and Chronic Health Evaluation II and Sequential Organ Failure Assessment scores in the first 3 days of ICU stay as compared with moderate DKA. Mechanical ventilation was received in 39%, vasopressors in 17%, and renal replacement therapy in 12% of DKA patients, respectively. One-year mortality and readmission rates were 9% and 36%. By logistic regression, death and/or readmission occurring in 1 year was independently associated with insulin use (odds ratio, 4.79; 95% CI, 1.14-20.05) and treatment noncompliance (odds ratio, 3.33; 95% CI, 1.04-10.64). Compared with matched non-DKA patients, those with DKA had lower mortality and were more likely to be discharged home. Conclusions: Diabetic ketoacidosis necessitating ICU admission is associated with considerable resource utilization and long-term risk for death. Interventions aimed to improve compliance with therapy may prevent readmissions and improve the long-term outcome. © 2014 Elsevier Inc. All rights reseved.
1. Introduction ☆ Conflicts or disclosures: All authors declare no support from any organization for the submitted work; no financial relationships with any organizations that might have an interest in the submitted work; and no other relationships or activities that could appear to have influenced the submitted work. ☆☆ This study was unfunded. Dr Bagshaw holds a Canada Research Chair in Critical Care Nephrology and is a clinical investigator supported by Alberta Innovates–Health Solutions. ⁎ Corresponding author at: Dr Sean M. Bagshaw, Division of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta, 2-124E Clinical Sciences Building, 8440-122 St NW, Edmonton, AB, T6G 2B7, Canada. Tel.: +1 780 491 8311; fax: +1 780 492 1500. E-mail address: [email protected] (S.M. Bagshaw). http://dx.doi.org/10.1016/j.jcrc.2014.07.034 0883-9441/© 2014 Elsevier Inc. All rights reseved.
Diabetic ketoacidosis (DKA) is characterized by a pathologic imbalance of insulin deficiency and catecholamine/glucagon excess. This imbalance results in the metabolic complications of hyperglycemia, metabolic acidosis, and ketoacidosis [1,2]. It is a common complication of patients with diabetes mellitus (DM), accounting for 9% to 28% of all diabetes-related hospital admissions [1]. More than 100 000 patients yearly are admitted with DKA to US hospitals, resulting in significant treatment costs [3]. In Canada, an estimated 5000 to 10 000 patients are hospitalized annually with a primary diagnosis of
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Table 1 Clinical characteristics of DKA patients stratified by severity at presentation Variable
All patients (n = 76)
Moderate DKA Severe DKA (n = 44) (n = 32)
Pa
Age, y Male sex, n (%) Charlson score, points APACHE II score, points SOFA score D1, points (n = 72) SOFA score D2, points (n = 70) SOFA score D3, points (n = 47) ΔSOFA D1-D2, points (n = 70) ΔSOFA D1-D3, points (n = 47) Origin, n (%) Emergency room Ward Transfer from another hospital DM diagnosis, n (%) (n = 63) Type I DM Type II DM New DM diagnosis, n (%) Time of diagnosis, y Medications before DKA episode, n (%) b Insulin use OHA use No therapy Any complications, n (%) b Nephropathy Retinopathy Neuropathy Peripheral vascular disease Gastroparesis Coronary artery disease Medications (prior), n (%) b Antihypertensives Statin Psychiatric medications Acetylsalicylic acid Precipitant for DKA, n (%) b Noncompliance Infection Ethanol abuse Pancreatitis New diagnosis Unknown Time-to-DKA resolution, d
38.6 ± 12.9 41 (54) 1 (1-3) 21.1 ± 8.4 5 (2-7)
38 ± 12.5 21 (48) 2 (1-3) 17 ± 6.1 3 (2-5)
40 ± 13.4 20 (62) 1 (1-3) 27 ± 7.4 7 (5-9)
.424 .202 .398 b.001 b.001
3 (1-5)
2 (1-4)
5 (2.5-8)
b.001
3 (1-5)
1 (0-4)
3.5 (2-7)
.006
1 (0-3)
1 (0-2)
2 (0-3)
.380
2 (1-5)
2 (1-4)
3.5 (0.5-6)
.207
55 (72) 4 (5) 17 (22)
32(73) 2 (5) 10 (23)
23 (72) 2 (6) 7 (22)
50 (79) 13 (21) 9 (13) 6 (1.5-19.5)
27 (61) 7 (16) 6 (14) 5.5 (0.5-19.5)
23 (72) 6 (19) 3 (10) 7.5 (2-19.5)
54 (71) 9 (12) 17 (22)
29 (66) 4 (9) 12 (27)
25 (78) 5 (16) 5 (16)
14 (18) 13 (17) 12 (16) 9 (12) 5 (7) 3 (4)
