Objective To systematically review the studies on predictive models for delayed graft function (DGF) after kidney transplantation. Methods Databases including China Biology Medicine Database, China National Knowledge Infrastructure, Wanfang Database, VIP Database, PubMed, Web of Science and CINAHL were searched to collect studies on predictive models for DGF after kidney transplantation published from the establishment of each database to June 29, 2025. Two researchers screened the literatures according to the inclusion and exclusion criteria, evaluated the quality of the literatures using the prediction model risk of bias assessment tool (PROBAST), and conducted a meta-analysis of the common predictors of the models using R software. Results A total of 12 literatures were included, involving 14 predictive models with sample sizes ranging from 103 to 24 653 cases. Donor serum creatinine level, cold ischemia time, donor age and donor body mass index were the top four common predictors. All the predictive models were at high risk of bias and low in applicability. The results of meta-analysis showed that abnormal donor body mass index, advanced donor age, prolonged cold ischemia time and elevated donor serum creatinine level were all associated with an increased risk of DGF after transplantation (all P<0.01), but there was high heterogeneity among the studies. Fixed-effect model and random-effect model were used to re-pool the effect sizes separately. The results indicated that the fixed-effect model and random-effect model had good consistency in terms of donor body mass index, donor age and cold ischemia time, while there was a significant difference in the effect sizes of the two models for donor serum creatinine level. Conclusions The predictive models for DGF risk after kidney transplantation have good predictive performance, but the overall risk of bias is high. In the future, large-sample, multicenter and high-quality prospective clinical studies should be carried out to optimize the predictive models, so as to improve their predictive ability and clinical application value.

Objective To compare the efficacy and tolerability of the novel bowel-cleansing agent TCIC-001 and the traditional polyethylene glycol (PEG) regimen for bowel preparation prior to colonoscopy. Methods Prospective inclusion of 62 patients who were scheduled to undergo colonoscopy at Zhongshan Hospital, Fudan University from July 2021 to July 2022. They were randomly divided into TCIC-001 group (n=31) and PEG group (n=31) using a random number table method. The TCIC-001 group took TCIC-001 orally, drinking water in stages, with a total liquid intake of 1 500 mL; the PEG group took PEG orally, taking it in 4 doses, with a total liquid intake of 3 000 mL. The primary endpoint indicator is the quality of intestinal hygiene evaluated by the Boston Bowel Preparation Scale (BBPS), the secondary endpoint indicators were medication adherence, medication duration, frequency of bowel movements, duration of bowel movements, and incidence of adverse events between two groups. Results No significant differences were observed in sex, age, or defecation frequency between the two groups. For efficacy, both groups achieved equivalent bowel cleanliness, with a “good preparation” rate of 93.55% and comparable BBPS score of each intestinal segment and total scores. For tolerability, the TCIC-001 group had a shorter medication duration compared to the PEG group ([48.8±25.9] min vs [82.8±28.4] min, P<0.001), a longer defecation duration ([288.6±74.0] min vs [236.5±74.3] min, P<0.001), and a lower incidence of first defecation before medication completion (9.68% vs 41.94%, P=0.004). Regarding safety, no significant differences were observed between the TCIC-001 group and the PEG group in incidences of chloride disturbances (0% vs 9.68%) and calcium disturbances (3.23% vs 6.45%), and no other adverse events. Conclusions TCIC-001 demonstrated comparable bowel-cleansing efficacy to PEG while significantly improving tolerability (reduced medication time and lower risk of premature defecation) and maintaining favorable safety.

BACKGROUND: Several studies have demonstrated the occurrence of secondary tumors as a rare but significant complication of chimeric antigen receptor T (CAR-T) cell therapy, underscoring the need for a detailed investigation. Given the limited variety of secondary tumor types reported to date, a comprehensive characterization of the various secondary tumors arising after CAR-T therapy is essential to understand the associated risks and to define the role of the immune microenvironment in malignant transformation. This study aims to characterize the immune microenvironment of a newly identified secondary tumor post-CAR-T therapy, to clarify its pathogenesis and potential therapeutic targets. METHODS: In this study, the bone marrow (BM) samples were collected by aspiration from the primary and secondary tumors before and after CD19 CAR-T treatment. The CD45 + BM cells were enriched with human CD45 microbeads. The CD45 + cells were then sent for 10× genomics single-cell RNA sequencing (scRNA-seq) to identify cell populations. The Cell Ranger pipeline and CellChat were used for detailed analysis. RESULTS: In this study, a rare type of secondary chronic myelomonocytic leukemia (CMML) were reported in a patient with diffuse large B-cell lymphoma (DLBCL) who had previously received CD19 CAR-T therapy. The scRNA-seq analysis revealed increased inflammatory cytokines, chemokines, and an immunosuppressive state of monocytes/macrophages, which may impair cytotoxic activity in both T and natural killer (NK) cells in secondary CMML before treatment. In contrast, their cytotoxicity was restored in secondary CMML after treatment. CONCLUSIONS This finding delineates a previously unrecognized type of secondary tumor, CMML, after CAR-T therapy and provide a framework for defining the immune microenvironment of secondary tumor occurrence after CAR-T therapy. In addition, the results provide a rationale for targeting macrophages to improve treatment strategies for CMML treatment.
Humans ; Lymphoma, Large B-Cell, Diffuse/therapy* ; Tumor Microenvironment/genetics* ; Antigens, CD19/metabolism* ; Leukemia, Myelomonocytic, Chronic/genetics* ; Immunotherapy, Adoptive/adverse effects* ; Male ; Single-Cell Analysis/methods* ; Female ; Sequence Analysis, RNA/methods* ; Receptors, Chimeric Antigen ; Middle Aged

