[Objective] To establish a new scoring system to predict the perioperative outcomes (operation time, intraoperative blood loss, and trifecta achievement) in patients undergoing robot-assisted partial nephrectomy (RAPN) by integrating the RENAL and Mayo adhesive probability (MAP) scores. [Methods] Clinical data of 178 patients with renal cell carcinoma who underwent RAPN performed by the same surgeon in our hospital during Jan.2015 and Jan.2022 were retrospectively analyzed.The RENAL and MAP scores of all patients were calculated.Linear regression and logistic regression were used to evaluate the associations between the components of the RENAL and MAP scores (a total of 6 variables) and perioperative outcomes.The factors with significant associations were then included into logistic regression analysis to identify independent predictors for constructing an assessment system for perioperative outcomes, and the receiver operating characteristic (ROC) curve was plotted to calculate the area under the curve (AUC) to predict its efficacy. [Results] Multivariate linear regression analysis showed that tumor size (β=6.14, 95%CI: 1.93—10.34, P=0.004), exophytic rate (β=10.60, 95%CI: 3.44—17.76, P=0.004), and perinephric fat thickness (β=16.48, 95%CI: 8.52—24.45, P<0.001) were significantly associated with operation time.Tumor size (β=10.55 95%CI: 5.60—15.49, P<0.001) was associated with both intraoperative blood loss and trifecta achievement (OR=1.73, 95%CI: 1.26—2.36, P=0.001). Multivariate logistic regression analysis of these 3 factors identified tumor size (OR=9.07, 95% CI: 1.18—69.45, P=0.03) and perinephric fat thickness (OR=2.28, 95%CI: 1.86—6.04, P=0.01) as independent predictors of perioperative outcomes.Based on these findings, the tumor size and perinephric fat thickness (RP) scoring was constructed, which demonstrated better predictive ability than RENAL score or MAP score alone (RP vs.RENAL vs.MAP: 0.766 vs.0.548 vs.0.684). [Conclusion] The RP score includes fewer variables than the RENAL and MAP scores but outperforms them.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

Objective:To compare demographic characteristics,clinical characteristics,therapeutic characteris-tics and physiological indicators of patients with bipolar Ⅰ disorder and bipolar Ⅱ disorder.Methods:A total of 381 patients with bipolar disorder(BD)diagnosed by the Diagnostic and Statistical Manual of Mental Disorders 5 th Edi-tion(DSM-5)were selected,including 302 patients with BD-Ⅰ(79.27％),74 patients with BD-Ⅱ(19.42％)and 5 patients with other specific and related disorders(1.31％).Demographic and clinical characteristics were collected with self-designed clinical information questionnaire.Multivariate logistic regression and multivariate linear regres-sion analysis were used for analysis.Results:Compared with patients with BD-Ⅱ,patients with BD-Ⅰ had more risk to have psychotic features(OR=5.75,95％CI:2.82-11.76),longer disease duration,and more repeated transcra-nial magnetic therapy(OR=3.09,95％CI:1.02-9.35),higher uric acid,total cholesterol and high-density lipo-protein.BD-Ⅰ in Han nationality was more common(OR=11.50,95％CI:1.76-75.30),and had lower education level(OR=10.22,95％CI:1.16-89.77),and less family history of psychosis(OR=2.34,95％CI:1.01-5.42).Conclusion:There are significant differences between BD-Ⅰ and BD-Ⅱ in demographic and clinical charac-teristics,treatment status,and physiological indicators,which could provide clues for exploring the pathogenesis of bipolar disorder.

Objective:To evaluate the efficacy of cerebral-placental-uterine ratio(CPUR)in predicting late-on-set fetal growth restriction(FGR).Methods:From May 2020 to May 2021,1255 women with singleton pregnancy who underwent prenatal examinations at the University of Hong Kong Shenzhen Hospital were selected for fetal growth and Doppler measurements at 35-37 +6 weeks of gestation.Pregnant women with birth weight of newbo-rns＜the 10th percentile were the FGR group.The pulsatility index(PI)of uterine artery(UtA),umbilical artery(UA)and fetal middle cerebral artery(MCA)were analyzed separately and in combination.ROC curve was used to analyze the cerebral-placental-uterine ratio(CPUR),cerebral-placental ratio(CPR),cerebral-uterine ratio(C-UtA)for predicting late-onset FGR;and to evaluate the sensitivity,positive and negative predictive value and of CPUR in the prediction of late-onset FGR.Results:The area under the curve(AUC)of CPUR,CPR,C-UtA and mean UtA-PI for FGR grope were 0.88,0.86,0.84 and 0.72.Under certain cut-off values and 87% specificity,the specificity of CPUR,CPR,C-UtA and mean UtA-Pifor predicting FGR group was 43.2%,46.6%,39.8% and 23.9%,respectively.The positive predictive values of CPUR,CPR,C-UtA and mean UtA-PI,UA-PI for predicting FGR group were 90.5%,71.9%,83.3%,63.6%and 5.2%,respectively.Conclusions:CPUR is more effective in predicting late onset FGR than CPR,C-UtA and mean UtA-PI.It can effectively increase the detection rate of fetal growth restrictionand reduce the FGR risk.

