Objective To develop a decision support system for clinical nursing plans based on nursing diagno-sis and explore its application effects,in order to provide references for optimizing the clinical nursing process and improving the quality of nursing.Methods A multidisciplinary research team was established to construct a clini-cal nursing plan decision support system framework from 3 aspects,namely nursing diagnosis,nursing interventions,and outcome tracking.The system built a clinical nursing diagnosis decision knowledge base through 3 dimensions,namely basic nursing diagnoses,specialty disease nursing diagnoses,and nursing-related technical diagnoses.Deep learning-based artificial intelligence capture technology was developed to achieve intelligent matching and generate clinical nursing plan forms.Implemented in a tertiary hospital in Yichang City,Hubei Province,a control group(June to August 2024)and an experimental group(October to December 2024)were compared regarding nursing diagnosis implementation rate,nursing plan documentation accuracy,and clinical nursing quality scores.Results This research showed a significant improvements for nursing diagnosis implementation rate increased from 94.88％to 97.25％,and nursing plan documentation accuracy improved from 90.38％to 95.33％.Compared with the control group,the experimental group demonstrated statistically significant enhancements in deep vein thrombosis preven-tion,fall prevention,pressure injury management,unplanned extubation control,bloodstream infection control,catheter-related infection prevention,and key specialty nursing quality indicators(all P＜0.05).Conclusion The nursing di-agnosis-based clinical decision support system effectively improves nurses'diagnostic implementation rates,enhances documentation accuracy of nursing plans,and elevates overall clinical nursing quality.

Debates persist regarding the efficacy and safety of azvudine, particularly its real-world outcomes. This study involved patients aged ≥60 years who were admitted to 25 hospitals in mainland China with confirmed SARS-CoV-2 infection between December 1, 2022, and February 28, 2023. Efficacy outcomes were all-cause mortality during hospitalization, the proportion of patients discharged with recovery, time to nucleic acid-negative conversion (T _NANC), time to symptom improvement (T _SI), and time of hospital stay (T _HS). Safety was also assessed. Among the 5884 participants identified, 1999 received azvudine, and 1999 matched controls were included after exclusion and propensity score matching. Azvudine recipients exhibited lower all-cause mortality compared with controls in the overall population (13.3% vs. 17.1%, RR, 0.78; 95% CI, 0.67-0.90; P = 0.001) and in the severe subgroup (25.7% vs. 33.7%; RR, 0.76; 95% CI, 0.66-0.88; P < 0.001). A higher proportion of patients discharged with recovery, and a shorter T _NANC were associated with azvudine recipients, especially in the severe subgroup. The incidence of adverse events in azvudine recipients was comparable to that in the control group (2.3% vs. 1.7%, P = 0.170). In conclusion, azvudine showed efficacy and safety in older patients hospitalized with COVID-19 during the SARS-CoV-2 omicron wave in China.

Objective To observe the clinical efficacy of toripalimab combined with bronchial ar-terial chemoembolization(BACE)and intensity-modulated radiotherapy(IMRT)in advanced lung cancer.Methods A prospective single-arm trial was conducted in 104 patients with programmed death-ligand 1(PD-L1)-positive,driver gene-negative non-small cell lung cancer(NSCLC)in stages of Ⅲ B to Ⅳ admitted to the First People's Hospital of Guangyuan City of Sichuan Province.All patients received toripalimab combined with BACE and IMRT.Clinical efficacy,symptom improve-ment time,tumor biomarker levels[carcinoembryonic antigen(CEA),carbohydrate antigen 199(CA199),cytokeratin 19 fragment(CYFRA21-1),neuron-specific enolase(NSE)],T-lymphocyte subsets(CD3+,CD4+,CD4+/CD8+),survival outcomes,and adverse events were analyzed.Results Among 102 patients,the objective response rate(ORR)was 75.49％,disease control rate(DCR)was 90.20％,survival rate was 68.63％,and 12-month progression-free survival rate was 62.75％.The overall incidence of adverse events of any grade was 72.55％.Post-BACE,post-IMRT,and post-toripalimab treatment levels of CEA,CYFRA21-1,CA199,and NSE were significantly lower than baseline data(P＜0.05),with the lowest levels observed after toripalimab treatment compared to post-BACE and post-IMRT(P＜0.05).CD3+,CD4+,and CD4+/CD8+decreased after BACE,IMRT and toripalimab therapy,but they were increased following toripalimab therapy compared with the other two therapies(P＜0.05).Conclusion Toripalimab combined with BACE and IMRT demonstrates significant clinical efficacy and acceptable tolerability in PD-L1-positive,driver gene-negative NSCLC in stages of ⅢB to Ⅳ,serving as a preferred consolidation regimen after unresect-able chemoradiotherapy.

