Objective To investigate the early diagnostic value of AI-assisted transvaginal ultrasound combined with serum biomarkers for intrauterine and ectopic combined pregnancy(heterotopic pregnancy,HP)after IVF-ET.Methods This retrospective case-control study included 86 patients diagnosed with HP after IVF-ET at Cangzhou Hospital of Integrated Traditional Chinese and Western Medicine between January 2022 and December 2024.Control groups consisted of 86 patients with normal intrauterine pregnancies and 86 patients with simple ectopic pregnancy.All patients were diagnosed through clinical diagnosis,imaging examinations,and surgical confirmation.An AI ultrasound image analysis model and serum markers(hCG,PAPP-A,APA,progesterone,PlGF)were used to jointly assess HP diagnostic efficiency.Diagnostic performance was compared by calculating sensitivity,specificity,positive predictive value,and negative predictive value.Results The AI ultrasound image analysis model's AUC was 0.835,significantly superior to traditional ultrasound(AUC=0.696).Serum hCG and PAPP-A levels were(36,210±9,820)IU/L and(0.81±0.25)μg/mL,respectively.The joint diagnostic AUC was 0.909,with a sensitivity of 94.2％,specificity of 88.4％,positive predictive value of 91.6％,and negative predictive value of 92.8％.Conclusion AI-assisted ultrasound combined with serological markers significantly improves the early diagnostic accuracy of HP,outperforming single methods and providing a reliable clinical tool.

Objective:To investigate the interactive effect of mismatch repair (MMR) protein status and adverse clinicopathological features on prognosis of stage Ⅰ-Ⅲ colon cancer.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 650 patients with colon cancer of stage Ⅰ-Ⅲ who were admitted to 7 hospitals in China from January 2016 to December 2017 were collected. There were 963 males and 687 females, aged 62(53,71)years. Patients were classified as 230 cases of MMR deficiency (dMMR) and 1 420 cases of MMR proficiency (pMMR) based on their MMR protein status. Observation indicators: (1) comparison of clinicopathological characteristics between patients of different MMR protein status; (2) analysis of factors affecting the survival outcomes of patients of dMMR; (3) analysis of factors affecting the survival outcomes of patients of pMMR; (4) interaction analysis of MMR and adverse clinicopathological features on survival outcomes. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was conducted using the independent t test. Measurement data with skewed distribution were represented as M( Q1, Q3), and comparison between groups was conducted using the Mann-Whitney U test. Count data were described as absolute numbers, and comparison between groups was conducted using the chi-square test or Fisher exact probability. Comparison of ordinal data was conducted using the Mann-Whitney U test. The random forest interpolation method was used for missing values in data interpolation. Univariate analysis was conducted using the COX proportional risk regression model, and multivariate analysis was conducted using the COX stepwise regression with forward method. The coefficient of multiplication interaction effect was obtained using the interaction term coefficient of COX proportional risk regression model. Evaluation of additive interaction effects was conducted using the relative excess risk due to interaction ( RERI). Results:(1) Comparison of clinicopathological characteristics between patients of different MMR protein status. There were significant differences in age, T staging, the number of lymph node harvest, the number of lymph node harvest <12, high grade tumor between patients of dMMR and pMMR ( P<0.05). (2) Analysis of factors affecting the survival outcomes of patients of dMMR. Results of multivariate analysis showed that T staging, N staging, the number of lymph node harvest <12 were independent factors affecting the disease-free survival (DFS) of colon cancer patients of dMMR ( hazard ratio=3.548, 2.589, 6.702, 95% confidence interval as 1.460-8.620, 1.064-6.301, 1.886-23.813, P<0.05). Age and N staging were independent factors affecting the overall survival (OS) of colon cancer patients of dMMR ( hazard ratio=1.073, 10.684, 95% confidence interval as 1.021-1.126, 2.311-49.404, P<0.05). (3) Analysis of factors affecting the survival outcomes of patients of pMMR. Results of multivariate analysis showed that age, T staging, N staging, vascular tumor thrombus were independent factors affecting the DFS of colon cancer patients of pMMR ( hazard ratio=1.018, 2.214, 2.598, 1.549, 95% confidence interval as 1.006-1.030, 1.618-3.030, 1.921-3.513, 1.118-2.147, P<0.05). Age, T staging, N staging, high grade tumor were independent factors affecting the OS of colon cancer patients of pMMR ( hazard ratio=1.036, 2.080, 2.591, 1.615, 95% confidence interval as 1.020-1.052, 1.407-3.075, 1.791-3.748, 1.114-2.341, P<0.05). (4) Interaction analysis of MMR and adverse clinicopathological features on survival outcomes. Results of interaction analysis showed that the multiplication interaction effect between the number of lymph node harvest <12 and MMR protein status was significant on DFS of colon cancer patients ( hazard ratio=3.923, 95% confidence interval as 1.057-14.555, P<0.05). The additive interaction effects between age and MMR protein status, between high grade tumor and MMR protein status were significant on OS of colon cancer patients ( RERI=-0.033, -1.304, 95% confidence interval as -0.049 to -0.018, -2.462 to -0.146). Conclusions:There is an interaction between the MMR protein status and the adverse clinicopathological features (the number of lymph node harvest <12, high grade tumor) on prognosis of colon cancer patients of stage Ⅰ-Ⅲ. In patients of dMMR, the number of lymph node harvest <12 has a stronger predictive effect on poor prognosis. In patients of pMMR, the high grade tumor has a stronger predictive effect on poor prognosis.