Objective To explore the expression of serum fatty acid-binding protein 4(FABP4)and fibroblast growth factor 19(FGF19)in patients with β-thalassemia and their relationship with clinical prognosis.Methods A total of 112 cases ofβ-thalassemia patients diagnosed and treated in Qianjiang Hospital Affiliated to Chongqing University from January 2018 to August 2020 were selected as the case group,and 60 healthy individuals who underwent physical examinations during the same period were taken as the control group.Enzyme-linked immunosorbent assay was used to detect levels of serum FABP4 and FGF19 expression.Multivariate logistic regression analysis was used to analyze factors affecting the prognosis of patients with β-thalassemia.Receiver operating characteristic curve was used to analyze the prognostic value of FABP4 and FGF19 in patients with β-thalassemia.Results The serum FABP4 level(67.13±11.35 μg/L)in the case group was higher than that in the control group(22.01±4.16μg/L),while the serum FGF19 level(104.24±21.46 ng/L)was lower than that in the control group(218.01±36.79 ng/L),with significant differences(t=29.708,25.620,all P＜0.05).The serum FABP4 levels(54.20±12.63 μ g/L,66.83±10.5 μ g/L,79.72±11.05 μ g/L)in the mild group,intermediate group,and severe group were increased sequentially,while FGF19 levels(122.53±22.36 ng/L,103.16±20.37 ng/L,86.53±18.14 ng/L)were decreased sequentially,and the differences were significant(F=39.701,24.231,all P＜0.05).Compared to the survival group,serum FGF19 level(62.80±22.09 ng/L vs 110.16±20.69 ng/L),Hb and the proportion of heterozygous genotypes in the death group patients(β CD17/β N,β CD41-42/β N)was lower,while serum FABP4(116.69±12.30 ng/L vs 60.05±10.17 ng/L),ferritin and the proportion of cardiac enlargement were higher,with significant differences(t/x2=4.436～18.981,all P＜0.05).FGF19(OR=0.634,95％CI:0.451～0.891)was an independent protective factor for β-thalassemia patients(P＜0.001),and serum FABP4(OR=1.840,95％CI:1.193～2.838)was an independent risk factor for prognosis(P＜0.001).The area under the curve(95％CI)of serum FABP4 and FGF19 combination in prognosis evaluation for β-thalassemia patients was 0.897(0.853～0.951),which was greater than the single serum indicator detection of 0.842(0.801～0.879)and 0.814(0.762～0.858),with significant differences(Z=4.864,5.270,P=0.002,0.001).Conclusion The serum FABP4 expression is increased,but serum FGF19 expression is decreased in patients with β-thalassemia.The combination of serum FABP4 and FGF19 may have a high predictive value for the prognosis of patients with β-thalassemia.

Objective To investigate the risk factors of in-hospital mortality and establish a risk prediction model for patients receiving venoarterial extracorporeal membrane oxygenation(VA-ECMO).Methods We retrospectively collected the data of 302 patients receiving VA-ECMO in ICU of 3 hospitals in Guangdong Province between January,2015 and January,2022 using a convenience sampling method.The patients were divided into a derivation cohort(201 cases)and a validation cohort(101 cases).Univariate and multivariate logistic regression analyses were used to analyze the risk factors for in-hospital death of these patients,based on which a risk prediction model was established in the form of a nomogram.The receiver operator characteristic(ROC)curve,calibration curve and clinical decision curve were used to evaluate the discrimination ability,calibration and clinical validity of this model.Results The in-hospital mortality risk prediction model was established based the risk factors including hypertension(OR=3.694,95%CI:1.582-8.621),continuous renal replacement therapy(OR=9.661,95%CI:4.103-22.745),elevated Na2+ level(OR=1.048,95%CI:1.003-1.095)and increased hemoglobin level(OR=0.987,95%CI:0.977-0.998).In the derivation cohort,the area under the ROC curve(AUC)of this model was 0.829(95%CI:0.770-0.889),greater than those of the 4 single factors(all AUC<0.800),APACHE Ⅱ Score(AUC=0.777,95%CI:0.714-0.840)and the SOFA Score(AUC=0.721,95%CI:0.647-0.796).The results of internal validation showed that the AUC of the model was 0.774(95%CI:0.679-0.869),and the goodness of fit test showed a good fitting of this model(χ2=4.629,P>0.05).Conclusion The risk prediction model for in-hospital mortality of patients on VA-ECMO has good differentiation,calibration and clinical effectiveness and outperforms the commonly used disease severity scoring system,and thus can be used for assessing disease severity and prognostic risk level in critically ill patients.

