Clinical and Prognostic Features of Diabetic Ketoacidosis According to the Trigger of the Syndrome.

BACKGROUND: Diabetic ketoacidosis (DKA) is an acute metabolic, life-threatening complication of diabetes mellitus with a mortality rate that now stand at less than 1%. Although mortality is coupled with the etiology of DKA, literature on the influence of DKA etiology on patient outcome is scarce. OBJECTIVES: To study different triggers for DKA and their effect on outcomes. METHODS: We conducted a retrospective study that include 385 DKA patients from 2004 to 2017. The study compared demographics, clinical presentation, and mortality rates by different precipitating factors. RESULTS: Patients with DKA due to infections had a higher risk to develop in-hospital mortality after controlling for age and sex (odds ratio 4.40, 95% confidence interval 1.35-14.30), had a higher Charlson Comorbidity Index score, a higher risk of being mechanical ventilated (14% vs. 3%, P < 0.01), and a longer duration of hospitalization (5 days vs. 3 days, P < 0.001). CONCLUSIONS: It is crucial to find the triggers that precipitate DKA and start the treatment as early as possible in addition to the metabolic aspect of the treatment especially when the trigger is an infectious disease.

Superior ophthalmic vein thrombosis in unique double origin: a case report.

Superior ophthalmic vein thrombosis (SOVT) is a rare orbital pathology. It can cause serious complications if it isn´t diagnosed appropriately. It can be secondary to many etiologies, septic or aseptic ones. Diabetic ketoacidosis (DKA) may disturb the vascular endothelium and promote a prothrombotic state. The presence of which is related to a significantly increased risk of morbidity and mortality. We report the case of a 45-year-old woman who presented a SOVT revealing DKA. Orbit magnetic resonance imaging (MRI) showed thrombosis of the right superior ophthalmic vein. A treatment based on thrombolytic treatment, associated with antibiotic coverage and a glycemic balance was initiated. This case highlights the importance of considering both infection and diabetes as an important part of the diagnosis and management of SOVT.

A Rare Case of Hyperglycemia, Ketoacidosis, and Central Facial Paralysis in a Newly-Diagnosed Diabetic Woman.

BACKGROUND Diabetes mellitus is a chronic disease that occurs when the pancreas does not produce enough insulin or when the body is unable to effectively use the insulin it produces. Uncontrolled diabetes mellitus is usually associated with neurological manifestations, such as hemichorea, focal epileptic seizures, peripheral neuropathy, and peripheral facial paralysis. This report describes a 59-year-old woman presenting with hyperglycemia and ketoacidosis due to newly diagnosed diabetes mellitus, as well as a temporary episode of central facial paralysis, which regressed within a few days after medical treatment and metabolic correction. CASE REPORT A 59-year-old patient with hypertension and a family history of diabetes mellitus presented with polyuro-polydipsic syndrome and signs of metabolic ketoacidosis, with an elevated anion gap, compatible with newly discovered type 1 diabetes mellitus. Six hours after admission, we noted the abrupt onset of left central facial paralysis, with no brain damage shown on magnetic resonance imaging. Initially, the diagnosis was transient ischemic attack. After a second, normal cerebral magnetic resonance image on the fourth day, and clinical improvement on the fifth day after metabolic correction by insulin therapy and rehydration, the diagnosis of a regressive central facial paralysis was retained. CONCLUSIONS Central facial paralysis in diabetic ketoacidosis is a rare neuroendocrine entity. The pathophysiological mechanisms that can explain the occurrence of central facial paralysis are not yet described and require further investigation. This report highlights the importance of diagnosis, early management of hyperglycemia and diabetic ketoacidosis, and reversibility of central facial paralysis after treatment.

Epidemiology, microbiology, and diagnosis of infection in diabetic ketoacidosis and hyperosmolar hyperglycemic syndrome: A multicenter retrospective observational study.