8 (18) 7 (16) 6 (14) 5 (11) 3 (7) 1 (2)
6 6 6 4 2 2
(19) (19) (19) (13) (6) (6)
.894 .891 .671 1.000 .836 .429
16 13 11 10
(21) (17) (14) (13)
12 (27) 8 (18) 8 (18) 7 (16)
4 5 3 3
(13) (16) (9) (9)
.076 .632 .213 .322
34 (45) 30 (39) 10 (13) 10 (13) 9 (12) 9 (12) 1 (1,2)
15 (34) 19 (43) 4 (9) 6 (14) 6 (14) 5 (11) 1 (1,2)
19 (59) 11 (34) 6 (18) 4 (13) 3 (9) 4 (13) 2 (1,2)
.065 .262 .286 .761 .473 1.000 .293
.936 – – – .996 – .455
.246 .384 .229
OHA indicates oral hypoglycemic agent. a Student t test for comparisons of continuous parametric data, Mann-Whitney U for continuous nonparametric data, and χ2 and Fisher exact tests for comparisons of categorical data. b More than one may apply.
Thus, we performed a retrospective cohort study to describe the incidence, clinical characteristics, acute physiology, and treatment intensity of adult ICU patients admitted with moderate-tosevere DKA. Moreover, we aimed to compare their course and outcome with matched non-DKA ICU controls. We further aimed to identify factors associated with mortality and hospital readmission within 1 year. 2. Methods This study was approved by the Health Research Ethics Board at the University of Alberta before commencement, and due to its retrospective observational design, the need for informed consent was waived. 2.1. Design, setting, and population This was a retrospective matched cohort study. All adult (age, ≥ 18 years) patients with a primary diagnosis of DKA admitted to the General Systems ICU at the University of Alberta Hospital and the General Medical/Surgical ICU at the Royal Alexandria Hospital (Edmonton, Canada) between January 1, 2002, and December 31, 2009 were retrieved. The decision to admit these patients to ICU was left at the discretion of emergency department physician or internist referral to the ICU as well as to the intensivist in charge of the ICU. Cases were defined as adult critically ill patients with a confirmed diagnosis of DKA. Patients with nonketotic hyperosmolar hyperglycemic state and ICU readmission within the index hospitalization were excluded. Controls were randomly selected age-, sex-, and Acute Physiology and Chronic Health Evaluation (APACHE) II score-matched patients admitted to the same ICU during the same interval (1:4.5 matching ratio). 2.2. Outcomes The primary outcome of interest was the incidence of ICU admissions with a primary diagnosis of DKA, defined as a proportion (no. of cases per number of individual admissions) and as the number of cases per 1000 ICU admissions. Secondary outcomes were shortterm (ICU/hospital) and long-term (90-day and 1-year) mortality, ICU/hospital lengths of stay, changes in Sequential Organ Failure Assessment (SOFA) scores during the first 3 days in the ICU, and measures of treatment intensity (ie, mechanical ventilation [MV], vasoactive therapy, and renal replacement therapy [RRT]). Because all ICUs in Edmonton are closed units, the decision on patients' admission and intensity of treatment during ICU stay is done at the discretion of intensive care–trained physicians. 2.3. Operational definitions
DKA [4]. Patients presenting with DKA are variably admitted to the intensive care unit (ICU) [5], in part, due to hospital-specific policies that prevent the use of intravenous insulin infusions on general medical wards [1,6]. Mortality attributable to DKA exceeded 90% before the discovery of insulin [7]. However, the implementation of standardized protocols for resuscitation and insulin replacement has contributed to near-universal survival [7,8]. Despite this marked improvement in survival, DKA remains a serious and often avoidable complication and contributor to major morbidity in diabetic patients [9]. Few studies have evaluated adult DKA admissions to the ICU, including precipitants, physiologic parameters, outcomes, and long-term follow-up. Comprehensive information about the clinical characteristics, treatment intensity, and long-term outcomes for these patients will have value for clinicians and decision makers regarding outcomes, policy, and resource use.
