In the era of evidence-based medicine， the progress of medical science and technology has enriched medical diagnostic tools and treatment methods， but it has also led to the loss of medical warmth and the alienation of the doctor-patient relationships. William Osler emphasized that while medical technology advances， attention should also be paid to the practice of narrative medicine and the development of physician’s narrative literacy. The view of the physician he advocated reminds us that the core of medicine still lies in the narrative connection between doctors and patients， as well as a deep understanding of human nature. By exploring the relationship between Osler’s view of the physician and narrative medicine as well as physician’s narrative literacy， this paper analyzed the methods of cultivating physician’s narrative literacy， providing references for modern medical education and practice， and assisting in the harmony and unity of science and technology and humanity.

Objective To summarize and analyze the efficacy and influencing factors of second allogeneic hematopoietic stem cell transplantation (allo-HSCT) for acute leukemia relapsing after the first allo-HSCT. Methods Clinical data of 17 patients with acute leukemia who underwent second allo-HSCT at Peking University First Hospital from January 2005 to December 2024 were retrospectively analyzed. Results Among the 17 patients, 7 achieved long-term disease-free survival after second transplantation. The median progression-free survival after successful second transplantation was 7 months (range 8 days to 69 months). The relapse fatality was 24%, and the transplant-related fatality was 35%. Conclusions Second transplantation is an effective treatment for relapsed and refractory acute leukemia, but the relapse fatality and transplant-related fatality remain high. Patient age, time of relapse after the first transplantation and disease status before second transplantation are all factors that affect the efficacy of second transplantation. Younger age, late relapse and complete remission of disease before second transplantation are all beneficial for long-term disease-free survival after second transplantation.

BACKGROUND:Fibromyalgia syndrome,as a common rheumatic disease,is related to central sensitization and immune abnormalities.However,the specific mechanism has not been elucidated,and there is a lack of specific diagnostic markers.Exploring the possible pathogenesis of this disease has important clinical significance. OBJECTIVE:To screen the potential diagnostic marker genes of fibromyalgia syndrome and analyze the possible immune infiltration characteristics based on bioinformatics methods,such as weighted gene co-expression network analysis(WGCNA),and machine learning. METHODS:Gene expression profiles in peripheral serum of fibromyalgia syndrome patients and healthy controls were obtained from the gene expression omnibus(GEO)database.The differentially co-expressed genes were screened in the expression profile by differential analysis and WGCNA analysis.Least absolute shrinkage and selection operator(LASSO)and support vector machine-recursive feature elimination(SVM-RFE)machine learning algorithm were further used to identify hub biomarkers,and draw receiver operating characteristic curve(ROC)to evaluate the accuracy of diagnosing fibromyalgia syndrome.Finally,single sample gene set enrichment analysis(ssGSEA)and gene set enrichment analysis(GSEA)were used to evaluate the immune cell infiltration and pathway enrichment in patients with fibromyalgia syndrome. RESULTS AND CONCLUSION:Eight down-regulated differentially expressed genes(DEGs)were obtained after differential analysis of the GSE67311 dataset according to the conditions of log2|(FC)|>0 and P<0.05.After WGCNA analysis,497 genes were included in the module(MEdarkviolet)with the highest positive correlation(r=0.22,P=0.04),and 19 genes were included in the module(MEsalmon2)with the highest negative correlation(r=-0.41,P=6×10-5).After intersecting DEGs and the module genes of WGCNA,seven genes were obtained.Four genes were screened out by LASSO regression algorithm and five genes were screened out by SVM-RFE machine learning algorithm.After the intersection of the two,three core genes were identified,which were germinal center associated signaling and motility like,integrin beta-8,and carboxypeptidase A3.The areas under the ROC curve of the three core genes were 0.744,0.739,and 0.734,respectively,indicating that they have good diagnostic value and can be used as biomarkers for fibromyalgia syndrome.The results of immune infiltration analysis showed that memory B cells,CD56 bright NK cells,and mast cells were significantly down-regulated in patients with fibromyalgia syndrome compared with the control group(P<0.05),and were significantly positively correlated with the above three biomarkers(P<0.05).The enrichment analysis suggested that there were nine fibromyalgia syndrome enrichment pathways,mainly related to olfactory transduction pathway,neuroactive ligand-receptor interaction,and infection pathway.The above results showed that the occurrence and development of fibromyalgia syndrome are related to the involvement of multiple genes,abnormal immune regulation,and multiple pathways imbalance.However,the interactions between these genes and immune cells,as well as their relationships with various pathways need to be further investigated.

