Clinical profile of patients with diabetic ketoacidosis and hyperglycemic hyperosmolar syndrome in Japan: A multicenter retrospective cohort study

Clinical profile of patients with diabetic ketoacidosis and hyperglycemic hyperosmolar syndrome in Japan: A multicenter retrospective cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Clinical profile of patients with diabetic ketoacidosis and hyperglycemic hyperosmolar syndrome in Japan: A multicenter retrospective cohort study Kyosuke Takahashi, Norimichi Uenishi, Masamitsu Sanui, Shigehiko Uchino, and 26 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2467653/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Diabetic ketoacidosis (DKA) and hyperglycemic hyperosmolar syndrome (HHS) are life-threatening complications of diabetes mellitus. Their clinical profiles have not been fully investigated in the Japanese population. Methods: A multicenter retrospective cohort study was conducted in 21 acute care hospitals in Japan. Patients included were adults aged 18 or older who had been hospitalized from January 1, 2012, to December 31, 2016 due to DKA or HHS. The clinical characteristics and outcomes were extracted from patient medical records. A four-group comparison (mild DKA, moderate DKA, severe DKA, and HHS) was performed to evaluate outcomes. Results: A total of 771 patients including 545 patients with DKA and 226 patients with HHS were identified during the study period. The major precipitating factors of disease episodes were poor medication compliance, infectious diseases, and excessive drinking of sugar-sweetened beverages. The median hospital stay was 16 days [IQR 10-26 days] and was longer in the HHS group (19.5 days) compared to the DKA groups (16 days). The intensive care unit (ICU) admission rate was 44.4% (mean) and the rate at each hospital ranged from 0% to 100%. The median ICU stay was 3 days for all groups. The in-hospital mortality rate was 2.8% in patients with DKA and 7.1% in the HHS group. No significant difference in mortality was seen among the three DKA groups. The most common complication was infection (18%), followed by pulmonary edema (2.7%), stroke (2.1%), ventricular arrhythmia (1.6%), and deep vein thrombosis (1%). Conclusions: The mortality rate of patients with DKA in Japan is similar to other studies, while that of HHS was lower. The ICU admission rate varied among institutions. There was no significant association between the severity of DKA and mortality in the study population. Trial registration: This study is registered in the UMIN clinical trial registration system (UMIN000025393, Registered 23th December 2016) diabetes hyperglycemic emergencies hyperglycemic crisis intensive care epidemiology prognosis Figures Figure 1 Figure 2 Background Hyperglycemic emergencies are serious acute complications of diabetes that include diabetic ketoacidosis (DKA) and hyperglycemic hyperosmolar syndrome (HHS)[ 1 ]. DKA is characterized by hyperglycemia, metabolic acidosis, and ketonemia while HHS presents with severe hyperglycemia, high serum osmolality, and dehydration[ 2 ], which require close monitoring of electrolytes and vital signs. Clinical characteristics of patients with hyperglycemic emergencies have been investigated in several studies. Typically, DKA is common among young patients with type 1 diabetes while HHS often occurs in the elderly with type 2 diabetes. Common precipitating factors of hyperglycemic emergencies are infection, non-compliance, or acute conditions such as stroke, myocardial infarction, and trauma[ 3 ] , [ 4 ]. Additionally, many drugs such as corticosteroids and antipsychotic medications have been reported to impair glucose tolerance[ 5 ]. These factors affect not only the pathophysiology of the hyperglycemic crisis but also the overall prognosis. Although these precipitating factors have been suggested, the actual prevalence of these factors in patients with hyperglycemic emergencies is unknown. The epidemiology and management of patients with acute hyperglycemic emergencies vary among countries. The reported mortality rate of patients with DKA in developed countries ranges from 0.16–4.1% [ 6 ] , [ 7 ] , [ 8 ]whereas in developing countries it is higher[ 9 ] , [ 10 ]. HHS-related mortality is reported to be 10 to 20%, approximately 10 times higher than that of DKA[ 3 ] , [ 11 ]. Trends in the rate of hospitalization and use of intensive care for patients with DKA and HHS vary by country and variation exists even among institutions in the same region[ 12 ] , [ 13 ]. Interestingly, these variations were reported not to affect the length of hospital stay or mortality of the patients[ 13 ]. Some feel that emergency departments or even general wards can provide an appropriate level of care with improved cost-effectiveness compared to admission to the intensive care unit (ICU) [ 14 ]. Currently, there is no consensus regarding whether to use the ICU for the care of such patients, leaving optimal resource allocation in controversy[ 15 ]. The aim of this study is to provide a detailed clinical profile of patients with DKA and HHS and the use of the ICU for these patients in Japan. The patients’ background, mortality, complications, precipitants, and use of hospital beds and other medical resources were investigated. Methods Study design A retrospective cohort study was conducted to investigate the clinical characteristics of patients with hyperglycemic emergencies. Participating facilities included 21 acute care hospitals in Japan. This is a part of the CLORINE study (The effeCt of fLuid therapy On kidney function in hypeRglycemIc emergeNciEs. A multicenter retrospective study), registered in the UMIN clinical trial registration system (UMIN000025393). The study design was approved by the ethics committee of each institution with a waiver of informed consent prior to collecting the data. Patients Patients included in the study were adults aged 18 years or older admitted to the hospital due to DKA or HHS from January 1, 2012, to December 31, 2016. Individuals who received treatment in the emergency department were also included. Patients were initially identified according to ICD-10 coding. Subsequently, diagnoses were confirmed with laboratory data according to the criteria of the American Diabetes Association as follows: DKA (meets all below): Serum glucose > 250 mg/dl pH of arterial blood gas (ABG) ≤ 7.30 or HCO 3 ≤ 18 mmol/L Positive urine or blood ketone HHS (meets all below): Serum glucose > 600 mg/dl pH of ABG > 7.30 and HCO 3 > 18 mmol/L Negative or low positive urine/blood ketone Patients with DKA were also classified into 3 groups- severe (ABG pH < 7.0 or HCO3 7.25 and HCO3 < 10 mmol/L), and moderate (neither mild nor severe) for analysis. Exclusion criteria were missing data necessary for diagnosis. Outcomes and Data collection The primary outcome was in-hospital mortality from any cause. Secondary outcomes were serious complications including cardiovascular events, infection, length of hospital stay and ICU stay, and use of intensive therapy (ventilator, vasopressors, and renal replacement therapy). Data were obtained through patient medical records in participating facilities. Data extraction for each patient included patient characteristics, type, duration, and treatment of diabetes, complications of diabetes, precipitating factors for hyperglycemic emergencies (including factors associated with patient behavior, acute medical events, and medications affecting diabetes), admission route and type of ward, complications during hospitalization, and requirement for intensive therapy. Medications affecting diabetes were defined as corticosteroids, atypical antipsychotics, thiazides, quinolones, and phenytoin. Complications were limited to newly diagnosed adverse events during hospitalization, excluding comorbidities that existed prior to admission. For patients who died, causes of death were also recorded. Statistical analysis Continuous variables were presented with a mean (±SD: standard deviation) and median (IQR: interquartile range) as appropriate. Categorical variables were expressed with percentages. Clinical features and outcomes were compared among the four groups (HHS and the 3 groups of DKA stratified by severity). The type of admission ward is aggregated by each institution. On the basis of the normality of the data, continuous variables were analyzed with the ANOVA or the Kruskal-Wallis test for four-group comparisons. For categorical data, the chi-square test was used. P-value < 0.05 was considered statistically significant. All analyses were performed using R version 4.0.3 (R Foundation for Statistical Computing, Vienna, Austria). Results During the study period, 771 patients were admitted to participating hospitals with DKA (545 patients) and HHS (226 patients). The mean age of the patients was 58.3 years (SD 19.3) and the proportion of males was 54.7%. Among patients with DKA, 19% (n = 104) were mild, 23.7% (n = 129) were moderate, and 57.2% (n = 312) were severe. Table 1 shows the baseline characteristics of the patients. Compared with the DKA groups, patients with HHS were older and had more comorbidities, including hypertension, ischemic heart disease, chronic heart failure, and stroke. Table 1 Patient baseline characteristics Mild DKA Moderate DKA Severe DKA HHS P value (n = 104) (n = 129) (n = 312) (n = 226) Age, years, mean (SD) 56.0 (18.8) 56.3 (18.7) 49.9 (17.1) 71.9 (14.9) < 0.001 Female gender, n (%) 47 (45.2) 60 (46.5) 141 (45.2) 103 (45.6) 0.99 Body-mass index, mean (SD) 23.3 (6.1) 22.1 (5.0) 21.9 (4.8) 21.6 (4.7) 0.04 Diabetic retinopathy, n (%) 20 (27.8) 26 (28.6) 40 (18.4) 37 (28.9) 0.07 Diabetic nephropathy, n (%) 32 (41.6) 25 (26.6) 75 (32.1) 50 (35.0) 0.20 Diabetic neuropathy, n (%) 22 (31.0) 20 (22.0) 68 (30.9) 26 (20.5) 0.10 Hypertension, n (%) 44 (45.8) 43 (35.8) 73 (25.9) 123 (57.2) < 0.001 Dyslipidemia, n (%) 26 (27.1) 34 (29.3) 62 (21.7) 56 (27.2) 0.32 Ischemic heart disease, n (%) 4 (4.3) 8 (7.1) 12 (4.2) 33 (16.1) < 0.001 Chronic heart failure, n (%) 3 (3.2) 4 (3.5) 11 (3.8) 37 (18.0) < 0.001 Stroke, n (%) 11 (11.7) 8 (7.1) 10 (3.5) 52 (25.0) < 0.001 Peripheral artery disease, n (%) 3 (3.3) 2 (1.8) 4 (1.4) 2 (1.0) 0.54 Mental disorder, n (%) 16 (15.4) 21 (16.3) 51 (16.3) 20 (8.8) 0.07 Duration of diabetes, n (%) < 0.001 New onset 29 (28.2) 34 (26.6) 79 (25.3) 40 (17.8) 10 years 39 (37.9) 39 (30.5) 98 (31.4) 78 (34.7) Unknown 15 (14.6) 22 (17.2) 40 (12.8) 68 (30.2) Fulminant type 1 diabetes, n (%) 4 (3.9) 8 (6.2) 25 (8.2) 1 (0.4) 0.001 Type of diabetes, n (%) < 0.001 Type 1 37 (35.9) 54 (42.2) 163 (52.2) 24 (10.7) Type 2 62 (60.2) 71 (55.5) 126 (40.4) 184 (81.8) Others 2 (1.9) 2 (1.6) 12 (3.8) 7 (3.1) Unknown 2 (1.9) 1 (0.8) 11 (3.5) 10 (4.4) Treatment before admission, n (%) < 0.001 Insulin 29 (27.9) 50 (38.8) 120 (38.6) 31 (13.8) Oral medications 18 (17.3) 19 (14.7) 30 (9.6) 79 (35.3) Insulin + Oral medications 12 (11.5) 12 (9.3) 47 (15.1) 28 (12.5) No medication 45 (43.3) 46 (35.7) 110 (35.4) 83 (37.1) Unknown 0 (0.0) 2 (1.6) 4 (1.3) 3 (1.3) Admission route, n (%) 0.17 Emergency department 77 (74.0) 101 (78.3) 252 (80.8) 179 (79.2) General outpatient 13 (12.5) 18 (14.0) 24 (7.7) 29 (12.8) Transfer from other hospitals 14 (13.5) 10 (7.8) 36 (11.5) 18 (8.0) DKA: Diabetic ketoacidosis, HHS: Hyperosmolar hyperglycemic syndrome, SD: Standard deviation P values are results of the ANOVA or the Kruskal-Wallis test for four-group comparisons. The duration of diabetes varied among the patients. While the proportion of new onset diabetes was 23.6%, 32.9% of the patients had been treated for more than 10 years. Type 2 diabetes was prevalent in the HHS group (81.8%) and type 1 diabetes was most frequent in the severe DKA group (52.5%). Regarding treatment before admission, the proportion of patients receiving insulin therapy is higher in DKA groups, while oral medication was common in the HHS group. A total of 284 (36.8%) patients had taken no medications to treat diabetes mellitus prior to hospital admission. In terms of factors precipitating a hyperglycemic emergency, poor adherence to treatment, infectious diseases, and excessive intake of sugar-sweetened beverages were major factors (Table 2 ). Poor adherence was most prevalent in the DKA groups (47.7%) and infectious diseases were the