The criteria for DKA were adapted from the American Diabetes Association (ADA), which defines DKA as a blood glucose more than 13.9 mmol/L, moderate ketonuria or ketonemia, arterial pH less than 7.30, and serum bicarbonate less than 15 mmol/L. The definition for DKA resolution was also adapted from ADA guidelines, which included blood glucose less than 11.1 mmol/L, serum bicarbonate more than 18 mmol/L, and venous pH more than 7.30 [10]. The evaluation of DKA severity, in terms of metabolic complications, was adapted from ADA criteria grading for DKA severity (Table E1, Supplemental Digital Content) [11,12]. Acute kidney injury (AKI) was defined according to the Risk, Injury, Failure, Loss and End-Stage diagnostic classification scheme [13]. Treatment compliance (noncompliance) was defined by documentation in the medical record of non-adherence to prescribed diabetic therapy as the most likely contributing factor to DKA. During the period of data collection, there
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was no specific protocol for treatment of patients with DKA in the 2 ICUs that were evaluated in this study. 2.4. Data sources Data were captured from patients' medical records. Data collected included demographics, course of hospitalization, and clinical outcome measures. Demographic data included age, sex, prehospital medications, precipitating factors and complications related to DKA, measures of illness severity (APACHE), measures of organ failure (SOFA), acute physiology, acute laboratory parameters, dates of hospital/ICU admission, and dates of discharge or death. Follow-up up to 1 year after discharge was made by tracking provincial administrative data in Alberta for readmission and/or death. 2.5. Statistical analysis Analysis was carried out using Stata 12.0 (Stata Corp, College Station, TX). Normality was assessed using Kolmogorov-Smirnov test. Clinical variables and univariate comparison between groups were reported for normally or near-normally distributed variables as means with SDs and compared by Student t test. Non‐normally distributed continuous data were reported as medians and P25 to P75 and compared by Mann-Whitney U test. Categorical data were reported as proportions and compared using χ 2 or Fisher exact test. Univariate analyses of DKA cases were done to evaluate for clinical factors associated with DKA severity and long-term survival and/or rehospitalization. Logistic regression analysis for the composite
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end point of death and/or readmission associated with DKA for up to 1 year after index ICU admission, adjusting for age, sex, and APACHE II score was also performed. A P b .05 was considered statistically significant for all comparisons.
3. Results From 2002 to 2009, there were a total of 76 unique patients admitted to the study ICUs with a diagnosis of DKA. The total number of admissions to the 2 ICUs for the same period was 16 524 patients. Thus, the proportion of DKA per total admissions was 0.45% for an estimated incidence density of 4.59 (95% confidence interval [CI], 3.64-5.71) per 1000 admissions. The incidence rate of DKA patients admitted to ICU relative to all DKA patients presenting to the ED during the study period was 112.8 ICU admissions per 121 1,000 ED presentations (95% CI, 89.5-140.4).
3.1. Clinical characteristics Table 1 demonstrates clinical characteristics of DKA stratified by severity at admission. Those with severe DKA at presentation had higher admission APACHE II scores and SOFA scores over the first 3 days. There were no other significant differences by DKA severity including type of DM, duration of time from DM diagnosis, therapy for DM, non-DM medications, diabetic complications, or precipitating factors for DKA. Time-to-DKA resolution was similar between groups.
