Objective:To investigate the risk factors for patients with hypertriglyceridemia-related acute pancreatitis (HTG-AP) developing into severe acute pancreatitis or experiencing organ failure.Methods:This retrospective cohort study collected clinical data from 2 429 patients diagnosed with acute pancreatitis from five hospitals in China between January 2019 and December 2023 using a pre-designed data collection form. The cohort included 1 516 males and 913 females,with an age of (50.2±16.5)years(range: 11 to 99 years). Among them,353 patients (16.1%) had HTG-AP,while 1 846 (83.9%) had non-HTG-AP. HTG-AP was defined as serum triglyceride levels>500 mg/dl with other etiologies excluded. Intergroup comparisons were performed using t-tests,Mann-Whitney U test or χ2 tests,respectively. Univariate and multivariate logistic regression analyses were conducted to assess risk factors for severe acute pancreatitis after adjusting for potential confounders,and a predictive model was developed and validated. Results:Compared with other etiologies,HTG-AP patients had a higher risk of progressing to SAP ( OR=1.415,95% CI: 0.866 to 2.312, P=0.017) and organ failure ( OR=1.256,95% CI: 1.015 to 1.554, P=0.036). Among HTG-AP patients,risk factors for SAP included body mass index ( OR=1.856,95% CI: 1.742 to 1.987, P=0.033),fasting blood glucose ( OR=1.128,95% CI: 1.036 to 1.229, P=0.006),white blood cell count( OR=1.162,95% CI: 1.055 to 1.281, P=0.002),and the presence of pleural effusion ( OR=13.151,95% CI: 4.330 to 19.946, P<0.01). A nomogram prediction model for SAP in HTG-AP was constructed based on these risk factors,demonstrating good discriminative ability with area under the curve values of 0.877 in the training set and 0.894 in the validation set,along with satisfactory calibration. Conclusions:HTG-AP patients are at higher risk of developing SAP and organ failure. The risk prediction model incorporating body mass index,fasting blood glucose,white blood cell count,and pleural effusion shows good predictive value for SAP.

Objective:To investigate the risk factors for patients with hypertriglyceridemia-related acute pancreatitis (HTG-AP) developing into severe acute pancreatitis or experiencing organ failure.Methods:This retrospective cohort study collected clinical data from 2 429 patients diagnosed with acute pancreatitis from five hospitals in China between January 2019 and December 2023 using a pre-designed data collection form. The cohort included 1 516 males and 913 females,with an age of (50.2±16.5)years(range: 11 to 99 years). Among them,353 patients (16.1%) had HTG-AP,while 1 846 (83.9%) had non-HTG-AP. HTG-AP was defined as serum triglyceride levels>500 mg/dl with other etiologies excluded. Intergroup comparisons were performed using t-tests,Mann-Whitney U test or χ2 tests,respectively. Univariate and multivariate logistic regression analyses were conducted to assess risk factors for severe acute pancreatitis after adjusting for potential confounders,and a predictive model was developed and validated. Results:Compared with other etiologies,HTG-AP patients had a higher risk of progressing to SAP ( OR=1.415,95% CI: 0.866 to 2.312, P=0.017) and organ failure ( OR=1.256,95% CI: 1.015 to 1.554, P=0.036). Among HTG-AP patients,risk factors for SAP included body mass index ( OR=1.856,95% CI: 1.742 to 1.987, P=0.033),fasting blood glucose ( OR=1.128,95% CI: 1.036 to 1.229, P=0.006),white blood cell count( OR=1.162,95% CI: 1.055 to 1.281, P=0.002),and the presence of pleural effusion ( OR=13.151,95% CI: 4.330 to 19.946, P<0.01). A nomogram prediction model for SAP in HTG-AP was constructed based on these risk factors,demonstrating good discriminative ability with area under the curve values of 0.877 in the training set and 0.894 in the validation set,along with satisfactory calibration. Conclusions:HTG-AP patients are at higher risk of developing SAP and organ failure. The risk prediction model incorporating body mass index,fasting blood glucose,white blood cell count,and pleural effusion shows good predictive value for SAP.