AIMS: We investigated the characteristics of infection and the utility of inflammatory markers in diabetic ketoacidosis (DKA) and hyperosmolar hyperglycemic syndrome (HHS). METHODS: A multicenter, retrospective observational study in 21 acute-care hospitals was conducted in Japan. This study included adult hospitalized patients with DKA and HHS. We analyzed the diagnostic accuracy of markers including C-reactive protein (CRP) and procalcitonin (PCT) for bacteremia. Multiple regression models were created for estimating bacteremia risk factors. RESULTS: A total of 771 patients, including 545 patients with DKA and 226 patients with HHS, were analyzed. The mean age was 58.2 (SD, 19.3) years. Of these, 70 tested positive for blood culture. The mortality rates of those with and without bacteremia were 14 % and 3.3 % (P-value < 0.001). The area under the curve (AUC) of CRP and PCT for diagnosis of bacteremia was 0.85 (95 %CI, 0.81-0.89) and 0.76 (95 %CI, 0.60-0.92), respectively. Logistic regression models identified older age, altered level of consciousness, hypotension, and higher CRP as risk factors for bacteremia. CONCLUSIONS: The mortality rate was higher in patients with bacteremia than patients without it. CRP, rather than PCT, may be valid for diagnosing bacteremia in hyperglycemic emergencies. TRIAL REGISTRATION: This study is registered in the UMIN clinical trial registration system (UMIN000025393, Registered December 23, 2016).

Predicting type 1 diabetes in children using electronic health records in primary care in the UK: development and validation of a machine-learning algorithm.

BACKGROUND: Children presenting to primary care with suspected type 1 diabetes should be referred immediately to secondary care to avoid life-threatening diabetic ketoacidosis. However, early recognition of children with type 1 diabetes is challenging. Children might not present with classic symptoms, or symptoms might be attributed to more common conditions. A quarter of children present with diabetic ketoacidosis, a proportion unchanged over 25 years. Our aim was to investigate whether a machine-learning algorithm could lead to earlier detection of type 1 diabetes in primary care. METHODS: We developed the predictive algorithm using Welsh primary care electronic health records (EHRs) linked to the Brecon Dataset, a register of children newly diagnosed with type 1 diabetes. Children were included from their first primary care record within the study period of Jan 1, 2000, to Dec 31, 2016, until either type 1 diabetes diagnosis, they turned 15 years of age, or study end. We developed an ensemble learner (SuperLearner) using 26 potential predictors. Validation of the algorithm was done in English EHRs from the Clinical Practice Research Datalink (primary care) and Hospital Episode Statistics, focusing on the ability of the algorithm to identify children who went on to develop type 1 diabetes and the time by which diagnosis could be anticipated. FINDINGS: The development dataset comprised 34 754 400 primary care contacts, relating to 952 402 children, and the validation dataset comprised 43 089 103 primary care contacts, relating to 1 493 328 children. Of these, 1829 (0·19%) children younger than 15 years in the development dataset, and 1516 (0·10%) in the validation dataset had a reliable date of type 1 diabetes diagnosis. If set to give an alert in 10% of contacts, an estimated 71·6% (95% CI 68·8-74·4) of the children with type 1 diabetes would receive an alert by the algorithm in the 90 days before diagnosis, with diagnosis anticipated, on average, by an estimated 9·34 days (95% CI 7·77-10·9). INTERPRETATION: If implemented into primary care settings, this predictive algorithm could substantially reduce the proportion of patients with new-onset type 1 diabetes presenting in diabetic ketoacidosis. Acceptability of alert thresholds should be explored in primary care. FUNDING: Diabetes UK.

High Prevalence of A-ß+ Ketosis-Prone Diabetes in Children with Type 2 Diabetes and Diabetic Ketoacidosis at Diagnosis: Evidence from the Rare and Atypical Diabetes Network (RADIANT).

