Aim To develop and validate a dynamic nomogram to predict the risk of no-reflow phenomenon(NRP)after percutaneous coronary intervention(PCI)in patients with ST-segment elevation myocardial infarction(STE-MI)by constructing HALP based on haemoglobin(Hb),albumin(Alb),lymphocytes(LYM),and platelets(PLT).Methods A retrospective analysis of 449 STEMI patients admitted to Nanyang Central Hospital from January 2022 to Janu-ary 2024 was divided into 145 cases in the NRP group and 304 cases in the normal reflow group according to whether the patients developed NRP after surgery.HALP was calculated based on Hb,Alb,LYM and PLT observations.Independ-ent influences on NRP risk were determined by multivariate Logistic regression analysis.Dynamic nomogram of NRP risk after PCI in STEMI patients were developed using the R language correlation software package.Results The incidence of NRP was 32.3％(145/449)among 449 patients with NRP.The HALP of patients in the NRP group was lower than that of patients in the normal reflow group(P＜0.05).The area under the curve(AUC)of HALP for diagno-sis of NRP was 0.880(0.847-0.909),and the Kappa coefficient of its optimal cutoff value ≤3.04 versus patients with accurate diagnosis of NRP was 0.612.The results of multivariate Logistic regression analysis showed that age,diabetes mellitus,and high sensitivity C-reactive protein(hs-CRP)were independent risk factors for NRP after PCI in STEMI pa-tients(P＜0.05),and left ventricular ejection fraction(LVEF)and HALP were independent protective factors(P＜0.05).A dynamic nomogram(https://xz0311.shinyapps.io/DynNamicNRP/)based on HALP combined with age,di-abetes,LVEF,and hs-CRP was effective in predicting the risk of post-PCI NRP in STEM1 patients.Conclusion HALP is more effective than traditional risk factors in predicting NRP risk in STEMI patients after PCI,and the dynamic nomogram developed based on HALP will help develop personalized treatment strategies for patients with high NRP risk.

Objective:To explore the application effect of transitional care based on Siebens domain management model in patients with atrial fibrillation.Methods:Using the convenient sampling method, a total of 150 atrial fibrillation patients who were admitted to Nanyang Central Hospital from October 2021 to December 2022 were selected as the research objects. Patients were divided into the study group and the control group using the random number table method, with 75 cases in each group. The control group received routine transitional care, while the study group received transitional care based on the Siebens domain management model. The intervention effect was evaluated using Morisky Medication Adherence Scale and Atrial Fibrillation Self Care Ability Scale.Results:There was no statistically significant difference in scores of Morisky Medication Adherence Scale and Atrial Fibrillation Self Care Ability Scale of patients between the two groups before intervention ( P>0.05). After intervention, scores of Morisky Medication Adherence Scale and Atrial Fibrillation Self Care Ability Scale of patients in the study group were higher than those of the control group, and the differences were statistically significant ( P<0.05) . Conclusions:Transitional care based on Siebens domain management model can improve medication adherence and self-care ability of atrial fibrillation patients.