ObjectiveTo investigate the effects of luteinizing hormone （LH） levels on in vitro fertilization and embryo transfer （IVF-ET） outcomes in an infertile population with normal ovarian reserve （NOR） undergoing controlled ovarian hyperstimulation （COH） with gonadotropin-releasing hormone antagonist protocol， and to explore the reasonable level intervals of LH during the follicular phase. MethodsA retrospective analysis was conducted on 911 NOR infertility patients undergoing IVF-ET treated with gonadotropin-releasing hormone antagonist protocol. Patients were grouped based on baseline LH （bLH） levels， LH levels on the day of antagonist addition， and LH levels on the day of human chorionic gonadotropin （hCG） injection. According to bLH levels， patients were divided into Group A2 （n=391） and Group B2 （n=391）. Based on LH levels on the day of antagonist addition， patients were divided into Group A3 （n=600） and Group B3 （n=311）. According to LH levels on the day of hCG injection， patients were classified into Group A4 （n=225）， Group B4 （n=227）， Group C4 （n=231）， and Group D4 （n=228）. The clinical characteristics， COH outcomes， and pregnancy outcomes of patients in each group were compared. Results① The bLH level could be used as a predictor of assisted reproduction outcomes in an infertile population with NOR， and going for assisted reproduction at bLH≥4.51 IU/L was more favorable for the development of pregnancy outcomes； ② Addition of antagonist at LH≥5 IU/L on the day of antagonist addition improved pregnancy outcome ；③ On the day of hCG injection， there was no statistically significant difference in pregnancy outcomes among the four groups； ④ Analyses using generalized linear models revealed that basal follicle-stimulating hormone （bFSH）， basal estradiol （bE₂）， Gn days， Gn volume and 2PN affected the number of good quality embryos. ConclusionIn an infertile population with NOR using gonadotropin-releasing hormone antagonist， bLH and gonadotropin-releasing hormone antagonist addition day LH levels may influence IVF outcomes. LH levels should be controlled at 5 IU/L and above on antagonist addition days， and bLH levels should be controlled at 4.51 IU/L and above.

[Objective] To establish a method for detecting the potency of recombinant human coagulation factor Ⅶa for injection. [Methods] By adding the sample and factor Ⅶ deficient plasma to the sample cup and activating the reaction with prothrombin time assay reagent (PT reagent), the coagulation time of the sample was determined by the change in magnetic bead swing amplitude in the sample cup. The logarithm of coagulation time was inversely proportional to the logarithm of human factor Ⅶa potency. [Results] Under the experimental conditions, the specificity of the methodology was evaluated through spiked recovery, and the recovery rates ranged from 90.0% to 110.0%. Within the range from 0.125 to 1.000 IU/mL, there was a good linear response between the potency and coagulation time of the standard and sample, with correlation coefficients r>0.99. As for the accuracy and repeatability, the recovery rates of various concentrations detected in the stock solution were 101.0%, 100.0% and 112.0%, respectively, with RSD values of 2.6%, 4.0% and 0.0%, respectively. The recovery rates of various concentrations in finished product testing were 104.0%, 94.7% and 112.0%, respectively, with RSD values of 1.9%, 2.4% and 0.0%, respectively. As for the intermediate precision, the RSD were 4.5% and 3.7%, respectively. After treated with sample diluent, the sample was tested at room temperature for 6 hours and still exhibited relatively stable biological activity. [Conclusion] This detection method is accurate, stable, easy to operate and highly automated, and is suitable for detecting the potency of recombinant human coagulation factor Ⅶa for Injection.

Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

Objective To explore the diagnostic value of 68Ga-PSMA-11 PET/CT combined with abnormal prothrombin(PIVKA-Ⅱ)in the diagnosis of different tumors.Methods A total of 200 patients with suspected cancer who underwent examinations in the Affiliated Hospital of Southwest Medical University from September 2021 to December 2023 were retrospectively selected,including 51 suspected liver cancer,49 suspected pancreatic cancer,52 suspected rectal cancer and 48 suspected prostate cancer.All patients underwent both serum PIVKA-Ⅱ testing and 68Ga-PSMA-11 PET/CT imaging.Receiver operating characteristic(ROC)curve analysis was used to assess the diagnostic performance of 68Ga-PSMA-11 PET/CT and serum PIVKA-Ⅱ for liver cancer,pancreatic cancer,rectal cancer and prostate cancer.Results No significant differences were found in general data of 4 suspected tumor groups(P>0.05)except for age.Serum PIVKA-Ⅱ levels were significantly higher in patients with suspected liver cancer and rectal cancer compared with those with suspected pancreatic cancer and prostate cancer(P<0.05).No significant difference was observed in the serum PIVKA-Ⅱ levels between suspected pancreatic cancer group and suspected prostate cancer group(P>0.05).The positive rates of 68Ga-PSMA-11 PET/CT and serum PIVKA-Ⅱ for diagnosing liver,pancreatic,rectal,and prostate cancers were significantly lower than those of pathological examination(49.0%vs.47.1%vs.92.2%,57.1%vs.55.1%vs.87.8%,48.1%vs.44.2%vs.92.3%,64.6%vs.62.5%vs.89.6%,respectively,P<0.05).ROC curve analysis showed that serum PIVKA-Ⅱ had a sensitivity of 79.06%,specificity of 72.02%,area under ROC curve(AUC)of 0.822,and Youden index of 0.512.For 68Ga-PSMA-11 PET/CT,the sensitivity was 79.11%,specificity 72.07%,AUC 0.829,and Youden index 0.510.The combined use of 68Ga-PSMA-11 PET/CT and serum PIVKA-Ⅱ achieved higher diagnostic accuracy,with a sensitivity of 93.28%,specificity of 81.15%,AUC of 0.924 and Youden index of 0.744,all surpassing the single index.Conclusion Both 68Ga-PSMA-11 PET/CT and serum PIVKA-Ⅱ are effective diagnostic tools for liver,pancreatic,rectal,and prostate cancers,with the combined approach yielding superior diagnostic performance.

OBJECTIVE: To assess the effectiveness of bone acupuncture in improving pain and function in degenerative lumbar spinal stenosis (DLSS) and compare it with Jiaji acupuncture. METHODS: From January to December 2023, 80 DLSS patients were treated with acupuncture and divided into bone acupuncture and Jiaji acupuncture groups. Among them, 40 patients in the bone acupuncture group included 15 males and 25 females, with a mean age of (60.60±6.98) years old;anthor 40 patients in the Jiaji acupuncture group included 16 males and 24 females, with a mean age of (61.48±9.55) years old. The Roland Morris disability questionnaire(RMDQ), walking distance, visual analogue scale(VAS), and the MOS item short from health survey(SF-36) of two groups at baseline, 2 weeks, 4 weeks, and 12 weeks post-treatment were compared. RESULTS: Eighty patients were followed up for 3 to 5 months with an average of (3.62±0.59) months. There was no significant differences in general data and the scores before treatment between two groups(P>0.05). The RMDQ scores in both groups decreased significantly at 2, 4 and 12 weeks after treatment compared with before treatment(P<0.05), at each time point after treatment, the decrease was more significant in the bone acupuncture group than in the Jiaji acupuncture group(P<0.05). The VAS of waist and leg in both groups was significantly lower at 2, 4 and 12 weeks after treatment that before treatment(P<0.05). At all time points after treatment, the waist VAS in the bone acupuncture group was reduced more significant than in the Jiaji acupuncture group(P<0.05);there was no significant difference in leg VAS at 2 and 12 weeks after treatment between two groups(P>0.05), the improvement was more significant in the bone acupuncture group in the 4 weeks after treatment than in the Jiaji acupuncture group. The SF-36 scores in both groups were significantly higher at 2, 4, and 12 weeks after treatment than before treatment(P<0.05);the SF-36 score raised more significant in the bone acupuncture group than in the Jiaji acupunture group(P<0.05). No significant difference in the walking distance between two groups at 2 weeks after treatment(P>0.05);the walking distance in the bone acupuncture group was significantly higher than that in the Jiaji acupuncture group at 4 and 12 weeks after treatment(P<0.05). CONCLUSION Bone-penetrating acupuncture moderately improves functional impairment, pain, and quality of life in patients with DLSS, showing better efficacy than Jiaji acupuncture.