Background: A-ß+ ketosis-prone diabetes (KPD) in adults is characterized by presentation with diabetic ketoacidosis (DKA), negative islet autoantibodies, and preserved ß-cell function in persons with a phenotype of obesity-associated type 2 diabetes (T2D). The prevalence of KPD has not been evaluated in children. We investigated children with DKA at "T2D" onset and determined the prevalence and characteristics of pediatric A-ß+ KPD within this cohort. Methods: We reviewed the records of 716 children with T2D at a large academic hospital and compared clinical characteristics of those with and without DKA at onset. In the latter group, we identified patients with A-ß+ KPD using criteria of the Rare and Atypical Diabetes Network (RADIANT) and defined its prevalence and characteristics. Results: Mean age at diagnosis was 13.7 ± 2.4 years: 63% female; 59% Hispanic, 29% African American, 9% non-Hispanic White, and 3% other. Fifty-six (7.8%) presented with DKA at diagnosis and lacked islet autoantibodies. Children presenting with DKA were older and had lower C-peptide and higher glucose concentrations than those without DKA. Twenty-five children with DKA (45%) met RADIANT A-ß+ KPD criteria. They were predominantly male (64%), African American or Hispanic (96%), with substantial C-peptide (1.3 ± 0.7 ng/mL) at presentation with DKA and excellent long-term glycemic control (HbA1c 6.6% ± 1.9% at follow-up (median 1.3 years postdiagnosis)). Conclusions: In children with a clinical phenotype of T2D and DKA at diagnosis, approximately half meet criteria for A-ß+ KPD. They manifest the key characteristics of obesity, preserved ß-cell function, male predominance, and potential to discontinue insulin therapy, similar to adults with A-ß+ KPD.

Persistent chronic calcific pancreatitis with intraductal calculi associated with secondary diabetes mellitus type 3 and diabetic ketoacidosis - A case report.

Diabetes mellitus type 3 refers to diabetes secondary to an existing disease or condition of the exocrine pancreas and is an uncommon cause of diabetes occurring due to pancreatogenic pathology. It accounts for 15-20% of diabetic patients in Indian and Southeast Asian continents. This is case report of a rare case of type 3 diabetes mellitus (T3DM) presenting with diabetic ketoacidosis (DKA). The patient was admitted for DKA along with complaint of hyperglycemia, blood glucose of 405 mg/dl with HbA1c level of 13.7%. Computed tomography evidence revealed chronic calcific pancreatitis with intraductal calculi and dilated pancreatic duct.

Type 1 diabetes in pediatrics during the COVID-19 pandemic: Time from symptom onset and forms of presentation at a referral hospital. / Diabetes tipo 1 en pediatría durante la pandemia por COVID-19: tiempo de evolución de síntomas y formas de presentación en un centro de referencia.

Introduction. The COVID-19 pandemic impacted on the health care of patients with type 1 diabetes mellitus (DM1). An increase in diabetic ketoacidosis (DKA) as a form of diagnosis was reported. Objectives. To assess whether there were changes in the time from symptom onset, the causes of hospitalization due to DM1, and the proportion of severe forms, and to describe SARS-CoV-2 infection in these patients. Population and methods. Cross-sectional study in patients younger than 19 years hospitalized due to DM1 from March 2018 to August 2019 (pre-pandemic) and from March 2020 to August 2021 (pandemic). Results. The assessment included 135 hospitalizations in the pre-pandemic period and 96 during the pandemic. The time from symptom onset during the pandemic in those with debut of diabetes was shorter than in the pre-pandemic period (18.8 ± 10.2 versus 52.1 ± 12.1 days, respectively; p < 0.001). Hospitalizations due to all forms of diabetes debut and debut with DKA were more common during the pandemic than before it (59.4% versus 39.3%; odds ratio [OR]: 2.3; 95% confidence interval [CI]: 1.3-3.8; p = 0.003 and 40.6% versus 20.7%; OR: 2.6; 95% CI: 1.4-5.2; p = 0.006, respectively). Severe forms of DKA did not change between both periods (48.1% versus 59.9%; p = 0.3). Only 6 patients developed SARS-CoV-2 infection; 3 were severe. Conclusion. During the pandemic, the time from symptom onset decreased and the frequency of hospitalizations due to debut of DM1 increased. The proportion of severe forms of DKA did not change.