Table 2 Physiologic and laboratory characteristics of DKA patients at admission according to severity of presentation Variable
All patients (n = 76)
Moderate DKA (n = 44)
Severe DKA (n = 32)
Pa
Respiratory rate, breaths per minute Heart rate, beats per minute Mean arterial pressure, millimeters of mercury SOFA GCS score, points Hemoglobin level, grams per liter Platelets, 109 cells/mL White blood count, 109 cells/mL INR Serum albumin, grams per liter Serum ketones Quantity, millimolar Urine ketones Quantity Serum pH Lactate, millimolar PaCO2, millimeters of mercury PaO2, millimeters of mercury Serum anion gap, millimeters of mercury Serum osmolality, millimoles per kilogram Serum glucose, millimolar Serum bicarbonate, millimolar Serum sodium, millimolar Serum potassium, millimolar Serum chloride, millimolar Admission creatinine, millimolar Peak creatinine, millimolar Admission urea, millimolar Peak urea, millimolar AKI, n (%) AST, international unit per liter ALT, international unit per liter ALP, international unit per liter Total bilirubin, micromolar HbA1c (n = 21), (%) Elevated cTnI, n (%)
29.5 ± 6.8 122.9 ± 18.5 67.9 ± 11.2 1 (0-3) 130.2 ± 24.8 319.2 ± 132.5 20.8 ± 10.4 1.0 (1.0-1.1) 30.1 ± 6.2 n = 54 4.6 ± 1.4 n = 23 2.5 ± 0.8 7.11 ± 0.15 2.7 ± 2.2 18 ± 11 133 ± 66 25.4 ± 8.6 346.2 ± 39 44.1 ± 23.4 6.3 ± 4.3 135 ± 10 4.9 ± 1.5 101 ± 18 216 ± 154 209 ± 154 13.3 ± 8.6 13.3 ± 9 62 (82) 30 (17-62) 22.5 (17-43.5) 149 ± 63 24 ± 17 11.1 ± 2.6 11 (14)
29.0 ± 6.1 122.3 ± 19.1 72.1 ± 10.7 1 (0-1) 132.9 ± 27.7 322.2 ± 109.5 20.1 ± 7.51 1.0 (0.9-1.0) 30.8 ± 7.1 n = 31 4.5 ± 1.5 n = 12 2.7 ± 0.7 7.14 ± 0.13 2.2 ± 1.7 14 ± 7 122 ± 39 24 ± 7.7 331.3 ± 30.5 35.6 ± 18 5.7 ± 3.8 137 ± 9 4.6 ± 1.2 103 ± 13 183 ± 137 178 ± 140 10.6 ± 7.8 11.1 ± 9 32 (73) 21 (16-43) 20 (16-40.5) 144 ± 56 21 ± 17 10.9 ± 2.6 5 (11)
30.2 ± 7.3 123.6 ± 17.8 62.3 ± 9.4 3 (2,3) 126.9 ± 20.4 315.5 ± 158.4 21.7 ± 13.2 1.0 (1.0-1.1) 29.3 ± 4.7 n = 23 4.7 ± 1.4 n = 11 2.3 ± 0.9 7.07 ± 0.17 3.1 ± 2.6 24 ± 13 147 ± 87 27.1 ± 9.3 364.7 ± 41 56 ± 24.7 7.1 ± 5 133 ± 10 5.4 ± 1.8 99 ± 22 261 ± 166 251 ± 165 16.9 ± 8.5 16.3 ± 8.2 30 (94) 45 (27-86.5) 25.5 (17.5-44) 156 ± 71 26 ± 17 11.5 ± 9.1 6 (18)
.445 .767 b.001 b.001 .314 .831 .531 .067 .393 .588 .238 .052 .112 b.001 .108 .120 b.001 b.001 .166 .045 .039 .361 .028 .04 .001 .013 .094 b.001 .334 .430 .152 .631 .697
GCS indicates Glasgow Coma Scale; INR, international normalized ratio; AST, aspartate aminotransferase; ALT, alanine aminotransferase; ALP, alkaline phosphatase; HbA1c, glycated hemoglobin; cTnI, cardiac troponin I. a Student t test for comparisons of continuous parametric data, Mann-Whitney U for continuous nonparametric data, and χ2 and Fisher exact tests for comparisons of categorical data.
