Performance of risk prediction models for post-operative mortality in patients undergoing liver resection

BackgroundLiver resection is commonly performed for hepatic tumors, however preoperative risk stratification remains challenging. We evaluated the performance of contemporary prediction models for short-term mortality after liver resection in patients with and without cirrhosis.MethodsThis retrospective cohort study examined National Surgical Quality Improvement Program data. We included patients who underwent liver resections from 2014 to 2019. VOCAL-Penn, MELD, MELD-Na, ALBI, and Mayo risk scores were evaluated in terms of model discrimination and calibration for 30-day post-operative mortality.ResultsA total 15,198 patients underwent liver resection, of whom 249 (1.6%) experienced 30-day post-operative mortality. The VOCAL-Penn score had the highest discrimination (area under the ROC curve [AUC] 0.74) compared to all other models. The VOCAL-Penn score similarly outperformed other models in patients with (AUC 0.70) and without (AUC 0.74) cirrhosis.ConclusionThe VOCAL-Penn score demonstrated superior predictive performance for 30-day post-operative mortality after liver resection as compared to existing clinical standards.     

Deepm5C: A deep-learning-based hybrid framework for identifying human RNA N5-methylcytosine sites using a stacking strategy

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SARIMA模型在苏州市肺结核发病预测中的应用

目的 建立苏州市肺结核发病的SARIMA模型并预测发病,为苏州市肺结核防控提供参考。方法 收集结核病信息管理系统（新）中苏州市2010年1月—2018年12月肺结核月发病数,通过时间序列分析建立SARIMA模型并预测苏州市2019年肺结核的发病情况。结果 苏州市肺结核发病数具有明显的季节周期性,每年的发病最高峰为5月,发病最低谷为2月。苏州市肺结核发病数的最佳拟合模型为SARIMA (0,1,1)×(0,1,1)₁₂,AIC=9.590,SBC=9.644,模型参数均具有统计学意义,模型残差为白噪声序列,模型的预测值与实际值平均绝对百分比误差MAPE=7.943%,模型预测精度较高。预测苏州市2019年肺结核发病数为3 467例,月发病数平均值为289例,发病水平较2018年略有下降。结论 SARIMA(0,1,1)×(0,1,1)₁₂模型能较好拟合出苏州市肺结核发病数的时间变化趋势,可应用于苏州市肺结核月发病数的短期预测。     

Chemical applicability domain of the Local Lymph Node Assay (LLNA) for skin sensitisation potency. Part 2. The biological variability of the murine Local Lymph Node Assay (LLNA) for skin sensitisation

The Local Lymph Node Assay (LLNA) is the most common in vivo regulatory toxicology test for skin sensitisation, quantifying potency as the EC3, the concentration of chemical giving a threefold increase in thymidine uptake in the local lymph node. Existing LLNA data can, along with clinical data, provide useful comparator information on the potency of sensitisers. Understanding of the biological variability of data from LLNA studies is important for those developing non-animal based risk assessment approaches for skin allergy. Here an existing set of 94 EC3 values for 12 chemicals, all tested at least three times in the same vehicle have been analysed by calculating standard deviations (SD) for logEC3 values. The SDs range from 0.08 to 0.22. The overall SD for the 94 logEC3 values is 0.147. Thus the 95% confidence limits (2xSD) for LLNA EC3 values are within a factor of 2, comparable to those for physico-chemical measurements such as partition coefficients and solubility. The residual SDs of Quantitative Mechanistic Models (QMMs) based on physical organic chemistry parameters are similar to the overall SD of the LLNA, indicating that QMMs of this type are unlikely to be bettered for predictive accuracy.     

Gynecologic Malignancy-Associated Venous Thromboembolism and Predictive Tool at Thammasat University Hospital

Objectives: Aims were to investigate the prevalence and risk factors of venous thromboembolism (VTE) in gynecologic malignancy cases. Value of screening tool (Caprini) for prediction of VTE was also assessed. Study design: A retrospective study of gynecologic malignancy subjects who underwent major gynecological operation via exploratory laparotomy at Thammasat University Hospital, Pathum Thani, Thailand from January 2015 to December 2020. Participants were categorized into VTE and non-VTE groups. Caprini score, associated laboratory and clinical factors of both groups were evaluated. Results: A total of 392 subjects were recruited into the study. Prevalence of VTE was 7.4 (29/392) percent. VTE was diagnosed in subjects with endometrial, ovarian and cervical cancer at percentage of 7.8 (15/192), 7.9 (11/138) and 5.7 (3/53), respectively. Demographic characters of both groups were comparable. VTE group had significant more Caprini score, platelets count and platelet lymphocyte ratio (PLR) than non-VTE group. Modified Caprini score (2 multiply Caprini score plus 1 multiply PLR) was generated for better VTE prediction. Sensitivity and specificity of Caprini (≥5.5) and modified Caprini scores (≥22.8) were 72.4 vs 39.4, and 79.3 vs 52.1 percent, respectively. Conclusion: Prevalence of VTE among gynecologic malignancy cases was 7.4 percent. The modified Caprini score was an alternative VTE predictive tool. Cut-off point of modified Caprini score at equal or more than 22.8 was proposed.     

SI和DBP对女性产后出血的风险预测效果

目的考察休克指数(shock index,SI)和舒张压(diastolic blood pressure,DBP)对女性产后出血的风险预测效果。方法选取2016年1月～2018年12月在我院行产检并分娩的320例产后出血孕妇作为研究组,另外选取同期进行正常分娩的健康孕妇240例作为对照组,比较两组患者的一般临床资料、血红蛋白(hemoglobin,Hb)、舒张压(diastolic blood pressure,DBP)、收缩压(systolic blood pressure,SBP)、心率(heart rate,HR)及休克指数(shock index,SI),并采用Ordinal逻辑回归分析各参数对产后出血的风险预警。结果两组患者在年龄、孕周、BMI及新生儿体重相比,差异无统计学意义(P0.05),而孕次相比,差异具有统计学意义(P0.05);与对照组产后24 h相比,研究组产后24 h患者的DBP、SBP及Hb均显著降低,而HR和SI显著升高(P0.05);与对照组产前相比,产后24 h患者的SBP、HR及SI显著降低(P0.05);与研究组产前相比,产后24 h患者的DBP、SBP、HR及Hb均显著降低,而SI显著升高,差异具有统计学意义(P0.05);Ordinal逻辑回归分析结果显示,休克指数和舒张压对产后出血具有预警作用(P0.05)。结论休克指数和舒张压可作为评估女性产后出血的风险预测指标,临床应密切监护。     

基于机器学习的脑胶质瘤多模态影像分析

脑部胶质瘤是临床中常见的一种原发性脑肿瘤，具有复发率高、死亡率高以及治愈率低的特点。常规临床诊断主要依靠计算机断层扫描(CT)和磁共振成像(MRI)检查技术进行鉴别。随着成像技术和机器学习方法的不断发展，多模态影像智能分析技术已经逐步成为研究热点，在脑胶质瘤的病灶分割测量、肿瘤分级、预后生存周期预测和基因型辨别等方面具有重要的应用前景。本文重点介绍基于机器学习和多模态影像在脑胶质瘤临床辅助诊断和预后评估中的应用进展。