Introducción. La pandemia por COVID-19 afectó la atención de pacientes con diabetes mellitus tipo 1 (DM1). Además, se reportó un aumento de cetoacidosis diabética (CAD) como forma de diagnóstico. Objetivos. Evaluar si durante la pandemia por COVID-19 se modificaron el tiempo de evolución de síntomas, las causas de hospitalización por DM1 y la proporción de formas graves, y describir la infección por SARS-CoV-2 en estos pacientes. Población y métodos. Estudio transversal que incluyó pacientes menores de 19 años hospitalizados por DM1 en un centro pediátrico de referencia de marzo de 2018 a agosto de 2019 (prepandemia) y de marzo de 2020 a agosto de 2021 (pandemia). Resultados. Se analizaron 231 internaciones, 135 prepandemia y 96 en pandemia. Los pacientes con debut diabético presentaron menor tiempo de evolución de síntomas en pandemia que en prepandemia (18,8 ± 10,2 vs. 52,1 ±12,1 días, respectivamente; p <0,001). Las hospitalizaciones por todas las formas de debut diabético y el debut con CAD fueron más frecuentes en pandemia que en prepandemia (59,4 % vs. 39,3 %; OR 2,3; IC95% 1,3-3,8; p = 0,003); y (40,6 % vs. 20,7 %; OR 2,6; IC95% 1,4-5,2; p = 0,006) respectivamente. La proporción de formas graves de CAD no se modificó entre ambos períodos (48,1 % vs. 59,9 %; p = 0,3). Solo 6 pacientes presentaron infección por SARS-CoV-2; 3 fueron formas graves. Conclusión. Durante la pandemia, disminuyó el tiempo de evolución de síntomas y aumentó la frecuencia de hospitalizaciones por debut de DM1, con mayor proporción de CAD. No se modificó la proporción de formas graves de CAD.

Does an episode of diabetic ketoacidosis affect thyroid function tests in pediatric patients?

OBJECTIVES: The aim of our study was to investigate the changes in thyroid hormone levels during and after acute metabolic disorder in patients with diabetic ketoacidosis (DKA). METHODS: Eighty five patients diagnosed with DKA were included in the study. Patients with control thyroid function test (TFT) values at admission (the first blood sample) and 1 month later were included in the study. Thyroid function tests obtained during diabetic ketoacidosis and at the first month follow-up were compared. Euthyroidism and euthyroid sick syndrome were defined and grouped according to current guidelines. The mild and moderate groups, according to DKA classification, were combined and compared with the severe group. RESULTS: A significant increase was observed between the first admission and the control TFT values 1 month later. However, there was no significant difference found in TFT between mild/moderate and severe groups taken at the time of DKA. Difference between two groups, euthyroid sick syndrome and euthyroid, was examined and the result that was different from the literature was the difference between TSH levels. We found that low FT4 levels were associated with higher HgbA1c, although the correlation was weak. CONCLUSIONS: Thyroid hormone levels may not reflect a thyroid disease during severe DKA attack. Therefore, it is unnecessary to check thyroid function tests.

Inaccurate diagnosis of diabetes type in youth: prevalence, characteristics, and implications.