most frequent factor in the HHS group (42.7%). Some patients took medications that could increase the severity of diabetes. Corticosteroids were prescribed for 6.2% of patients with HHS, and the proportion was higher than in patients with DKA. Table 2 Precipitating factors identified in patients with DKA and HHS Mild DKA Moderate DKA Severe DKA HHS P value (n = 104) (n = 129) (n = 312) (n = 226) Precipitating factors Poor adherence 39 (39.0) 65 (51.2) 156 (51.7) 71 (32.1) < 0.001 Excessive sugar sweetened beverages 25 (25.3) 33 (26.2) 69 (23.2) 47 (21.4) 0.74 Excessive alcohol beverages 6 (5.9) 15 (11.7) 32 (10.7) 4 (1.8) < 0.001 Cessation of diabetes medication by treating physician 3 (2.9) 1 (0.8) 5 (1.6) 11 (4.9) 0.057 Infectious disease 38 (36.9) 39 (31.0) 108 (35.2) 96 (42.7) 0.14 Ischemic heart disease 0 (0.0) 2 (1.6) 4 (1.3) 3 (1.3) 0.69 Heart failure 0 (0.0) 0 (0.0) 3 (1.0) 7 (3.1) 0.03 Stroke 6 (5.8) 3 (2.3) 1 (0.3) 4 (1.8) 0.004 Pancreatitis 2 (1.9) 3 (2.4) 15 (4.8) 2 (0.9) 0.048 Trauma 3 (2.9) 3 (2.3) 2 (0.6) 8 (3.5) 0.12 Surgery 0 (0.0) 0 (0.0) 0 (0.0) 1 (0.4) 0.49 Medications Corticosteroids 1 (1.0) 4 (3.1) 4 (1.3) 14 (6.2) 0.006 Thiazides 0 (0.0) 1 (0.8) 3 (1.0) 6 (2.7) 0.16 Beta blockers 0 (0.0) 0 (0.0) 2 (0.6) 4 (1.8) 0.19 Olanzapine 0 (0.0) 1 (0.8) 0 (0.0) 1 (0.4) 0.44 Quetiapine 1 (1.0) 1 (0.8) 2 (0.6) 1 (0.4) 0.95 Clozapine 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) NA Asenapine 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) NA Quinolones 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) NA Phenytoin 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) NA All data are presented as number (%). DKA: Diabetic ketoacidosis, HHS: Hyperosmolar hyperglycemic syndrome P values are results of the ANOVA or the Kruskal-Wallis test for four-group comparisons. Outcomes during hospital admission are shown in Table 3 . The median hospital stay was 16 days [IQR 10–26 days] and was longer in the HHS group (19.5 days) compared to the DKA groups (16 days). The ICU admission rate was 44.4% on average and highest in the severe DKA group (55.1%). ICU admission rate in each hospital ranged from 0–100% (Fig. 1 ). The median ICU stay was 3 days, the same for all groups. Table 3 Outcomes Mild DKA Moderate DKA Severe DKA HHS P value (n = 104) (n = 129) (n = 312) (n = 226) In-hospital mortality, n (%) 3 (2.9) 3 (2.3) 9 (2.9) 16 (7.1) 0.05 Infection, n (%) 17 (16.3) 13 (10.1) 57 (18.3) 52 (23.0) 0.02 Acute coronary syndrome, n (%) 1 (1.0) 1 (0.8) 0 (0.0) 1 (0.4) 0.45 Pulmonary edema, n (%) 2 (1.9) 2 (1.6) 7 (2.2) 10 (4.4) 0.30 Ventricular arrhythmia(%) 2 (1.9) 2 (1.6) 2 (0.6) 6 (2.7) 0.31 Stroke, n (%) 3 (2.9) 1 (0.8) 8 (2.6) 4 (1.8) 0.60 Deep vein thrombosis, n (%) 1 (1.0) 1 (0.8) 3 (1.0) 3 (1.3) 0.96 Hospital stay, days, median [IQR] 16 [ 10 , 26 ] 15 [ 8 , 22.5] 16 [ 10 , 24 ] 19.5 [ 12 , 31 ] 0.001 ICU admission, n (%) 28 (26.9) 53 (41.1) 172 (55.1) 89 (39.4) < 0.001 ICU stay, days, median [IQR] 3 [ 2 , 5 ] 3 [ 2 , 4 ] 3 [ 2 , 5 ] 3 [ 2 , 5 ] 0.19 HCU admission, n(%) 31 (29.8) 39 (30.2) 106 (34.0) 51 (22.6) 0.04 HCU stay, days, median [IQR] 3 [ 2 , 4 ] 3 [ 2 , 5 ] 3 [ 2 , 5 ] 4 [ 2 , 7 ] 0.41 SOFA score on admission, median [IQR] 0 [0, 2] 0.5 [0, 3] 2 [0, 4] 2.5 [0, 5] < 0.001 Organ support Mechanical ventilation, n (%) 6 (5.8) 3 (2.3) 34 (10.9) 9 (4.0) 0.001 Vasopressor use, n (%) 3 (2.9) 3 (2.3) 42 (13.5) 20 (8.8) < 0.001 Renal replacement therapy, n (%) 1 (1.0) 2 (1.6) 16 (5.1) 5 (2.2) 0.06 Renal replacement therapy on discharge, n (%) 0 (0.0) 1 (0.8) 2 (0.6) 3 (1.3) 0.62 DKA: Diabetic ketoacidosis, HHS: Hyperosmolar hyperglycemic syndrome, GCS: Glasgow coma scale, SBP: Systolic blood pressure, SOFA: sequential organ failure assessment, ICU: Intensive care unit, HCU: High care unit, IQR: Interquartile range P values are results of the ANOVA or the Kruskal-Wallis test for four-group comparisons. With regard to intensive therapy, 52 (6.7%) patients were mechanically ventilated, 68 (8.8%) were treated with vasopressors, and 24 (3.1%) required renal replacement therapy. Six (0.7%) patients needed maintenance dialysis on discharge. Overall, patients in the severe DKA group required organ support more frequently compared to the other groups. In the entire cohort, 31 (4%) patients died during admission. The in-hospital mortality rate was 2.8% in patients with DKA and 7.1% in the HHS group, respectively. No significant difference was seen among the DKA groups. The most common complication was infection (18%), followed by pulmonary edema (2.7%), stroke (2.1%), ventricular arrhythmia (1.6%), and deep vein thrombosis (1%). Figure 2 shows in-hospital events (mortality + complications) according to group. The rate of events was higher in the HHS group than in other groups and was similar among the 3 DKA groups (not proportional to severity). The causes of mortality are presented in Table 4 . Twenty (65%) of 31 deaths were due to infection. Other causes included stroke, pulmonary edema, acute coronary syndrome, and ventricular arrhythmia. Table 4 Causes of mortality Mild DKA Moderate DKA Severe DKA* HHS* P value (n = 3) (n = 3) (n = 9) (n = 16) Infection 1 (33.3) 1 (33.3) 5 (55.6) 13 (81.2) 0.19 Stroke 1 (33.3) 1 (33.3) 0 (0.0) 0 (0.0) 0.03 Acute coronary syndrome 0 (0.0) 0 (0.0) 1 (11.1) 0 (0.0) 0.47 Pulmonary edema 0 (0.0) 0 (0.0) 0 (0.0) 2 (12.5) 0.57 Ventricular arrhythmia 0 (0.0) 0 (0.0) 0 (0.0) 1 (6.2) 0.81 Pulmonary embolism 0 (0.0) 0 (0.0) 1 (11.1) 0 (0.0) 0.47 Others 1 (33.3) 1 (33.3) 4 (44.4) 2 (12.5) 0.35 All data are presented as number numbers (%). *Some patients with severe DKA and HHS had multiple causes. DKA: Diabetic ketoacidosis, HHS: Hyperosmolar hyperglycemic syndrome P values are results of the ANOVA or the Kruskal-Wallis test for four-group comparisons. Discussion The present study describes the clinical characteristics of patients with hyperglycemic crises using data obtained from multiple institutions in Japan. The mortality rate of patients with DKA and HHS was 2.8% and 7.1%, respectively. No linear relationship was found between the severity of DKA and mortality. Major precipitating factors of acute episodes were poor adherence to treatment regimens, infections, and intake of excessive sugar-sweetened beverages. The rate of ICU admission varied among institutions. The mortality rate of patients with DKA and HHS varies among countries and has changed over time. In recent publications, the mortality rate of patients with DKA has been reported from 0.16–4.1%[ 6 ] , [ 7 ] , [ 8 ] whereas that of HHS was between 10 to 20%[ 3 ] , [ 11 ]. The results of the present study are similar to previous reports for DKA but the mortality rate of patients with HHS in the present study was lower. The reason for this difference is unclear but could be explained by global trends in improving diabetes care. A report based on a US national survey showed that the mortality rate of patients with DKA was decreasing while hospitalization was increasing[ 7 ]. This improvement might be attributed to increased awareness of the disease and adaption of established guidelines for the treatment of patients with DKA. It is unclear if severity of DKA correlates with mortality or not. While some studies indicated an association between them[ 8 ] , [ 16 ], other studies found that other factors were more important than DKA severity. For example, a previous study of a prediction model for the prognosis of patients with DKA concluded that coexisting severe diseases are the most significant predictor for mortality[ 17 ]. Another study suggested that advanced age and altered levels of consciousness were important predictors of mortality as well as electrolyte disturbances[ 18 ]. In the present study, the severe DKA group was younger and the prevalence of comorbidities such as stroke was lower compared with the other DKA groups. Considering the findings of the present study and previous reports, the severity of DKA may be less important than other factors such as patient age or comorbidities. Treatment in the ICU has been considered appropriate for patients with hyperglycemic crises for decades as indicated in the guidelines[ 19 ] , [ 20 ]. The essentials of treatment for hyperglycemic crises are fluid resuscitation, electrolyte replacement, and insulin infusion, which require close monitoring of vital signs, electrolytes, and blood glucose levels. However, recent studies have shown that DKA can be safely managed in the emergency department[ 21 ] or even in general wards[ 22 ]. We found that differences in ICU utilization for these patients by institution was quite varied, ranging from 0–100%. Such a discrepancy may reflect variations in practice and setting of each hospital. A study including 159 hospitals in the United States also reported ICU admission rates from 2.1 to 87.7% but no association was found between the rates of ICU utilization and mortality or length of hospital stay[ 13 ]. Another large retrospective study involving 15,022 patients with DKA showed that institutions that utilized ICUs more frequently had higher costs but had no improvement in hospital mortality[ 23 ]. As far as proper triage and management are provided, where care is provided for these patients could be less important. Nevertheless, it should be emphasized that patients who need organ support or have severe comorbidities are suitable for management in the ICU[ 15 ]. As the present study suggests, a considerable number of patients required mechanical ventilation, vasopressor use, and renal replacement therapy. Patient profile and conditions also affect prognosis, which should be considered. Past reports suggested that older age, sepsis, coma and lower levels of activity of daily living, and severe comorbidities were risk factors for mortality[ 17 ] , [ 24 ]. Accordingly, the use of organ support as well as patient background should be taken into account for the selection of providing care in the ICU. In the present study, more than 20% of the patients reported excessive consumption of sugar-sweetened beverages prior to hyperglycemic emergencies. Both patients’ behavior and medical illnesses are important triggers for hyperglycemic emergencies[ 25 ] , [ 26 ]. Previous reports identified poor adherence and infection as common precipitants[ 2 ] , [ 27 ] , [ 28 ]. Recent studies demonstrated that increased consumption of sweet soft drinks worsens insulin resistance and impairs pancreatic beta-cell function[ 29 ] , [ 30 ], which is related to the pathophysiology of decompensated hyperglycemia. Although the exact prevalence was not documented in previous studies, the results of the present study suggest that excessive consumption of sugar-sweetened beverages may be a significant trigger for developing DKA and HHS. The present study shows the proportion of patients who were taking medications that could worsen diabetes. Several types of medication, e.g., corticosteroids[ 31 ], beta blockers[ 32 ], anti-psychotics[ 33 ], thiazides[ 34 ], quinolones[ 35 ] and phenytoin[ 5 ], have been reported to be associated with deterioration of diabetes control. Although the overall prevalence of drug-induced diabetes is unknown, approximately 15 to 50% of patients taking corticosteroids and 10% of people taking anti-psychotic medications develop diabetes[ 36 ] , [ 37 ]. Some studies have also described patients with drug-induced DKA and HHS[ 38 ] , [ 39 ]. We reviewed prescriptions for the patients with diabetes requiring emergency admission and found that a few patients were taking such medications. Although corticosteroids were prescribed in 6% of patients with HHS, only a small number of patients were taking other medications which could affect diabetes. Given that other precipitating factors are more frequent, the impact of these drugs may be less important in the context of the overall acute critical episodes. To the best of our knowledge, this is one of the largest and most detailed epidemiological studies of hyperglycemic crises in the medical literature. The strengths of this study are the large sample size and comprehensive description of patient characteristics including precipitating factors, medical resources used, and complications during hospitalization. However, the present study has also acknowledged limitations. First, multivariable regression analysis could not