Risk Factors For Diabetic Ketoacidosis Research Articles

Diabetic Ketoacidosis and Adverse Outcomes Among Pregnant Individuals With Pregestational Diabetes in the United States, 2010-2020.

To assess the frequency of, risk factors for, and adverse outcomes associated with diabetic ketoacidosis (DKA) at delivery hospitalization among individuals with pregestational diabetes (type 1 and 2 diabetes mellitus) and secondarily to evaluate the frequency of and risk factors for antepartum and postpartum hospitalizations for DKA. We conducted a serial, cross-sectional study using the Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project Nationwide Readmissions Database from 2010 to 2020 of pregnant individuals with pregestational diabetes hospitalized for delivery. The exposures were 1) sociodemographic and clinical risk factors for DKA and 2) DKA. The outcomes were DKA at delivery hospitalization, maternal morbidity (nontransfusion severe maternal morbidity (SMM), critical care procedures, cardiac complications, acute renal failure, and transfusion), and adverse pregnancy outcomes (preterm birth, hypertensive disorders of pregnancy, and cesarean delivery) and secondarily DKA at antepartum and postpartum hospitalizations. Of 392,796 deliveries in individuals with pregestational diabetes (27.2% type 1 diabetes, 72.8% type 2 diabetes), there were 4,778 cases of DKA at delivery hospitalization (89.1% type 1 diabetes, 10.9% type 2 diabetes). The frequency of DKA at delivery hospitalization was 1.2% (4.0% with type 1 diabetes, 0.2% with type 2 diabetes), and the mean annual percentage change was 10.8% (95% CI, 8.2-13.2%). Diabetic ketoacidosis at delivery hospitalization was significantly more likely among those who had type 1 diabetes compared with those with type 2 diabetes, who were younger in age, who delivered at larger and metropolitan hospitals, and who had Medicaid insurance, lower income, multiple gestations, and prior psychiatric illness. Diabetic ketoacidosis during the delivery hospitalization was associated with an increased risk of nontransfusion SMM (20.8% vs 2.4%, adjusted odds ratio [aOR] 8.18, 95% CI, 7.20-9.29), critical care procedures (7.3% vs 0.4%, aOR 15.83, 95% CI, 12.59-19.90), cardiac complications (7.8% vs 0.8%, aOR 8.87, 95% CI, 7.32-10.76), acute renal failure (12.3% vs 0.7%, aOR 9.78, 95% CI, 8.16-11.72), and transfusion (6.2% vs 2.2%, aOR 2.27, 95% CI, 1.87-2.75), as well as preterm birth (31.9% vs 13.5%, aOR 2.41, 95% CI, 2.17-2.69) and hypertensive disorders of pregnancy (37.4% vs 28.1%, aOR 1.11, 95% CI, 1.00-1.23). In secondary analyses, the overall frequency of antepartum DKA was 3.1%, and the mean annual percentage change was 4.1% (95% CI, 0.3-8.6%); the overall frequency of postpartum DKA was 0.4%, and the mean annual percentage change was 3.5% (95% CI, -1.6% to 9.6%). Of 3,092 antepartum hospitalizations among individuals with DKA, 15.7% (n=485) had a recurrent case of DKA at delivery hospitalization. Of 1,419 postpartum hospitalizations among individuals with DKA, 20.0% (n=285) previously had DKA at delivery hospitalization. The above risk factors for DKA at delivery hospitalization were similar for DKA at antepartum and postpartum hospitalizations. The frequency of DKA at delivery hospitalization and antepartum hospitalizations for DKA increased between 2010 and 2020 among deliveries in individuals with pregestational diabetes in the United States. Diabetic ketoacidosis is associated with an increased risk of maternal morbidity and adverse pregnancy outcomes. Risk factors for DKA at delivery were similar to those for DKA during the antepartum and postpartum periods.

Risk factors for ketoacidosis in children/adolescents with type 1 diabetes mellitus and establishment of a predictive model

