Development and validation of a deep learning model to screen hypokalemia from electrocardiogram in emergency patients / 中华医学杂志(英文版)

BACKGROUND@#A deep learning model (DLM) that enables non-invasive hypokalemia screening from an electrocardiogram (ECG) may improve the detection of this life-threatening condition. This study aimed to develop and evaluate the performance of a DLM for the detection of hypokalemia from the ECGs of emergency patients.@*METHODS@#We used a total of 9908 ECG data from emergency patients who were admitted at the Second Affiliated Hospital of Nanchang University, Jiangxi, China, from September 2017 to October 2020. The DLM was trained using 12 ECG leads (lead I, II, III, aVR, aVL, aVF, and V1-6) to detect patients with serum potassium concentrations <3.5 mmol/L and was validated using retrospective data from the Jiangling branch of the Second Affiliated Hospital of Nanchang University. The blood draw was completed within 10 min before and after the ECG examination, and there was no new or ongoing infusion during this period.@*RESULTS@#We used 6904 ECGs and 1726 ECGs as development and internal validation data sets, respectively. In addition, 1278 ECGs from the Jiangling branch of the Second Affiliated Hospital of Nanchang University were used as external validation data sets. Using 12 ECG leads (leads I, II, III, aVR, aVL, aVF, and V1-6), the area under the receiver operating characteristic curve (AUC) of the DLM was 0.80 (95% confidence interval [CI]: 0.77-0.82) for the internal validation data set. Using an optimal operating point yielded a sensitivity of 71.4% and a specificity of 77.1%. Using the same 12 ECG leads, the external validation data set resulted in an AUC for the DLM of 0.77 (95% CI: 0.75-0.79). Using an optimal operating point yielded a sensitivity of 70.0% and a specificity of 69.1%.@*CONCLUSIONS@#In this study, using 12 ECG leads, a DLM detected hypokalemia in emergency patients with an AUC of 0.77 to 0.80. Artificial intelligence could be used to analyze an ECG to quickly screen for hypokalemia.

Pharmacokinetics and metabolism study of isoboldine, a major bioactive component from Radix Linderae in male rats by UPLC-MS/MS.

ETHNOPHARMACOLOGICAL RELEVANCE: Isoboldine is one of the major bioactive constituents in the total alkaloids from Radix Linderae (TARL) which could effectively alleviate inflammation and joints destruction in mouse collagen-induced arthritis. To better understand its pharmacological activities, we need to determine its pharmacokinetic and metabolic profiles. MATERIALS AND METHODS: In this study, a sensitive and simple UPLC-MS/MS method was developed and validated for determination of isoboldine in rat plasma. Isoboldine in plasma was recovered by liquid-liquid extraction using 1 mL of methyl tert-butyl ether. Chromatographic separation was performed on a C18 column at 45°C, with a gradient elution consisting of acetonitrile and water containing 0.1% (v/v) formic acid at a flow rate of 0.3 mL/min. The detection was performed on an electrospray triple-quadrupole MS/MS by positive ion multiple-reaction monitoring mode. This newly developed method was successfully applied to a pharmacokinetic study after oral and intravenous dosing in rats. For metabolites identification, isoboldine was orally administered to rats and the metabolite in plasma, bile, urine and feces were characterized by the established UPLC-MS/MS method. RESULTS: Good linearity (r(2)>0.9956) was achieved in a concentration range of 4.8-2400 ng/mL with a lower limit of quantification of 4.8 ng/mL for isoboldine. The intra- and inter-day precisions of the assay were 1.7-5.1% and 2.2-4.4% relative standard deviation with an accuracy of 91.3-102.3%. A total of five phase II metabolites in rat plasma, bile, urine and feces were characterized by comparing retention time in UPLC, and by molecular mass and fragmentation pattern of the metabolites by mass spectrometry with those of isoboldine. CONCLUSION: isoboldine has extremely low oral bioavailability due to the strong first-pass effect by the rats, and glucuronidation and sulfonation were involved in metabolic pathways of isoboldine in rats. These results have paved the way for further clarifying therapeutic ingredients and provided new knowledge regarding pharmacokinetic features of this category of isoquinoline alkaloids.