Introduction: Diabetic ketoacidosis (DKA) is a life-threatening complication associated with significant morbidity and healthcare burden. Despite advances in diabetes care, recurrent DKA remains common, often reflecting gaps in treatment adherence and patient education. Identifying predictors of recurrence is crucial for risk stratification and targeted intervention. Methodology: We conducted a retrospective observational study of all adult DKA admissions to a tertiary centre between 2001 and 2025. Electronic medical records were reviewed for demographic data, biochemical parameters, precipitating factors, and clinical outcomes. DKA was defined using standard biochemical criteria. Recurrent DKA was defined as ≥2 admissions during the study period. Factors associated with recurrent DKA admissions were analyzed. Patients under the age of 18 years and those with missing vital information were excluded. Results: A total of 667 DKA admissions, comprising 566 patients, were identified, of which 101 admissions (15.1%) were recurrent, involving 65 patients. Among recurrent DKA episodes, the most common precipitating factors were infection (64.4%) and insulin omission (62.4%). After multivariate analyses, patients with type 1 diabetes mellitus (T1DM) were more likely to develop recurrent DKA compared to those with type 2 diabetes mellitus (aOR 4.16; 95% confidence interval [CI] 2.58–6.70; p <0.001). Insulin omission was strongly associated with recurrent DKA (aOR 2.29; 95% CI 1.46–3.60; p <0.001). In contrast, baseline glycated hemoglobin and chronic kidney disease were not significantly associated with recurrence. Diabetic counseling during the first DKA admission did not reduce recurrent DKA. There were no significant differences in mortality (3.9% vs 6.2%, p = 0.524) or critical care admission rates (40.6% vs 38.7%, p = 0.718) between recurrent and first DKA episodes. Conclusion Recurrent DKA accounts for a substantial proportion of DKA admissions and is strongly associated with insulin omission and T1DM. Our findings suggest that recurrent DKA is driven predominantly by behavioral and adherencerelated factors, indicating the need for multidisciplinary interventions beyond standard inpatient counseling.
Diabetic Ketoacidosis ; Retrospective Studies

Introduction: The rising incidence of diabetic ketoacidosis (DKA) in type 2 diabetes mellitus (T2DM) represents a paradigm shift from its traditional recognition as a hallmark complication of type 1 diabetes mellitus (T1DM). However, contemporary data comparing clinical presentation, precipitating factors, and outcomes between these two populations remain limited. Methodology: In this retrospective observational study, all adult DKA admissions with T1DM or T2DM at a tertiary centre between 2001 and 2025 were studied. DKA was defined according to standard biochemical criteria. Electronic medical records were reviewed to extract demographic data, biochemical parameters, precipitating factors, management details, and clinical outcomes of all adult DKA admission in T1DM and T2DM. Patients aged <18 years or those with incomplete data were excluded. Results: A total of 601 DKA episodes were analyzed, comprising 130 (21.6%) in patients with T1DM and 471 (78.4%) in those with T2DM. Mean age was 26.9 ± 0.71 years for T1DM and 52.1 ± 0.7 years for T2DM. Gender distribution was balanced (male 48.3%, female 51.7%). Mean hemoglobin A1c (HbA1c) was 11.3 ± 0.3% in T1DM and 12.1 ± 0.2% in T2DM. Infection was the most common precipitating factor overall (69.0%), occurring more frequently in T2DM than in T1DM (74.7% vs. 56.2%), followed by medication non-adherence (62.4% vs. 43.8%). Significant differences were observed between groups in admission pH, bicarbonate (both p <0.001), blood ketones (p = 0.028), and HbA1c (p = 0.010), whereas anion gap (p = 0.056) and blood glucose levels (p = 0.755) did not differ significantly. Clinical outcomes were comparable with respect to intensive care unit (ICU) admission rates (40.0% in T1DM vs. 39.0% in T2DM, p = 0.779) and median resolution time (p = 0.462). However, the median length of hospital stay was significantly longer in T2DM (8.2 ± 0.32 vs. 5.4 ± 0.4 days; p <0.001). Overall mortality was 6.0%, with substantially higher mortality in T2DM compared to T1DM (7.4% vs. 0.8%, p = 0.013). Conclusion In this large regional series of adult DKA, most episodes occurred in T2DM. Despite similar ICU admission rates and time to resolution, T2DM was associated with more frequent infection-related precipitants, longer hospital stays, and higher mortality, underscoring the need for targeted preventive strategies in this population.
Adult ; Diabetes Mellitus, Type 1 ; Diabetic Ketoacidosis ; Diabetes Mellitus, Type 2