To investigate the risk factors for diabetic ketoacidosis (DKA) in children/adolescents with type 1 diabetes mellitus (T1DM) and to establish a model for predicting the risk of DKA. A retrospective analysis was performed on 217 children/adolescents with T1DM who were admitted to General Hospital of Ningxia Medical University from January 2018 to December 2021. Among the 217 children/adolescents,169 cases with DKA were included as the DKA group and 48 cases without DKA were included as the non-DKA group. The risk factors for DKA in the children/adolescents with T1DM were analyzed, and a nomogram model was established for predicting the risk of DKA in children/adolescents with T1DM. For the 217 children/adolescents with T1DM, the incidence rate of DKA was 77.9% (169/217). The multivariate logistic regression analysis showed that high levels of random blood glucose, hemoglobin A1c (HbA1c), blood ketone body, and triglyceride on admission were closely associated with the development of DKA in the children/adolescents with T1DM (OR=1.156, 3.2031015, 20.131, and 9.519 respectively; P<0.05). The nomogram prediction model had a C-statistic of 0.95, with a mean absolute error of 0.004 between the risk of DKA predicted by the nomogram model and the actual risk of DKA, indicating that the model had a good overall prediction ability. High levels of random blood glucose, HbA1c, blood ketone body, and triglyceride on admission are closely associated with the development of DKA in children/adolescents with T1DM, and targeted intervention measures should be developed to reduce the risk of DKA.

FREQUENCY OF RISK FACTORS ASSOCIATED WITH DIABETIC KETOACIDOSIS IN PATIENTS PRESENTING AT KHYBER TEACHING HOSPITAL PESHAWAR

Objectives: To determine the frequency of risk factors associated with diabetic ketoacidosis in patients presenting at Khyber Teaching Hospital Peshawar. Materials and methods: Patients of either gender, aged between 18 and 60 years, with either type I or type II diabetes mellitus presenting with diabetic ketoacidosis with the duration of diabetes &gt; 1 year were included in the study. DKA was diagnosed based on the clinical presentation of respective patients, serum Random Blood Sugar (RBS), and urinary ketones. Careful scrutinization was done for the detection of common risk factors for DKA like infections, stroke, myocardial infarction, and pancreatitis. Based on the clinical examination for Stroke and acute pancreatitis, CT imaging of the brain and CT of the abdomen with pancreatic protocol were performed. Results: Among 111 DKA patients, the mean age was 43 years with standard deviation ± 12.05. 63(57%) patients were male while 48(43%) were female. Infection was found in 54(49%) patients, stroke in 4(4%) myocardial infarctions in 3(3%), and pancreatitis was found in 7(6%) patients. Conclusion: The most common risk factor for diabetic ketoacidosis is infections in half of the participants while stroke was 4%, myocardial infarction was 3% and pancreatitis was 6%. KEYWORDS: diabetic ketoacidosis; type I diabetes; type II diabetes

Risk factors for diabetic ketoacidosis in acute pancreatitis patients with type 2 diabetes

Background and purposeIn cinical, some acute pancreatitis patients with diabetes may have diabetic ketoacidosis (DKA). However, the risk factors for DKA in these patients remain unclear. The purpose of this study is to analyze the risk factors for DKA in acute pancreatitis patients with type 2 diabetes.Patients and methodsTwenty-five patients were included in this prospective single-centre study to analyze the incidence and risk factors for DKA in acute pancreatitis patients with type 2 diabetes.ResultsSeven of the twenty-five patients (28%) developed DKA within 48 h of admission. According to whether they had DKA, the twenty-five AP patients were divided into DKA group and non-DKA group. There were significant differences in age (P = 0.014), BMI (P = 0.034), poor previous blood glucose control (P < 0.001) and uric acid concentration (P = 0.041), but no statistically significant differences in sex (P = 0.597), number of drinkers (P = 0.407), number of smokers (P = 1.000), triglyceride level (P = 0.389) and total cholesterol concentration (P = 0.534) between the two groups. In both groups, 1 patients had severe pancreatitis, and the difference was no statistically significant (P = 0.490).ConclusionsThe incidence of DKA in AP patients with diabetes is high. Age, BMI, worse glycemic control and uric acid concentration may be predictors of DKA in AP patients with diabetes.

An "All-Data-on-Hand" Deep Learning Model to Predict Hospitalization for Diabetic Ketoacidosis in Youth With Type 1 Diabetes: Development and Validation Study.

