OBJECTIVE: To investigate the effect of different previous treatments on the efficacy of flumatinib in patients with chronic myeloid leukemia (CML). METHODS: The clinical data of 69 patients with CML treated with flumatinib in the Affiliated Hospital of Xuzhou Medical University from 2019 to 2024 were retrospectively analyzed. The patients were divided into a first-line flumatinib group and a first-line non-flumatinib group according to whether flumatinib was used as first-line treatment. The molecular response (MR) at 3, 6 and 12 months of treatment was compared between the two groups to evaluate the early efficacy. The first-line non-flumatinib group was further divided into imatinib group, nilotinib group, and dasatinib group according to the previous first-line drugs used. The efficacy data of these three groups at 3, 6 and 12 months after switching to flumatinib were collected, and the MR was evaluated to compare efficacy differences. RESULTS: The rate of early molecular response (EMR) in the first-line flumatinib group was significantly higher than that in the first-line non-flumatinib group (P < 0.05). At 6 months and 12 months of treatment, the proportion of patients achieving MR 4.5 in the first-line flumatinib group was significantly higher than that in the first-line non-flumatinib group (P < 0.05). Compared with the imatinib and nilotinib groups, the previous dasatinib group showed a significantly higher proportion of patients achieving MR 5.0 at 3, 6, and 12 months after switching to flumatinib (P < 0.05). CONCLUSION Compared with the previous treatment with other tyrosine kinase inhibitors (TKIs), initial use of flumatinib at diagnosis enable patients to achieve deeper molecular remission more rapidly. Compared with previous use of imatinib or nilotinib, previous use of dasatinib is associated with deeper molecular remission after switching to flumatinib.
Humans ; Leukemia, Myelogenous, Chronic, BCR-ABL Positive/drug therapy* ; Retrospective Studies ; Imatinib Mesylate/therapeutic use* ; Dasatinib/therapeutic use* ; Treatment Outcome ; Pyrimidines/therapeutic use* ; Female ; Male ; Protein Kinase Inhibitors/therapeutic use* ; Middle Aged ; Antineoplastic Agents/therapeutic use*

OBJECTIVE: To study the efficacy and prognosis of patients with myelodysplastic/myeloproliferative neoplasms (MDS/MPN) treated with hypomethylating agents (HMA), and to analyze the factors that may affect their efficacy and prognosis, in order to provide a clinical basis for the choice of treatment options for patients with MDS/MPN. METHODS: 35 patients with newly diagnosed MDS/MPN who received hypomethylating therapy from January 2018 to April 2024 in the Department of Hematology of Affiliated Hospital of Xuzhou Medical University were included. The patients were divided into decitabine group (15 cases) and azacitidine group (20 cases) according to the treatment regimen. The efficacy, median overall survival (OS), and median progression-free survival (PFS) of the patients after HMA treatment were evaluated. The differences in efficacy and survival between the two groups were compared, and factors affecting efficacy and prognosis of MDS/MPN patients were analyzed. RESULTS: The overall response rate (ORR) of the 35 MDS/MPN patients treated with HMA was 51.4%. The ORR was 73.3% in decitabine group and 35.0% in azacitidine group, with a statistically significant difference (P =0.041). Survival analysis showed that the median OS was 12 months and the median PFS was 10 months in the entire cohort of the patients. There was no difference in median OS between decitabine group and azacitidine group. The median PFS in decitabine group was 12 months, higher than that in azacitidine group (7 months), but the difference was not statistically significant (P =0.505). Multivariate analysis showed that the treatment regimen and platelet count were independent influencing factors for the efficacy of HAM treatment; The course and therapeutic efficacy of HMA treatment were independent influencing factors for OS in MDS/MPN patients. The main adverse reactions of HMA treatment were myelosuppression and pulmonary infection. Gastrointestinal reactions were more likely to occur in the azacitidine group than in the decitabine group, and the difference was statistically significant (P =0.027). CONCLUSION HMA treatment is effective and well-tolerated in some MDS/MPN patients. Decitabine shows superior efficacy compared with azacitidine and is less likely to cause gastrointestinal reactions. Patients who received ≥4 courses of HMAs and responded to hypomethylating therapy had longer OS.
Humans ; Prognosis ; Decitabine/therapeutic use* ; Azacitidine/therapeutic use* ; Male ; Female ; Myelodysplastic Syndromes/drug therapy* ; Middle Aged ; Myelodysplastic-Myeloproliferative Diseases/drug therapy* ; Antimetabolites, Antineoplastic/therapeutic use* ; Treatment Outcome ; Aged ; Myeloproliferative Disorders/drug therapy* ; Adult ; DNA Methylation

