Objective:To identify the relevant factors for the first-course remission of acute myeloid leukemia (AML) and to develop a predictive model as well as assess its predictive capability.Methods:Clinical data of 749 patients newly diagnosed with AML admitted to the Department of Hematology, the First Affiliated Hospital, Zhejiang University, School of Medicine from January 1, 2019, to April 30, 2023, were collected and randomly divided into training and validation sets. Multivariate logistic regression analysis was conducted to determine variables associated with complete remission in the first course of induction therapy, and a predictive model was established based on these variables. The receiver operating characteristic (ROC) curve of the predictive model was plotted, and the area under the curve (AUC) was calculated.Results:The indicators predicting the first remission course included peripheral blood white blood cell count during onset, CBF::MYH11 fusion gene, CEBPA bZIP region mutation, myelodysplastic syndrome-related gene mutation, and induction chemotherapy regimen selection as independent factors for the first remission course. The model’s area under the training and validation curves was 0.738 (95% CI: 0.696-0.780) and 0.726 (95% CI: 0.650-0.801), respectively. The Hosmer-Lemeshow test results yielded P-values of 0.993 and 0.335, respectively. Conclusion:In this study, the developed model demonstrates a strong predictive capability for the efficacy of the first course of patients with AML, providing valuable guidance to clinicians in assessing patient prognosis and selecting appropriate treatment strategies.

Objective:To identify the relevant factors for the first-course remission of acute myeloid leukemia (AML) and to develop a predictive model as well as assess its predictive capability.Methods:Clinical data of 749 patients newly diagnosed with AML admitted to the Department of Hematology, the First Affiliated Hospital, Zhejiang University, School of Medicine from January 1, 2019, to April 30, 2023, were collected and randomly divided into training and validation sets. Multivariate logistic regression analysis was conducted to determine variables associated with complete remission in the first course of induction therapy, and a predictive model was established based on these variables. The receiver operating characteristic (ROC) curve of the predictive model was plotted, and the area under the curve (AUC) was calculated.Results:The indicators predicting the first remission course included peripheral blood white blood cell count during onset, CBF::MYH11 fusion gene, CEBPA bZIP region mutation, myelodysplastic syndrome-related gene mutation, and induction chemotherapy regimen selection as independent factors for the first remission course. The model’s area under the training and validation curves was 0.738 (95% CI: 0.696-0.780) and 0.726 (95% CI: 0.650-0.801), respectively. The Hosmer-Lemeshow test results yielded P-values of 0.993 and 0.335, respectively. Conclusion:In this study, the developed model demonstrates a strong predictive capability for the efficacy of the first course of patients with AML, providing valuable guidance to clinicians in assessing patient prognosis and selecting appropriate treatment strategies.

At present, most of the common medical clothes in clinic are uniform medical clothes, but there is no special clothes for patients in intensive care unit (ICU). In recent years, with the extensive application of critical ultrasound in the field of critical medicine, it is obviously difficult to meet the clinical needs on traditional patients' clothes. Guangdong Provincial People's Hospital designed a patient's clothing for critical ultrasound examination. The left/right chest, lateral chest, groin and abdomen of the patient's clothing body were covered with cloth and marked areas. When critically ill patients need to be examined by ultrasound and electrocardiogram, the site can be quickly located only by removing the cloth. At the same time, it can protect patients' privacy, avoid aggravating the condition due to cold, increase patients' comfort in clothing, and also facilitate medical care. It is worthy popularizing in clinic because of its practicability and novel design.

Objective To explore the association of apoB gene polymorphisms with dyslipidemia and lipid levels in Xinjiang Shihezi Han Chinese. Methods 150 dyslipidemia patients and 150 normal pople were involved in this study. EcoRI and XbaI polymorphisms of apolipoprotein B was analyzed by PCR-restriction fragment length polymorphism. The levels of plasma total cholesterol, triglyceride, low density lipoprotein cholesterol, high density lipoprotein cholesterol, apoAI and apoB were determined. Results The frequency of E + E -/E - E - genotype and E-Allele(37.3% and 19% ) in dyslipidemia group was significantly higher than that in controls( 12. 7% and 6. 3% ). The levels of TC, TG and LDL-C in the E +E -/E - E - gene type were significantly higher than those of the E + E + gene type in each group ( P ＜0. 01 ). The frequency of X + X -/X + X + genotype and X + Allele( 20. 7% and 1 1% ) in dyslipidemia group was significantly higher than that in controls (8% and 4% ). The levels ofTC, TG, LDL-C and apoB in the X + X -/X + X + gene type patients were significantly higher than those in the X - X - gene type patients in every group ( P ＜ 0. 05 ). Conclusion The EcoRI and XbaI polymorphism of ApoB gene was related to dyslipidemia in population of Xinjiang Shihezi Han Chinese, and the E - and X + Allele may be the genetic risk factors for dyslipidemia.