Classifying diabetes at diagnosis is crucial for disease management but increasingly difficult due to overlaps in characteristics between the commonly encountered diabetes types. We evaluated the prevalence and characteristics of youth with diabetes type that was unknown at diagnosis or was revised over time. We studied 2073 youth with new-onset diabetes (median age [IQR] = 11.4 [6.2] years; 50% male; 75% White, 21% Black, 4% other race; overall, 37% Hispanic) and compared youth with unknown versus known diabetes type, per pediatric endocrinologist diagnosis. In a longitudinal subcohort of patients with data for ≥ 3 years post-diabetes diagnosis (n = 1019), we compared youth with steady versus reclassified diabetes type. In the entire cohort, after adjustment for confounders, diabetes type was unknown in 62 youth (3%), associated with older age, negative IA-2 autoantibody, lower C-peptide, and no diabetic ketoacidosis (all, p < 0.05). In the longitudinal subcohort, diabetes type was reclassified in 35 youth (3.4%); this was not statistically associated with any single characteristic. In sum, among racially/ethnically diverse youth with diabetes, 6.4% had inaccurate diabetes classification at diagnosis. Further research is warranted to improve accurate diagnosis of pediatric diabetes type.

Diabetic Ketoacidosis in Type 1 Diabetes Onset in Latin American Children.

OBJECTIVE: To describe the patterns of diabetic ketoacidosis (DKA) occurrence in children newly diagnosed with type 1 diabetes (T1DM) across several Latin American pediatric diabetes centers from 2018 to 2022. METHODS: A retrospective chart review included children under 18 with new-onset T1DM from 30 Latin American pediatric diabetes centers (Argentina, Chile, and Peru) between 30 December 2018 and 30 December 2022. Multiple logistic regression models examined the relationships between age, gender, medical insurance, BMI, and DKA at new-onset T1DM. As far as we know, there are no large studies in Latin American countries exploring the patterns of DKA in new-onset T1DM. RESULTS: A total of 2,026 (983 females) children, median age 9.12 (5.8 -11.7) years with new-onset-T1DM were included. Approximately 50% had no medical insurance. Mean glucose values were 467 mg/dL, pH 7.21, bicarbonate 13 mEq/L, HbA1c 11.3%, and BMI 18. The frequency of DKA was 1,229 (60.7%), out of which only 447 (36%) were severe. There was a significant decrease in the frequency of DKA as age increased: 373 (70.2%) in children under 6, 639 (61.6%) in those between 6 and 12, 217 and (47.5%) in those over 12. Children with medical insurance (58.8%) had a significantly lower frequency of DKA than those without (62.7%). The multiple logistic regression models showed that DKA was significantly and inversely associated with age [OR, 0.72 (95% CI 0.60-0.86)], BMI [OR, 0.95 (95% CI 0.92-0.99)], and medical insurance [OR, 0.75 (95% CI 0.60-0.94)] adjusted for sex. CONCLUSION: Latin American children with new-onset T1DM exhibited a substantial occurrence of DKA. Younger ages and the lack of medical insurance were significantly associated with DKA in new-onset T1DM.

Feature selection and risk prediction for diabetic patients with ketoacidosis based on MIMIC-IV.

Background: Diabetic ketoacidosis (DKA) is a frequent acute complication of diabetes mellitus (DM). It develops quickly, produces severe symptoms, and greatly affects the lives and health of individuals with DM.This article utilizes machine learning methods to examine the baseline characteristics that significantly contribute to the development of DKA. Its goal is to identify and prevent DKA in a targeted and early manner. Methods: This study selected 2382 eligible diabetic patients from the MIMIC-IV dataset, including 1193 DM patients with ketoacidosis and 1186 DM patients without ketoacidosis. A total of 42 baseline characteristics were included in this research. The research process was as follows: Firstly, important features were selected through Pearson correlation analysis and random forest to identify the relevant physiological indicators associated with DKA. Next, logistic regression was used to individually predict DKA based on the 42 baseline characteristics, analyzing the impact of different physiological indicators on the experimental results. Finally, the prediction of ketoacidosis was performed by combining feature selection with machine learning models include logistic regression, XGBoost, decision tree, random forest, support vector machine, and k-nearest neighbors classifier. Results: Based on the importance analysis conducted using different feature selection methods, the top five features in terms of importance were identified as mean hematocrit (haematocrit_mean), mean hemoglobin (haemoglobin_mean), mean anion gap (aniongap_mean), age, and Charlson comorbidity index (charlson_comorbidity_index). These features were found to have significant relevance in predicting DKA. In the individual prediction using logistic regression, these five features have been proven to be effective, with F1 scores of 1.000 for hematocrit mean, 0.978 for haemoglobin_mean, 0.747 for age, 0.692 for aniongap_mean and 0.666 for charlson_comorbidity_index. These F1 scores indicate the effectiveness of each feature in predicting DKA, with the highest score achieved by mean hematocrit. In the prediction of DKA using machine learning models, including logistic regression, XGBoost, decision tree, and random forest demonstrated excellent results, achieving an F1 score of 1.000. Additionally, by applying feature selection techniques, noticeable improvements were observed in the experimental performance of the support vector machine and k-nearest neighbors classifier. Conclusion: The study found that hematocrit, hemoglobin, anion gap, age, and Charlson comorbidity index are closely associated with ketoacidosis. In clinical practice, these five baseline characteristics should be given with the special attention to achieve early detection and treatment, thus reducing the incidence of the disease.