Humans ; Female ; Male ; Middle Aged ; Acupuncture Therapy/methods* ; Spinal Stenosis/physiopathology* ; Aged ; Lumbar Vertebrae/physiopathology* ; Pain Management

OBJECTIVE: To observe the efficacy and safety of 21-day venetoclax (VEN) plus azacitidine (AZA) (21-day VA) in newly diagnosed unfit acute myeloid leukemia (AML) patients in the real-world. METHODS: The clinical data of patients with unfit-AML who received 21-day VA regimen from December 2020 to July 2024 in our center and completed at least 1 cycle of therapeutic effect assessment was retrospectively collected to analyze the safety, efficacy and its influencing factors. RESULTS: A total of 59 patients were enrolled in our study, with a median age of 67(48-87) years old. After 1 cycle of therapy, the composite complete remission (cCR) rate was 74.5%, 54.2% of cases were negative for minimal residual disease (MRD). Among them, the MRD negative rate of patients with NPM1 mutation was significantly higher than that of patients without NPM1 mutation ( P =0.032). The median follow-up of patients was 19(2-38) months, the best cCR and MRD negative rates were 78% and 64.4%, respectively, the median overall survival (OS) time was 12 months, and the median progression free survival (PFS) time was 5 months. Multivariate Cox regression analysis showed less than 4 cycles of VA chemotherapy were independent risk factor for PFS and OS ( P < 0.05). After achieving remission, anemia and thrombocytopenia improved with the increase of the number of chemotherapy cycle. CONCLUSION In real-world, 21-day VA regimen still shows significant efficacy in the treatment of newly diagnosed unfit-AML, without adversely affecting remission rate and MRD negative rate of the first cycle.
Humans ; Leukemia, Myeloid, Acute/drug therapy* ; Aged ; Middle Aged ; Bridged Bicyclo Compounds, Heterocyclic/therapeutic use* ; Sulfonamides/therapeutic use* ; Azacitidine/therapeutic use* ; Aged, 80 and over ; Male ; Female ; Retrospective Studies ; Nucleophosmin ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Remission Induction ; Mutation ; Treatment Outcome

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 explore the relationship between serum chitosinase 3-like protein 1(CHI3L1)and Syndecan-1(SDC1)levels and bone metabolism in elderly patients with type 2 diabetes mellitus and their predictive efficacy on osteoporosis.Methods A total of 412 elderly patients with type 2 diabetes admitted to this hospital from May 2019 to May 2023 were included in this study,and were divided into normal bone mass group(n=151),reduced bone mass group(n=138)and osteoporosis group(n=123)according to the iffer-ences in bone mineral density.Serum CHI3L1 and SDC1 levels were detected by enzyme-linked immunosor-bent assay,and serum levels of type 1 collagen cross-linked carboxyl terminal peptide(CTX),25-hydroxyvita-min D[25-(OH)D],osteocalcin(OC),and type 1 procollagen N-terminal propeptide(P1NP)were deter-mined by automatic chemiluminescence immunoassay.Pearson correlation analysis was used to investigate the relationship between serum CHI3L1,SDC1 and bone metabolism in elderly patients with type 2 diabetes.Re-ceiver operating characteristic(ROC)curve was drawn to evaluate the predictive value of serum CHI3L1 and SDC1 on osteoporosis in elderly patients with type 2 diabetes.Multivariate Logistic regression analysis was used to investigate the influencing factors of osteoporosis in elderly patients with type 2 diabetes.Results There were significant differences in diabetes course,fasting blood glucose,HbA1c and HDL-C a-mong normal bone mass group,decreased bone mass group and osteoporosis group(P＜0.05).The levels of serum CHI3L1,25-(OH)D,P1NP and osteocalcin in osteoporosis group were lower than those in osteopenia group,and those in osteopenia group were