Although prior research has identified multiple risk factors for diabetic ketoacidosis (DKA), clinicians continue to lack clinic-ready models to predict dangerous and costly episodes of DKA. We asked whether we could apply deep learning, specifically the use of a long short-term memory (LSTM) model, to accurately predict the 180-day risk of DKA-related hospitalization for youth with type 1 diabetes (T1D). We aimed to describe the development of an LSTM model to predict the 180-day risk of DKA-related hospitalization for youth with T1D. We used 17 consecutive calendar quarters of clinical data (January 10, 2016, to March 18, 2020) for 1745 youths aged 8 to 18 years with T1D from a pediatric diabetes clinic network in the Midwestern United States. The input data included demographics, discrete clinical observations (laboratory results, vital signs, anthropometric measures, diagnosis, and procedure codes), medications, visit counts by type of encounter, number of historic DKA episodes, number of days since last DKA admission, patient-reported outcomes (answers to clinic intake questions), and data features derived from diabetes- and nondiabetes-related clinical notes via natural language processing. We trained the model using input data from quarters 1 to 7 (n=1377), validated it using input from quarters 3 to 9 in a partial out-of-sample (OOS-P; n=1505) cohort, and further validated it in a full out-of-sample (OOS-F; n=354) cohort with input from quarters 10 to 15. DKA admissions occurred at a rate of 5% per 180-days in both out-of-sample cohorts. In the OOS-P and OOS-F cohorts, the median age was 13.7 (IQR 11.3-15.8) years and 13.1 (IQR 10.7-15.5) years; median glycated hemoglobin levels at enrollment were 8.6% (IQR 7.6%-9.8%) and 8.1% (IQR 6.9%-9.5%); recall was 33% (26/80) and 50% (9/18) for the top-ranked 5% of youth with T1D; and 14.15% (213/1505) and 12.7% (45/354) had prior DKA admissions (after the T1D diagnosis), respectively. For lists rank ordered by the probability of hospitalization, precision increased from 33% to 56% to 100% for positions 1 to 80, 1 to 25, and 1 to 10 in the OOS-P cohort and from 50% to 60% to 80% for positions 1 to 18, 1 to 10, and 1 to 5 in the OOS-F cohort, respectively. The proposed LSTM model for predicting 180-day DKA-related hospitalization was valid in this sample. Future research should evaluate model validity in multiple populations and settings to account for health inequities that may be present in different segments of the population (eg, racially or socioeconomically diverse cohorts). Rank ordering youth by probability of DKA-related hospitalization will allow clinics to identify the most at-risk youth. The clinical implication of this is that clinics may then create and evaluate novel preventive interventions based on available resources.

Overlapping risk factors for diabetic ketoacidosis in patients with type 1 diabetes on ipragliflozin: case analysis of spontaneous reports in Japan from a pharmacovigilance safety database

ABSTRACT Background In patients with type 1 diabetes mellitus (T1D), sodium-glucose cotransporter 2 (SGLT2) inhibitors are associated with an increased risk of diabetic ketoacidosis (DKA). Ipragliflozin is an SGLT2 inhibitor approved in Japan in combination with insulin for patients with T1D. Research design and methods Spontaneous safety reports of ipragliflozin adverse drug reactions (ADRs) in patients with T1D were collected during early post-marketing phase vigilance (EPPV; 21 December 2018–20 June 2019). For patients with T1D prescribed ipragliflozin who experienced DKA, we examined DKA event data registered in the manufacturer’s safety database (21 December 2018–31 December 2021), including patient background characteristics. Results During EPPV, there were 189 total events (45 serious) of ADRs, including 32 serious events of ketoacidosis. From 2018 to 2021, the major DKA risk factors were sick days, stopping or inappropriately decreasing insulin, insulin pump trouble, and low carbohydrate diet, with substantial overlap among these factors. Conclusions In Japanese patients with T1D using ipragliflozin, DKA events were linked to several overlapping factors, including sick days and reduced dose/interruption of insulin, whether intentional or unexpected. These results highlight the need for improved patient education regarding ipragliflozin use and appropriate self-management of ketosis from an early stage.

Clinical characteristics and prognoses of patients with diabetic ketoacidosis in Finland

AimsTo assess the prognosis and risk factors for diabetic ketoacidosis (DKA) in Tampere University Hospital (Tays) in a retrospective case-control study. MethodsAll 282 patients (age ≥15 years) treated for DKA in Tays during the period 2014–2020 were included. A total of 846 controls adjusted for age, gender, diabetes type and municipality, and without any DKA during follow-up were collected from the Finnish National Diabetes Registry. HbA1c, mental and behavioural disorders, and mortality obtained from the Finnish National Diabetes Registry were compared between patients with and without DKA. ResultsPatients’ median age was 36 years. Ten percent of the patients with DKA died during the median follow-up time of three years. Mortality rate was sixfold higher in patients with DKA than among the controls (OR 6.28; 95% CI 3.17–12.42). Patients with DKA had higher rates of substance abuse (OR 4.68; 95% CI 3.23–6.78) and depression (OR 2.24; 95% CI 1.58–3.18), and higher median HbA1c levels (84 vs. 61 mmol/mol, p < 0.001). Nineteen percent of the DKA patients (n = 53) had recurrent DKA. ConclusionsDKA is a strong indicator for premature death. Poor glycaemic control, depression and substance abuse are risk factors for DKA.

Risk Factors Associated with Diabetic Ketoacidosis at the Onset of Type 1 Diabetes Mellitus.