be conducted due to the low incidence of mortality. As a result, predictors of mortality or association between ICU admission and outcomes were not investigated. Considering the low mortality rate, studies with a much larger population such as a nationwide database will be needed to conduct multivariable regression analysis. Second, since the inclusion criteria included hyperglycemia, the present study did not enroll patients with euglycemic DKA which is currently an emerging problem[ 40 ]. However, this may be a minor issue because most of the study period was before the widespread use of sodium-glucose cotransporter 2 inhibitors in Japan. Conclusions The present study describes the clinical profile of patients with DKA and HHS in acute care hospitals in Japan. The mortality rate of patients with DKA was similar while that of HHS was lower compared to previous studies. No significant association was seen between the severity of DKA and mortality, which suggests that other factors are more important for prognosis. We found excessive consumption of sugar-sweetened beverages as a new precipitating factor of hyperglycemic crises. This risky behavior should be noted in future educational guides for the dietary habits of patients with diabetes. The indications for ICU admission should be based on not only the severity of disease but also on patient background and the need for organ support. Further studies are needed regarding the epidemiology of acute diabetic emergencies as it changes over time. Abbreviations ABG Atrial blood gas DKA Diabetic ketoacidosis HHS Hyperglycemic hyperosmolar syndrome ICU Intensive Care Unit Declarations Ethics approval and consent to participate The study design was approved by the ethics committee of Jichi Medical University (ID: RINS17-023. Registered 4 th September 2017) and each institution with a waiver of informed consent prior to collecting the data. The study was performed in accordance with the Declaration of Helsinki. Consent for publication Not applicable Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests Funding Not applicable Authors' contributions KT collected and analyzed the data and wrote the manuscript. NU designed the study and collected and analyzed the data. MS designed and directed the project. SU analyzed the data and supervised the manuscript. NY, TT, NN, HK, SO, KY, HY, SK, HT, NF, TK, TI, TK, KE, TM, TO, MH, AH, TM, YM, AY, TW, TU, TK, and TS collected and analyzed the data. AL supervised the manuscript and provided a reliable edit to correct English language errors. All authors checked and approved the final version of the manuscript. Acknowledgements Not applicable References Kitabchi AE, Umpierrez GE, Murphy MB, Kreisberg RA. Hyperglycemic crises in adult patients with diabetes: A consensus statement from the American Diabetes Association. Diabetes Care. 2006;29:2739–48. French EK, Donihi AC, Korytkowski MT. Diabetic ketoacidosis and hyperosmolar hyperglycemic syndrome: Review of acute decompensated diabetes in adult patients. BMJ. 2019;365. Pasquel FJ, Umpierrez GE. Hyperosmolar hyperglycemic state: A historic review of the clinical presentation, diagnosis, and treatment. Diabetes Care. 2014;37:3124–31. Dhatariya KK, Nunney I, Higgins K, Sampson MJ, Iceton G. National survey of the management of Diabetic Ketoacidosis (DKA) in the UK in 2014. Diabet Med. 2016;33:252–60. Fathallah N, Slim R, Larif S, Hmouda H, Ben Salem C. Drug-Induced Hyperglycaemia and Diabetes. Drug Saf. Springer International Publishing; 2015;38:1153–68. Gibb FW, Teoh WL, Graham J, Lockman KA. Risk of death following admission to a UK hospital with diabetic ketoacidosis. Diabetologia [Internet]. Diabetologia; 2016;59:2082–7. Available from: http://dx.doi.org/10.1007/s00125-016-4034-0 Benoit SR, Zhang Y, Geiss LS, Gregg EW, Albright A. Trends in Diabetic Ketoacidosis Hospitalizations and In-Hospital Mortality — United States, 2000–2014. MMWR Morb Mortal Wkly Rep [Internet]. 2018;67:362–5. Available from: http://www.cdc.gov/mmwr/volumes/67/wr/mm6712a3.htm?s_cid=mm6712a3_w Barski L, Nevzorov R, Rabaev E, Jotkowitz A, Harman-Boehm I, Zektser M, et al. Diabetic ketoacidosis: Clinical characteristics, precipitating factors and outcomes of care. Isr Med Assoc J. 2012;14:298–302. Mekonnen GA, Gelaye KA, Gebreyohannes EA, Abegaz TM. Treatment outcomes of diabetic ketoacidosis among diabetes patients in Ethiopia. Hospital-based study. PLoS One. 2022;17:1–15. Siregar NN, Soewondo P, Subekti I, Muhadi M. Seventy-two hour mortality prediction model in patients with diabetic ketoacidosis: A retrospective cohort study. J ASEAN Fed Endocr Soc. 2018;33:124–9. Fadini GP, de Kreutzenberg SV, Rigato M, Brocco S, Marchesan M, Tiengo A, et al. Characteristics and outcomes of the hyperglycemic hyperosmolar non-ketotic syndrome in a cohort of 51 consecutive cases at a single center. Diabetes Res Clin Pract. 2011;94:172–9. Venkatesh B, Pilcher D, Prins J, Bellomo R, Morgan TJ, Bailey M. Incidence and outcome of adults with diabetic ketoacidosis admitted to ICUs in Australia and New Zealand. Crit Care [Internet]. Critical Care; 2015;19:1–12. Available from: http://dx.doi.org/10.1186/s13054-015-1171-7 Gershengorn HB, Iwashyna TJ, Cooke CR, Scales DC, Kahn JM, Wunsch H. Variation in use of intensive care for adults with diabetic ketoacidosis. Crit Care Med. 2012;40:2009–15. Zhou VL, Shofer FS, Desai NG, Lorincz IS, Mull NK, Adler DH, et al. Predictors of Short Intensive Care Unit Stay for Patients with Diabetic Ketoacidosis Using a Novel Emergency Department–Based Resuscitation and Critical Care Unit. J Emerg Med [Internet]. Elsevier Inc; 2019;56:127–34. Available from: https://doi.org/10.1016/j.jemermed.2018.09.048 Mendez Y, Surani S, Varon J. Diabetic ketoacidosis: Treatment in the intensive care unit or general medical/surgical ward? World J Diabetes. 2017;8:40. John Titus George, Ajay Kumar Mishra RI. Correlation between the outcomes and severity of diabetic ketoacidosis: A retrospective pilot study. J Fam Med Prim Care [Internet]. 2018;7:787–90. Available from: http://www.jfmpc.com/article.asp?issn=2249-4863;year=2017;volume=6;issue=1;spage=169;epage=170;aulast=Faizi Efstathiou SP, Tsiakou AG, Tsioulos DI, Zacharos ID, Mitromaras AG, Mastorantonakis SE, et al. A mortality prediction model in diabetic ketoacidosis. Clin Endocrinol (Oxf). 2002;57:595–601. Novida H, Setiyawan F, Soelistijo SA. A Prediction Model of Mortality in Patients Hospitalized with Diabetic Ketoacidosis in a Tertiary Referral Hospital in Surabaya, Indonesia. Indian J Forensic Med Toxicol. 2021;15:2519–26. Kitabchi AE, Umpierrez GE, Murphy MB, Barrett EJ, Kreisberg RA, Malone JI WB. Management of Hyperglycemic Crises. Diabetes Care. 2001;24:131–53. Kitabchi AE, Umpierrez GE, Miles JM, Fisher JN. Hyperglycemic crises in adult patients with diabetes. Diabetes Care. 2009;32:1335–43. Haas NL, Whitmore SP, Cranford JA, Tsuchida RE, Nicholson A, Boyd C, et al. An Emergency Department–Based Intensive Care Unit is Associated with Decreased Hospital and Intensive Care Unit Utilization for Diabetic Ketoacidosis. J Emerg Med [Internet]. Elsevier Inc; 2020;58:620–6. Available from: https://doi.org/10.1016/j.jemermed.2019.10.005 Braatvedt G, Kwan A, Dransfield W, McNamara C, Schauer C, Miller S, et al. Differing protocols of managing adult diabetic ketoacidosis outside of the intensive care unit make no difference to the rate of resolution of hyperglycaemia and acidosis. N Z Med J. 2019;132:13–23. Chang DW, Shapiro MF. Association between intensive care unit utilization during hospitalization and costs, use of invasive procedures, and mortality. JAMA Intern Med. 2016;176:1492–9. Sato Y, Morita K, Okada A, Matsui H, Fushimi K, Yasunaga H. Factors affecting in-hospital mortality of diabetic ketoacidosis patients: A retrospective cohort study. Diabetes Res Clin Pract [Internet]. Elsevier B.V.; 2021;171:108588. Available from: https://doi.org/10.1016/j.diabres.2020.108588 Yamada K, Nonaka K. Diabetic ketoacidosis in young obese Japanese men. Diabetes Care. 1996;19:671. Tanaka K, Moriya T, Kanamori A, Yajima Y. Analysis and a long-term follow up of ketosis-onset Japanese NIDDM patients. Diabetes Res Clin Pract. 1999;44:137–46. Wachtel TJ, Tetu-Mouradjian LM, Goldman DL, Ellis SE, O’Sullivan PS. Hyperosmolarity and acidosis in diabetes mellitus - A three-year experience in Rhode Island. J Gen Intern Med. 1991;6:495–502. Randall L, Begovic J, Hudson M, Smiley D, Peng L, Pitre N, et al. Recurrent diabetic ketoacidosis in inner-city minority patients: Behavioral, socioeconomic, and psychosocial factors. Diabetes Care. 2011;34:1891–6. Yoshida M, McKeown NM, Rogers G, Meigs JB, Saltzman E, D’Agostino R, et al. Surrogate markers of insulin resistance are associated with consumption of sugar-sweetened drinks and fruit juice in middle and older-aged adults. J Nutr. 2007;137:2121–7. den Biggelaar LJCJ, Sep SJS, Mari A, Ferrannini E, van Dongen MCJM, Wijckmans NEG, et al. Association of artificially sweetened and sugar-sweetened soft drinks with β-cell function, insulin sensitivity, and type 2 diabetes: the Maastricht Study. Eur J Nutr [Internet]. Springer Berlin Heidelberg; 2020;59:1717–27. Available from: https://doi.org/10.1007/s00394-019-02026-0 Jessica L. Hwang Roy E. Weiss. Steroid-induced diabetes: a clinical and molecular approach to understanding and treatment. Diabetes Metab Res Rev [Internet]. 2014;30:96–102. Available from: http://libweb.anglia.ac.uk/ Sarafidis PA, Bakris GL. Antihypertensive treatment with beta-blockers and the spectrum of glycaemic control. Qjm. 2006;99:431–6. Lean MEJ, Pajonk F-G. Patients on Atypical Antipsychotic Drugs. Diabetes Care. 2003;26:1597–605. Shafi T, Appel LJ, Miller ER, Klag MJ, Parekh RS. Changes in serum potassium mediate thiazide-induced diabetes. Hypertension. 2008;52:1022–9. Chou HW, Wang JL, Chang CH, Lee JJ, Shau WY, Lai MS. Risk of severe dysglycemia among diabetic patients receiving levofloxacin, ciprofloxacin, or moxifloxacin in Taiwan. Clin Infect Dis. 2013;57:971–80. Bonaventura A, Montecucco F. Steroid-induced hyperglycemia: An underdiagnosed problem or clinical inertia? A narrative review. Diabetes Res Clin Pract [Internet]. Elsevier B.V.; 2018;139:203–20. Available from: https://doi.org/10.1016/j.diabres.2018.03.006 Manu P, Correll CU, Van Winkel R, Wampers M, De Hert M. Prediabetes in patients treated with antipsychotic drugs. J Clin Psychiatry. 2012;73:460–6. Vuk A, Kuzman MR, Baretic M, Osvatic MM. Diabetic ketoacidosis associated with antipsychotic drugs: Case reports and a review of literature. Psychiatr Danub. 2017;29:121–35. Chinthapalli K, Newey A, Krause M. Corticosteroid induced hyperosmolar hyperglycaemic state and hemiballismus. Oxford Med Case Reports. 2015;2015:320–2. Peters AL, Buschur EO, Buse JB, Cohan P, Diner JC, Hirsch IB. Euglycemic diabetic ketoacidosis: A potential complication of treatment with sodium-glucose cotransporter 2 inhibition. Diabetes Care. 2015;38:1687–93. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2467653","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":171588927,"identity":"4495a61d-f515-4d90-abb7-571f05944119","order_by":0,"name":"Kyosuke Takahashi","email":"data:image/png;base64,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","orcid":"","institution":"Jichi Medical University Saitama Medical Center","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Kyosuke","middleName":"","lastName":"Takahashi","suffix":""},{"id":171588928,"identity":"175f3775-b6a4-4373-abcd-d7b281b41d95","order_by":1,"name":"Norimichi Uenishi","email":"","orcid":"","institution":"Fujita Health University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Norimichi","middleName":"","lastName":"Uenishi","suffix":""},{"id":171588929,"identity":"2c14ada4-140d-4d47-a176-ae040edeae60","order_by":2,"name":"Masamitsu Sanui","email":"","orcid":"","institution":"Jichi Medical University Saitama Medical Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Masamitsu","middleName":"","lastName":"Sanui","suffix":""},{"id":171588930,"identity":"5999265d-15df-4d34-899c-0debb19e8cf9","order_by":3,"name":"Shigehiko Uchino","email":"","orcid":"","institution":"Jichi Medical University Saitama Medical Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shigehiko","middleName":"","lastName":"Uchino","suffix":""},{"id":171588931,"identity":"08339bc5-0889-48f8-98e0-087739433f1f","order_by":4,"name":"Naoki Yonezawa","email":"","orcid":"","institution":"Yokohama City Minato Red Cross Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Naoki","middleName":"","lastName":"Yonezawa","suffix":""},{"id":171588932,"identity":"d25c53ae-d856-4b93-b954-3b6611146464","order_by":5,"name":"Tetsuhiro Takei","email":"","orcid":"","institution":"Yokohama City Minato Red Cross Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tetsuhiro","middleName":"","lastName":"Takei","suffix":""},{"id":171588933,"identity":"d926f9df-1883-48bc-9491-bf3916135137","order_by":6,"name":"Norihiro Nishioka","email":"","orcid":"","institution":"Kyoto University Graduate School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Norihiro","middleName":"","lastName":"Nishioka","suffix":""},{"id":171588934,"identity":"b4667503-5391-4c2b-8799-a98df966264b","order_by":7,"name":"Hirotada Kobayashi","email":"","orcid":"","institution":"Sunnybrook Health Sciences Centre","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hirotada","middleName":"","lastName":"Kobayashi","suffix":""},{"id":171588935,"identity":"20f3d4a6-4e31-4dd8-b356-8ff059ceb658","order_by":8,"name":"Shunichi Otaka","email":"","orcid":"","institution":"International University of Health and Welfare Narita Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shunichi","middleName":"","lastName":"Otaka","suffix":""},{"id":171588936,"identity":"93b1cc24-c9b5-4fee-8440-1b78892bdce8","order_by":9,"name":"Kotaro Yamamoto","email":"","orcid":"","institution":"Musashino Red Cross Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kotaro","middleName":"","lastName":"Yamamoto","suffix":""},{"id":171588937,"identity":"5a81b9f5-2ca7-4ad4-b628-826ed3f2fcfd","order_by":10,"name":"Hideto Yasuda","email":"","orcid":"","institution":"Jichi Medical University Saitama Medical Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hideto","middleName":"","lastName":"Yasuda","suffix":""},{"id":171588939,"identity":"4630b9a7-5e28-42d7-9d85-e1e8124497fc","order_by":11,"name":"Shintaro Kosaka","email":"","orcid":"","institution":"Nerima Hikarigaoka Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shintaro","middleName":"","lastName":"Kosaka","suffix":""},{"id":171588941,"identity":"796ba62b-1690-4065-b9f7-39b6185133be","order_by":12,"name":"Hidehiko Tokunaga","email":"","orcid":"","institution":"Nerima Hikarigaoka Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hidehiko","middleName":"","lastName":"Tokunaga","suffix":""},{"id":171588944,"identity":"a0909ac2-55ac-4ab8-9be0-7bb69ac186ad","order_by":13,"name":"Naoki Fujiwara","email":"","orcid":"","institution":"Nerima Hikarigaoka Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Naoki","middleName":"","lastName":"Fujiwara","suffix":""},{"id":171588946,"identity":"9b2d8202-4832-4e77-a1d3-79c685f9f397","order_by":14,"name":"Takashiro Kondo","email":"","orcid":"","institution":"National Hospital Organization Nagoya Medical Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Takashiro","middleName":"","lastName":"Kondo","suffix":""},{"id":171588948,"identity":"ff6a785a-311f-4467-b569-3216e131c4ac","order_by":15,"name":"Tomoki Ishida","email":"","orcid":"","institution":"Nanohana Clinic","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tomoki","middleName":"","lastName":"Ishida","suffix":""},{"id":171588950,"identity":"f47da4c1-37a8-4290-ad34-83f4008183d8","order_by":16,"name":"Takayuki Komatsu","email":"","orcid":"","institution":"Juntendo University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Takayuki","middleName":"","lastName":"Komatsu","suffix":""},{"id":171588951,"identity":"2a00878e-a6ba-4551-bf37-779fb6ff20d1","order_by":17,"name":"Koji Endo","email":"","orcid":"","institution":"Kyoto University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Koji","middleName":"","lastName":"Endo","suffix":""},{"id":171588952,"identity":"d6f663c1-1ac6-4e6c-baed-86aa55d61dd6","order_by":18,"name":"Taiki Moriyama","email":"","orcid":"","institution":"Saiseikai Senri Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Taiki","middleName":"","lastName":"Moriyama","suffix":""},{"id":171588953,"identity":"046cea57-b774-41ad-8f50-c5fc2eea19b3","order_by":19,"name":"Takayoshi Oyasu","email":"","orcid":"","institution":"Hokkaido University Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Takayoshi","middleName":"","lastName":"Oyasu","suffix":""},{"id":171588954,"identity":"65984827-5522-41a5-9882-939da5aa0a93","order_by":20,"name":"Mineji Hayakawa","email":"","orcid":"","institution":"Hokkaido University Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mineji","middleName":"","lastName":"Hayakawa","suffix":""},{"id":171588955,"identity":"6bee5567-6678-4b64-abf8-6dbe17578bcd","order_by":21,"name":"Atsumi Hoshino","email":"","orcid":"","institution":"Tokyo Women’s Medical University Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Atsumi","middleName":"","lastName":"Hoshino","suffix":""},{"id":171588956,"identity":"a6ac3ad1-79eb-442f-8a32-b013213bdbfd","order_by":22,"name":"Tasuku Matsuyama","email":"","orcid":"","institution":"Kyoto Prefectural University of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tasuku","middleName":"","lastName":"Matsuyama","suffix":""},{"id":171588957,"identity":"44e11619-6bc0-4f31-9898-c98bfe2e7e02","order_by":23,"name":"Yuki Miyamoto","email":"","orcid":"","institution":"Kyoto Prefectural University of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yuki","middleName":"","lastName":"Miyamoto","suffix":""},{"id":171588960,"identity":"510281dd-7918-4d9c-8894-16e6c3e6822e","order_by":24,"name":"Akihiro Yanagisawa","email":"","orcid":"","institution":"Gyoda General Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Akihiro","middleName":"","lastName":"Yanagisawa","suffix":""},{"id":171588962,"identity":"b05d7641-3b38-4f78-8234-52b28416ea7f","order_by":25,"name":"Tadamasa Wakabayashi","email":"","orcid":"","institution":"Suwa Central Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tadamasa","middleName":"","lastName":"Wakabayashi","suffix":""},{"id":171588964,"identity":"84936218-ee2c-4442-a148-40788ec0b507","order_by":26,"name":"Takeshi Ueda","email":"","orcid":"","institution":"Rakuwakai Marutamachi Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Takeshi","middleName":"","lastName":"Ueda","suffix":""},{"id":171588966,"identity":"08f6d929-2d30-4f73-96fb-b32b4ffe24b1","order_by":27,"name":"Tetsuya Komuro","email":"","orcid":"","institution":"TMG Muneoka Central Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tetsuya","middleName":"","lastName":"Komuro","suffix":""},{"id":171588968,"identity":"b3899dec-cb90-4d84-923d-386d69205fdd","order_by":28,"name":"Toshiro Sugimoto","email":"","orcid":"","institution":"Shiga University of Medical Science","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Toshiro","middleName":"","lastName":"Sugimoto","suffix":""},{"id":171588971,"identity":"203393f8-74c1-4f01-a1c0-5a29bb250d7c","order_by":29,"name":"Alan Kawarai Lefor","email":"","orcid":"","institution":"Jichi Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Alan","middleName":"Kawarai","lastName":"Lefor","suffix":""}],"badges":[],"createdAt":"2023-01-11 14:29:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2467653/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2467653/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":32292978,"identity":"e73a5f1b-2dfc-4f13-8c1e-8f0ba76490ea","added_by":"auto","created_at":"2023-01-31 20:44:46","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":45582,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage of admission wards by hospital. Each bar-chart represents a hospital. Intensive care unit (ICU), high care unit (HCU), or general ward (Ward) displayed in black, gray or white, respectively.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2467653/v1/baff75676a64ea4502d9dfdb.jpg"},{"id":32292977,"identity":"c4ca5556-e491-4716-a9e3-01bfc0a2e3f4","added_by":"auto","created_at":"2023-01-31 20:44:46","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":33577,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage of mortality and complications by group. Each bar-chart represents a group of diabetic ketoacidosis (DKA) or hyperglycemic hyperosmolar syndrome (HHS). Mortality and complications are combined and expressed with black and gray, respectively.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2467653/v1/1c2425be48736f73292cd437.jpg"},{"id":32293393,"identity":"c06bda81-425e-4071-8210-9ab5f3ccb9a5","added_by":"auto","created_at":"2023-01-31 20:52:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":480386,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2467653/v1/591c006c-cce2-4f2e-8391-b276cedaea71.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinical profile of patients with diabetic ketoacidosis and hyperglycemic hyperosmolar syndrome in Japan: A multicenter retrospective cohort study","fulltext":[{"header":"Background","content":"\u003cp\u003eHyperglycemic emergencies are serious acute complications of diabetes that include diabetic ketoacidosis (DKA) and hyperglycemic hyperosmolar syndrome (HHS)[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. DKA is characterized by hyperglycemia, metabolic acidosis, and ketonemia while HHS presents with severe hyperglycemia, high serum osmolality, and dehydration[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], which require close monitoring of electrolytes and vital signs. Clinical characteristics of patients with hyperglycemic emergencies have been investigated in several studies. Typically, DKA is common among young patients with type 1 diabetes while HHS often occurs in the elderly with type 2 diabetes. Common precipitating factors of hyperglycemic emergencies are infection, non-compliance, or acute conditions such as stroke, myocardial infarction, and trauma[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003csup\u003e,\u003c/sup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Additionally, many drugs such as corticosteroids and antipsychotic medications have been reported to impair glucose tolerance[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. These factors affect not only the pathophysiology of the hyperglycemic crisis but also the overall prognosis. Although these precipitating factors have been suggested, the actual prevalence of these factors in patients with hyperglycemic emergencies is unknown.\u003c/p\u003e \u003cp\u003eThe epidemiology and management of patients with acute hyperglycemic emergencies vary among countries. The reported mortality rate of patients with DKA in developed countries ranges from 0.16\u0026ndash;4.1% [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003csup\u003e,\u003c/sup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003csup\u003e,\u003c/sup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]whereas in developing countries it is higher[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003csup\u003e,\u003c/sup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. HHS-related mortality is reported to be 10 to 20%, approximately 10 times higher than that of DKA[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003csup\u003e,\u003c/sup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Trends in the rate of hospitalization and use of intensive care for patients with DKA and HHS vary by country and variation exists even among institutions in the same region[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003csup\u003e,\u003c/sup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Interestingly, these variations were reported not to affect the length of hospital stay or mortality of the patients[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Some feel that emergency departments or even general wards can provide an appropriate level of care with improved cost-effectiveness compared to admission to the intensive care unit (ICU) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Currently, there is no consensus regarding whether to use the ICU for the care of such patients, leaving optimal resource allocation in controversy[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe aim of this study is to provide a detailed clinical profile of patients with DKA and HHS and the use of the ICU for these patients in Japan. The patients\u0026rsquo; background, mortality, complications, precipitants, and use of hospital beds and other medical resources were investigated.