Objective We investigated the clinical features and the potential risk factors of malnutrition in patients with chronic heart failure(CHF),and constructed the risk prediction model of malnutrition.Methods A total of459 CHF patients admitted between January 2023 and July 2024 were classified into a normal nutrition group and a malnutrition group based on the geriatric Nutrition Risk Index(GNRI)score upon admission.The patient-related data were gathered,and single-variable and multi-variable logistic analyses were first carried out to identify the risk factors associated with the malnutrition risk.Subsequently,the stepwise regression approach was employed to define the inclusion criteria and construct a malnutrition nomogram model for CHF patients.The diagnostic efficacy and calibration of this model were appraised using the ROC curve and calibration curve,and its clinical utility was assessed via the clinical decision curve.A P value less than 0.05 signified statistically significant differences.Results Anxiety(OR=1.1902,95%CI:1.0217～1.3865),urea nitrogen(OR=1.4842,95%CI:1.1187～1.9691),low body weight(OR=0.8463,95%CI:0.7852～0.9121),and low albumin(OR=0.0467,95%CI:0.0172～0.1268)were risk factors for malnutrition.The optimal model inclusion factors were selected by stepwise regression,including:Body weight,7 items of Generalized Anxiety Disorder Scale(GAD-7),urea nitrogen,uric acid,albumin,total cholesterol,high density lipoprotein cholesterol(HDL-L),low density lipoprotein cholesterol(LDL-L),D-dimer.The area under the ROC curve(AUC)of the column chart model based on the above factors is 0.996(95%CI:0.971～0.978),with a sensitivity of 97.8%and a specificity of 97.1%.The C-index validated internally in the calibration curve was 0.824.The calibration chart and validation results demonstrate good consis-tency and applicability.Conclusion The column chart prediction model created in this study based on nine factors including body weight,GAD-7,urea nitrogen,uric acid,albumin,total cholesterol,HDL-L,LDL-L,and D-dimer had good calibration and prediction performance,and had good clinical practicality,which was helpful for clinicians to make diagnosis and treatment decisions for malnutrition in CHF patients.

Objective We investigated the clinical features and the potential risk factors of malnutrition in patients with chronic heart failure(CHF),and constructed the risk prediction model of malnutrition.Methods A total of459 CHF patients admitted between January 2023 and July 2024 were classified into a normal nutrition group and a malnutrition group based on the geriatric Nutrition Risk Index(GNRI)score upon admission.The patient-related data were gathered,and single-variable and multi-variable logistic analyses were first carried out to identify the risk factors associated with the malnutrition risk.Subsequently,the stepwise regression approach was employed to define the inclusion criteria and construct a malnutrition nomogram model for CHF patients.The diagnostic efficacy and calibration of this model were appraised using the ROC curve and calibration curve,and its clinical utility was assessed via the clinical decision curve.A P value less than 0.05 signified statistically significant differences.Results Anxiety(OR=1.1902,95%CI:1.0217～1.3865),urea nitrogen(OR=1.4842,95%CI:1.1187～1.9691),low body weight(OR=0.8463,95%CI:0.7852～0.9121),and low albumin(OR=0.0467,95%CI:0.0172～0.1268)were risk factors for malnutrition.The optimal model inclusion factors were selected by stepwise regression,including:Body weight,7 items of Generalized Anxiety Disorder Scale(GAD-7),urea nitrogen,uric acid,albumin,total cholesterol,high density lipoprotein cholesterol(HDL-L),low density lipoprotein cholesterol(LDL-L),D-dimer.The area under the ROC curve(AUC)of the column chart model based on the above factors is 0.996(95%CI:0.971～0.978),with a sensitivity of 97.8%and a specificity of 97.1%.The C-index validated internally in the calibration curve was 0.824.The calibration chart and validation results demonstrate good consis-tency and applicability.Conclusion The column chart prediction model created in this study based on nine factors including body weight,GAD-7,urea nitrogen,uric acid,albumin,total cholesterol,HDL-L,LDL-L,and D-dimer had good calibration and prediction performance,and had good clinical practicality,which was helpful for clinicians to make diagnosis and treatment decisions for malnutrition in CHF patients.

AIM:To investigate the impact of aquaporin 4(AQP4)expression inhibition on autophagy and apoptosis in a mouse model of cerebral ischemia-reperfusion(I/R)injury,and to elucidate its underlying mechanism.METHODS:Cerebral I/R injury was induced in mice via transient middle cerebral artery occlusion(tMCAO).Totally 60 mice were randomly divided into sham group,I/R group,AQP4 inhibition group,and 3-methyladenine(3-MA)group,with 15 mice in each group.Among them,the mice in sham and I/R groups received intraperitoneal injections of normal saline,while those in AQP4 inhibition group and 3-MA group received intraperitoneal injections of AER-271(2 mg·kg-1·d-1)and AER-271+3-MA(2 mg·kg-1·d-1)for 3 d,respectively,once per day.Longa score was adopted to assess the neu-rological function,and to record changes in body weight.Cerebral infarction volume and histopathological alterations were evaluated using hematoxylin-eosin staining.Western blot analysis was performed to determine the levels of AQP4,LC3-Ⅱ,P62 and cleaved caspase-3,while the LC3-Ⅱ,P62,cleaved caspase-3 and NeuN(neuronal marker)colocalization and expression assessment were conducted with immunofluorescence.RESULTS:The mice in I/R and AQP4 inhibition groups exhibited extensive cerebral infarction,cerebral edema,and elevated Longa scores.However,in comparision to I/R group,the mice in AQP4 inhibition group showed significantly reduced cerebral infarct volume,cerebral edema vol-ume,and Longa score(P<0.05).Additionally,in contrast to sham group,the mice in I/R group displayed increased ex-pression of AQP4,LC3-Ⅱ and cleaved caspase-3(P<0.01),accompanied by decreased body weight and P62 expression(P<0.05 or P<0.01).Furthermore,compared with I/R group,the mice in both AQP4 inhibition group and 3-MA group demonstrated a decrease in the expression levels of AQP4,LC3-Ⅱ and cleaved caspase-3(P<0.05 or P<0.01),along with increased body weight and P62 expression(P<0.05 or P<0.01).Nonetheless,no significant differences were ob-served between AQP4 inhibition group and 3-MA group regarding Longa score,cerebral infarct volume,body weight,and the expression of AQP4,LC3-Ⅱ,cleaved caspase-3 and P62.CONCLUSION:Inhibition of AQP4 expression signifi-cantly reduces cerebral infarction area and nerve injury severity in tMCAO mice.Moreover,AQP4 expression inhibition decelerates autophagy and apoptosis after cerebral infarction,with the additional autophagy inhibitor showing no notable impact on the protective effect of AQP4 inhibition.

Omega-3 polyunsaturated fatty acids are a kind of nutrients mainly derived from deep-sea fish, and their role in cardiocerebrovascular diseases has been extensively studied. This article reviews the correlation between omega-3 polyunsaturated fatty acids and the risk and outcome of ischemic stroke and its mechanism of action.