Objective To construct a prediction model for the progression of knee osteoarthritis(KOA)based on ultrasound score,magnetic resonance imaging(MRI)score,and serum levels of transforming growth factor-β1(TGF-β1)and cathepsin D(Cat D).Methods Clinical data from 270 patients with KOA in Hengshui People's hospital from December 2022 to June 2024 were retrospec-tively analyzed.The patients were randomly divided into a modeling set(n=189)and validation set(n=81)at a ratio of 7∶3.The patients in the modeling set were categorized into mild-to-moderate and severe groups based on the degree of disease progression.Mul-tivariate logistic regression analysis was used to identify factors influencing KOA progression,and a prediction model was constructed using R software.Results Multivariate logistic regression analysis showed that body mass index,knee injury history,ultrasound score,WORMS score,TGF-β1,and Cat D were significant predictors of KOA progression(P＜0.05).A nomogram-based prediction model was developed using these variables.The areas under the curve(AUC)of the nomograms for predicting disease progression in the modeling and validation sets were 0.889 and 0.860,respectively.The calibration curves showed that the predicted probability was in good agreement with the actual probability.Conclusion The prediction model developed in this study is effective in identifying patients at high-risk of KOA progression and may servce as a valuable tool for clinical assessment and decision making.

Objective To construct a prediction model for the progression of knee osteoarthritis(KOA)based on ultrasound score,magnetic resonance imaging(MRI)score,and serum levels of transforming growth factor-β1(TGF-β1)and cathepsin D(Cat D).Methods Clinical data from 270 patients with KOA in Hengshui People's hospital from December 2022 to June 2024 were retrospec-tively analyzed.The patients were randomly divided into a modeling set(n=189)and validation set(n=81)at a ratio of 7∶3.The patients in the modeling set were categorized into mild-to-moderate and severe groups based on the degree of disease progression.Mul-tivariate logistic regression analysis was used to identify factors influencing KOA progression,and a prediction model was constructed using R software.Results Multivariate logistic regression analysis showed that body mass index,knee injury history,ultrasound score,WORMS score,TGF-β1,and Cat D were significant predictors of KOA progression(P＜0.05).A nomogram-based prediction model was developed using these variables.The areas under the curve(AUC)of the nomograms for predicting disease progression in the modeling and validation sets were 0.889 and 0.860,respectively.The calibration curves showed that the predicted probability was in good agreement with the actual probability.Conclusion The prediction model developed in this study is effective in identifying patients at high-risk of KOA progression and may servce as a valuable tool for clinical assessment and decision making.

Purpose: To determine the non-contrast computer tomography imaging features of pyonephrosis and evaluate the predictive value of Hounsfield units (HUs) in different hydronephrotic region slices. Materials and Methods: We retrospectively reviewed data from patients with hydronephrosis who had renal-ureteral calculi. All patients were categorized into pyonephrosis and simple hydronephrosis groups. Baseline characteristics, the mean HU values in the maximal hydronephrotic region (uHU) slice, and the range of uHU in different slices (△uHU) were compared between the two groups. Univariate and multivariate analyses were performed to identify risk factors for pyonephrosis. Results: Among the 181 patients enrolled in the current study, 71 patients (39.2%) were diagnosed with pyonephrosis. The mean dilated pelvis surface areas were comparable between patients with pyonephrosis and simple hydronephrosis (822.61 ㎟ vs.877.23 ㎟ , p=0.722). Collecting system debris (p=0.022), a higher uHU (p=0.038), and a higher △uHU (p<0.001) were identified as independent risk factors for pyonephrosis based on multivariate analysis. The △uHU sensitivity and specificity were 88.7% and 86.4%, respectively, at a cutoff value of 6.56 (p<0.001), whereas the sensitivity and specificity for detecting pyonephrosis at a uHU cutoff value of 7.96 was 50.7% and 70.9%, respectively (p=0.003). Conclusions Non-contrast computer tomography was shown to accurately distinguish simple hydronephrosis from pyonephrosis in patients with obstructive uropathy. Evaluation of the △uHU in different slices may be more reliable than the uHU acquired from a single slice in predicting pyonephrosis.