Fulminant type 1 diabetes, an underrecognized and unique subtype of type 1 diabetes: A case series from Singapore.

Fulminant type 1 diabetes (FT1D) is a unique subtype of type 1 diabetes, characterized by acute absolute insulin deficiency, severe ketosis, and increased risk of hypoglycemia, glycemic variability and microvascular complications. Seven people with FT1D were identified from two tertiary centers in Singapore. Six were Chinese, the mean age was 35 years and all were lean (mean body mass index 20.3 kg/m2). All presented with diabetes ketosis or ketoacidosis and low C-peptide. All but one had low glutamic acid decarboxylase antibodies. Nearly half had a missed/delayed diagnosis of FT1D. Three had frequent hypoglycemia, which improved after transition to continuous subcutaneous insulin infusion therapy. Individuals with FT1D experience unique diagnostic and management challenges associated with rapid absolute insulin deficiency. Greater awareness about this clinical entity is required.

Increased Severity of Presentation Signs in Children with Newly Diagnosed Type 1 Diabetes during the COVID-19 Pandemic: A Tertiary Center Experience.

INTRODUCTION: Diabetic ketoacidosis (DKA) is an important complication of type 1 diabetes mellitus (T1DM) which is worsened when the diagnosis of T1DM is delayed. The aim of this study was to evaluate the presentation patterns, severity, autoantibody status, and seasonal variability of newly diagnosed T1DM patients during the pandemic period of 2 years compared to those in the pre-pandemic period. METHODS: In this single tertiary center retrospective cohort study, newly diagnosed T1DM patients were grouped as pre-pandemic and pandemic period. Age, gender, the month of diagnosis, hemoglobin A1c, venous blood gas parameters, duration of symptoms, glutamic-acid-decarboxylase-antibody (anti-GAD), islet-cell antibody (ICA), and insulin autoantibody levels were recorded. The data obtained were compared between the groups. RESULTS: Number of patients presenting with DKA was significantly higher during the pandemic period (92 [65.7%] vs. 62 [40.8%] patients, p < 0.001). In terms of clinical severity of DKA, pH, and HCO3 levels were lower during the pandemic period (p < 0.001), while the number of patients presenting with severe DKA was significantly higher during the pandemic period (41 [44.6%] vs. 17 [27.4%] patients, p = 0.031). ICA positivity was significantly higher in patients admitted during the pandemic period (47 [36.4%] vs. 21 patients [16.9%], p < 0.001), especially in the second year of the pandemic (p < 0.001). Anti-GAD-ICA co-positivity was significantly higher in patients admitted during the pandemic period and also in second year of the pandemic (p < 0.001). CONCLUSION: DKA rates increased in newly diagnosed T1DM cases during the pandemic. Despite the relaxation of bans, the second year of the pandemic also saw increased rates of DKA and severe DKA compared to the pre-pandemic period. The significantly increased ICA positivity in the pandemic may support the effects of COVID-19 on autoimmune T1DM.