Objective:s To investigate the risk factors for delayed encephalopathy after acute carbon monoxide poisoning (DEACMP) in patients with acute carbon monoxide poisoning (ACOP) and to develop predictive models based on machine learning algorithms.Methods:Patients with ACOP hospitalized at the First Affiliated Hospital of Zhengzhou University from August 2019 to October 2024 were included, with the occurrence of DEACMP as the outcome measure. The dataset was randomly divided into training and validation sets at a ratio of 7:3. Lasso regression was used to select features influencing the outcome in training sets. Nine machine learning models—including Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM)—were constructed. Receiver operating characteristic (ROC) curves were plotted and the area under the curve (AUC) calculated for each model. Calibration curves were used to assess accuracy, and decision curve analysis (DCA) was applied to evaluate clinical utility. The SHapley Additive exPlanations (SHAP) method was employed to visualize and interpret the best-performing model.Results:A total of 264 ACOP patients were included, of whom 54 (20.5%) developed DEACMP. Lasso regression identified eight key feature variables. Based on these factors, predictive models were constructed, showing good AUC stability across the nine machine learning models in both training (0.92–0.99) and validation sets (0.85–0.91). The RF model performed best, with an AUC of 0.99 in the training set and 0.90 in the validation set; its calibration curve and DCA curve also demonstrated excellent performance. SHAP analysis of the RF model revealed the importance ranking of factors from highest to lowest as follows: Glasgow Coma Scale (GCS) score, duration of coma, age, history of coronary heart disease, CK-MB level, monocyte count, diastolic blood pressure (DBP), and drinking history.Conclusions:The RF model exhibited the highest predictive performance for DEACMP occurrence in ACOP patients. The influencing factors, ranked in order of importance from highest to lowest, are as follows: GCS score, duration of coma, age, history of coronary heart disease, CK-MB level, monocyte count, DBP, and drinking history.

OBJECTIVE: To assess the clinical value of digital PCR (dPCR) for the prenatal diagnosis of common fetal aneuploidies. METHODS: A dPCR-based assay was developed for detecting trisomies 21, 18, and 13. A retrospective analysis was carried out on 173 amniotic fluid samples collected by the Prenatal Diagnosis Center of Taizhou Hospital between January 2017 and December 2023. By using chromosomal karyotyping as the gold standard, the diagnostic performance of the multiplex dPCR system was evaluated in a double-blind manner. This study has been approved by the Ethics Committee of Taizhou Hospital (Ethics No. K20250339). RESULTS: Chromosomal karyotyping has identified 59 cases of trisomy 21, 5 cases of trisomy 18, 2 cases of trisomy 13, 6 cases with chromosomal structural abnormalities or mosaicisms, and 101 cases with a normal karyotype. The dPCR results (Z-score cutoff = 4.0, CI = 99.997%) showed full concordance with karyotyping (sensitivity = 100%, specificity = 100%, Kappa = 1). Among the 6 structurally abnormal or mosaicism samples, dPCR has accurately detected 4 cases, but mis-classified 2 cases of trisomy 21 with very low-level mosaicisms (3.3%, 6.9%, respectively) as normal. CONCLUSION The established multiplex dPCR system demonstrated high diagnostic accuracy for common chromosomal aneuploidies, with results available within 24 hours. It can serve as an efficient supplementary tool to conventional chromosomal karyotyping, providing reliable support for time-sensitive clinical decision-making in prenatal diagnosis.
Humans ; Female ; Pregnancy ; Aneuploidy ; Prenatal Diagnosis/methods* ; Karyotyping ; Retrospective Studies ; Polymerase Chain Reaction/methods* ; Chromosome Disorders/genetics* ; Adult ; Trisomy 13 Syndrome/diagnosis* ; Trisomy 18 Syndrome/genetics* ; Down Syndrome/genetics*