Objective:To investigate the association between estimated cumulative low-density lipoprotein cholesterol (LDL-C) exposure and the severity of coronary artery disease and long-term adverse cardiovascular and cerebrovascular events (MACCE) in patients with acute coronary syndrome (ACS).Methods:The subjects were from the PROMISE study. This study was a prospective cohort study led by Fuwai Hospital, Chinese Academy of Medical Sciences, with participation from eight regional tertiary hospitals as sub-centers, and enrolled 18 701 patients with confirmed coronary heart disease between January 2015 and May 2019. Among them, 8 429 patients with ACS were included in this study. The estimated cumulative LDL-C exposure was calculated by multiplying LDL-C by age. Participants were then divided into four groups based on quartiles. Baseline data and coronary angiography data were collected, and participants were followed for 2 years. The primary endpoint was MACCE, which was composed of all-cause death, cardiac death, myocardial infarction, revascularization, and stroke. Spearman correlation analysis was used to estimate the correlation between cumulative LDL-C exposure and the severity of coronary artery disease. The differences in MACCE among the four groups were compared, and multivariate Cox regression was used to divide the estimated cumulative exposure LDL-C into two groups, three groups, and four groups to analyze its relationship with MACCE.Results:The 8 429 ACS patients included in the study had an age of (60.9±11.4) years, with 1 951(23.1%) females. Spearman correlation analysis revealed that estimated cumulative LDL-C exposure was positively associated with the preoperative SYNTAX score, three-vessel lesions disease, left main disease, and the number of target lesions (correlation coefficients r=0.14, 0.10, 0.04 and 0.03, respectively, with all P<0.05). The 2-year follow-up results indicated that the incidence rates of MACCE, all-cause death, cardiac death, myocardial infarction, and stroke in ACS patients grouped by different levels of estimated cumulative LDL-C exposure were statistically significant (all P<0.05). The results of the Cox multivariate regression analysis showed that when the estimated cumulative LDL-C exposure was treated as a continuous variable and analyzed in two, three, and four groups, with the lowest group as the reference, the risk of MACCE occurrence in the high-value group increased by 21% (95% CI 1.08-1.37, P=0.002), 24% (95% CI 1.07-1.43, P=0.004), and 21% (95% CI 1.02-1.43, P=0.025) respectively. Conclusions:A positive correlation was found between estimated cumulative LDL-C exposure and severity of coronary artery disease. High estimated cumulative LDL-C exposure level is a risk factor for MACCE in ACS patients within 2 years.

Objective To develop a decision support system for clinical nursing plans based on nursing diagno-sis and explore its application effects,in order to provide references for optimizing the clinical nursing process and improving the quality of nursing.Methods A multidisciplinary research team was established to construct a clini-cal nursing plan decision support system framework from 3 aspects,namely nursing diagnosis,nursing interventions,and outcome tracking.The system built a clinical nursing diagnosis decision knowledge base through 3 dimensions,namely basic nursing diagnoses,specialty disease nursing diagnoses,and nursing-related technical diagnoses.Deep learning-based artificial intelligence capture technology was developed to achieve intelligent matching and generate clinical nursing plan forms.Implemented in a tertiary hospital in Yichang City,Hubei Province,a control group(June to August 2024)and an experimental group(October to December 2024)were compared regarding nursing diagnosis implementation rate,nursing plan documentation accuracy,and clinical nursing quality scores.Results This research showed a significant improvements for nursing diagnosis implementation rate increased from 94.88％to 97.25％,and nursing plan documentation accuracy improved from 90.38％to 95.33％.Compared with the control group,the experimental group demonstrated statistically significant enhancements in deep vein thrombosis preven-tion,fall prevention,pressure injury management,unplanned extubation control,bloodstream infection control,catheter-related infection prevention,and key specialty nursing quality indicators(all P＜0.05).Conclusion The nursing di-agnosis-based clinical decision support system effectively improves nurses'diagnostic implementation rates,enhances documentation accuracy of nursing plans,and elevates overall clinical nursing quality.