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Table 3 Treatment intensity and outcomes for DKA patients according to severity of presentation Variable
All patients Moderate Severe DKA (n = 76) DKA (n = 44) (n = 32)
MV, n (%) Vasopressors, n (%) RRT, n (%) ICU LOS, d Hospital LOS, d ICU death, n (%) Hospital death, n (%) Death in 90 d, n (%) Death in 1 y, n (%) Prior DKA admission, n (%) Readmission within 1 y, n (%) Discharge plan in chart, n (%) Follow-up with endocrinologist, n (%) Follow-up with GP, n (%) Follow-up for DM teaching/ outpatient clinic, n (%)
30 (39) 13 (17) 9 (12) 2 (1-4) 7 (4-11) 3 (4) 3 (4) 4 (5) 7 (9) 24 (32) 27 (36) 35 (46) 16 (21) 12 (16) 14 (18)
3 (7) 2 (4.5) 4 (9) 2 (1-2.5) 6 (3-10) 0 (0) 0 (0) 1 (2) 1 (2) 12 (27) 16 (36) 19 (43) 6 (14) 8 (18) 7 (16)
Pa
27 (84) b.001 11 (34) .001 5 (16) .473 3.5 (2-5) b.001 7.5 (4-12.5) .157 3 (9) .038 3 (9) .038 3 (9) .213 6 (19) .024 12 (37) .383 11 (34) .777 16 (50) .833 10 (31) .099 4 (13) 7 (22)
.396 .641
LOS indicates length of stay; GP, general practitioner. a Student t test for comparisons of continuous parametric data, Mann-Whitney U for continuous nonparametric data, and χ2 and Fisher exact tests for comparisons of categorical data.
3.2. Laboratory variables Table 2 describes the physiologic and laboratorial parameters of DKA patients stratified by severity at ICU admission. Patients with severe DKA had lower mean arterial pressure and serum pH, higher anion gap, serum lactate, sodium, potassium, and creatinine. As anticipated, severe DKA was associated with greater increases in serum osmolality and blood glucose compared with moderate DKA. Although blood PaCO2 levels were higher in those with severe compared with moderate DKA, this was confounded by a higher proportion of severe DKA patients receiving MV (PaCO2 MV 26.4 mmol/L [13.5] vs no MV 13.5 [6.1]; P b .001). Patients with severe DKA more often reduced level of consciousness as demonstrated by increased median of neurologic SOFA as compared with moderate DKA patients. This may partially explain the higher need for ventilatory support in this group (Table 3). 3.3. Resource utilization and clinical outcomes Table 3 shows ICU utilization and outcomes for DKA patients admitted to ICU. Advanced life support was not uncommonly used among DKA patients, with 39%, 17%, and 12% receiving MV, vasopressor therapy, and RRT, respectively. Median ICU length of stay was longer for those with severe compared with moderate DKA. In-hospital death was uncommon, occurring exclusively in those with severe DKA. Hospital readmission was common, occurring in 36% by 1 year. Documentation of a discharge plan in the medical record was poor, occurring in only 46%. Follow-up with an endocrinologist, general practitioner, and/or DM clinic was relatively uncommon (Table 3). When compared with matched non-DM ICU patients, DKA patients had lower ICU and in-hospital mortality and lower overall ICU and hospital lengths of stay (Table 4). 3.4. Analysis of patients with unfavourable outcomes Table 5 describes DKA patients stratified by death and/or hospital readmission at 1 year. No patient with a new diagnosis of DM died or was readmitted. However, death/readmission was more common among DKA patients with noncompliance and sepsis as precipitants.
Table 4 Comparison of clinical characteristics and outcomes of DKA patients and matched controls Variable
Overall DKA patients (n = 76)
Matched controls (n = 356)
Pa
Age, y Male sex, n (%) APACHE II, points Diagnostic category, n (%) Medical, n (%) Surgical, n (%) Major diagnosis, n (%) Pneumonia/sepsis Gastrointestinal diseases Trauma (excluding TBI) TBI Drug overdose Other ICU LOS, d Hospital LOS, d ICU mortality, n (%) Hospital mortality, n (%) Discharge disposition, n (%) Home Acute care Chronic care Other b
38.6 ± 12.9 41 (54) 21.1 ± 8.4
38.3 ± 13 198 (56) 21.0 ± 8.3
74 (97) 2 (3)
268 (75) 87 (25)
.847 .790 .781 b.001 – –
– – – – – – 2 (1-4) 7 (4-11) 3 (4) 3 (4) n = 73 59 (80) 7 (10) 3 (4) 4 (6)
72 (20) 45 (13) 35 (10) 32 (9) 34 (9) 138 (39) 3 (2-9) 14.5 (7-31) 53 (15) 67 (19) n = 289 195 (67) 55 (19) 31 (11) 8 (3)
– – – – – – b.001 b.001 .001 .001 .036 – – – –
TBI indicates traumatic brain injury. a Student t test for comparisons of continuous parametric data, Mann-Whitney U for continuous nonparametric data, and χ2 and Fisher exact tests for comparisons of categorical data. b Left without authorization or unknown.