Objective To investigate the predictive value of bone metabolism parameters on cardiac autonomic nervous system function in patients with type 2 diabetes mellitus(T2DM).Methods A total of 328 patients with T2DM hospitalized in the Department of Endocrinology of Gansu Provincial People's Hospital were enrolled in this study from October 2022 to October 2023.According to the serum 25(OH)D level,all the participants were divided into<10 ng/ml group(n=80),10～20 ng/ml group(n=173),and 20～30 ng/ml group(n=75).Biochemical indicators,bone metabolic parameters,left ventricular mass(LVM)and left ventricular mass index(LVMI)were compared.Time domain indicators ofheart rate variability(HRV)in 24 h holter electrocardiogram,including the global standard deviation of normal sinus RR interval(SDNN),sinus RR interval mean standard deviation(SDANN),and normal continuous sinus RR interval difference root mean square(RMSSD).Meanwhile,adjacent RR interval difference>50 ms as a percentage of the total inter-period(PNN50),HRV triangle index,standard deviation of the difference between the length of the entire adjacent NN interperiod(SDSD),and 24 h holter electrocardiogram HRV time-domain relevant indicators were compared among the three groups.The influence of bone metabolism parameters on cardiac autonomic nervous function and their correlation were analyzed,and the optimal cutting point of cardiac autonomic nervous function was predicted by receiver operating characteristic(ROC)curve.Results SBP,heart rate(HR),FPG,PWV,PTH and β-CTX in groups of 10 ng/ml,10～20 ng/ml and 20～30 ng/ml decreased in turn(P<0.05),while HDL-C,ABI,25(OH)D,Ca2+and PNN50 decreased.Correlation analysis between Spearman and Pearson showed that 25(OH)D was positively correlated with SDNN,HRV triangle index,PNN50 and rMSSD(P<0.01).Logistic regression analysis showed that 25(OH)D,Ca2+and HR were the influencing factors of cardiac autonomic nervous dysfunction in patients with T2DM.The ROC curve analysis showed that the areas under the ROC curve of 25(OH)D,Ca2+and HR were 0.791,0.607 and 0.629,respectively,with sensitivity of 73.4%,53.2%and 38.7%,and specificity of 74.0%,93.6%and 81.4%,respectively.Conclusions 25(OH)D is the influencing factor of cardiac autonomic nervous dysfunction in patients with T2DM,and patients with high degree of deficiency are more prone to cardiac autonomic nervous dysfunction.

Objective To analyze the factors affecting the prevalence of hyperuricemia(HUA)in an island troop.Methods A total of 1 113 soldiers stationed on an island from December 2021 to December 2022 were selected as research objects by cluster sampling.Their lifestyle and health information were collected.Physical examination and laboratory detection were conducted.Multivariate logistic regression was used to analyze the influencing factors of HUA.Results The prevalence rate of HUA was 21.02%(234/1 113).There were significant differences in the body mass index(BMI),waist-to-hip ratio,triglyceride,alanine aminotransferase,and creatinine between the soldiers with hyperuricemia and the soldiers with normal blood uric acid(P<0.05).Multivariate logistic regression analysis showed that BMI≥24(OR=1.49,95%CI:1.09-2.05),abnormal liver function(OR=2.26,95%CI:1.31-3.92),and dyslipidemia(OR=1.46,95%CI:1.01-2.12)were positively correlated with hyperuricemia;age>30 years old(OR=0.59,95%CI:0.37-0.93)and exercise time>1 h per week(OR=0.46,95%CI:0.22-0.97)were negatively correlated with HUA.Conclusion The prevalence rate of hyperuricemia is at a high level in an island troop.BMI≥24,age≤30 years old,exercise time≤1 h per week,abnormal liver function,and dyslipidemia are the risk factors for HUA.Prevention and control measures should be taken as early as possible for the soldiers with these risk factors.

Objective:To build an internet hospital cost-benefit evaluation index system based on a large public tertiary hospital, for references for improving the operation and management of internet hospitals.Methods:From May to October 2024, this study identified the elements of cost-benefit through on-site investigation, literature analysis and expert discussion, and built an initial evaluation index system of cost-benefit of internet hospitals; Delphi method and Pareto chart method were used to determine indicators and their weights; This evaluation index system was used to quantitatively evaluate an internet hospital since its operation for two years (from May 2022 to April 2024).Results:Five profit entities and 26 cost-benefit components had been identified; The expert authority coefficient of the two rounds of Delphi method was 0.73, and the Kendall coefficient was 0.80 ( P<0.001). The costs and benefits of an internet hospital since its operation for two years were 14.06 million yuan and 134.95 million yuan, respectively, with a benefit cost ratio of 9.60. Conclusions:The cost-benefit evaluation index system of internet hospitals built in this study was suitable for these relying on physical hospitals. This system was scientific and practical, and could provide references for cost-benefit evaluation of other Internet hospitals.