Objective To establish a novel clinical application process of the optical surface monitoring system(OSMS)guided volumetric modulated arc therapy(VMAT)for total body irradiation(TBI),and to assess the accuracy and effectiveness of OSMS in inter-fractional auxiliary positioning before radiotherapy and real-time monitoring of intra-fractional motion during radiotherapy.Methods A retrospective analysis was conducted on 15 leukemia patients who underwent OSMS-guided VMAT-TBI before hematopoietic stem cell transplantation.CT simulation positioning was performed,and the whole-body image data which were collected in head-first supine position(HFS)and feet-first supine position(FFS)were transmitted to the treatment planning system for image registration,multicenter VMAT planning and dose verification.The prescription dose was 800 cGy in 4 fractions twice daily.OSMS was used to assist positioning before delivery,and CBCT was used for position verification.During treatment,OSMS was used for monitoring.The intra-fractional error monitored by OSMS in real time was obtained by analyzing the offline log files.Results The mean dose and coverage of the target area in HFS plan were(905.4±19.0)cGy and 93.0%±2.8%.The mean doses to lung and kidney were(603.7±55.7)cGy and(600.4±49.6)cGy,respectively,and the maximum dose to the lens was(393.9±58.9)cGy.The mean dose and coverage of the target area in FFS plan were(888.5±58.9)cGy and 94.0%±3.2%;and the maximum dose at the junction was(1148.9±72.9)cGy.Fractional treatment delivery time was(75.1±15.1)min.OSMS-assisted positioning was carried out before delivery,and the total deviations of CBCT three-dimensional vector in translational and rotation directions were(2.71±1.96)mm and 0.91°±0.90°,respectively.The three-dimensional vector deviation of the intra-fractional motion amplitude in translational direction monitored by OSMS during the treatment was(1.95±1.88)mm,of which the deviation within 1 mm accounted for 57.5%,79.7%and 62.1%in longitudinal,lateral and vertical directions,respectively.The three-dimensional vector deviation in rotation direction was 0.76°±0.72°,of which the deviation within 1°accounted for 93.1%,85.7%and 94.3%in rotation,pitch and roll directions,respectively.Conclusion VMAT simplifies TBI process,while improving target coverage and organs-at-risk sparing.The use of OSMS can reduce positioning errors,especially rotation errors.In order to ensure the accurate implementation of TBI and the safety of patients,it is necessary to use OSMS for auxiliary positioning and intra-fractional position monitoring.

