OBJECTIVE To develope a predictive model for medication deviation risks during the hospital-to-home transition period in coronary heart disease （CHD） patients with initial treatment， aiming to assist medical staff in rapidly identifying high-risk groups for medication deviation. METHODS A total of 462 CHD patients with initial treatment from the Affiliated Hospital of North China University of Science and Technology （hereinafter referred to as “our hospital”） between January and July 2024 were enrolled. The patients were randomly divided into a modeling group and an internal validation group. The modeling group was further categorized into a medication deviation group and a non-medication deviation group based on whether medication deviations occurred. Similarly， 57 CHD patients with initial treatment from the cardiology department of our hospital between June and September 2025 were collected as an external validation group. Univariate analysis was used to screen predictive factors， followed by multivariate Logistic regression to construct the predictive model. Internal validation methods were employed to evaluate model performance， while external validation methods were used to test the model’s generalizability. RESULTS The 462 patients were divided into a modeling group （319 cases） and an internal validation group （143 cases）. In the modeling group， the medication deviation group （192 cases， 60.19%） and the non-medication deviation group （127 cases， 39.81%） were identified. Multivariate Logistic regression analysis revealed that age， medication type， medication adherence， and self-efficacy in rational medication use were predictive factors for medication deviations in CHD patients with initial treatment （ P ＜0.05）. The predictive model equation was logit P ＝ln[ P /（1－ P ） ] ＝1.321+1.732×age+4.091×medication type －4.360×medication adherence －3.081×self-efficacy in rational medication use. The model demonstrated good discrimination， with a Hosmer-Lemeshow goodness-of-fit test P -value of 0.439， an area under the receiver operating characteristic curve （AUC） of 0.870， sensitivity of 0.970， and specificity of 0.607. A risk nomogram with a total score of 350 points and a cutoff value of 110 points was plotted. The internal validation group showed an AUC o f 0.787 and a prediction accuracy of 77.6%， while the external validation group exhibited an AUC of 0.802 and a prediction accuracy of 73.7%. CONCLUSIONS This study successfully developed a predictive model for medication deviation risks during the hospital-to-home transition period in CHD patients with initial treatment. The model demonstrates excellent discrimination and predictive accuracy， effectively identifying high-risk populations for medication deviations. Age （＞70 years）， number of drug types≥5， poor medication adherence， and poor self-efficacy in rational medication use are independent risk factors for medication deviations.

OBJECTIVE To evaluate the influence of pharmaceutical quality control on the efficiency and outcomes of standardized medication therapy management （MTM） services for patients with coronary heart disease by using Economic， Clinical and Humanistic Outcomes （ECHO） model. METHODS This study collected case data of coronary heart disease patients who received MTM services during January-March 2023 （pre-quality control implementation group， n＝96） and June-August 2023 （post-quality control implementation group， n＝164）. Using propensity score matching analysis， 80 patients were selected from each group. The study subsequently compared the economic， clinical， and humanistic outcome indicators of pharmaceutical services between the two matched groups. RESULTS There were no statistically significant differences in baseline data between the two groups after matching （P＞0.05）. Compared with pre-quality control implementation group， the daily treatment cost （16.26 yuan vs. 24.40 yuan， P＜0.001）， cost-effectiveness ratio [23.12 yuan/quality-adjusted life year （QALY） vs. 32.32 yuan/QALY， P＜0.001]， and the incidence of general adverse drug reactions （2.50% vs. 10.00%， P＝0.049） of post-quality control implementation group were decreased significantly； the utility value of the EuroQol Five-Dimensional Questionnaire （0.74± 0.06 vs. 0.71±0.07， P＝0.003）， the reduction in the number of medication related problems （1.0 vs. 0.5， P＜0.001）， the medication adherence score （[ 6.32±0.48） points vs. （6.10±0.37） points， P＝0.001]， and the satisfaction score （[ 92.56±1.52） points vs. （91.95±1.56） points， P＝0.013] all showed significant improvements. Neither group experienced serious adverse drug reactions. There was no statistically significant difference in the incidence of new adverse reactions between the two groups （1.25% vs. 3.75%， P＝0.310）. CONCLUSIONS Pharmaceutical quality control can improve the quality of pharmaceutical care， and the ECHO model can quantitatively evaluate the effect of MTM services， making pharmaceutical care better priced and more adaptable to social needs， thus being worthy of promotion.