By logistic regression analysis, after adjusting for age, sex, and APACHE II score, the use of insulin (odds ratio, 4.79; 95% CI, 1.1420.05; P = .032) and noncompliance as a precipitant (odds ratio, 3.33; 95% CI, 1.04-10.64; P = .042) were independently associated with death and/or readmission within 1 year (Fig. 1.). 3.5. Sensitivity analysis of noncompliant patients Tables E1 and E2 (Supplemental Digital Content) describe the clinical characteristics, resource use, and outcomes of DKA patients stratified by noncompliance as the major precipitant for DKA. Noncompliant patients were younger, were more likely to have had a prior hospitalization for DKA, were more likely to have severe DKA at presentation, were more likely admitted from the emergency department, and were more likely users of insulin. Noncompliant patients also had higher mortality at 1 year (19% vs 2%; P = .024) as compared with those with adequate treatment. 4. Discussion We performed a 2-center retrospective matched cohort study of all adult patients admitted to intensive care with DKA to describe the incidence, clinical characteristics, resource utilization, and long-term outcomes. We found that DKA was an uncommon diagnosis associated with ICU admission, representing only 0.45% of total admissions. However, we showed that these patients often receive substantial advanced life support, including MV, vasoactive drugs, and RRT, to treat complications associated with DKA and its precipitants. We also identified noncompliance with DM treatment and sepsis as the predominant precipitants for DKA, in particular, for those presenting with more severe illness. As expected, the mortality associated with DKA was low, however, was not insignificant. Approximately 1 in 10 DKA patients admitted to ICU were dead at 1 year. Moreover, rehospitalization among patients admitted to ICU with DKA was common, occurring in 36% by 1 year. Noncompliance with prescribed diabetic therapy and insulin use were both found to be independent risk factors for mortality or rehospitalization. When compared with matched ICU controls, DKA patients generally
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Table 5 Clinical characteristics, resource intensity, and outcomes of DKA patients according to death or readmission in 1 year after index DKA admission Variable
All patients (n = 76)
Alive/not-readmitted (n = 44)
Death/ readmission (n = 32)
Pa
Age, y Male Sex, n (%) Charlson score, points APACHE II, points SOFA score D1, points DM diagnosis, (n = 63) Type I DM, n (%) Type II DM, n (%) New DM diagnosis, n (%) Time of diagnosis, y Medications before DKA episode, n (%) b Insulin use OHA use No therapy Precipitant for DKA, n (%)b Noncompliance Infection Ethanol abuse Pancreatitis New diagnosis Unknown DKA severe at presentation, n (%) Time-to-DKA resolution, d MV, n (%) Vasopressors, n (%) RRT, n (%) AKI, n (%) ICU LOS, d Hospital LOS, d Prior DKA admission, n (%) Discharge plan in chart, n (%) Follow-up with endocrinologist, n (%) Follow-up with general practitioner, n (%) Follow-up for DM teaching/outpatient clinic, n (%)
38.6 ± 12.9 41 (54) 1 (1-3) 21.1 ± 8.4 5 (2-7)
38.6 ± 12.6 24 (55) 1(1-2.5) 20.5 ± 7.2 5 (3-7)
38.6 ± 13.3 17 (53) 1 (1-3) 21.8 ± 9.7 4.5 (2-8)
.991 .902 .748 .505 .745
50 (79) 112 (21) 9 (13) 6 (1.5-19.5)
24 (55) 7 (16) 9 (20) 6.5 (0-20.5)
26 (81) 5 (16) 0 (0) 5.5 (3-19.5)
.707 – .004 .623
54 (71) 9 (12) 17 (22)
25 (57) 6 (14) 15 (34)
29 (91) 3 (9) 2 (6)
.001 .570 .004
34 (45) 30 (39) 10 (13) 10 (13) 9 (12) 9 (12) 32 (42) 1 (1,2) 30 (39) 13 (17) 9 (12) 62 (82) 2 (1-4) 7 (4-11) 24 (32) 35 (46) 16 (21) 12 (16) 14 (18)
13 (30) 21 (48) 6 (14) 6 (14) 8 (18) 4 (9) 17 (38) 1 (1,2) 18 (41) 8 (18) 3 (7) 36 (82) 2 (1-5) 8 (4.5-12.5) 10 (23) 23 (52) 10 (23) 10 (23) 9 (20)
21 (66) 9 (28) 4 (13) 4 (13) 1 (3) 5 (16) 15 (46) 1 (1,2) 12 (38) 5 (16) 6 (19) 26 (81) 2 (1-3) 6 (3-9) 14 (44) 12 (38) 6 (18) 2 (6) 5 (16)
.005 .037 .761 .761 .031 .473 .473 .639 .521 .632 .151 .286 .208 .056 .087 .092 .526 .034 .464
a b