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eA retrospective cohort study was conducted to investigate the clinical characteristics of patients with hyperglycemic emergencies. Participating facilities included 21 acute care hospitals in Japan. This is a part of the CLORINE study (The effeCt of fLuid therapy On kidney function in hypeRglycemIc emergeNciEs. A multicenter retrospective study), registered in the UMIN clinical trial registration system (UMIN000025393). The study design was approved by the ethics committee of each institution with a waiver of informed consent prior to collecting the data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003ePatients included in the study were adults aged 18 years or older admitted to the hospital due to DKA or HHS from January 1, 2012, to December 31, 2016. Individuals who received treatment in the emergency department were also included. Patients were initially identified according to ICD-10 coding. Subsequently, diagnoses were confirmed with laboratory data according to the criteria of the American Diabetes Association as follows:\u003c/p\u003e \u003cp\u003eDKA (meets all below):\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eSerum glucose\u0026thinsp;\u0026gt;\u0026thinsp;250 mg/dl\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003epH of arterial blood gas (ABG)\u0026thinsp;\u0026le;\u0026thinsp;7.30 or HCO\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;\u0026le;\u0026thinsp;18 mmol/L\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePositive urine or blood ketone\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eHHS (meets all below):\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eSerum glucose\u0026thinsp;\u0026gt;\u0026thinsp;600 mg/dl\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003epH of ABG\u0026thinsp;\u0026gt;\u0026thinsp;7.30 and HCO\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;\u0026gt;\u0026thinsp;18 mmol/L\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eNegative or low positive urine/blood ketone\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003ePatients with DKA were also classified into 3 groups- severe (ABG pH\u0026thinsp;\u0026lt;\u0026thinsp;7.0 or HCO3\u0026thinsp;\u0026lt;\u0026thinsp;10 mmol/L), mild (ABG pH\u0026thinsp;\u0026gt;\u0026thinsp;7.25 and HCO3\u0026thinsp;\u0026lt;\u0026thinsp;10 mmol/L), and moderate (neither mild nor severe) for analysis. Exclusion criteria were missing data necessary for diagnosis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eOutcomes and Data collection\u003c/h2\u003e \u003cp\u003eThe primary outcome was in-hospital mortality from any cause. Secondary outcomes were serious complications including cardiovascular events, infection, length of hospital stay and ICU stay, and use of intensive therapy (ventilator, vasopressors, and renal replacement therapy).\u003c/p\u003e \u003cp\u003eData were obtained through patient medical records in participating facilities. Data extraction for each patient included patient characteristics, type, duration, and treatment of diabetes, complications of diabetes, precipitating factors for hyperglycemic emergencies (including factors associated with patient behavior, acute medical events, and medications affecting diabetes), admission route and type of ward, complications during hospitalization, and requirement for intensive therapy. Medications affecting diabetes were defined as corticosteroids, atypical antipsychotics, thiazides, quinolones, and phenytoin. Complications were limited to newly diagnosed adverse events during hospitalization, excluding comorbidities that existed prior to admission. For patients who died, causes of death were also recorded.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were presented with a mean (\u0026plusmn;SD: standard deviation) and median (IQR: interquartile range) as appropriate. Categorical variables were expressed with percentages. Clinical features and outcomes were compared among the four groups (HHS and the 3 groups of DKA stratified by severity). The type of admission ward is aggregated by each institution. On the basis of the normality of the data, continuous variables were analyzed with the ANOVA or the Kruskal-Wallis test for four-group comparisons. For categorical data, the chi-square test was used. P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. All analyses were performed using R version 4.0.3 (R Foundation for Statistical Computing, Vienna, Austria).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eDuring the study period, 771 patients were admitted to participating hospitals with DKA (545 patients) and HHS (226 patients). The mean age of the patients was 58.3 years (SD 19.3) and the proportion of males was 54.7%. Among patients with DKA, 19% (n\u0026thinsp;=\u0026thinsp;104) were mild, 23.7% (n\u0026thinsp;=\u0026thinsp;129) were moderate, and 57.2% (n\u0026thinsp;=\u0026thinsp;312) were severe. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the baseline characteristics of the patients. Compared with the DKA groups, patients with HHS were older and had more comorbidities, including hypertension, ischemic heart disease, chronic heart failure, and stroke.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient baseline characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild DKA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModerate DKA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSevere DKA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHHS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;104)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;129)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;312)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;226)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.0 (18.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56.3 (18.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49.9 (17.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71.9 (14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale gender, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47 (45.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60 (46.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e141 (45.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e103 (45.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody-mass index, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.3 (6.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.1 (5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.9 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.6 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetic retinopathy, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (27.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (28.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40 (18.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37 (28.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetic nephropathy, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (41.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (26.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75 (32.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50 (35.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetic neuropathy, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (31.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (22.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68 (30.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26 (20.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (45.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43 (35.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73 (25.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e123 (57.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidemia, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26 (27.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (29.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62 (21.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56 (27.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIschemic heart disease, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33 (16.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic heart failure, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37 (18.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroke, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (11.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeripheral artery disease, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMental disorder, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51 (16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20 (8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of diabetes, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNew onset\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (28.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (26.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79 (25.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40 (17.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1 year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (8.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47 (15.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12 (5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u0026ndash;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (10.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38 (12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19 (8.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39 (37.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (30.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98 (31.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78 (34.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (14.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (17.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40 (12.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68 (30.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFulminant type 1 diabetes, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 (8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of diabetes, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37 (35.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (42.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e163 (52.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24 (10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62 (60.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71 (55.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e126 (40.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e184 (81.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment before admission, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsulin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (27.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (38.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120 (38.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31 (13.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOral medications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (17.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 (9.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79 (35.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsulin\u0026thinsp;+\u0026thinsp;Oral medications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (11.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (9.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47 (15.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28 (12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo medication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45 (43.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46 (35.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e110 (35.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83 (37.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdmission route, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmergency department\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77 (74.