Objective To systematically evaluate the risk prediction models for anastomotic leakage (AL) in patients with esophageal cancer after surgery. Methods A computer-based search of PubMed, EMbase, Web of Science, Cochrane Library, Chinese Medical Journal Full-text Database, VIP, Wanfang, SinoMed and CNKI was conducted to collect studies on postoperative AL risk prediction model for esophageal cancer from their inception to October 1st, 2023. PROBAST tool was employed to evaluate the bias risk and applicability of the model, and Stata 15 software was utilized for meta-analysis. Results A total of 19 literatures were included covering 25 AL risk prediction models and 7373 patients. The area under the receiver operating characteristic curve (AUC) was 0.670-0.960. Among them, 23 prediction models had a good prediction performance (AUC>0.7); 13 models were tested for calibration of the model; 1 model was externally validated, and 10 models were internally validated. Meta-analysis showed that hypoproteinemia (OR=9.362), postoperative pulmonary complications (OR=7.427), poor incision healing (OR=5.330), anastomosis type (OR=2.965), preoperative history of thoracoabdominal surgery (OR=3.181), preoperative diabetes mellitus (OR=2.445), preoperative cardiovascular disease (OR=3.260), preoperative neoadjuvant therapy (OR=2.977), preoperative respiratory disease (OR=4.744), surgery method (OR=4.312), American Society of Anesthesiologists score (OR=2.424) were predictors for AL after esophageal cancer surgery. Conclusion At present, the prediction model of AL risk in patients with esophageal cancer after surgery is in the development stage, and the overall research quality needs to be improved.

BACKGROUND: Primary pulmonary mucoepidermoid carcinoma (PMEC) is an exceedingly rare malignancy originating from bronchial submucosal glands, accounting for <0.2% of lung cancers. Histologically characterized by a triphasic composition of mucinous, epidermoid, and intermediate cells, PMEC is classified into low-grade (favorable prognosis) and high-grade (aggressive behavior) subtypes. This study aimed to investigate the clinicopathological characteristics and prognostic indicators of PMEC. METHODS: Clinicopathological, radiological, molecular, and survival data from 26 PMEC patients were retrospectively analyzed, including immunohistochemical profiles and MAML2 rearrangement status, supplemented by literature review. RESULTS: The cohort comprised 14 males and 12 females (mean age: 55.6 years). Eight patients (30.8%) were smokers, and 19 (73.1%) presented with symptoms. Central tumors predominated (n=19, 73.1%) versus peripheral lesions (n=7, 26.9%). Computed tomography (CT) imaging consistently revealed hypo-to-isodense masses/nodules. Pathologically, 19 cases were low-grade and 7 high-grade. Immunohistochemically, the tumor cells were positive for CK7, P40, P63 and CK5/6, and the Ki-67 index ranged from 2% to 70%. MAML2 rearrangement was detected in 52.4% (11/21) of tested cases. Clinical staging distribution: stage I (n=14), stage II (n=8), stage III (n=3), stage IV (n=1). Treatment modalities: radical surgery alone (n=13), surgery with adjuvant chemotherapy (n=11), chemoradiotherapy (n=1), and conservative management (n=1). With a median follow-up of 57 months, 6 patients (23.1%) died. Prognostic analysis demonstrated: (1) Significantly inferior survival in high-grade versus low-grade groups (P<0.05); (2) Lymph node metastasis, advanced stage, Ki-67>20%, and high-grade histology significantly correlated with reduced overall survival (P<0.05); (3) Lymph node metastasis constituted an independent poor prognostic factor (HR=12.73, 95%CI: 1.22-132.96). CONCLUSIONS PMEC exhibits distinct clinicopathological features, with MAML2 rearrangement present in approximately half of cases. Lymph node metastasis, advanced stage, high Ki-67 proliferation index, and high-grade histology are key determinants of poor prognosis, with lymph node metastasis serving as an independent risk factor.
Humans ; Male ; Female ; Middle Aged ; Carcinoma, Mucoepidermoid/mortality* ; Lung Neoplasms/mortality* ; Trans-Activators/genetics* ; Prognosis ; Adult ; Gene Rearrangement ; Aged ; Retrospective Studies ; Transcription Factors/genetics* ; DNA-Binding Proteins/genetics*