Student t test for comparisons of continuous parametric data, Mann-Whitney U for continuous nonparametric data, and χ2 and Fisher exact tests for comparisons of categorical data. More than one may apply.
remained in the ICU and hospital for fewer days and had lower mortality. However, our data suggest that many of these deaths and readmissions associated with DKA may have been avoidable. These observations would imply that there are likely missed opportunities for reducing complications, improving outcomes, and reducing unnecessary resource use among patients with DM. 4.1. Interpretation and context with prior literature Few data have specifically evaluated the characteristics, outcomes, and resource use among adult patients with DKA admitted to ICU [1,6,14]. Studies not focused solely in pediatric populations to date have been limited by study design, small sample size, and variable case mix (ie, inclusion of both ICU and non-ICU patients) [15,16]. Likewise, prior studies have limited generalizability due to variation in policy for management of DKA and in critical care service delivery. A previous large study of DKA admissions in the United States found wide variability on the utilization of ICU for DKA patients (range, 2.1%87.7%). Hospitals with greater volume of DKA admissions were less likely to admit these patients to the ICU. Although this observed variation was not associated with significant differences in lengths of stay or mortality, these data suggest that institutional practice patterns appear to impact ICU utilization for DKA patients [6]. Furthermore, among patients admitted to hospital with DKA, prior data have suggested that only 8% to 23% had received MV [14,15], implying the decision to triage to ICU may not have centered solely on patient illness severity but rather determined by policy for DKA management (ie, insulin infusion). In contrast, DKA patients in our cohort were significantly more likely to be supported with MV (39% overall and 84% among severe DKA subgroup). Likewise, in a cohort
study of a single-center medical ICU in the United States, DKA was the primary admission diagnosis in 7.6% with an average APACHE II score of 12 [1]. In contrast, in our data, DKA represented less than 1% of admissions, and our cohort was characterized by markedly higher APACHE II score, in particular, among those with severe DKA. Prior studies have shown the development of severe AKI associated with DKA, and initiation of RRT is a relatively uncommon complication [17]. In contrast, 82% of the DKA patients in our cohort presented with AKI and 12% were temporarily supported with RRT. This trend is likely related to both the severity of underlying and precipitating conditions (ie, sepsis) and severity of DKA, whereas patients with milder DKA likely had less severe AKI that resolved rapidly with resuscitation and were more likely triaged to non-ICU settings (ie, hospital ward or high-dependency unit). Noncompliance in our study was found to be the most common precipitant for moderate-to-severe DKA requiring ICU admission, occurring more commonly among younger patients and insulin users. These patients also had trends for higher illness severity at presentation and worse long-term glycemic control (ie, as measured by hemoglobin A1C levels). Moreover, noncompliance was also shown to predict with higher health resource use, in particular, rehospitalization and less favorable outcomes. Noncompliance has repeatedly been identified as an important and potentially avoidable precipitant for DKA across all age groups [18-20]. Indeed, in the diabetes audit and research in Tayside Scotland (DARTS) study, adherence to prescribed diabetic therapy in young patients was inversely related to episodes of DKA, hospitalizations, and poor long-term glycemic control [21]. Similar to our data, Hjort and Christensen [18] found that noncompliance was the major precipitant among mainly young diabetic patients hospitalized with DKA. Psychosocial factors may
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Fig. 1. Interaction of independent risk factors for DKA readmission and/or death in the 1 year after a DKA episode.