BACKGROUND: The association of systemic inflammatory response index (SIRI) with prognosis of coronary artery disease (CAD) patients has never been investigated in a large sample with long-term follow-up. This study aimed to explore the association of SIRI with all-cause and cause-specific mortality in a nationally representative sample of CAD patients from United States. METHODS: A total of 3386 participants with CAD from the National Health and Nutrition Examination Survey (NHANES) 1999-2018 were included in this study. Cox proportional hazards model, restricted cubic spline (RCS), and receiver operating characteristic curve (ROC) were performed to investigate the association of SIRI with all-cause and cause-specific mortality. Piece-wise linear regression and sensitivity analyses were also performed. RESULTS: During a median follow-up of 7.7 years, 1454 all-cause mortality occurred. After adjusting for confounding factors, higher lnSIRI was significantly associated with higher risk of all-cause (HR = 1.16, 95% CI: 1.09-1.23) and CVD mortality (HR = 1.17, 95% CI: 1.05-1.30) but not cancer mortality (HR = 1.17, 95% CI: 0.99-1.38). The associations of SIRI with all-cause and CVD mortality were detected as J-shaped with threshold values of 1.05935 and 1.122946 for SIRI, respectively. ROC curves showed that lnSIRI had robust predictive effect both in short and long terms. CONCLUSIONS SIRI was independently associated with all-cause and CVD mortality, and the dose-response relationship was J-shaped. SIRI might serve as a valid predictor for all-cause and CVD mortality both in the short and long terms.

Objective:To develop an artificial intelligence (AI)-based platelet review strategy to identify abnormal platelet histograms with no significant difference between initial impedance platelet count (PLT-I) and PLT-F results.Methods:This study included 5 119 routine blood analysis in Nanfang Hospital of Southern Medical University and its Ganzhou branch from July 2023 and March 2024. Specimens exhibiting abnormal platelet histograms and an initial platelet count >40×10?/L underwent review using the fluorescent platelet count (PLT-F) channel. Consistency of the results was defined as a difference between impedance platelet count (PLT-I) and PLT-F less than ±20% of the PLT-F results. A deep learning model was developed using platelet and red blood cell histogram data from a training set of 3 807 specimens. The model′s diagnostic performance was evaluated on an independent external validation set ( n=805) using receiver operating characteristic (ROC) curve analysis. Changes in the number of reviewed samples and sample turnaround time were analyzed to assess its clinical utility. Results:The deep learning model based on platelet and red blood cell histograms achieved an area under the ROC curve (AUC) of 0.854 in the training set. At a cutoff value of 0.1, the sensitivity was 0.954 and specificity was 0.358. The model could reduce review by 16.80% (190/1 131). In the validation set, the AUC was 0.805, with a sensitivity of 0.955 and specificity of 0.307, corresponding to a reduction of 17.41% (47/270) in reviewed specimens.Conclusion:The platelet review prediction model developed based on deep learning technology can efficiently identify samples with consistent results before and after review, reducing unnecessary reviews and shortening specimen testing time, thereby improving the efficiency of platelet test.