Microalgae possess high photosynthetic efficiency, robust adaptability, and substantial biomass, serving as excellent biological resources for large-scale cultivation. Malic enzyme (ME), a ubiquitous metabolic enzyme in living organisms, catalyzes the decarboxylation of malate to produce pyruvate, CO₂, and NAD(P)H, playing a role in multiple metabolic pathways including energy metabolism, photosynthesis, respiration, and biosynthesis. In this study, we identified the Scenedesmus quadricauda malic enzyme gene (SqME) and its biological functions, aiming to provide excellent target genes for the genetic improvement of higher plants. Based on the RNA-seq data from S. quadricauda under the biofilm cultivation mode with high CO₂ and light energy transfer efficiency and small water use, a highly expressed gene (SqME) functionally annotated as ME was cloned. The physicochemical properties of the SqME-encoded protein were systematically analyzed by bioinformatics tools. The subcellular localization of SqME was determined via transient transformation in Nicotiana benthamiana leaves. The biological functions of SqME were identified via genetic transformation in Nicotiana tabacum, and the potential of SqME in the genetic improvement of higher plants was evaluated. The ORF of SqME was 1 770 bp, encoding 590 amino acid residues, and the encoded protein was located in chloroplasts. SqME was a NADP-ME, with the typical structural characteristics of ME. The ME activity in the transgenic N. tabacum plant was 1.8 folds of that in the wild-type control. Heterologous expression of SqME increased the content of chlorophyll a, chlorophyll b, and total chlorophyll by 20.9%, 26.9%, and 25.2%, respectively, compared with the control. The transgenic tobacco leaves showed an increase of 54.0% in the fluorescence parameter NPQ and a decrease of 30.1% in Fo compared with the control. Moreover, the biomass, total lipids, and soluble sugars in the transgenic tobacco leaves enhanced by 20.5%, 25.7%, and 9.5%, respectively. On the contrary, the starch and protein content in the transgenic tobacco leaves decreased by 22.4% and 12.2%, respectively. Collectively, the SqME-encoded protein exhibited a strong enzymatic activity. Heterologous expressing of SqME could significantly enhance photosynthetic protection, photosynthesis, and biomass accumulation in the host. Additionally, SqME can facilitate carbon metabolism remodeling in the host, driving more carbon flux towards lipid synthesis. Therefore, SqME can be applied in the genetic improvement of higher plants for enhancing photosynthetic carbon fixation and lipid accumulation. These findings provide scientific references for mining of functional genes from S. quadricauda and application of these genes in the genetic engineering of higher plants.
Nicotiana/genetics* ; Photosynthesis/physiology* ; Malate Dehydrogenase/biosynthesis* ; Plant Leaves/genetics* ; Scenedesmus/enzymology* ; Carbon Cycle/genetics* ; Lipid Metabolism/genetics* ; Plants, Genetically Modified/metabolism*