Introduction: Diabetic ketoacidosis (DKA) in pregnancy is an uncommon yet life-threatening emergency, with disproportionate risks to both mother and fetus. Pregnancy-specific physiological changes predispose patients to rapid metabolic decompensation, often with atypical presentations. Despite this, local data remain limited. We describe the clinical profile, precipitating factors, and outcomes of DKA in pregnancy in a tertiary centre, with emphasis on potentially preventable triggers. Cases: Nine pregnant patients with DKA were identified from a retrospective review of all cases admitted for DKA from 2002 to 2025. Mean age was 31.67 ± 5.20 years; all were Malay. The majority had type 2 diabetes mellitus (55.6%), followed by type 1 diabetes (33.3%) and latent autoimmune diabetes in adults (11.1%). The mean period of amenorrhea was 19.67 ± 12.62 weeks. Infection was the leading precipitant (44.4%), with additional triggers including insulin omission (22.2%), hyperemesis gravidarum, preterm labor, steroid exposure, and perioperative fasting. Most diagnoses were made in the emergency department (55.6%). Biochemical parameters reflected significant severity (mean bicarbonate 7.89 ± 2.98 mmol/L; anion gap 25.00 ± 5.81), with 88.9% classified as severe DKA. Intensive Care Unit (ICU) care was required in 77.8% of cases. The majority (77.8%) were admitted to the ICU unit, with a median time to resolution of 13.00 ± 12.00 hours (interquartile range [IQR]), and the median hospital length of stay was 7.00 ± 5.00 days (IQR). Complications during treatment included hypokalemia (33.3%), acute kidney injury (22.2%), and hypoglycemia (11.1%). Rebound DKA occurred in one-third of patients. All patients were discharged clinically stable. Outcome data demonstrated pregnancy loss in three cases and one preterm birth. Conclusion DKA in pregnancy remains a severe and resource-intensive condition. This series highlights missed opportunities in prevention, with modifiable precipitants such as infection and insulin omission commonly identified. The high severity at presentation suggests delays in recognition. Early detection, optimized metabolic care, and targeted preventive strategies are crucial to improving maternal and fetal outcomes.
Female ; Pregnancy ; Diabetic Ketoacidosis

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

INTRODUCTION: Achieving low-density lipoprotein cholesterol (LDL-C) levels is key to preventing atherosclerotic cardiovascular events. However, many high-risk cardiovascular patients still experience poor LDL-C goal attainment and receive suboptimal lipid-lowering therapy (LLT) prescriptions. Herein, we evaluated LLT prescription patterns, LDL-C goal attainment and cardiovascular mortality among this population group in Singapore. METHODS: This prospective observational cohort study included 555 patients with ischaemic heart disease (IHD) admitted to the hospital in 2020. The LLT prescriptions, corresponding LDL-C levels and cardiovascular outcomes were assessed over a 24-month period. RESULTS: Most participants were male (82.3%), with 48.5% identified as Chinese. High-intensity statin prescriptions increased from 45.4% at hospital admission to 87.1% at discharge and remained stable at approximately 80% at 6, 12, and 24 months post-discharge. Combination LLT prescriptions increased from 12.3% at discharge to 33.8% by 24 months. Ezetimibe was the most commonly prescribed second-line LLT (40.8%), followed by inclisiran (1.09%) and anti-proprotein convertase subtilisin/kexin type 9 monoclonal antibody therapies (0.87%). Over 24 months, LDL-C goal attainment rates were 22.1% for LDL-C < 1.4 mmol/L and 47.2% for LDL-C < 1.8 mmol/L. Multivariable Cox proportional hazards regression indicated that achieving LDL-C < 1.8 mmol/L goal was associated with a reduction in all-cause mortality at 24 months (hazard ratio 0.53, 95% confidence interval 0.30-0.94, P = 0.030). CONCLUSION Treatment gaps in lipid management persist in 80% of the study population, indicating that statin monotherapy alone is insufficient to achieve LDL-C goals. Greater efforts to improve LDL-C goal attainment rates in high-risk cardiovascular patients are imperative.
Humans ; Male ; Cholesterol, LDL/blood* ; Female ; Myocardial Ischemia/drug therapy* ; Middle Aged ; Prospective Studies ; Aged ; Singapore/epidemiology* ; Hydroxymethylglutaryl-CoA Reductase Inhibitors/therapeutic use* ; Ezetimibe/therapeutic use* ; Anticholesteremic Agents/therapeutic use* ; Treatment Outcome