Objective To explore the clinical application values of the score for the targeting of atrial fibrillation (STAF) and left atrial diameter (L),age (A),diagnosis of stroke or TIA (D),and smoking one year before onset (S) (LADS) and acute stroke atrial fibrillation score (ASAS) (including 4 indicators:age,National Institutes of Health Stroke Scale [NIHSS] score,left atrial enlargement,and vascular etiology) in the screening of patients with ischemic stroke complicated with atrial fibrillation.Methods From April 2016 to April 2017,the clinical and imaging data of 317 patients with acute ischemic stroke admitted to the Department of Neurology,the Second Affiliated Hospital of Guangzhou Medical University were analyzed retrospectively.The patients were divided into either an atrial fibrillation group (n =56) or a non-atrial fibrillation group (n =261) according to whether they had atrial fibrillation or not.The relative clinical data including gender,age,past history,NIHSS score,echocardiographic results,and cerebrovascular assessment were collected.STAF,LADS,and ASAS scores were performed in all patients,the receiver operating characteristic (ROC) curve was drawn,the area under the curve was calculated,and the sensitivity,specificity,and accuracy of the 3 methods for predicting ischemic stroke with atrial fibrillation were compared.Results Compared with the non-atrial fibrillation group,the differences were statistically significant in age (69 ± 11 years vs.62 ± 12 years),NIHSS scores (8.2 ± 1.3 vs.4.4 ± 0.3),and internal diameter of left atrium (42.3 ± 6.8 mm vs.31.7 ± 2.5 mm) in the atrial fibrillation group (t =2.99,3.38,and 6.32,respectively,all P ＜ 0.01).The area under the curve of STAF score for the diagnosis of ischemic stroke complicated with atrial fibrillation was 0.801.The optimal cut-off point was STAF ≥5,the sensitivity was 58.9％,specificity was 81.2％,and accuracy was 77.3％.The area under the curve of LADS score for diagnosis of atrial fibrillation was 0.846,the optimal cut-off point was LADS ≥ 4,the sensitivity was 66.1％,specificity 83.5 ％,and accuracy was 80.4％.The area under the curve of pr (ASAS) score for diagnosis of ischemic stroke complicated with atrial fibrillation was 0.835,the optimal cut-off point was pr (ASAS) ≥0.09,the sensitivity was 85.7％,specificity 56.7％,and accuracy was 61.8％.The sensitivity,specificity and accuracy of the three scoring methods were statistically significant (x2 =10.308,59.685,and 32.054,respectively,all P ＜ 0.01).Conclusion The accuracy of LADS ≥ 4 is the highest in screening of acute ischemic stroke complicated with atrial fibrillation

Objective To investigate the carrying rate and genotype of thalassemia in the household population of Yantian dis-trict in Shenzhen city so as to provide the scientific basis for Thalassemia genetic counseling,prenatal diagnosis and prevention plan. Methods 3 mL of anticoagulation blood by EDTA-K2 was extract for conducting the whole blood cells analysis.With the mean cor-puscular volume(MCV)<80 fL as the preliminary screening test,then the suspected cases were performed the DNA extraction for conducting the gene test.In theα-thalassemia detection,4 pairs of PCR primer were used to amplify in the same reaction system and the results were analyzed according to the band after the agarose gel electrophoresis.In theβ-thalassemia detection,the PCR product sequencing was adopted.Results After the preliminary screening,4 657 suspected cases all were performed the gene detection.510 carriers with thalassemia gene were detected out with the thalassemia gene carrying rate of 10.95%,including 389 cases carryingα-thalassemia gene with the carrying rate of 8.35%,which was dominated by α-3.7,α-4.2 and α-SEA,and 121 cases carrying βthalassemia gene with the carrying rate of 2.59%,which was dominated by CD41.42,LVS-Ⅱ-654,CD17 and CD71.Conclusion The carrying rate of thalassemia gene in the household population of Yantian district was 10.95%,which is closed to that in other districts within Guangdong province,all of the 8 detected genotypes of thalassemia are the common types.