contribute to noncompliance, including lower socioeconomic status (ie, social welfare or unemployment) and self-reported treatment error (ie, incorrect management of insulin during illness) [22]. 4.2. Implications for health policy Episodes of DKA among patients known to have DM should be avoidable, in particular, for those with noncompliance as a primary precipitant. The observation that noncompliance remains the most common precipitant for moderate-to-severe DKA prompting ICU admission would imply an important gap in health services delivery. Importantly, we observed that a relatively low proportion of these DKA patients had documented discharge care plans or scheduled follow-up, in particular, among those with noncompliance as a precipitant. These at-risk patients would appear to benefit from patient-centered strategies focused on simplifying access, education (ie, insulin management during illness), and treatment of concomitant illness (ie, mental illness) [19,23]. Prior data have supported the implementation of multidisciplinary programs to address barriers to communication, access to care, and treatment. From an economics perspective, based on US data of an average 100 000 annual hospitalizations for DKA, with an estimated average cost of $13 000 United States Dollars per patient, the annual attributable acute hospitalization costs for episodes of DKA may exceed $1 billion United States Dollars per year [24]. Moreover, the costs associated with admission to ICU may exceed 20% of these estimated expenditures [20,25]. Accordingly, these observations and our study would highlight the importance of additional research to investigate the most cost-effective strategies, whether in the inpatient or outpatient setting, to improve diabetes self-management and prevent unnecessary health resource use for avoidable episodes of DKA. 4.3. Limitations Our study has a number of limitations to consider. First, it was retrospective in design with a relatively small sample size and few
events, limiting the statistical power. Second, our study was focused on DKA patients admitted to ICU. As such, we have no data on those DKA patients admitted directly to hospital wards or managed in the emergency department. Third, DKA patients in this study were admitted to the 2 tertiary level teaching hospitals in a large urban health region in Canada. Accordingly, our results may have limited generalizability to other health jurisdictions with differing health insurance models. Fourth, we were unable to perform a more detailed matching of DKA and non-DKA patients for additional variables such as Charlson comorbidity score and SOFA score, which may have reduced the risk of residual confounding. Finally, we did not have data available on the long-term outcomes for matched controls that limited comparison of health resource utilization after index hospitalization. 5. Conclusions Diabetic ketoacidosis in adult patients necessitating ICU admission is associated with considerable resource utilization and long-term risk for death. Insulin use and noncompliance are independent risk factors for death or readmission. Interventions aimed to increase compliance with therapy may prevent avoidable readmissions and improve the long-term outcome. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.jcrc.2014.07.034. References [1] Freire AX, Umpierrez GE, Afessa B, et al. Predictors of intensive care unit and hospital length of stay in diabetic ketoacidosis. J Crit Care 2002;17(4):207–11. [2] Magee MF, Bhatt BA. Management of decompensated diabetes. Diabetic ketoacidosis and hyperglycemic hyperosmolar syndrome. Crit Care Clin 2001;17 (1):75–106. [3] Bull SV, Douglas IS, Foster M, et al. Mandatory protocol for treating adult patients with diabetic ketoacidosis decreases intensive care unit and hospital lengths of stay: results of a nonrandomized trial. Crit Care Med 2007;35(1):41–6. [4] Chiasson JL, Aris-Jilwan N, Belanger R, et al. Diagnosis and treatment of diabetic ketoacidosis and the hyperglycemic hyperosmolar state. CMAJ 2003;168(7):859–66. [5] Marinac JS, Mesa L. Using a severity of illness scoring system to assess intensive care unit admissions for diabetic ketoacidosis. Crit Care Med 2000;28(7):2238–41.
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