There are various factors which increase the risk of diabetic ketoacidosis at the onset of type 1 diabetes mellitus. There have not been any such studies in our setting. This study was done to find the prevalence and risk factors associated with the development of diabetic ketoacidosis at onset of type 1 diabetes mellitus. Children and young adults with type 1 diabetes mellitus being treated at Patan hospital were approached and after obtaining an informed consent, all the patient information on various risk factors for diabetic ketoacidosis were collected in a pre-developed proforma. Data was entered in Microsoft Excel and analysis was done using statistical package for the social sciences-16. Ethical approval was taken from Institutional Review Committee- Patan Academy of Health Sciences. Out of 99 patients with type 1 diabetes enrolled in the study, 52.5% presented in diabetic ketoacidosis at the onset. The duration of symptoms was significantly less in patient presenting with diabetic ketoacidosis than without diabetic ketoacidosis (6.45±7.57 vs 9.13±10.12, p=0.04). There was no significant difference in the mean age, mean glycosylated hemoglobin, mean body mass index, gender, parents' literacy and medical consultations prior to diagnosis. More than half of the patients with type 1 diabetes presented in diabetic ketoacidosis. The shorter duration of symptoms prior to presentation was the only significant factor leading to presentation as diabetic ketoacidosis.

Risk Factors for Diabetic Ketoacidosis in Children with Type 1 Diabetes Mellitus: A Single-center, Cross-sectional Study in Indonesia

Background: Diabetic ketoacidosis (DKA), the leading cause of mortality in childhood with diabetes mellitus (DM). Identification of risk factors for DKA in children with type 1 DM (T1DM), can aid in reducing the incidence of DKA.Objective: To determine risk factors for DKA in children with T1DM.Methods: This was a single-centre, cross-sectional study of patients aged 0–16 years diagnosed with T1DM who were hospitalised in or visited Dr. Soetomo General Hospital in Surabaya between January 2016 and June 2021. Data on sex, age, parental educational background, parental occupation, parental age, family history of DM and DKA frequency were collected, and statistical analyses using the SPSS software. Results: The risk of DKA was higher in children with working mothers (OR 9.3, 95%; CI 2.168–40.182, p = 0.003). Significant correlation between maternal age younger than 40 years and DKA frequency (OR 1.73, 95%; CI 8.684–3.478, p = 0.000). The highest frequency of DKA was observed in children with low parental educational level, whereas there was no correlation between age at diagnosis and parental educational level with DKA.Conclusion: Young maternal age and working mothers might be associated with increased frequency of DKA in children with T1DM.

Risk Factors for Diabetic Ketoacidosis among Type 1 Diabetic Children Registered at “Heraa Diabetes Center” in Makkah Al-Mokarramah City, Saudi Arabia

Aim of Study: To assess risk factors associated with DKA among T1DM children registered at “Heraa Diabetes Center”, Makkah Al-Mokarramah City, Saudi Arabia. Patients and Methods: A retrospective hospital-based, case-control research design was followed and included 375 diabetic patients aged less than 15 years. The “Study Group” included 125 children who had a past history of diabetic ketoacidosis (DKA Group), while the “Control Group” comprised 250 diabetic children who did not have past history of DKA. A data collection sheet was designed by the researchers. Results: There was significantly more positive family history in the DKA group than the control group (78.4% and 68%, respectively, p=0.036). The mothers were the main person who injects the child. Differences between both study groups according to the person who injects the child was statistically significant (p=0.029). DKA occurred more than once in 59.2% of diabetic children, and in 46.4% of children with over-activity. The main presenting symptoms of DKA were polyuria, thirst and vomiting. The main causes and triggering factors were eating too many sweets (65.6%), missing blood sugar monitoring (57.6%), omitting the insulin dose (22.4%), or infection (12.8%). Children in the control group were significantly more compliant than those in the DKA group regarding daily measurement of blood sugar (82.8% and 71.2%, respectively, p=0.009), timely receiving treatment (96% and 82.4%, respectively, p&lt;0.001), following a healthy diet (79.6% and 65.6%, respectively, p=0.003), and receiving health education (95.2% and 88%, respectively, p=0.011). Conclusions: Risk factors for DKA include positive family history of diabetes, and less educated or employed mothers, but its incidence is lower among children of parents with health-related jobs. It can be triggered by over-activity. It is caused by eating too many sweets, missing blood sugar monitoring, omitting the insulin dose, or infection. Noncompliance is associated with higher incidence of DKA. Recommendations: All parents of diabetic children should receive health education and be trained about management of diabetes, compliance to diabetes management, continuous monitoring of glucose levels, and early manifestations of DKA. Key Words: Diabetic ketoacidosis, Type 1 diabetes, Children, Risk factors, Compliance, Saudi Arabia.