lower than those in normal bone mass group,the differences were statistically significant(P＜0.05).Serum SDC1 and CTX levels in osteoporosis group were higher than those in osteopenia group,and those in osteopenia group were higher than those in normal bone mass group,the differences were statistically significant(P＜0.05).Serum CHI3L1 was positively correlated with 25-(OH)D,P1NP and OC(P＜0.05),and negatively correlated with CTX(P＜0.05).Serum SDC1 was negatively correlated with 25-(OH)D,P1NP,OC(P＜0.05),and positively correlated with CTX(P＜0.05).The area under the curve(AUC)of serum CHI3L1,SDC1 and their combination predicted osteoporosis in elderly pa-tients with type 2 diabetes were 0.851,0.772 and 0.904,respectively.Multivariate Logistic regression analysis showed that long duration of diabetes,increased HbA1c,high expression of OC,CHI3L1＞4.16 ng/mL,SDC1≥50.94 ng/mL were all influential factors for osteoporosis in elderly patients with type 2 diabetes(P＜0.05).Conclusion Low expression of CHI3L1 and high expression of SDC1 in serum are associated with ab-normal bone metabolism in elderly patients with type 2 diabetes.These two indexes are expected to be used as biological markers to predict osteoporosis in elderly patients with type 2 diabetes.

Objective To evaluate the effect of pneumatic logistics transport system(PTS)on the trans-portation efficiency of the transferred samples and the accuracy of the results.Methods The transportation speed,temperature and humidity change of PTS were analyzed by temperature and humidity transmitter.Anti-coagulant samples containing disodium ethylenediaminetetraacetate(EDTA-K2),sodium citrate,lithium hepa-rin and samples containing inert separation gel coagulant were selected.and used respectively for complete blood cell analysis,prothrombin time(PT),activated partial prothrombin time(APTT),troponin T(TnT)and other myocardial markers,as well as the detection of items such as glucose(Glu)and lactate dehydrogen-ase(LDH).According to the transfer mode,they were divided into the manual transfer group and the PTS transfer group,and according to the number of PTS transfers,they were divided into the one-time transfer group,the three-time transfer group and before transfer(control).The differences among each group were statistically analyzed,and 1/3 allowable total error(1/3TEa)was adopted as the criterion for determining the clinical application value.Results There was no statistically significant difference in the changes of tempera-ture and humidity during the transportation process of PTS compared with manual transportation(P＞0.05),but it was significantly faster than manual transportation in terms of transportation time(P＜0.05).Com-pared with before transfer,the differences between the PT,APTT,Glu and LDH items in the one-time trans-fer group and the three-time transfer group were statistically significant(P＜0.01),and their deviations were all much greater than 1/3TEa.However,in the plasma samples,compared with before transport,there were statistically significant differences in Glu and LDH between the one-time transfer group and the three-time transfer group(P＜0.05),but the deviations were all less than 1/3TEa.For the items of TnT,red blood cell count and hematocrit,compared with before transfer,there were statistically significant differences between some groups of the one-time transfer group and the three-time transfer group(P＜0.05),but the deviations were all less than 1/3TEa.Conclusion PTS can significantly improve the transportation efficiency of sam-ples,but it significantly affects the detection of Glu and LDH in plasma samples,which can be improved by u-sing serum sample transportation instead.In addition,PTS also affects the detection of PT and APTT,and it is not recommended to use PTS to transport coagulation specimen.