This study was aimed at identifying the pathogenic bacteria responsible for the death of a young tiger at the Fujian Meihua Mountain South China Tiger Breeding Research Institute.Tissue samples from the lungs,liver,and intestines of the deceased tiger were collected,and the bacteria were cultured inasterile environment.The bacterial strains were characterized according to their morphological and molecular biological properties,including assessment of virulence genes and antibiotic resistance genes,mouse lethality tests,and antibiotic susceptibility evaluations.A predominant bacterial strain isolated from the liver of the deceased tiger was identified as enterotoxigenic Escherichia coli(ETEC)strain Tiger22513F.Phylogenetic analysis of the 16S rRNA gene revealed that the Tiger22513F strain exhibited close genetic similarity to the reference strain ETEC(MF919609.1),with 99.9%nucleotide similarity,and resided on the same evolutionary branch.The Tiger22513F strain contained 11 antibiotic resistance genes(tetA,sul1,sul3,cmlA,floR,blaTEM,blaSHV,blaCMY-2,qnrA,qnrS,and qnrD)along with five virulence genes(VT1,fyuA,tsh,iucD,and ST).Mouse lethality tests indicated significant pathogenicity toward mice,affecting primarily the lungs,liver,and intestines.Antibiotic susceptibility testing demonstrated that this strain exhibited resistance to various classes of beta-lactam antibiotics,as well as quinolones and aminoglycosides.This investigation successfully isolated a multi-drug resistant enterotoxigenic Escherichia coli strain with pronounced pathogenicity from the liver of a deceased tiger;thus providing valuable scientific insights for clinical diagnosis,as well as prevention and control measures,against ETEC infections in South China tigers.

This study was aimed at identifying the pathogenic bacteria responsible for the death of a young tiger at the Fujian Meihua Mountain South China Tiger Breeding Research Institute.Tissue samples from the lungs,liver,and intestines of the deceased tiger were collected,and the bacteria were cultured inasterile environment.The bacterial strains were characterized according to their morphological and molecular biological properties,including assessment of virulence genes and antibiotic resistance genes,mouse lethality tests,and antibiotic susceptibility evaluations.A predominant bacterial strain isolated from the liver of the deceased tiger was identified as enterotoxigenic Escherichia coli(ETEC)strain Tiger22513F.Phylogenetic analysis of the 16S rRNA gene revealed that the Tiger22513F strain exhibited close genetic similarity to the reference strain ETEC(MF919609.1),with 99.9%nucleotide similarity,and resided on the same evolutionary branch.The Tiger22513F strain contained 11 antibiotic resistance genes(tetA,sul1,sul3,cmlA,floR,blaTEM,blaSHV,blaCMY-2,qnrA,qnrS,and qnrD)along with five virulence genes(VT1,fyuA,tsh,iucD,and ST).Mouse lethality tests indicated significant pathogenicity toward mice,affecting primarily the lungs,liver,and intestines.Antibiotic susceptibility testing demonstrated that this strain exhibited resistance to various classes of beta-lactam antibiotics,as well as quinolones and aminoglycosides.This investigation successfully isolated a multi-drug resistant enterotoxigenic Escherichia coli strain with pronounced pathogenicity from the liver of a deceased tiger;thus providing valuable scientific insights for clinical diagnosis,as well as prevention and control measures,against ETEC infections in South China tigers.

Objective:To develop an artificial intelligence (AI)-based platelet review strategy to identify abnormal platelet histograms with no significant difference between initial impedance platelet count (PLT-I) and PLT-F results.Methods:This study included 5 119 routine blood analysis in Nanfang Hospital of Southern Medical University and its Ganzhou branch from July 2023 and March 2024. Specimens exhibiting abnormal platelet histograms and an initial platelet count >40×10?/L underwent review using the fluorescent platelet count (PLT-F) channel. Consistency of the results was defined as a difference between impedance platelet count (PLT-I) and PLT-F less than ±20% of the PLT-F results. A deep learning model was developed using platelet and red blood cell histogram data from a training set of 3 807 specimens. The model′s diagnostic performance was evaluated on an independent external validation set ( n=805) using receiver operating characteristic (ROC) curve analysis. Changes in the number of reviewed samples and sample turnaround time were analyzed to assess its clinical utility. Results:The deep learning model based on platelet and red blood cell histograms achieved an area under the ROC curve (AUC) of 0.854 in the training set. At a cutoff value of 0.1, the sensitivity was 0.954 and specificity was 0.358. The model could reduce review by 16.80% (190/1 131). In the validation set, the AUC was 0.805, with a sensitivity of 0.955 and specificity of 0.307, corresponding to a reduction of 17.41% (47/270) in reviewed specimens.Conclusion:The platelet review prediction model developed based on deep learning technology can efficiently identify samples with consistent results before and after review, reducing unnecessary reviews and shortening specimen testing time, thereby improving the efficiency of platelet test.