Objective:To study the impact of the Varian real-time position management (RPM) respiratory gating system on radiotherapy planning dosimetry.Methods:The radiotherapy plans of 40 cases with thoracic or abdominal tumors were retrospectively selected in this study. The motion phantom for quality control was adopted to generate respiratory gating signals, and the 30%-60% stable phase at the end of expiratory was selected as the respiratory gating window. The dose verification for the abovementioned radiotherapy plans was performed using the Portal Dosimetry (PD) system under RPM respiratory gating mode with the Edge accelerator. Afterwards, dose analysis was performed with different γ passing rate criteria and the distribution characteristics of γ values were analyzed. Finally, the verification results between the non-gating mode and the gating mode were compared.Results:Under the respiratory gating mode, the passing rates of all intensity-modulated radiation therapy/volumetric-modulated arc therapy (IMRT/VMAT) plans with or without flattening filters were over 95.5% by γ criteria of (3%, 3 mm) or (3%, 2 mm) and were over 90% by stricter γ criteria of (2%, 2 mm). All plans met the clinical requirements recommended by the American Association of Physicists in Medicine (AAPM). The passing rates of dose verification under non-gating mode were slightly better than those under respiratory gating mode, and the differences between the two modes were statistically significant (3%/3 mm, Z =-1.45; 3%/2 mm, Z =-2.86; 2%/2 mm, Z =-3.70; 1%/1 mm, Z =-4.52; P<0.05). There was no significant difference in the minimum and maximum values of γ and the share of γ > 1.5 of plan verification result under the two modes. However, the average value and standard deviation of the γ were generally smaller under the non-gating mode. Conclusions:The impact of the introduction of RPM respiratory gating technology on dose is clinically acceptable, and the execution of these plans in this gating mode is safe and reliable.

Objective:To explore the clinical data of acute rejection in kidney transplant recipients of different ages with elderly donor kidneys.Methods:During January 2012 and June 2020, a retrospective review was conducted for clinical data of 298 recipients undergoing kidney transplantation from elderly donors aged ≥60 years after citizen's death.According to the age, recipients were divided into group A(age<30 yr, 59 cases), group B(30~39 yr, 125 cases), group C(40~49 yr, 83 cases)and group D(age≥50 yr, 31 cases). The incidence of acute rejection(AR)was analyzed.Also based upon age difference between donors and recipients, they were divided into two groups of(30~39 yr)and (40~49 yr)and the occurrence of AR was recorded.Results:The incidence of AR within 1 year post-transplantation in groups A, B, C, and D were 15.3%(9/59), 8.8%(11/125), 7.2%(6/83) and 3.2%(1/31)respectively.The incidence of AR in age difference≥25 yr group(12.5%)and age difference <25 yr group(5.3%) had significant difference( P<0.05). The proportion and absolute value of peripheral blood lymphocytes in each group at 1 week/month post-transplantation had significant difference( P<0.05). No significant difference was observed in serum level of creatinine(SCr), the incidence of pulmonary infection and urinary tract infection or the survival rate of recipients and transplanted kidneys in each group within 1 year post-transplantation among four groups( P>0.05). Conclusions:Elderly donor kidneys can obtain better transplant outcomes in kidney transplant recipients of different ages.As the age of recipients decreases, AR shows an upward trend.Clinicians should pay more attention to the prevention and treatment of AR in recipients with large age difference between donors and recipients.