Objective:To retrospectively analyze the treatment status of tyrosine kinase inhibitors (TKI) in newly diagnosed patients with chronic myeloid leukemia (CML) in China.Methods:Data of chronic phase (CP) and accelerated phase (AP) CML patients diagnosed from January 2006 to December 2022 from 77 centers, ≥18 years old, and receiving initial imatinib, nilotinib, dasatinib or flumatinib-therapy within 6 months after diagnosis in China with complete data were retrospectively interrogated. The choice of initial TKI, current TKI medications, treatment switch and reasons, treatment responses and outcomes as well as the variables associated with them were analyzed.Results:6 893 patients in CP ( n=6 453, 93.6%) or AP ( n=440, 6.4%) receiving initial imatinib ( n=4 906, 71.2%), nilotinib ( n=1 157, 16.8%), dasatinib ( n=298, 4.3%) or flumatinib ( n=532, 7.2%) -therapy. With the median follow-up of 43 ( IQR 22-75) months, 1 581 (22.9%) patients switched TKI due to resistance ( n=1 055, 15.3%), intolerance ( n=248, 3.6%), pursuit of better efficacy ( n=168, 2.4%), economic or other reasons ( n=110, 1.6%). The frequency of switching TKI in AP patients was significantly-higher than that in CP patients (44.1% vs 21.5%, P<0.001), and more AP patients switched TKI due to resistance than CP patients (75.3% vs 66.1%, P=0.011). Multi-variable analyses showed that male, lower HGB concentration and ELTS intermediate/high-risk cohort were associated with lower cytogenetic and molecular responses rate and poor outcomes in CP patients; higher WBC count and initial the second-generation TKI treatment, the higher response rates; Ph + ACA at diagnosis, poor PFS. However, Sokal intermediate/high-risk cohort was only significantly-associated with lower CCyR and MMR rates and the poor PFS. Lower HGB concentration and larger spleen size were significantly-associated with the lower cytogenetic and molecular response rates in AP patients; initial the second-generation TKI treatment, the higher treatment response rates; lower PLT count, higher blasts and Ph + ACA, poorer TFS; Ph + ACA, poorer OS. Conclusion:At present, the vast majority of newly-diagnosed CML-CP or AP patients could benefit from TKI treatment in the long term with the good treatment responses and survival outcomes.

Background::Cardiovascular disease (CVD) has emerged as the leading cause of death from prostate cancer (PCa) in recent decades, bringing a great disease burden worldwide. Men with preexisting CVD have an increased risk for major adverse cardiovascular events when treated with androgen deprivation therapy (ADT). The present study aimed to explore the prevalence and risk evaluation of CVD among people with newly diagnosed PCa in China.Methods::Clinical data of newly diagnosed PCa patients were retrospectively collected from 34 centers in China from 2010 to 2022 through convenience sampling. CVD was defined as myocardial infarction, arrhythmia, heart failure, stroke, ischemic heart disease, and others. CVD risk was estimated by calculating Framingham risk scores (FRS). Patients were accordingly divided into low-, medium-, and high-risk groups. χ2 or Fisher’s exact test was used for comparison of categorical variables. Results::A total of 4253 patients were enrolled in the present study. A total of 27.0% (1147/4253) of patients had comorbid PCa and CVD, and 7.2% (307/4253) had two or more CVDs. The enrolled population was distributed in six regions of China, and approximately 71.0% (3019/4253) of patients lived in urban areas. With imaging and pathological evaluation, most PCa patients were diagnosed at an advanced stage, with 20.5% (871/4253) locally progressing and 20.5% (871/4253) showing metastasis. Most of them initiated prostatectomy (46.6%, 1983/4253) or regimens involving ADT therapy (45.7%, 1944/4253) for prostate cancer. In the present PCa cohort, 43.1% (1832/4253) of patients had hypertension, and half of them had poorly controlled blood pressure. With FRS stratification, as expected, a higher risk of CVD was related to aging and metabolic disturbance. However, we also found that patients with treatment involving ADT presented an originally higher risk of CVD than those without ADT. This was in accordance with clinical practice, i.e., aged patients or patients at advanced oncological stages were inclined to accept systematic integrative therapy instead of surgery. Among patients who underwent medical castration, only 4.0% (45/1118) received gonadotropin releasing hormone antagonists, in stark contrast to the grim situation of CVD prevalence and risk.Conclusions::PCa patients in China are diagnosed at an advanced stage. A heavy CVD burden was present at the initiation of treatment. Patients who accepted ADT-related therapy showed an original higher risk of CVD, but the awareness of cardiovascular protection was far from sufficient.