Objective:To analyze the clinical characteristics of patients with Epstein-Barr virus(EBV)-associated hemophagocytic lymphohistiocytosis(HLH)with acute kidney injury(AKI).Methods:EBV-HLH patients who were hospitalized in our hospital from January 2014 to December 2020 were collected,and their clinical characteristics,treatment,concurrent acute kidney injury and prognosis were retrospectively analyzed.Results:In this study,the incidence of AKI complicated by EBV-HLH was 65.5％,and the 28-day mortality rate was 15.3％.Compared with non-AKI group,patients in the AKI group had higher levels of bilirubin,lactate dehydrogenase,creatinine,urea nitrogen,and β2-microglobulin(β2-MG),poorer coagulation,and lower soluble IL-2 receptor(sCD25).Patients in the AKI group had a higher proportion of chemotherapy,transplantation,mechanical ventilation,and the application of vasoactive medications,and were hospitalized for longer periods of time,with higher in-hospital mortality rates and 28-day mortality rates.Patients in the AKI group were analyzed in subgroups according to the Kidney Disease Improving Global Outcomes(KDIGO)classification,and the levels of leukocytes,bilirubin,albumin,creatinine,urea nitrogen,β2-MG,activated partial thromboplastin time(APTT),and prothrombin time activity(PTA)were more responsive to the severity of the patient's condition.KDIGO grade 2 and 3 had higher proportions of receiving transplants,diuretics,organ support(mechanical ventilation,application of vasoactive medications,and renal replacement therapy),and admissions to the intensive care unit(ICU),and with higher in-hospital mortality rates and 28-day mortality rates.Regression analysis found that creatinine,β2-MG,APTT,transplantation,and chemotherapy were independent risk factors for the development of AKI;the application of vasoactive drugs was both an independent risk factor for the development of AKI and for death at 28 days;and chemotherapy,length of hospitalization,and HGB and fibrinogen levels were protective factors for death at 28 days.Conclusion:AKI in EBV-HLH has high incidence and high rate of progression to severe disease and death,early attention should be given and strengthened in order to carry out early treatment and improve the prognosis of patients.

Objective:This study aims to evaluate the impact of Diagnosis-Related-Groups(DRGs)payment on the average total cost,length of stay,service volume,effectiveness,and characteristics of traditional Chinese medicine(TCM)hospitals.Methods:A national medical center specializing in TCM was selected as the research subject.The Difference-in-Difference Model(DID)was utilized to analyze the differences in various indicators between insured patients(intervention group)and uninsured patients(control group)before and after the implementation of the payment reform policy.The reliability and stability of the model were verified through parallel trend tests and placebo tests.Results:The coefficients of DID interaction terms for eleven indicators including average total hospitalization cost,number of cases,length of stay,proportion of medical service revenue,and proportion of herbal medicine revenue were significant(P<0.05).The DID interaction term coefficients for four indicators including herbal medicine usage rate and proportion of non-pharmacological TCM therapy revenue were not significant(P>0.05).Conclusion:DRG payment significantly reduced the per-admission cost,with significant decreases in consumables and medical technology expenses,optimizing cost structure,and a slight decrease in the proportion of herbal medicine costs.It is necessary to further expand the sample size,track policy impacts,and comprehensively evaluate the effects of DRG payment on TCM hospitals in China.