Objective To analyze the differences and correlations of imaging parameters in patients with Parkinson's disease(PD)combined with cerebral small vessel disease(CSVD)with different cognitive functions based on MRI.Methods A retrospective selection was conducted on 192 PD patients combined with CSVD.According to the Montreal cognitive assessment(MoCA)and mini-mental state examination(MMSE)scores,they were divided into cognitive impairment PD group(n=69)and cognitive normal PD group(n=123),and the clinical data and MRI imaging parameters of the two groups were compared.Results The age and drinking history of the cog-nitive impairment PD group were higher than those of the cognitive normal PD group(P<0.05);the lacune of presumed vascular origin(LPVO)score,periventricular white matter hyperintensity(PVWMH)score,basal ganglia-perivascular space(BG-PVS)score,brain atrophy(BA)score,and CSVD total score in the cognitive impairment PD group were higher than those in the cognitive normal PD group(P<0.05),while there was no statistically significant difference in deep white matter hyperintensity(DWMH)score,cen-trum semiovale perivascular space(CS-PVS)score,and cerebral microbleed(CMB)score between the two groups(P>0.05);Multi-variate logistic analysis showed that age,LPVO score,BG-PVS score,BA score,and CSVD total score were independent influencing factors of cognitive impairment(P<0.05).Conclusion There are differences in imaging parameters such as LPVO score,PVWMH score,BG-PVS score,BA score,and CSVD total score among PD patients combined with CSVD with different cognitive functions,and they are correlated with MMSE and MoCA scores.

Objective:To analyze the differences in clinicopathological features between non-elderly and elderly patients with melanoma, and to identify risk factors for prognosis in elderly patients with melanoma.Methods:A retrospective analysis was conducted on clinical and pathological data collected from non-elderly (aged < 60 years) and elderly (aged ≥ 60 years) patients with melanoma, who were confirmedly diagnosed according to clinical manifestations and histopathological findings at the People's Hospital of Xinjiang Uygur Autonomous Region from January 2008 to December 2023. The differences in clinical and pathological characteristics between the two groups were analyzed using the chi-square test and Wilcoxon rank-sum test. Survival curves were estimated using the Kaplan-Meier method and log-rank test. The relationship between clinicopathological variables and overall survival was analyzed using a Cox regression model.Results:A total of 233 patients with cutaneous melanoma were included, with the age being 60.3 ± 14.7 years, and the number of patients was highest in the age group of 60 - 69 years. There were 102 cases (43.8%) in the < 60 years old group and 131 cases (56.2%) in the ≥ 60 years old group. Compared with the < 60 years old group, the ≥ 60 years old group showed a significant increase in the proportion of patients with active tumor-infiltrating lymphocytes ( P = 0.040), proportion of those with Ki-67 index ≥ 30% ( P = 0.010), and Charlson comorbidity index ( P = 0.002), but a significant decrease in the proportion of patients with BRAF/KIT/NRAS mutations ( P = 0.003), proportion of those receiving surgical treatment ( P = 0.034), and proportion of those receiving adjuvant therapy ( P = 0.042). There was a significant difference in the overall survival between the two groups (log-rank test, χ2 = 6.10, P = 0.014). The gender, metastasis status, presence or absence of ulceration, distant metastasis status, American Joint Committee on Cancer staging, Charlson comorbidity index, and Breslow thickness were important prognostic indicators affecting the overall survival in the elderly patients with melanoma. Multivariate Cox regression analysis showed that males ( P = 0.015, HR = 4.622, 95% CI: 1.352 - 15.798), presence of distant metastasis ( P = 0.013, HR = 9.844, 95% CI: 4.621 - 59.763), and Charlson comorbidity index ≥ 3 ( P = 0.038, HR = 3.149, 95% CI: 1.067 - 9.294) were independent risk factors affecting the overall survival in the elderly patients with melanoma. Conclusions:Compared with the non-elderly patients with melanoma, a higher Ki-67 index, a higher Charlson comorbidity index, less surgical treatment, and less adjuvant therapy were more common in the elderly patients with melanoma. Males, the presence of distant metastasis, and Charlson comorbidity index ≥ 3 appeared to be independent risk factors affecting the overall survival in the elderly patients with melanoma.