Objective:To construct a machine learning model based on localization CT-based radiomics, dosiomics and clinical features for predicting radiotherapy response in non-small cell lung cancer (NSCLC) and validate its application value.Methods:A retrospective case series study was conducted. A total of 138 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022 were selected. The efficacy was evaluated according to the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, and the patients were stratified according to the objective remission (complete remission+partial remission). Random stratified sampling was used to divide the 138 patients into a training group (96 cases) and an internal validation group (42 cases) at a ratio of 7∶3. Additionally, 33 patients who received radiotherapy at Jining Cancer Hospital from January 2019 to December 2022 were included as the external validation group. Based on the pre-radiotherapy data of the radiotherapy planning system, PyRadiomics software package was used to extract 107 radiomics features and 107 dosiomics features for each patient. Pearson correlation analysis and LASSO regression analysis were used for dimensionality reduction screening; the final selected features were weighted and integrated to generate radiomics-dosiomics scores (RDS), which were then input into logistic regression (LR), support vector machine (SVM), extremely randomized forest (Extra Trees), K-nearest neighbor algorithm (KNN), lightweight gradient boosting machine (Light GBM), and multi-layer perceptron (MLP) machine learning algorithms to construct 6 radiomics-dosiomics models (RDM) for predicting the objective remission. RECIST 1.1 standard was used to evaluate objective remission as the gold standard, receiver operating characteristic (ROC) curve of 6 RDM for predicting objective remission was plotted, and the optimal algorithm for RDM was selected. Univariate and multivariate logistic regression were performed on demographic characteristics, hematological indicators and radiotherapy parameters of the training group to screen independent risk factors for NSCLC patients who received radiotherapy but did not achieve objective remission. These factors were input into the optimal machine learning algorithm to construct a clinical model (CM). Combined with features from RDS and CM, the clinical feature-radiomics-dosiomics combined model (CRDM) was established, and the nomogram of the model for predicting objective remission in NSCLC patients with radiotherapy was drawn. ROC curves were used to evaluate the efficacy of CM, RDM and CRDM in predicting the objective remission in NSCLC patients with radiotherapy in the training group, internal validation group and external validation group.Results:Four radiomics features (including grayscale variance, low grayscale long-range operation emphasis, low grayscale area emphasis, and small area low grayscale area emphasis, all of which were texture features) and 6 dosiomics features [including 1 first-order feature (robust mean absolute deviation), 4 texture features (grayscale non-uniformity, large area emphasis, large area high grayscale emphasis, contrast) and 1 shape feature (shortest axis length)] were selected. ROC curve analysis showed that the area under the curve (AUC) of the RDM constructed using SVM algorithm for judging the objective remission in the training group and the internal validation group was 0.907 (95% CI: 0.836-0.977) and 0.822 (95% CI: 0.685-0.959), which were higher than RDM constructed using other algorithms, and the sensitivity (96.2% and 91.7%), specificity (78.6% and 76.7%) and accuracy (83.3% and 81.0%) at the optimal cut-off values were all higher. Considering the stability and generalization ability of the model, SVM algorithm was ultimately used to construct RDM, CM and CRDM uniformly. Based on training group data, univariate and multivariate logistic regression analysis showed that elevated platelet-to-lymphocyte ratio (PLR) ( OR = 1.001, 95% CI: 1.000-1.003, P = 0.035) and increased target volume of radiotherapy plan ( OR = 1.001, 95% CI: 1.000-1.001, P = 0.008) were independent risk factors for failure to achieve objective remission. ROC curve analysis showed that in the training group and the internal validation group, the AUC of CRDM predicting objective remission were 0.914 (95% CI: 0.856-0.972) and 0.864 (95% CI: 0.754-0.974), respectively, which were better than CM [AUC were 0.735 (95% CI: 0.612-0.857) and 0.697 (95% CI: 0.507-0.888)] and RDM, respectively. In the external validation group, the AUC of CRDM, CM and RDM were 0.778 (95% CI: 0.500-1.000), 0.667 (95% CI: 0.434-0.899) and 0.741 (95% CI: 0.463-1.000), respectively. Conclusions:The CRDM constructed by combining radiomics, dosiomics and clinical features can comprehensively and accurately evaluate the radiotherapy response of NSCLC patients, and may have important clinical application value in achieving precision medicine and optimizing treatment strategies.