Background::Breast cancer is ranked among the most prevalent malignancies in the Chinese female population. However, comprehensive reports detailing the latest epidemiological data and attributable disease burden have not been extensively documented.Methods::In 2018, high-quality cancer surveillance data were recorded in 700 population-based cancer registries in China. We extracted data on female breast cancers (International Classification of Diseases, Tenth Revision [ICD-10]: C50) and estimated the incidence and mortality in 2022 according to the baseline data and corresponding trends from 2010 to 2018. Pathological types were classified according to the ICD for Oncology, 3rd Edition codes. Disability-adjusted life years (DALYs) were calculated as the sum of the years of life lost (YLLs) and years lived with disability (YLDs).Results::In 2022, approximately 357,200 new female breast cancer cases and 75,000 deaths occurred in China, accounting for 15.59% and 7.94% of total new cancer cases and deaths, respectively. The age-standardized incidence rate (ASIR) was 33.04 per 100,000. When analyzed by pathological type, the ASIRs for papillary neoplasms, invasive breast carcinoma, rare and salivary gland-type tumors, and other types were 1.13, 29.79, 0.24, and 1.88 per 100,000, respectively. The age-standardized mortality rate (ASMR) was 6.10 per 100,000. A total of 2,628,000 DALYs were found to be attributable to female breast cancer in China, comprising 2,278,300 YLLs and 349,700 YLDs. The ASIR, ASMR, and age-standardized rate (ASR) for DALYs in urban areas were consistently higher than those in rural areas. We observed a four-fold increase in the ASIR and ASR for DALYs and an eight-fold increase in the ASMR among females over 55 years compared with those aged under 55 years.Conclusion::These data provide invaluable insights into the latest epidemiology of female breast cancer in China and highlight the urgency for disease prevention and control strategy formulation.

Objective:To comprehensively understand the disease burden of liver cirrhosis and other chronic liver diseases caused by alcohol use in China from 1990 to 2019, as well as to predict the trends in disease burden from 2020 to 2030.Methods:The analysis utilized data from the Global Burden of Disease study in 2019 (GBD2019). Key indicators such as incidence rate, mortality rate, disability-adjusted life years (DALY), years of life lost due to premature mortality, and years lived with disability were selected to describe the disease burden of alcohol-related liver cirrhosis and other chronic liver diseases in China from 1990 to 2019. The estimated annual percentage change (EAPC) was used to depict the temporal trends in disease burden. Furthermore, a Bayesian age-period-cohort (BAPC) model was constructed using R software to predict the age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR) of alcohol-related liver cirrhosis and other chronic liver diseases in China from 2020 to 2030.Results:From 1990 to 2019, the incidence of alcohol-related liver cirrhosis and other chronic liver diseases in China showed an upward trend, with an EAPC of 0.31% (95% CI: 0.10%-0.52%). However, the DALY declined, with an EAPC of -2.81% (95% CI: -2.92% - -2.70%). The ASMR showed a downward trend, with an EAPC of -2.55% (95% CI: -2.66% - -2.45%). The highest incidence of cirrhosis of liver caused by alcohol and other chronic liver diseases was reported in the age group of 35-49 years, while the ASMR increased gradually with age, with a significant rise after the age of 30. The age-standardized DALY rate peaked between the ages of 55 and 64. The disease burden indicators for males were consistently higher than those for females during the same period. According to the predictions of the BAPC model, from 2020 to 2030, the ASIR for cirrhosis of liver caused by alcohol and other chronic liver diseases in the entire population of China was projected to increase from 3.45/100 000 in 2020 to 3.78/100 000 in 2030, a growth of 9.57%. Conversely, the ASMR was expected to decrease from 1.45/100 000 in 2020 to 1.24/100 000 in 2030, a reduction of 14.48%. Conclusions:The disease burden of cirrhosis of liver caused by alcohol and other chronic liver diseases remained serious in China, especially in men and the middle-aged to elderly population. There is a pressing need to prioritize attention and resources towards these groups. Despite the projected decrease in ASMR, the ASIR continued to rise and is expected to persist in its upward trend until 2030.