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101 (78.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e252 (80.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e179 (79.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneral outpatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (14.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29 (12.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransfer from other hospitals\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (11.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18 (8.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eDKA: Diabetic ketoacidosis, HHS: Hyperosmolar hyperglycemic syndrome, SD: Standard deviation\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eP values are results of the ANOVA or the Kruskal-Wallis test for four-group comparisons.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe duration of diabetes varied among the patients. While the proportion of new onset diabetes was 23.6%, 32.9% of the patients had been treated for more than 10 years. Type 2 diabetes was prevalent in the HHS group (81.8%) and type 1 diabetes was most frequent in the severe DKA group (52.5%). Regarding treatment before admission, the proportion of patients receiving insulin therapy is higher in DKA groups, while oral medication was common in the HHS group. A total of 284 (36.8%) patients had taken no medications to treat diabetes mellitus prior to hospital admission.\u003c/p\u003e \u003cp\u003eIn terms of factors precipitating a hyperglycemic emergency, poor adherence to treatment, infectious diseases, and excessive intake of sugar-sweetened beverages were major factors (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Poor adherence was most prevalent in the DKA groups (47.7%) and infectious diseases were the most frequent factor in the HHS group (42.7%). Some patients took medications that could increase the severity of diabetes. Corticosteroids were prescribed for 6.2% of patients with HHS, and the proportion was higher than in patients with DKA.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrecipitating factors identified in patients with DKA and HHS\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild DKA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModerate DKA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSevere DKA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHHS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;104)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;129)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;312)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;226)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrecipitating factors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor adherence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39 (39.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65 (51.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e156 (51.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71 (32.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExcessive sugar sweetened beverages\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (25.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (26.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69 (23.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47 (21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExcessive alcohol beverages\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (5.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (11.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32 (10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCessation of diabetes medication by treating physician\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11 (4.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfectious disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (36.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (31.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e108 (35.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e96 (42.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIschemic heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePancreatitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrauma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 (3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCorticosteroids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThiazides\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeta blockers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOlanzapine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuetiapine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClozapine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsenapine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuinolones\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhenytoin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eAll data are presented as number (%). DKA: Diabetic ketoacidosis, HHS: Hyperosmolar hyperglycemic syndrome\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eP values are results of the ANOVA or the Kruskal-Wallis test for four-group comparisons.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOutcomes during hospital admission are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The median hospital stay was 16 days [IQR 10\u0026ndash;26 days] and was longer in the HHS group (19.5 days) compared to the DKA groups (16 days). The ICU admission rate was 44.4% on average and highest in the severe DKA group (55.1%). ICU admission rate in each hospital ranged from 0\u0026ndash;100% (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The median ICU stay was 3 days, the same for all groups.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOutcomes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild DKA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModerate DKA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSevere DKA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHHS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;104)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;129)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;312)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;226)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIn-hospital mortality, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16 (7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfection, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (10.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57 (18.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52 (23.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute coronary syndrome, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulmonary edema, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVentricular arrhythmia(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroke, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeep vein thrombosis, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital stay, days, median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, 22.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.5 [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICU admission, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (26.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53 (41.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e172 (55.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e89 (39.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICU stay, days, median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCU admission, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 (29.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (30.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e106 (34.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51 (22.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCU stay, days, median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOFA score on admission, median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 [0, 2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5 [0, 3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 [0, 4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.5 [0, 5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrgan support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanical ventilation, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34 (10.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVasopressor use, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42 (13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20 (8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal replacement therapy, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal replacement therapy on discharge, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eDKA: Diabetic ketoacidosis, HHS: Hyperosmolar hyperglycemic syndrome, GCS: Glasgow coma scale, SBP: Systolic blood pressure, SOFA: sequential organ failure assessment, ICU: Intensive care unit, HCU: High care unit, IQR: Interquartile range\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eP values are results of the ANOVA or the Kruskal-Wallis test for four-group comparisons.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWith regard to intensive therapy, 52 (6.7%) patients were mechanically ventilated, 68 (8.8%) were treated with vasopressors, and 24 (3.1%) required renal replacement therapy. Six (0.7%) patients needed maintenance dialysis on discharge. Overall, patients in the severe DKA group required organ support more frequently compared to the other groups.\u003c/p\u003e \u003cp\u003eIn the entire cohort, 31 (4%) patients died during admission. The in-hospital mortality rate was 2.8% in patients with DKA and 7.1% in the HHS group, respectively. No significant difference was seen among the DKA groups. The most common complication was infection (18%), followed by pulmonary edema (2.7%), stroke (2.1%), ventricular arrhythmia (1.6%), and deep vein thrombosis (1%). Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows in-hospital events (mortality\u0026thinsp;+\u0026thinsp;complications) according to group. The rate of events was higher in the HHS group than in other groups and was similar among the 3 DKA groups (not proportional to severity).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe causes of mortality are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Twenty (65%) of 31 deaths were due to infection. Other causes included stroke, pulmonary edema, acute coronary syndrome, and ventricular arrhythmia.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCauses of mortality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild DKA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModerate DKA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSevere DKA*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHHS*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13 (81.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute coronary syndrome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulmonary edema\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVentricular arrhythmia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulmonary embolism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eAll data are presented as number numbers (%). *Some patients with severe DKA and HHS had multiple causes.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eDKA: Diabetic ketoacidosis, HHS: Hyperosmolar hyperglycemic syndrome\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eP values are results of the ANOVA or the Kruskal-Wallis test for four-group comparisons.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study describes the clinical characteristics of patients with hyperglycemic crises using data obtained from multiple institutions in Japan. The mortality rate of patients with DKA and HHS was 2.8% and 7.1%, respectively. No linear relationship was found between the severity of DKA and mortality. Major precipitating factors of acute episodes were poor adherence to treatment regimens, infections, and intake of excessive sugar-sweetened beverages. The rate of ICU admission varied among institutions.