Objective To construct,implement and evaluate the effectiveness of the virtual simulation technology-based prenatal health education course.Methods The curriculum included 4 parts:"warm delivery room and easy delivery","medicated analgesic delivery","non-medicated analgesic delivery"and"early maternal and infant health care".From May to September 2022,100 primiparas in an obstetrics and gynecology hospital in Zhejiang Province were investigated by convenient sampling method.Random number table method was used to divide the participants into an experimental group and a control group,with 50 participants per group.The control group received conventional health education,while the experimental group received an augmented virtual reality technology-based prenatal health education course during the late stages of pregnancy on this basis.We conducted a post-intervention comparative analysis of antenatal anxiety levels,fear of childbirth,and birth outcomes between the 2 groups.Furthermore,a post-intervention satisfaction survey was administered to the experimental group.Results After intervention,the antenatal anxiety of the experimental group was lower than that of the control group(x2=4.943,P=0.026),and the decrease in fear of childbirth scores was higher than that of the control group(t=3.200,P=0.002).The experimental group was highly satisfied with all of the 4 dimensions of the course,and the overall evaluation was(31.8±3.23)points.However,there were no significant differences in vaginal delivery rate,postpartum bleeding volume,postpartum hemorrhage incidence,perineal injury degree and duration of each labor stage between the 2 groups(P＞0.05).Conclusion The virtual reality technology-based prenatal health education course was effective in improving the antenatal anxiety and fear of childbirth of primipara,and the use satisfaction is high.

Objective To explore the value of dynamic ultrasound combined with 3.0T MRI for diagnosing and typing synovial plica of knee joint.Methods Dynamic ultrasound and 3.0T MRI data of 100 patients with suspected synovial plica of knee joint were retrospectively analyzed.Taking the results of arthroscopy as standards,the efficacy of dynamic ultrasound and 3.0T MRI alone and their combination for diagnosing synovial plica of knee joint were evaluated and compared.The length and thickness of synovial plica of knee joint measured with dynamic ultrasound,3.0T MRI alone and their combination were compared with those of arthroscopy,and the consistencies of the location and classification of synovial plica of knee joint with arthroscopy were analyzed.Results Synovial plica was detected in 70 cases,including 11 cases of supropatellar synovial plica,15 cases of infrapatellar synovial plica,medial patellar in 30 cases and lateral patellar synovial plica in 14 cases,among them type A,B,C and D were classified in 9,35,23 and 3 cases,respectively.No significant difference of sensitivity was found between dynamic ultrasound and 3.0T MRI alone for diagnosing synovial plica of knee joint(P＞0.05),which were both lower than that of their combination(both P＜0.05).The length and thickness of knee synovial plica measured with dynamic ultrasound and 3.0T MRI alone were lower than those measured with their combination and arthroscopy(all P＜0.05),and there was no significant difference between the results of their combination and arthroscopy(both P＞0.05).Dynamic ultrasound,3.0T MRI alone and their combination had high consistency of location(Kappa=0.755,0.826,0.897)and classification of knee synovial plica with those of arthroscopy(Kappa=0.721,0.744,0.860).Conclusion Dynamic ultrasound combined with 3.0T MRI was valuable for diagnosing and typing of synovial plica of knee joint.

Objective To study the splenic injuries caused by high-altitude falling and underwater explosion and the 2-dimensional ultrasound and contrast-enhanced ultrasound(CEUS)characteristics.Methods Twenty-three healthy Beagle dogs were divided into high-altitude falling group(n=13)and underwater explosion group(n=10).Free-fall high-platform device and gram-grade trinitrotoluene were used to simulate high-altitude falling injury and underwater explosion injury in Beagle dogs,respectively.Ultrasound examination of the spleen was performed immediately after injury,with follow-up examinations every hour.CEUS examination was performed in surviving dogs.Spleen specimens were taken from deceased dogs after injury to observe gross injuries.Pathological changes in tissue morphology and cell apoptosis were observed by hematoxylin-eosin(H-E)staining.Results In the high-altitude falling model,6,2,1,and 1 dogs died in the 6 m,7 m,8 m,and 9 m groups,respectively;in the underwater explosion model,1 and 4 dogs died in the buoyancy and frogman groups,respectively.Two-dimensional ultrasound examination of the high-altitude falling model showed spleen rupture(disruption of splenic parenchymal structure),perisplenic fluid accumulation,subcapsular hematoma,intrasplenic hematoma,increased splenic vein echo,and uneven splenic parenchymal echo.Two-dimensional ultrasound examination of the underwater explosion model showed increased splenic vein echo and uneven splenic parenchymal echo,which were less serious compared with the high-altitude falling model.CEUS results indicated 4 major contrast patterns in both models.The Beagle dogs with type Ⅰ(large focal contrast defect),type Ⅱ(diffuse contrast defect),or type Ⅲ(no contrast agent entry into the splenic vein)contrast patterns all had splenic rupture after injury.H-E staining results showed true splenic rupture,diffuse intrasplenic hemorrhage,splenic hematoma/ecchymosis,subcapsular hematoma/ecchymosis,and venous congestion after spleen injury,which were consistent with the 2-dimensional ultrasound findings.Conclusion High-altitude falling causes more serious spleen injuries in Beagle dogs compared with underwater explosions.Routine ultrasound performs well in diagnosing typical splenic injuries,while CEUS has advantages in evaluating atypical splenic injuries and has good predictive ability for delayed splenic rupture.