Objective:To explore the prognostic utility of LifePort perfusion parameters plus perfusate biomarkers for predicting delayed graft function(DGF)and recovery time during deceased donor kidney transplantation(KT).Methods:From January 1, 2019 to August 31, 2019, retrospective analysis was performed for clinical data of 113 KT recipients. Based upon whether or not DGF occurred within 3 months, they were divided into two groups of DGF group(20 cases)and non-DGF (93 cases). Two groups were compared using LifePort perfusion parameters, biomarker concentrations, incidence of DGF and kidney recovery time. Statistical analysis was performed.Results:The incidence of DGF was 17.7%(20/113); Multivariate Logistic regression results indicated that terminal resistance(OR 1.879, 95% CI 1.145~3.56)and glutathione S-transferase(GST)(OR 1.62, 95% CI 1.23~2.46)were independent risk factors for DGF; Cox hazard model revealed that terminal resistance was a risk factor for recovery time of renal function(HR=0.823, 95% CI 0.735~0.981). The model combining terminal resistance and GST(AUC=0.888, 95% CI 0.842~0.933)significantly improved the predictive efficacy for DGF as compared with using terminal resistance(AUC=0.756, 95% CI 0.693~0.818)or GST alone(AUC=0.729, 95% CI 0.591~0.806).Conclusions:Combining LifePort perfusion parameters and fluid biomarkers can improve the predictive utility of DGF.

BACKGROUND: Delayed graft function (DGF) is the main cause of renal function failure after kidney transplantation. This study aims at investigating the value of hypothermic machine perfusion (HMP) parameters combined with perfusate biomarkers on predicting DGF and the time of renal function recovery after deceased donor (DD) kidney transplantation. METHODS: HMP parameters, perfusate biomarkers and baseline characteristics of 113 DD kidney transplantations from January 1, 2019 to August 31, 2019 in the First Affiliated Hospital of Xi'an Jiaotong University were retrospectively analyzed using univariate and multivariate logistic regression analysis. RESULTS: In this study, the DGF incidence was 17.7% (20/113); The multivariate logistic regression results showed that terminal resistance (OR: 1.879, 95% CI 1.145-3.56) and glutathione S-transferase (GST)(OR = 1.62, 95% CI 1.23-2.46) were risk factors for DGF; The Cox model analysis indicated that terminal resistance was an independent hazard factor for renal function recovery time (HR = 0.823, 95% CI 0.735-0.981). The model combining terminal resistance and GST (AUC = 0.888, 95% CI: 0.842-0.933) significantly improved the DGF predictability compared with the use of terminal resistance (AUC = 0.756, 95% CI 0.693-0.818) or GST alone (AUC = 0.729, 95% CI 0.591-0.806). CONCLUSION According to the factors analyzed in this study, the combination of HMP parameters and perfusate biomarkers displays a potent DGF predictive value.
Biomarkers ; Delayed Graft Function ; Graft Survival ; Humans ; Kidney/physiology* ; Kidney Transplantation/adverse effects* ; Organ Preservation ; Perfusion ; Retrospective Studies ; Tissue Donors

Objective To analyze the prediction efficiency of scoring models at home and abroad on delayed graft function (DGF) after renal transplantation in China. Methods The clinical data of 112 donors and 220 recipients undergoing renal transplantation were prospectively analyzed. The DGF predicted by KDRI model, Jeldres model, and model of our center was compared with actual DGF incidence of renal transplant recipients. The prediction efficiency of each model was analyzed. The predictive accuracy was compared by the area under curve (AUC) of receiver operating characteristic (ROC) curve. Results The DGF incidence of 220 renal transplant recipients was 14.1% (31/220). DGF prediction using KDRI model showed that 41 cases were high risk donors, the AUC was 0.57, the sensitivity was 0.37, the specificity was 0.66, and the positive predictive value was 22%. DGF prediction using Jedres model showed that 22 cases were high risk recipients, the AUC was 0.56, the sensitivity was 0.13, the specificity was 0.92 and the positive predictive value was 20%. DGF prediction using the model of our center showed that 25 cases were high risk donors, the AUC was 0.80, the sensitivity was 0.53, the specificity was 0.84, the positive predictive value was 40%. Conclusions Compared with the KDRI and Jedres models, the prediction model of our center has higher AUC and sensitivity with a better prediction efficiency on DGF. Therefore, it is a suitable evaluation system of donors from donation after citizen's death in Chinese.