Objective To explore the influencing factors of cognitive impairment in non-dialysis patients with chronic kidney disease(CKD).Methods A total of 60 hospitalized non-dialysis patients with CKD in the Department of Nephrology of Northern Jiangsu People's Hospital Affiliated to Yangzhou University from September 2022 to September 2023 were enrolled as research objects.According to the estimated glomerular filtration rate(eGFR),they were divided into stage 1 to 2 of CKD group[eGFR ≥60 mL/(min·1.73 m2)]with 23 cases,the stage 3 of CKD group[eGFR 30～＜60 mL/(min·1.73 m2)]with 20 cases,and stage 4 to 5 of CKD group[eGFR＜30 mL/(min·1.73 m2)]with 17 cases.The Montreal Cognitive Assessment Scale(MoCA)was used to evaluate the cognitive function of the patients.Basic data and common clinical laboratory in-dicators on hospital admission were collected to analyze the differences in cognitive function levels under different renal function statuses and to explore the influencing factors of cognitive impairment.Results The incidence rates of cognitive impairment in the stage 1 to 2 of CKD group,stage 3 of CKD group,and stage 4 to 5 of CKD group were 47.8％,85.0％,and 94.1％respectively,the median MoCA scored 26,24 and 20 respectively,with statistically significant between-group differ-ences(P＜0.05).Cognitive function was significantly negatively correlated with age(r=-0.634,P＜0.001),blood urea nitrogen(BUN)(r=-0.574,P＜0.001),serum creatinine(Cr)(r=-0.417,P＜0.001),cystatin C(Cys-C)(r=-0.327,P=0.011),serum β2-microglobulin(β2-MG)(r=-0.259,P=0.046),and N-terminal pro-brain natriuretic peptide(NT-proBNP)(r=-0.474,P＜0.001),and was significantly positively correlated with hemoglobin(HB)(r=0.401,P=0.001)and eGFR(r=0.485,P＜0.001).Multivariate Logistic regression analysis showed that age(P=0.006)and NT-proBNP(P=0.041)were influencing factors of cognitive im-pairment in non-dialysis patients with CKD.Receiver operating characteristic(ROC)curve analysis showed that the area under the curve(AUC),sensitivity,and specificity of age for prediction were 0.860,0.864 and 0.812 respectively,the AUC,sensitivity,and specificity of NT-proBNP for pre-diction were 0.808,0.795 and 0.875 respectively,and the combined prediction of age and NT-proBNP had an AUC,sensitivity,and specificity of 0.893,0.955,and 0.750,respectively.Conclusion As renal function deteriorates,the incidence rate and severity of cognitive impairment in non-dialysis patients with CKD tend to increase.Advanced age,renal function deterioration,high NT-proBNP level,and anemia are associated with the occurrence of cognitive impairment in non-di-alysis patients with CKD,among which age and NT-proBNP are influencing factors for cognitive im-pairment.

Objective To systematically review the risk prediction models for postoperative pancreatic fistula(POPF)after pancreaticoduodenectomy(PD),and to provide a reference for the clinical screening and application of POPF-related risk models.Methods This study was conducted according to the PRISMA guidelines,with a PROSPERO registration number of CRD42023437672.PubMed,Scopus,Embase,Web of Science,the Cochrane Library,CNKI,VIP,Wanfang Data,China Medical Journal Full-text Database,and CBM were searched for studies on establishing risk prediction models for POPF after PD published up to April 26,2024.The PROBAST tool was used to assess the quality of articles,and RevMan 5.4 and MedCalc were used to perform the Meta-analysis.Results A total of 36 studies were included,involving 20 119 in total,and the incidence rate of POPF after PD was 7.4%—47.8%.A total of 55 risk prediction models were established in the 36 articles,with an area under the receiver operating characteristic curve(AUC)of 0.690-0.952,among which 52 models had an AUC of>0.7.The quality assessment of the articles showed high risk of bias and good applicability.MedCalc was used to perform a statistical analysis of AUC values,and the results showed a pooled AUC of 0.833(95%confidence interval:0.808-0.857).The Meta-analysis showed that body mass index,amylase in drainage fluid on the first day after surgery,preoperative serum albumin,pancreatic duct diameter,pancreatic texture,fat score,tumor location,blood loss,sex,time of operation,main pancreatic duct index,and pancreatic CT value were predictive factors for POPF(all P<0.05).Conclusion The risk prediction models for POPF after PD is still in the exploratory stage.There is a lack of calibration methods and internal validation for most prediction models,and only the univariate analysis is used to for the screening of variables,which leads to the high risk of bias.In the future,it is necessary to improve the methods for model establishment,so as to develop risk prediction models with a higher prediction accuracy.