Nutritional ketosis is well-tolerated, even in type 1 diabetes: the ZeroFive100 Project; a proof-of-concept study.

The objective of this study was to test the feasibility of exercising over a 5-day period while fasting, in those with and without type 1 diabetes mellitus (T1DM).Eight individuals, ages 29--62 years, two with T1DM, walked/ran around 20 miles per day for five consecutive days while only consuming water. All eight individuals completed the project with no physical injuries or problems with diabetes control. The blood glucose levels ranged from less than 3 mmol/l to 7 mmol/l in those without T1D, and less than 3 mmol/l to 9 mmol/l in those with T1D. The continuous glucose traces in those with T1D showed little variability in glucose levels. The participants without T1D had no symptoms from blood glucose under 3 mmol/l. Ketone levels ranged from 0.3 to 7.5 and the ketones for those with T1D were no different to ketones in those without T1D. The respiratory quotient was overwhelmingly in the fat-burning range. There was very little subjective hunger, nor did it negatively affect mood. In keto-adapted individuals, with or without T1DM, prolonged exercise for 5 days while in nutritional ketosis was feasible, and well tolerated. Eight adults, ages 28-62 years, trained for and completed a 5-day zero calorie fast covering 100 miles over 5 days. Training involved each individual preparing for the event according to their own programme. Typically, it involved both cardiovascular and strength training with the addition of practice water only fasts over 24-72 h or more based upon the individual's assessment of what was needed to complete the event. There was no formal protocol provided for this. The recommendation was that the participants would be keto adapted and trained to a level sufficient to complete the 5-day event. Keto adaptation was measured by ketone blood testing of betahydroxybutyrate. Two people had type 1 diabetes. All but one person was keto-adapted ahead of the event. All eight individuals completed the project with no physical injuries or problems with diabetes control. Prolonged fasting did neither lead to hunger nor did it negatively affect mood, which, if anything, was enhanced in most individuals. All keto-adapted people were shown to be burning fat stores throughout the 5 days, and everyone was measured to be in a state of nutritional ketosis. In type 1 diabetes, and ketones were in the same range as those without diabetes, insulin volumes were considerably reduced, and glucose control was close to physiological: nutritional ketosis is not a risk factor for diabetic ketoacidosis; consumption of sugar for energy is not required for distances of up to 100 miles in keto-adapted people; people who inject insulin do not necessarily need to consume carbohydrates unless rescuing a hypoglycaemic attack. The findings from this project should provide reassurance to those clinicians who want to provide the option of a ketogenic lifestyle to their patients with type 1 diabetes. They also confirm that the fat stores are available for aerobic respiration without apparent negative consequences on physical or mental function. http://links.lww.com/COE/A24.

Assessment of Risk Factors for Diabetic Ketoacidosis among Diabetic Patients at Sohag University Hospital.

Abstract: Background: Diabetic ketoacidosis (DKA) is a life-threatening complication of diabetes, Assessment of risk factors play important roles in decreasing morbidity and mortality secondary to diabetic ketoacidosis. Aim: To assess risk factors for diabetic ketoacidosis among diabetic patients at Sohag University Hospital. Research design: Casecontrol retrospective research design had been utilized. Setting: The study was conducted in Emergency Medical unit, Internal Medicine department, and Outpatient Clinics of diabetes at Sohag University Hospital. Sample: 160 adult diabetic patients enrolled in this study. Tool: Patient assessment sheet for diabetic ketoacidosis was utilized for data collections during the period from January 2019 and ended October 2020. Results: The finding shows that age (p-value <0.01) as non-modifiable risk factors, dehydration (p-value <0.01), infection (p-value <0.01) poor compliance with treatment (p-value <0.01) and acute pancreatitis (p-value <0.01) were modifiable risk factors. There was highly statistical significant (p-value <0.01) association between DKA and risk factors. Conclusions: This study found strong associations between DKA and risk factors such as age, infection, poor compliance with treatment, dehydration, acute pancreatitis, emotional stress, surgery, myocardial infarction, and stroke. Recommendations: Modifiable risk factors have a significant role in the development of Diabetic Ketoacidosis, so a complete multidisciplinary diabetes education should be accessible to control these factors.