Objective:To investigate the association between estimated cumulative low-density lipoprotein cholesterol (LDL-C) exposure and the severity of coronary artery disease and long-term adverse cardiovascular and cerebrovascular events (MACCE) in patients with acute coronary syndrome (ACS).Methods:The subjects were from the PROMISE study. This study was a prospective cohort study led by Fuwai Hospital, Chinese Academy of Medical Sciences, with participation from eight regional tertiary hospitals as sub-centers, and enrolled 18 701 patients with confirmed coronary heart disease between January 2015 and May 2019. Among them, 8 429 patients with ACS were included in this study. The estimated cumulative LDL-C exposure was calculated by multiplying LDL-C by age. Participants were then divided into four groups based on quartiles. Baseline data and coronary angiography data were collected, and participants were followed for 2 years. The primary endpoint was MACCE, which was composed of all-cause death, cardiac death, myocardial infarction, revascularization, and stroke. Spearman correlation analysis was used to estimate the correlation between cumulative LDL-C exposure and the severity of coronary artery disease. The differences in MACCE among the four groups were compared, and multivariate Cox regression was used to divide the estimated cumulative exposure LDL-C into two groups, three groups, and four groups to analyze its relationship with MACCE.Results:The 8 429 ACS patients included in the study had an age of (60.9±11.4) years, with 1 951(23.1%) females. Spearman correlation analysis revealed that estimated cumulative LDL-C exposure was positively associated with the preoperative SYNTAX score, three-vessel lesions disease, left main disease, and the number of target lesions (correlation coefficients r=0.14, 0.10, 0.04 and 0.03, respectively, with all P<0.05). The 2-year follow-up results indicated that the incidence rates of MACCE, all-cause death, cardiac death, myocardial infarction, and stroke in ACS patients grouped by different levels of estimated cumulative LDL-C exposure were statistically significant (all P<0.05). The results of the Cox multivariate regression analysis showed that when the estimated cumulative LDL-C exposure was treated as a continuous variable and analyzed in two, three, and four groups, with the lowest group as the reference, the risk of MACCE occurrence in the high-value group increased by 21% (95% CI 1.08-1.37, P=0.002), 24% (95% CI 1.07-1.43, P=0.004), and 21% (95% CI 1.02-1.43, P=0.025) respectively. Conclusions:A positive correlation was found between estimated cumulative LDL-C exposure and severity of coronary artery disease. High estimated cumulative LDL-C exposure level is a risk factor for MACCE in ACS patients within 2 years.

Objective To investigate the value of CT radiomics combined with CT and preoperative pathological features for predicting postoperative early recurrence(ER)of local advanced esophageal squamous cell carcinoma(LAESCC).Methods Data of 334 patients with LAESCC were retrospectively analyzed.The patients were divided into training set(n=234)and verification set(n=100)at the ratio of 7:3 and were followed up to observe ER(recurrence within 12 months after surgery)or not.Univariate and multivariate logistic regression were used to analyze clinical,CT and preoperative pathological features of LAESCC in patients with or without ER in training set.The independent risk factors of ER were screened,and a CT-preoperative pathology model was constructed.Based on venous phase CT in training set,the radiomics features of lesions were extracted and screened to establish radiomics model,and finally a combined model was established based on radiomics model and the independent risk factors.Receiver operating characteristic(ROC)curves were drawn,and the area under the curve(AUC)was calculated to evaluate the diagnostic efficacy of each model.Results Among 334 cases,168 were found with but 166 without ER.In training set,117 cases were found with while the rest 117 without ER,while in verification set,51 were found with but 49 without ER.The length of lesions,cT stage and cN stage shown on CT and tumor differentiation degree displayed with preoperative pathology were all independent risk factors for ER of LAESCC(all P＜0.05).The AUC of CT-preoperative pathology model in training set and validation set was 0.759 and 0.783,respectively.Ten best radiomics features of LAESCC were selected,and AUC of the established radiomics model in training set and validation set was 0.770 and 0.730,respectively.The AUC of combined model in training and validation set was 0.838 and 0.826,respectively.The AUC of CT radiomics combined with CT and preoperative pathological features in training set was higher than that of CT-preoperative pathologymodel and radiomics model(both P＜0.01).Conclusion CT radiomics combined with CT and preoperative pathological features could effectively predict postoperative ER of LAESCC.