\u003c/p\u003e \u003cp\u003eThe mortality rate of patients with DKA and HHS varies among countries and has changed over time. In recent publications, the mortality rate of patients with DKA has been reported from 0.16\u0026ndash;4.1%[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003csup\u003e,\u003c/sup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003csup\u003e,\u003c/sup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] whereas that of HHS was between 10 to 20%[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003csup\u003e,\u003c/sup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The results of the present study are similar to previous reports for DKA but the mortality rate of patients with HHS in the present study was lower. The reason for this difference is unclear but could be explained by global trends in improving diabetes care. A report based on a US national survey showed that the mortality rate of patients with DKA was decreasing while hospitalization was increasing[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This improvement might be attributed to increased awareness of the disease and adaption of established guidelines for the treatment of patients with DKA.\u003c/p\u003e \u003cp\u003eIt is unclear if severity of DKA correlates with mortality or not. While some studies indicated an association between them[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003csup\u003e,\u003c/sup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], other studies found that other factors were more important than DKA severity. For example, a previous study of a prediction model for the prognosis of patients with DKA concluded that coexisting severe diseases are the most significant predictor for mortality[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Another study suggested that advanced age and altered levels of consciousness were important predictors of mortality as well as electrolyte disturbances[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In the present study, the severe DKA group was younger and the prevalence of comorbidities such as stroke was lower compared with the other DKA groups. Considering the findings of the present study and previous reports, the severity of DKA may be less important than other factors such as patient age or comorbidities.\u003c/p\u003e \u003cp\u003eTreatment in the ICU has been considered appropriate for patients with hyperglycemic crises for decades as indicated in the guidelines[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003csup\u003e,\u003c/sup\u003e [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The essentials of treatment for hyperglycemic crises are fluid resuscitation, electrolyte replacement, and insulin infusion, which require close monitoring of vital signs, electrolytes, and blood glucose levels. However, recent studies have shown that DKA can be safely managed in the emergency department[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] or even in general wards[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. We found that differences in ICU utilization for these patients by institution was quite varied, ranging from 0\u0026ndash;100%. Such a discrepancy may reflect variations in practice and setting of each hospital. A study including 159 hospitals in the United States also reported ICU admission rates from 2.1 to 87.7% but no association was found between the rates of ICU utilization and mortality or length of hospital stay[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Another large retrospective study involving 15,022 patients with DKA showed that institutions that utilized ICUs more frequently had higher costs but had no improvement in hospital mortality[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. As far as proper triage and management are provided, where care is provided for these patients could be less important. Nevertheless, it should be emphasized that patients who need organ support or have severe comorbidities are suitable for management in the ICU[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. As the present study suggests, a considerable number of patients required mechanical ventilation, vasopressor use, and renal replacement therapy. Patient profile and conditions also affect prognosis, which should be considered. Past reports suggested that older age, sepsis, coma and lower levels of activity of daily living, and severe comorbidities were risk factors for mortality[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003csup\u003e,\u003c/sup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Accordingly, the use of organ support as well as patient background should be taken into account for the selection of providing care in the ICU.\u003c/p\u003e \u003cp\u003eIn the present study, more than 20% of the patients reported excessive consumption of sugar-sweetened beverages prior to hyperglycemic emergencies. Both patients\u0026rsquo; behavior and medical illnesses are important triggers for hyperglycemic emergencies[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003csup\u003e,\u003c/sup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Previous reports identified poor adherence and infection as common precipitants[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003csup\u003e,\u003c/sup\u003e [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003csup\u003e,\u003c/sup\u003e [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Recent studies demonstrated that increased consumption of sweet soft drinks worsens insulin resistance and impairs pancreatic beta-cell function[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003csup\u003e,\u003c/sup\u003e [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], which is related to the pathophysiology of decompensated hyperglycemia. Although the exact prevalence was not documented in previous studies, the results of the present study suggest that excessive consumption of sugar-sweetened beverages may be a significant trigger for developing DKA and HHS.\u003c/p\u003e \u003cp\u003eThe present study shows the proportion of patients who were taking medications that could worsen diabetes. Several types of medication, e.g., corticosteroids[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], beta blockers[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], anti-psychotics[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], thiazides[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], quinolones[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] and phenytoin[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], have been reported to be associated with deterioration of diabetes control. Although the overall prevalence of drug-induced diabetes is unknown, approximately 15 to 50% of patients taking corticosteroids and 10% of people taking anti-psychotic medications develop diabetes[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003csup\u003e,\u003c/sup\u003e [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Some studies have also described patients with drug-induced DKA and HHS[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003csup\u003e,\u003c/sup\u003e [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. We reviewed prescriptions for the patients with diabetes requiring emergency admission and found that a few patients were taking such medications. Although corticosteroids were prescribed in 6% of patients with HHS, only a small number of patients were taking other medications which could affect diabetes. Given that other precipitating factors are more frequent, the impact of these drugs may be less important in the context of the overall acute critical episodes.\u003c/p\u003e \u003cp\u003eTo the best of our knowledge, this is one of the largest and most detailed epidemiological studies of hyperglycemic crises in the medical literature. The strengths of this study are the large sample size and comprehensive description of patient characteristics including precipitating factors, medical resources used, and complications during hospitalization. However, the present study has also acknowledged limitations. First, multivariable regression analysis could not be conducted due to the low incidence of mortality. As a result, predictors of mortality or association between ICU admission and outcomes were not investigated. Considering the low mortality rate, studies with a much larger population such as a nationwide database will be needed to conduct multivariable regression analysis. Second, since the inclusion criteria included hyperglycemia, the present study did not enroll patients with euglycemic DKA which is currently an emerging problem[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. However, this may be a minor issue because most of the study period was before the widespread use of sodium-glucose cotransporter 2 inhibitors in Japan.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe present study describes the clinical profile of patients with DKA and HHS in acute care hospitals in Japan. The mortality rate of patients with DKA was similar while that of HHS was lower compared to previous studies. No significant association was seen between the severity of DKA and mortality, which suggests that other factors are more important for prognosis. We found excessive consumption of sugar-sweetened beverages as a new precipitating factor of hyperglycemic crises. This risky behavior should be noted in future educational guides for the dietary habits of patients with diabetes. The indications for ICU admission should be based on not only the severity of disease but also on patient background and the need for organ support. Further studies are needed regarding the epidemiology of acute diabetic emergencies as it changes over time.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eABG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAtrial blood gas\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDKA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDiabetic ketoacidosis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHHS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHyperglycemic hyperosmolar syndrome\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIntensive Care Unit\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study design was approved by the ethics committee of Jichi Medical University (ID: RINS17-023. Registered 4\u003csup\u003eth\u003c/sup\u003e September 2017) and each institution with a waiver of informed consent prior to collecting the data. The study was performed in accordance with the Declaration of Helsinki.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKT collected and analyzed the data and wrote the manuscript.\u003c/p\u003e\n\u003cp\u003eNU designed the study and collected and analyzed the data.\u003c/p\u003e\n\u003cp\u003eMS designed and directed the project.\u003c/p\u003e\n\u003cp\u003eSU analyzed the data and supervised the manuscript.\u003c/p\u003e\n\u003cp\u003eNY, TT, NN, HK, SO, KY, HY, SK, HT, NF, TK, TI, TK, KE, TM, TO, MH, AH, TM, YM, AY, TW, TU, TK, and TS\u0026nbsp;collected and analyzed the data.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAL supervised the manuscript and provided a reliable edit to correct English language errors.\u003c/p\u003e\n\u003cp\u003eAll authors checked and approved the final version of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKitabchi AE, Umpierrez GE, Murphy MB, Kreisberg RA. Hyperglycemic crises in adult patients with diabetes: A consensus statement from the American Diabetes Association. Diabetes Care. 2006;29:2739\u0026ndash;48. \u003c/li\u003e\n\u003cli\u003eFrench EK, Donihi AC, Korytkowski MT. Diabetic ketoacidosis and hyperosmolar hyperglycemic syndrome: Review of acute decompensated diabetes in adult patients. BMJ. 2019;365. \u003c/li\u003e\n\u003cli\u003ePasquel FJ, Umpierrez GE. Hyperosmolar hyperglycemic state: A historic review of the clinical presentation, diagnosis, and treatment. Diabetes Care. 2014;37:3124\u0026ndash;31. \u003c/li\u003e\n\u003cli\u003eDhatariya KK, Nunney I, Higgins K, Sampson MJ, Iceton G. National survey of the management of Diabetic Ketoacidosis (DKA) in the UK in 2014. Diabet Med. 2016;33:252\u0026ndash;60. \u003c/li\u003e\n\u003cli\u003eFathallah N, Slim R, Larif S, Hmouda H, Ben Salem C. Drug-Induced Hyperglycaemia and Diabetes. Drug Saf. Springer International Publishing; 2015;38:1153\u0026ndash;68. \u003c/li\u003e\n\u003cli\u003eGibb FW, Teoh WL, Graham J, Lockman KA. Risk of death following admission to a UK hospital with diabetic ketoacidosis. Diabetologia [Internet]. Diabetologia; 2016;59:2082\u0026ndash;7. Available from: http://dx.doi.org/10.1007/s00125-016-4034-0\u003c/li\u003e\n\u003cli\u003eBenoit SR, Zhang Y, Geiss LS, Gregg EW, Albright A. Trends in Diabetic Ketoacidosis Hospitalizations and In-Hospital Mortality \u0026mdash; United States, 2000\u0026ndash;2014. MMWR Morb Mortal Wkly Rep [Internet]. 