905-P: Modifiable and Nonmodifiable Risk Factors for Acute Complications of Type 1 Diabetes (T1D) in Adolescents

Aim: Diabetic ketoacidosis (DKA) and severe hypoglycemia (SH) are preventable, life-threatening complications of T1D, associated with morbidity, mortality, and healthcare costs. We examined incidence rates (IR) and risk factors for DKA and SH in a contemporary cohort of teens with T1D followed prospectively at 2 US pediatric diabetes centers. Methods: Data were collected by EHR review and parent-youth interview quarterly for 18 months in 301 adolescents, aged 13-17 at baseline, with T1D for 6+ months, and a wide range of A1c (6.5- Results: The sample (50% male, 22% non-white) had a mean±SD age 15.0±1.3 years, T1D duration 6.5±3.7 years, and A1c 8.5±1.1%; 59% pump-treated. DKA IR was 9.3/100 person-years; SH IR was 42.6/100 person-years. Many diabetes management factors were associated with higher IR of DKA and SH (Figure). Non-modifiable demographic and family factors associated with DKA and SH included non-white ethnicity, lower parent education, public insurance, and lower household income (p Summary: IR of DKA and SH remain high in teens with T1D. Recognized modifiable (glucose monitoring [possibly by CGM] and A1c) and non-modifiable socio-demographic factors can be targeted to reduce rates of acute complications. Disclosure M. D. Ivanova: None. L. K. Volkening: None. B. Anderson: None. L. M. Laffel: Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompe, Insulogic LLC, Janssen Pharmaceuticals, Inc., Laxmi Therapeutic Devices, LifeScan, Lilly Diabetes, Medtronic, Provention Bio, Inc. Funding National Institutes of Health (R01DK095273, P30DK036836); JDRF (2-SRA-2014-253-M-B)

Identifying Risk Factors for Diabetic Ketoacidosis Associated with SGLT2 Inhibitors: a Nationwide Cohort Study in the USA.

Sodium glucose co-transporter-2 inhibitors (SGLT2) are commonly prescribed to patients with type 2 diabetes mellitus, but can increase the risk of diabetic ketoacidosis. Identifying patients prone to diabetic ketoacidosis may help mitigate this risk. We conducted a population-based cohort study of adults initiating SGLT2 inhibitoruse from 2013 through 2017. The primary objective was to identify potential predictors of diabetic ketoacidosis. Two machine-learning methods were applied to model high-dimensional pre-exposure data: gradient boosted trees and least absolute shrinkage and selection operator (LASSO) regression. We rank ordered the variables produced from LASSO by the size of their estimated coefficient (largest to smallest). With gradient boosted trees, a relative importance measure for each variable is provided rather than a coefficient. The "top variables" were identified after reviewing the distributions of the effect estimates from LASSO and gradient boosted trees to identify where there was a substantial decrease in variable importance. The identified predictors were then assessed in a logistic regression model and reported as odds ratios (ORs) with 95% confidence intervals (CIs). We identified 111,442 adults who started SGLT2 inhibitoruse. The mean age was 57years, 44% were female, the mean hemoglobin A1C was 8.7%, and the mean creatinine was 0.89mg/dL. During a mean follow-up of 180days, 192 patients (0.2%, i.e., 2 per 1000) were diagnosed and hospitalized with diabetic ketoacidosis (DKA) and 475 (0.4%, i.e., 4 per 1000) were diagnosed in either an inpatient or outpatient setting. Using gradient boosted trees, the strongest predictors were prior DKA, baseline hemoglobin A1C level, baseline creatinine level, use of medications for dementia, and baseline bicarbonate level. Using LASSO regression not including laboratory test results due to missing data, the strongest predictors were prior DKA, digoxin use, use of medications for dementia, and recent hypoglycemia. The logistic regression model incorporating the variables identified from gradient boosted trees and LASSO regression suggested the following pre-exposure characteristics had the strongest association with a hospitalization for DKA: use of dementia medications (OR = 7.76, 95% CI 2.60, 23.1), prior intracranial hemorrhage (OR = 11.5, 95% CI 1.46, 91.1), a prior diagnosis of hypoglycemia (OR = 5.41, 95% CI 1.92,15.3), prior DKA (OR = 2.45, 95% CI 0.33, 18.0), digoxin use (OR = 4.00, 95% CI 1.21, 13.2), a baseline hemoglobin A1C above 10% (OR = 3.14, 95% CI 1.95, 5.06), and baseline bicarbonate below 18mmol/L (OR 5.09, 95% CI 1.58,16.4). Diabetic ketoacidosis affected approximately 2 per 1000 patients starting to use an SGLT2 inhibitor. We identified both anticipated, e.g., low baseline serum bicarbonate, and unanticipated, e.g., digoxin, dementia medications, risk factors for SGLT2inhibitor-induced DKA.

Performance assessment of different machine learning approaches in predicting diabetic ketoacidosis in adults with type 1 diabetes using electronic health records data.