Objective To observe the value of clinical data combined with CT radiomics features for evaluating programmed cell death-ligand 1(PD-L1)status in gastric cancer.Methods Totally 277 gastric cancer patients were retrospectively enrolled and randomly divided into training set(n=195)and validation set(n=82)at the ratio of 7:3.There were 88 cases in PD-L1 positive subgroup and 107 cases in negative subgroup of training set,while 37 and 45 cases of validation set,respectively.The clinical and conventional CT features were compared between subgroups in both sets,the independent influencing factors of PD-L1 status in gastric cancer were analyzed,and radiomic features were screened based on CT data.Then clinical model,radiomics model and clinical-radiomics model were established,and the efficacy of each model for evaluating PD-L1 status in gastric cancer was observed.Results In training set,Borrmann type,cN stage,cM stage,clinical stage,maximum diameter and thickness were significant difference between subgroups(all P＜0.05).Borrmann type,clinical stage and the thickness were all independent influencing factors of PD-L1 positivity(all P＜0.05).The area under the curve(AUC)of clinical model,radiomic model and clinical-radiomics model for evaluating PD-L1 status in gastric cancer in training set was 0.748,0.832 and 0.841,respectively,and was 0.657,0.801 and 0.789 in validation set,respectively.AUC of clinical model was lower than the other models(all P＜0.05).Conclusion Clinical data combined with CT radiomics features was helpful for evaluating PD-L1 status in gastric cancer.

To summarize the nursing experience of postoperative arrhythmia after transcatheter aortic valve replacement in an elderly patient with severe aortic stenosis.The key points of nursing include:implementing nurse led triple pre-rehabilitation,goal oriented hemodynamic monitoring and volume management,prevention and management of postoperative complications,psychological adaptation adjustment under the guidance of dual heart medicine,early and gradual rehabilitation training,and follow-up specialist guidance for extended care in the hospital.The patient was discharged from hospital with both stable physical and psychological condition after careful treatment and nursing care by the team in 12 days after operation.

This article systematically analyzes the historical evolution of the name， origin， scientific name evolution， medicinal parts， producting area， harvesting and processing， clinical efficacy of Paridis Rhizoma by consulting the ancient materia medica， medical books and prescription books， combined with modern literature， in order to provide a reference for the development of famous classical formulas containing Paridis Rhizoma. According to research， it can be verified that Paridis Rhizoma was first recorded in Shennong Bencaojing with the name of Zaoxiu， and this name has been used for ancient materia medica in the past generations. The name of Chonglou was first appeared in Xinxiu Bencao of the Tang dynasty， and has gradually become the rectification of name， with it being the correct name in modern legal names at all levels. The mainstream source of Paridis Rhizoma used in ancient times was the dried rhizomes of Paris polyphylla var. chinensis， but due to the similarity plant morphology of the genus Paris， there was much confusion， and the same genus of plants with thick rhizomes were also used as Paridis Rhizoma， such as P. polyphylla， P. polyphylla var. stenophylla. Since modern times， P. polyphylla var. yunnanensis has also been included as one of the mainstream sources of Paridis Rhizoma. The origin recorded in ancient materia medica are mainly in Shandong， Anhui， Jiangsu， Jiangxi， Yunnan and other regions， which are collected in the wild for medicinal purposes， modern cultivation is more prevalent in southwestern regions， such as Yunnan， Sichuan， Guizhou and Guangxi. In ancient times， the harvest time was mostly root harvesting in April and May of the lunar calendar， while in modern times， they are mostly harvested throughout the year or in autumn. Autumn harvesting is the best choice， with roots removed from the production area， washed， and dried in the sun. In ancient times， Paridis Rhizoma was processed by baking， grinding and other methods， but in modern times， sliced raw products were mainly used as medicine. Paridis Rhizoma has a slightly cold nature， a bitter taste， and a small toxicity. It can regulate the liver meridian， clear heat and detoxify， reduce swelling and pain， cool the liver and calm convulsions. It is used for symptoms such as boils and carbuncles， throat swelling and pain， snake and insect bites， and its flavor and efficacy are basically consistent in ancient and modern records. Based on the results of the textual research， it is recommended that the dried rhizomes of P. polyphylla var. chinensis or P. polyphylla var. yunnanensis should be used in the development of famous classical formulas containing Paridis Rhizoma， the processing method is selected according to the requirements of the formula， and the raw product is recommended to be used as medicine if not specified.