2018;67:362\u0026ndash;5. Available from: http://www.cdc.gov/mmwr/volumes/67/wr/mm6712a3.htm?s_cid=mm6712a3_w\u003c/li\u003e\n\u003cli\u003eBarski L, Nevzorov R, Rabaev E, Jotkowitz A, Harman-Boehm I, Zektser M, et al. Diabetic ketoacidosis: Clinical characteristics, precipitating factors and outcomes of care. Isr Med Assoc J. 2012;14:298\u0026ndash;302. \u003c/li\u003e\n\u003cli\u003eMekonnen GA, Gelaye KA, Gebreyohannes EA, Abegaz TM. Treatment outcomes of diabetic ketoacidosis among diabetes patients in Ethiopia. Hospital-based study. PLoS One. 2022;17:1\u0026ndash;15. \u003c/li\u003e\n\u003cli\u003eSiregar NN, Soewondo P, Subekti I, Muhadi M. Seventy-two hour mortality prediction model in patients with diabetic ketoacidosis: A retrospective cohort study. J ASEAN Fed Endocr Soc. 2018;33:124\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eFadini GP, de Kreutzenberg SV, Rigato M, Brocco S, Marchesan M, Tiengo A, et al. Characteristics and outcomes of the hyperglycemic hyperosmolar non-ketotic syndrome in a cohort of 51 consecutive cases at a single center. Diabetes Res Clin Pract. 2011;94:172\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eVenkatesh B, Pilcher D, Prins J, Bellomo R, Morgan TJ, Bailey M. Incidence and outcome of adults with diabetic ketoacidosis admitted to ICUs in Australia and New Zealand. Crit Care [Internet]. Critical Care; 2015;19:1\u0026ndash;12. Available from: http://dx.doi.org/10.1186/s13054-015-1171-7\u003c/li\u003e\n\u003cli\u003eGershengorn HB, Iwashyna TJ, Cooke CR, Scales DC, Kahn JM, Wunsch H. Variation in use of intensive care for adults with diabetic ketoacidosis. Crit Care Med. 2012;40:2009\u0026ndash;15. \u003c/li\u003e\n\u003cli\u003eZhou VL, Shofer FS, Desai NG, Lorincz IS, Mull NK, Adler DH, et al. Predictors of Short Intensive Care Unit Stay for Patients with Diabetic Ketoacidosis Using a Novel Emergency Department\u0026ndash;Based Resuscitation and Critical Care Unit. J Emerg Med [Internet]. Elsevier Inc; 2019;56:127\u0026ndash;34. Available from: https://doi.org/10.1016/j.jemermed.2018.09.048\u003c/li\u003e\n\u003cli\u003eMendez Y, Surani S, Varon J. Diabetic ketoacidosis: Treatment in the intensive care unit or general medical/surgical ward? World J Diabetes. 2017;8:40. \u003c/li\u003e\n\u003cli\u003eJohn Titus George, Ajay Kumar Mishra RI. Correlation between the outcomes and severity of diabetic ketoacidosis: A retrospective pilot study. J Fam Med Prim Care [Internet]. 2018;7:787\u0026ndash;90. Available from: http://www.jfmpc.com/article.asp?issn=2249-4863;year=2017;volume=6;issue=1;spage=169;epage=170;aulast=Faizi\u003c/li\u003e\n\u003cli\u003eEfstathiou SP, Tsiakou AG, Tsioulos DI, Zacharos ID, Mitromaras AG, Mastorantonakis SE, et al. A mortality prediction model in diabetic ketoacidosis. Clin Endocrinol (Oxf). 2002;57:595\u0026ndash;601. \u003c/li\u003e\n\u003cli\u003eNovida H, Setiyawan F, Soelistijo SA. A Prediction Model of Mortality in Patients Hospitalized with Diabetic Ketoacidosis in a Tertiary Referral Hospital in Surabaya, Indonesia. Indian J Forensic Med Toxicol. 2021;15:2519\u0026ndash;26. \u003c/li\u003e\n\u003cli\u003eKitabchi AE, Umpierrez GE, Murphy MB, Barrett EJ, Kreisberg RA, Malone JI WB. Management of Hyperglycemic Crises. Diabetes Care. 2001;24:131\u0026ndash;53. \u003c/li\u003e\n\u003cli\u003eKitabchi AE, Umpierrez GE, Miles JM, Fisher JN. Hyperglycemic crises in adult patients with diabetes. Diabetes Care. 2009;32:1335\u0026ndash;43. \u003c/li\u003e\n\u003cli\u003eHaas NL, Whitmore SP, Cranford JA, Tsuchida RE, Nicholson A, Boyd C, et al. An Emergency Department\u0026ndash;Based Intensive Care Unit is Associated with Decreased Hospital and Intensive Care Unit Utilization for Diabetic Ketoacidosis. J Emerg Med [Internet]. Elsevier Inc; 2020;58:620\u0026ndash;6. Available from: https://doi.org/10.1016/j.jemermed.2019.10.005\u003c/li\u003e\n\u003cli\u003eBraatvedt G, Kwan A, Dransfield W, McNamara C, Schauer C, Miller S, et al. Differing protocols of managing adult diabetic ketoacidosis outside of the intensive care unit make no difference to the rate of resolution of hyperglycaemia and acidosis. N Z Med J. 2019;132:13\u0026ndash;23. \u003c/li\u003e\n\u003cli\u003eChang DW, Shapiro MF. Association between intensive care unit utilization during hospitalization and costs, use of invasive procedures, and mortality. JAMA Intern Med. 2016;176:1492\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eSato Y, Morita K, Okada A, Matsui H, Fushimi K, Yasunaga H. Factors affecting in-hospital mortality of diabetic ketoacidosis patients: A retrospective cohort study. Diabetes Res Clin Pract [Internet]. Elsevier B.V.; 2021;171:108588. Available from: https://doi.org/10.1016/j.diabres.2020.108588\u003c/li\u003e\n\u003cli\u003eYamada K, Nonaka K. Diabetic ketoacidosis in young obese Japanese men. Diabetes Care. 1996;19:671. \u003c/li\u003e\n\u003cli\u003eTanaka K, Moriya T, Kanamori A, Yajima Y. Analysis and a long-term follow up of ketosis-onset Japanese NIDDM patients. Diabetes Res Clin Pract. 1999;44:137\u0026ndash;46. \u003c/li\u003e\n\u003cli\u003eWachtel TJ, Tetu-Mouradjian LM, Goldman DL, Ellis SE, O\u0026rsquo;Sullivan PS. Hyperosmolarity and acidosis in diabetes mellitus - A three-year experience in Rhode Island. J Gen Intern Med. 1991;6:495\u0026ndash;502. \u003c/li\u003e\n\u003cli\u003eRandall L, Begovic J, Hudson M, Smiley D, Peng L, Pitre N, et al. Recurrent diabetic ketoacidosis in inner-city minority patients: Behavioral, socioeconomic, and psychosocial factors. Diabetes Care. 2011;34:1891\u0026ndash;6. \u003c/li\u003e\n\u003cli\u003eYoshida M, McKeown NM, Rogers G, Meigs JB, Saltzman E, D\u0026rsquo;Agostino R, et al. Surrogate markers of insulin resistance are associated with consumption of sugar-sweetened drinks and fruit juice in middle and older-aged adults. J Nutr. 2007;137:2121\u0026ndash;7. \u003c/li\u003e\n\u003cli\u003eden Biggelaar LJCJ, Sep SJS, Mari A, Ferrannini E, van Dongen MCJM, Wijckmans NEG, et al. Association of artificially sweetened and sugar-sweetened soft drinks with \u0026beta;-cell function, insulin sensitivity, and type 2 diabetes: the Maastricht Study. Eur J Nutr [Internet]. Springer Berlin Heidelberg; 2020;59:1717\u0026ndash;27. Available from: https://doi.org/10.1007/s00394-019-02026-0\u003c/li\u003e\n\u003cli\u003eJessica L. Hwang Roy E. Weiss. Steroid-induced diabetes: a clinical and molecular approach to understanding and treatment. Diabetes Metab Res Rev [Internet]. 2014;30:96\u0026ndash;102. Available from: http://libweb.anglia.ac.uk/\u003c/li\u003e\n\u003cli\u003eSarafidis PA, Bakris GL. Antihypertensive treatment with beta-blockers and the spectrum of glycaemic control. Qjm. 2006;99:431\u0026ndash;6. \u003c/li\u003e\n\u003cli\u003eLean MEJ, Pajonk F-G. Patients on Atypical Antipsychotic Drugs. Diabetes Care. 2003;26:1597\u0026ndash;605. \u003c/li\u003e\n\u003cli\u003eShafi T, Appel LJ, Miller ER, Klag MJ, Parekh RS. Changes in serum potassium mediate thiazide-induced diabetes. Hypertension. 2008;52:1022\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eChou HW, Wang JL, Chang CH, Lee JJ, Shau WY, Lai MS. Risk of severe dysglycemia among diabetic patients receiving levofloxacin, ciprofloxacin, or moxifloxacin in Taiwan. Clin Infect Dis. 2013;57:971\u0026ndash;80. \u003c/li\u003e\n\u003cli\u003eBonaventura A, Montecucco F. Steroid-induced hyperglycemia: An underdiagnosed problem or clinical inertia? A narrative review. Diabetes Res Clin Pract [Internet]. Elsevier B.V.; 2018;139:203\u0026ndash;20. Available from: https://doi.org/10.1016/j.diabres.2018.03.006\u003c/li\u003e\n\u003cli\u003eManu P, Correll CU, Van Winkel R, Wampers M, De Hert M. Prediabetes in patients treated with antipsychotic drugs. J Clin Psychiatry. 2012;73:460\u0026ndash;6. \u003c/li\u003e\n\u003cli\u003eVuk A, Kuzman MR, Baretic M, Osvatic MM. Diabetic ketoacidosis associated with antipsychotic drugs: Case reports and a review of literature. Psychiatr Danub. 2017;29:121\u0026ndash;35. \u003c/li\u003e\n\u003cli\u003eChinthapalli K, Newey A, Krause M. Corticosteroid induced hyperosmolar hyperglycaemic state and hemiballismus. Oxford Med Case Reports. 2015;2015:320\u0026ndash;2. \u003c/li\u003e\n\u003cli\u003ePeters AL, Buschur EO, Buse JB, Cohan P, Diner JC, Hirsch IB. Euglycemic diabetic ketoacidosis: A potential complication of treatment with sodium-glucose cotransporter 2 inhibition. Diabetes Care. 2015;38:1687\u0026ndash;93. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"diabetes, hyperglycemic emergencies, hyperglycemic crisis, intensive care, epidemiology, prognosis","lastPublishedDoi":"10.21203/rs.3.rs-2467653/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2467653/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eDiabetic ketoacidosis (DKA) and hyperglycemic hyperosmolar syndrome (HHS) are life-threatening complications of diabetes mellitus. Their\u003cstrong\u003e \u003c/strong\u003eclinical profiles have not been fully investigated in the Japanese population.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA multicenter retrospective cohort study was conducted in 21 acute care hospitals in Japan. Patients included were adults aged 18 or older who had been hospitalized from January 1, 2012, to December 31, 2016 due to DKA or HHS. The clinical characteristics and outcomes were extracted from patient medical records. A four-group comparison (mild DKA, moderate DKA, severe DKA, and HHS) was performed to evaluate outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eA total of 771 patients including 545 patients with DKA and 226 patients with HHS were identified during the study period. The major precipitating factors of disease episodes were poor medication compliance, infectious diseases, and excessive drinking of sugar-sweetened beverages. The median hospital stay was 16 days [IQR 10-26 days] and was longer in the HHS group (19.5 days) compared to the DKA groups (16 days). The intensive care unit (ICU) admission rate was 44.4% (mean) and the rate at each hospital ranged from 0% to 100%. The median ICU stay was 3 days for all groups. The in-hospital mortality rate was 2.8% in patients with DKA and 7.1% in the HHS group. No significant difference in mortality was seen among the three DKA groups. The most common complication was infection (18%), followed by pulmonary edema (2.7%), stroke (2.1%), ventricular arrhythmia (1.6%), and deep vein thrombosis (1%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eThe mortality rate of patients with DKA in Japan is similar to other studies, while that of HHS was lower. The ICU admission rate varied among institutions. There was no significant association between the severity of DKA and mortality in the study population.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial registration: \u003c/strong\u003eThis study is registered in the UMIN clinical trial registration system (UMIN000025393, Registered 23th December 2016)\u003c/p\u003e","manuscriptTitle":"Clinical profile of patients with diabetic ketoacidosis and hyperglycemic hyperosmolar syndrome in Japan: A multicenter retrospective cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-01-31 20:44:41","doi":"10.21203/rs.3.rs-2467653/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"28b9e567-39f9-43c8-b1b2-0ed782cb430c","owner":[],"postedDate":"January 31st, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-01-31T20:52:44+00:00","versionOfRecord":[],"versionCreatedAt":"2023-01-31 20:44:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2467653","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2467653","identity":"rs-2467653","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}