PurposeTo assess the performance of different machine learning (ML) approaches in identifying risk factors for diabetic ketoacidosis (DKA) and predicting DKA.MethodsThis study applied flexible ML (XGBoost, distributed random forest [DRF] and feedforward network) and conventional ML approaches (logistic regression and least absolute shrinkage and selection operator [LASSO]) to 3400 DKA cases and 11 780 controls nested in adults with type 1 diabetes identified from Optum® de‐identified Electronic Health Record dataset (2007–2018). Area under the curve (AUC), accuracy, sensitivity and specificity were computed using fivefold cross validation, and their 95% confidence intervals (CI) were established using 1000 bootstrap samples. The importance of predictors was compared across these models.ResultsIn the training set, XGBoost and feedforward network yielded higher AUC values (0.89 and 0.86, respectively) than logistic regression (0.83), LASSO (0.83) and DRF (0.81). However, the AUC values were similar (0.82) among these approaches in the test set (95% CI range, 0.80–0.84). While the accuracy values >0.8 and the specificity values >0.9 for all models, the sensitivity values were only 0.4. The differences in these metrics across these models were minimal in the test set. All approaches selected some known risk factors for DKA as the top 10 features. XGBoost and DRF included more laboratory measurements or vital signs compared with conventional ML approaches, while feedforward network included more social demographics.ConclusionsIn our empirical study, all ML approaches demonstrated similar performance, and identified overlapping, but different, top 10 predictors. The difference in selected top predictors needs further research.

876 Diabetic ketoacidosis in pregnancy: disparities and trends over time

Recent population-based studies defining the frequency of and risk factors for diabetic ketoacidosis (DKA) in pregnancy are lacking. We aimed to identify sociodemographic and clinical factors associated with DKA in pregnancy. Repeated cross-sectional study with case-control analysis of women in the National Inpatient Sample (2012-Q3 2015) with pregestational diabetes (DM) admitted to the hospital during pregnancy. The primary outcome was DKA (ICD-9 codes 250.1, 250.10, 250.12, 250.13). DKA was compared over time using a test of trend. Demographic, hospital, and clinical characteristics were compared between women with and without DKA using chi-square and student’s t-test. Multivariable logistic regression assessed what characteristics were independently associated with DKA. Variables were included in the initial model if p < 0.20 in bivariable analysis and sequentially removed using likelihood ratio testing with p < 0.05 considered significant. Of 44,159 deliveries complicated by pregestational DM, there were 1,263 cases of DKA, or 286 cases per 10,000 DM deliveries. DKA increased from 2012 to 2015 (Figure). In addition to time, factors associated with higher adjusted odds of DKA included non-Hispanic Black (vs White) race, public (vs private) insurance, urban (vs rural) hospital, larger size hospital, anemia, substance use disorder, and antenatal depression (Table). Factors associated with a lower adjusted odds of DKA included older age, Hispanic or other race (vs White), and obesity (Table). Among these, the factors with the strongest associations were obesity (aOR 0.22, 95%CI 0.18-0.28) and time (aOR 3.40, 95%CI 2.67-4.32 for 2013; aOR 3.53, 95%CI 2.78-4.48 for 2014; aOR 3.87, 95%CI 3.03-4.94 for 2015 Q1-3; referent=2012). Hypertension, renal disease and US region were not associated with DKA. In a contemporary, nationwide US sample, DKA increased over time with sociodemographic and clinical disparities. Further investigation is needed to confirm the rise in DKA after 2012 and identify how to address the identified disparities to prevent DKA in the future.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

Dietary intake and hospitalisation due to diabetic ketoacidosis and hypoglycaemia in individuals with type 1 diabetes

We investigated the association between diet and risk of hospitalisation for diabetic ketoacidosis (DKA) or hypoglycaemia in type 1 diabetes. Food records were used to assess dietary intake. Data on DKA and hypoglycaemia hospitalisations, within two years of dietary assessments, were obtained from registries. Analyses were conducted with and without macronutrient substitution. Data were available from 1391 participants, 28 (2.0%) and 55 (4.0%) of whom were hospitalised due to DKA or hypoglycaemia, respectively. In the adjusted model, self-reported alcohol intake was associated with increased (per 10 g: B = 1.463, 95% CI = 1.114–1.922, p = 0.006; per E%: B = 1.113, 95% CI = 1.027–1.206, p = 0.009), and fibre intake with reduced (per g/MJ: B = 0.934, 95% CI = 0.878–0.995, p = 0.034) risk of DKA hospitalisation. Substituting carbohydrates for fats was associated with increased risk for hypoglycaemia hospitalisation (B = 1.361, 95% CI = 1.031–1.795, p = 0.029), while substituting alcohol for carbohydrates (B = 1.644, 95% CI = 1.006–2.685, p = 0.047) or proteins (B = 2.278, 95% CI = 1.038–4.999, p = 0.040) increased the risk for DKA hospitalisation. In conclusion, refraining from alcohol intake is a preventable risk factor for DKA, while higher fibre intake seems rather protective. Increasing carbohydrate intake while decreasing that of fats, is associated with higher hypoglycaemia risk. Whether this is a cause or effect of hypoglycaemia remains to be established.