Electronic Health Records (EHRs) are digital health tools that support comprehensive care and digital services. This paper provides an overview of EHRs, summarizes their current applications in palliative care, and proposes solutions to address issues in the use of EHRs in this field. The aim is to offer reference points for promoting the application of EHRs in palliative care in China.

Objective:To systematically integrate the qualitative research on effective pain management disorders of cancer patients and caregivers, and to provide reference for patients and caregivers to safely and effectively implement cancer pain management.Methods:The qualitative studies on the experiences and obstacles of cancer patients and caregivers in cancer pain management were retrieved from electronic databases of PubMed, Web of Science, Cochrane Library, Embase, CINAHL, China National Knowledge Infrastructure, China Biology Medicine, VIP and Wanfang data from inception to September 2023. The quality of the literature was evaluated according to Joanna Briggs Institute Evidence Based Healthcare Center Critical Appraisal Tool for qualitative studies in Australia. Meta-synthesis was used to conduct the synthesis.Results:A total of 9 articles were included, and 46 research results were extracted, forming 14 categories, which were further summarized into 4 integrated results: patient-related pain management disorders, caregiver-related pain management disorders, medical staff-related pain management disorders, and health care system-related pain management disorders.Conclusions:Multiple factors cause obstacles for cancer patients and caregivers to participate in pain management. Medical staff should have a deep understanding of patients′pain problems and explore pain management plans and interventions suitable for cancer patients, so as to reduce the degree of cancer pain management obstacles.

Objective To investigate the relationship between systemic immune-inflammation index (SII)and lower extremity vascular disease in patients with type 2 diabetes mellitus (T2DM).Methods A cross-sectional study was conducted on 390 T2DM patients admitted in our department from January 2013 to January 2024.According to the diagnostic criteria for lower extremity vascular disease in T2DM patients,they were divided into a lower extremity vascular disease group (n=158)and a control group (n=232).General data and results of laboratory tests were compared between the 2 groups.Spearman correlation analysis was used to identify the related factors for lower extremity vascular diseases in T2DM patients.The correlation between SII and lower extremity vascular diseases in T2DM patients was analyzed using the Row Mean Scores and Cochran-Armitage Trend analysis.Multivariate logistic regression analysis was applied to identify the risk factors for lower limb vascular lesions in T2DM patients.Receiver operating characteristic (ROC)curve was plotted to evaluate the diagnostic efficacy of SII for lower extremity vascular disease in the patients.Results Compared with T2DMpatients without lower extremity vascular disease,those with lower extremity vascular disease were older,had higher levels of total cholesterol (TC),low-density lipoprotein cholesterol (LDL-C),SII,larger proportion of carotid vascular lesions,and increased proportion of no-taking statins.The lower extremity vascular disease in T2DM patients was positively correlated with SII/100 (r=0.429,P<0.001),age (r=0.517,P<0.001),TC (r=0.161,P=0.001),LDL-C (r=0.117,P=0.021),carotid artery lesions (r=0.101,P=0.047),no-taking statins (r=0.266,P<0.001).Logistic regression analysis showed that SII,age,LDL-C,and no-taking statins were the risk factors for lower extremity vascular lesions in T2DM patients (P<0.01).The area under the curve (AUC)value of SII combined with age,LDL-C,and no-taking statins in predicting lower extremity vascular disease in T2DM patients was 0.896.Conclusion SII is not only a risk factor,but also a simple marker for lower extremity vascular disease in T2DM patients,suggesting that inflammatory response plays an important role in the occurrence and development of lower extremity vascular disease in T2DM.