W. Peamyao, T. Lokeskrawee, S. Lawanaskol, J. Patumanond, S. Chanlaor, W. Bumrungpagdee, et al. (2025). Predictive Factors for Diagnosing Diabetic Ketoacidosis or Simple Hyperglycemia in Adults With High Blood Glucose: The "1-DKA Alert" Study. Journal of clinical medicine research, 17(3), 164-173. https://doi.org/10.14740/jocmr6180

PubMed 40115837

[Abstract]
BACKGROUND: Hyperglycemia is commonly encountered in the Emergency Departments, necessitating the differential diagnosis between diabetic ketoacidosis (DKA) and simple hyperglycemia, as the treatment and prognosis differ significantly. In clinical practice, it is essential to investigate DKA in all patients; however, the final diagnosis of actual DKA is found in only 1-5% of these cases, resulting in unnecessary costs. This study aimed to develop an application for predicting the probability of DKA in patients with capillary blood glucose levels exceeding 250 mg/dL in the Emergency Department.

METHODS: This study was conducted as diagnostic prediction research, employing a retrospective observational delayed-type cross-sectional design. Data were collected from patients with capillary blood glucose levels exceeding 250 mg/dL between January and April 2023. The predictive variables were available at the time of prediction. Analysis was performed using multivariable risk ratio regression analysis, with results reported as multivariable risk ratios. The area under the receiver operating characteristic (AuROC) curve was calculated. Internal validation was performed using bootstrapping and calibration plots. An application named "1-DKA Alert" was developed to predict the probability of DKA for use in real-world clinical settings.

RESULTS: The study included 274 adult patients, of whom 52.9% were female, with an average age of 59 years. Predictive factors for DKA included initial capillary blood glucose, type of diabetes mellitus, insulin usage, poor compliance, respiratory rate, and suspected infection. These variables were readily available in clinical practice and yielded an AuROC of 0.8777 (95% confidence interval (CI): 0.8294 - 0.9259). Bootstrapping internal validation demonstrated an AuROC of 0.8770 and a shrinkage factor of 0.991.

CONCLUSIONS: The "1-DKA Alert" demonstrates excellent discriminative ability, and the model is valid, suggesting its potential for use in clinical practice. However, further studies for external validation are necessary.