Clinical features and risk factors for diabetic ketoacidosis in type 1 diabetes mellitus at tertiary care centre, Maharashtra, India

Background: Diabetes Mellitus is increasing in incidence, prevalence and importance as a chronic disease throughout the world. The International Diabetes Federation projects that by 2030 there will be 438 million people with diabetes on a global scale. Three essential components of Diabetic Ketoacidosis are hyperglycemia, ketosis, and resultant metabolic acidosis. 4% of all patients with diabetes and 20% of those with Type 1 Diabetes are admitted to hospital with manifestations of ketoacidosis. Objectives was to study clinical profile of patients presenting as Diabetic Ketoacidosis.Methods: It is a descriptive observational study was conducted at Department of Medicine, Dr. Shankarrao Chavan Medical College and Hospital, Nanded. The study included 77 patients of diabetic ketoacidosis (DKA) from Male Medicine ward, Female Medicine ward, Medical Intensive Care Unit. The study was carried out during Jan 2012 to October 2013. The data was analyzed using SPSS 24.0 version.Results: Majority of the subjects were from 10-20 years age group i.e. 31(40.3%). 51.9% were males and 42.9% were females. 38(49.4%) have onset of Diabetes type 1 between 10- 20 years of age and mean±S.D.20.11±7.09yrs. Most common symptoms at the time of admission were abdominal pain in 54(70.1%), vomiting in 52(67.5%), nausea in 41(53.2%) and fatigue in 40(51.9%) patients. Most common risk factor for DKA was found to be infections in 36(46.8%) patients.Conclusions: Most common clinical features of Diabetic Ketoacidosis were abdominal pain, vomiting, nausea and fatigue. Most common risk factor for Diabetic Ketoacidosis was infection followed by omission of treatment or irregular treatment. The most common infections were due to urinary tract &amp; respiratory tract infections.

Using population data to understand the epidemiology and risk factors for diabetic ketoacidosis in Australian children with type 1 diabetes

Children with type 1 diabetes (T1D) are at risk of diabetic ketoacidosis (DKA) at T1D diagnosis and/or subsequently. The objective is to determine the incidence and prevalence of T1D by the presence of DKA and identify the characteristics of subsequent DKA episodes. The study population included all children aged <15 years with T1D during a hospital/day-stay admission in New South Wales, Australia, from 1 January 2001 to 31 December 2013. T1D and DKA were identified using International Classification of Diseases Australian Modification codes. Data sources included routinely collected longitudinally linked population hospitalization and birth records. Chi-squared analyses, logistic, and multinomial regression were used to determine the association between child characteristics and admissions with and without DKA. The point prevalence of T1D among 0-14-year olds on 31 December 2013 was 144.2 per 100 000. For children aged 0-12 years, the incidence of T1D was 16.3 per 100 000 child-years. One-third had DKA at T1D diagnosis and were more likely to be readmitted with DKA than those without DKA at T1D diagnosis. Children with more than one readmission for DKA were more likely to be female, reside in an inner regional area or an area of socioeconomic disadvantage, and be Australian-born. Among all hospitalizations of children with T1D, those with DKA were more likely to be aged 10-14 years, require intensive care, have longer length of stay, and admitted outside school days. Routinely collected administrative health data are a reliable source to monitor incidence and health service use of childhood T1D. Children at risk of repeated DKA, particularly females, adolescents, and those from inner regional or socioeconomically disadvantaged areas, should be targeted during education and follow-up.

Tacrolimus Induced Diabetic Ketoacidosis Following Hematopoietic Stem Cell Transplantation.

Risk of diabetes mellitus increases after solid organ and hematopoietic stem cell transplantation. Diabetic ketoacidosis has been reported after solid organ transplantation in patients receiving tacrolimus but has rarely been reported after stem cell transplantation. The major risk factors for diabetic ketoacidosis are immunosuppressive drugs used after transplantation. We report here three cases of allogenic stem cell transplant who developed diabetic ketoacidosis while on treatment with tacrolimus. The drug was stopped in all the cases and patients were treated with insulin therapy resulting in complete recovery from diabetic ketoacidosis.