Objective To compare the clinical efficacy of different T lymphocyte polyclonal antibodies in renal transplantation from donor kidney of organ donation after citizen's death. Methods Clinical data of 691 donors and recipients undergoing renal transplantation from donor kidney of organ donation after citizen's death were retrospectively analyzed. According to different T lymphocyte polyclonal antibodies used for induction, all recipients were divided into the rabbit anti human T lymphocyte immunoglobulin (rALG) group (n=414) and rabbit anti human thymocyte immunoglobulin (rATG) group (n=277). The recovery of renal graft function in recipients of the two groups were collected, including the incidence of delayed graft function (DGF) and acute rejection (AR), and the changes of serum creatinine level after renal transplantation. The 1-year survival rate of the recipients and renal grafts was collected. The incidence of adverse effects within 1 year after operation was calculated. According to the DGF risk score of donors, all recipients were divided into 5 groups. The use proportion of rALG and rATG in the recipients of each group was calculated. Results The incidence of DGF in the recipients of rALG and rATG groups was 14.5% (60/414) and 11.9% (33/277), respectively. The duration of DGF in the recipients of rALG and rATG groups was (7±4) d and (12±7) d respectively, with no statistically significant difference between two groups (P > 0.05). The incidence of AR in the rALG group was 7.5% (31/414), significantly higher than 4.0% (11/277) in the rATG group (P < 0.05). The serum creatinine levels of recipients within 6 months after renal transplantation tended to gradually decline in both groups. In renal transplantation for donor kidney with a DGF risk score of 0-15, the use proportion of rALG was significantly higher than that of rATG. However, the use proportion of rATG was significantly higher than that of rALG in renal transplantation for donor kidney with a DGF risk score over 16 (P < 0.05). The 1-year survival rates of the recipients and renal grafts in the rALG and rATG groups were 99.8% and 99.6%, 98.1% and 98.2%, respectively. There was no significant difference between two groups (both P > 0.05). The incidence of acute pulmonary edema and leukopenia in the recipients of rATG group was significantly higher than that in the rALG group (both P < 0.05). Conclusions Both rALG and rATG can effectively reduce the incidence of DGF and AR and achieve good clinical efficacy after renal transplantation from donor kidney of organ donation after citizen's death. The incidence of leukopenia and acute pulmonary edema induced by rATG is higher than that by rALG in the renal transplant recipients.

Objective To evaluate the clinical effect of hypothermic machine perfusion (HMP) in the storage of renal grafts from deceased donor (DD) with high-risk delayed graft function (DGF). Methods Clinical data of 52 donors with high-risk DGF were collected in this prospective randomized controlled study. Two renal grafts from each donor were randomly divided into the HMP group (n=52) and static cold storage (SCS) group (n=52). In the HMP group, the renal grafts were stored by LifePort under HMP, whereas the renal grafts in the SCS group were preserved in University of Wisconsin solution (UW solution). The incidence of DGF and primary nonfunction (PNF) after renal transplantation was statistically compared between two groups. The recovery of renal graft function, the survival rates of the recipients and renal grafts within postoperative 1 year were observed in two groups. Results The incidence of DGF in the HMP group was 4%(2/52), significantly lower than 17% (9/52) in the SCS group (P < 0.05). No PNF was reported in the HMP group and 1 case of PND was noted in the SCS group, the difference was not statistically significant (P > 0.05). The recovery time of graft function of the recipients in the HMP and SCS groups were (7.2±0.6) d and (7.7±1.0) d with no statistical significance (P > 0.05). In the HMP group, the urine volume of the recipients on the day of operation, postoperative 1 and2 d was significantly larger than that in the SCS group (all P < 0.05). In the HMP group, the levels of serum creatinine at each time point after operation were significantly lower than those in the SCS group (all P < 0.05). The 1-year survival rates of the recipient and kidney were 98.1%, 92.3% and 100%, 96.2% in the HMP and SCS groups with no statistical significance (all P > 0.05). Conclusions HMP can significantly reduce the incidence of DGF after renal transplantation from DD with high-risk DGF and promote the early recovery of graft function.