In 2023, the Republic of Korea’s Korea Disease Control and Prevention Agency (KDCA) enhanced its event-based surveillance practices by using the World Health Organization’s (WHO) Epidemic Intelligence from Open Sources (EIOS) to actively screen and share information about potential public health threats to the country. This report describes the preliminary assessment of the results of implementing these enhanced event-based surveillance activities from June to October 2023. During this period, 425 (0.4%) events were detected globally by the KDCA from 99 945 media articles, with the highest frequency reported in Asia (185, 43.5%) and North America (81, 19.1%). The most frequently reported diseases or conditions were dengue fever (111, 26.1%) and mpox (32, 7.5%). Eight events were detected early by the KDCA using EIOS before being officially listed on WHO’s Event Information Site (EIS) or in Disease Outbreak News (DON), with an average interval of 20 days (range: 5–41) between the detection date and posting on EIS or DON. Thus, EIOS is efficient in aiding early detection of potential public health threats at the national level. This finding highlights the importance of sustaining international cooperation and support to enhance surveillance capabilities in resource-limited settings and expanding the scope of EIOS, including by incorporating additional sources and sources in additional languages, reducing noise. However, as the current report is based on a descriptive analysis, in the future a systematic evaluation of event-based surveillance using EIOS to identify relevant attributes will need to be conducted.

Background: School food service workers are highly likely to develop heat-related illnesses because of their work environment. However, studies that have examined the risk of heat-related illnesses among them are limited. The purpose of this study was to investigate the status of heat exposure, implementation of heat wave countermeasures, and prevalence of heat-related illness symptoms among school food service workers in Korea, and to explore the relationship between them. Methods: A cross-sectional study was conducted through an online survey of school food service workers from May 25 to June 12, 2023, via three labor unions. We analyzed 6,244 valid responses. We assessed general characteristics, heat-related illness symptoms (heat rash, heat cramps, heat edema, heat exhaustion, heat syncope), duration of heat exposure during heat waves, and heat wave preventive measures. Multiple logistic regression analyses were performed, with adjustments for age, occupation, hypertension, diabetes, and school type. Results: More than one-third of school food service workers reported heat exposure between May and September exceeding 4 hours daily, and 94.6% experienced at least one heat-related illness symptom during the last year. A dose-response relationship was observed between heat exposure duration and heat-related illness symptoms (p for trend < 0.001). School food service workers who did not have increased rest periods or did not reduce high-heat prepared foods showed significantly higher odds ratios for heat-related illness symptoms. Conclusions School food service workers experience substantial heat exposure and a high prevalence of heat-related illness symptoms. The risk of heat-related illness symptoms was associated with extended duration of heat exposure. Increasing rest periods and reducing high-heat food preparation were effective preventive measures. These findings underscore the need for improved heat exposure management and implementation of effective preventive measures to protect the health of school food service workers, with particular attention to appropriate rest periods.