经腹腔镜逆行胆囊切除术治疗复杂胆囊结石中转开腹的预测列线图的构建与验证

目的 探讨经腹腔镜逆行胆囊切除术（laparoscopic retrograde cholecystectomy,LRC）治疗复杂胆囊结石（complicated gallbladder stones,CGS）中转开腹的相关危险因素,构建预测列线图并进行验证。方法 选取2016年9月至2019年3月青海红十字医院行LRC治疗CGS的病人380例作为训练集,2019年4月至2021年9月该院行LRC治疗CGS的病人350例作为验证集,训练集依据术中是否中转开腹分为中转组（34例）和非中转组（346例）。单因素分析两组病人的临床病理特征,logistic多元回归模型分析经LRC治疗CGS中转开腹的危险因素,基于该多因素logistic回归模型,构建中转开腹的列线图,并对其进行外部验证以及绘制校正曲线。结果 训练集与验证集两组一般资料比较,各临床因素组间均差异无统计学意义（P>0.05）;单因素分析显示训练集中中转组与非中转组在身体质量指数（body mass index,BMI）、上腹部手术史、糖尿病、胆囊颈结石、胆囊增大、胆囊炎发作时间、胆囊壁增厚、结石数量、白蛋白、白细胞计数（w...     

Clinicopathologic features,treatment, survival,and prognostic factors of combined hepatocellular and cholangiocarcinoma: A nomogram development based on SEER database and validation in multicenter study

PurposeThe aim of the study was to comprehensively understand the combined hepatocellular and cholangiocarcinoma (CHC) and develop a nomogram for prognostic prediction of CHC.MethodsData were collected from the Surveillance, Epidemiology and End Results (SEER) database (year 2004–2014). Propensity-score matching (PSM) was used to match the demographic characteristic of the CHC versus hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). A nomogram model was established to predict the prognosis in terms of cancer specific survival (CSS). The established nomogram was externally validated by a multicenter cohort.ResultsA total of 71,756 patients enrolled in our study including 62,877 HCC patients, 566 CHC patients, and 8303 ICC patients. The CHC, HCC, and ICC are not exactly similar in clinical characteristic. After PSM, the CSS of CHC was better than HCC but comparable to ICC. Tumor size, M stage, surgery, chemotherapy, and surgery were independently prognostic factors of CHC and were included in the establishment of novel nomogram.The c-index of the novel nomogram in SEER training set and multicenter validation was 0.779 and 0.780, respectively, which indicated that the model was with better discrimination power. In addition, decision curve analyses proved the favorable potential clinical effect of the predictive model. Lastly, a risk classification based on nomogram also verified the reliability of the model.ConclusionCHC had better survival than HCC but was comparable to ICC. The nomogram was established based on tumor size, M stage, chemotherapy, surgery, and radiotherapy and well validated by external multicenter cohort.     

A predictive model for blood transfusion during liver resection

BackgroundA predictive model that can identify patients who are at increased risk of intraoperative blood transfusion could guide preoperative transfusion risk counseling, optimize health care resources, and reduce medical costs. Although previous studies have identified some predictors for particular populations, there is currently no existing model that uses preoperative variables to accurately predict blood transfusion during surgery, which could help anesthesiologists optimize intraoperative anesthetic management.MethodsWe collected data from 582 patients who underwent elective liver resection at a university-affiliated tertiary hospital between January 1, 2018, and December 31, 2020. The data set was then randomly divided into a training set (n = 410) and a validation set (n = 172) at a 7:3 ratio. The least absolute shrinkage and selection operating regression model was used to select the optimal feature, and multivariate logistic regression analysis was applied to construct the transfusion risk model. The concordance index (C-index) and the area under the receiver operating characteristic (ROC) curve (AUC) were used to evaluate the discrimination ability, and the calibration ability was assessed with calibration curves. In addition, we used decision curve analysis (DCA) to estimate the clinical application value. For external validation, the test set data were employed.ResultsThe final model had 8 predictor variables for intraoperative blood transfusion, which included the following: preoperative hemoglobin level, preoperative prothrombin time >14 s, preoperative total bilirubin >21 μmol/L, respiratory diseases, cirrhosis, maximum lesion diameter >5 cm, macrovascular invasion, and previous abdominal surgery. The model showed a C-index of 0.834 (95% confidence interval, 0.789–0.879) for the training set and 0.831 (95% confidence interval, 0.766–0.896) for the validation set. The AUCs were 0.834 and 0.831 for the training and validation sets, respectively. The calibration curve showed that our model had good consistency between the predictions and observations. The DCA demonstrated that the transfusion nomogram was reliable for clinical applications when an intervention was decided at the possible threshold across 1%–99% for the training set.ConclusionWe developed a predictive model with excellent accuracy and discrimination ability that can help identify those patients at higher odds of intraoperative blood transfusion. This tool may help guide preoperative counseling regarding transfusion risk, optimize health care resources, reduce medical costs, and optimize anesthetic management during surgery.     

IVc期下咽癌特征分析及列线图预后模型构建

目的 探讨IVc期下咽癌患者临床特征,筛选预后影响因素,构建列线图预后模型。 方法 在监测、流行病学及预后数据库中收集IVc期下咽癌患者的临床资料,应用χ2检验分析远处转移的相关特征,单因素及多因素Cox回归分析筛选预后影响因素,并构建列线图预后模型。 结果 肺(53.7%)是最常见的转移部位。位于梨状窝的肿瘤(P=0.029)和高级别肿瘤(P=0.010)更易发生肺转移。手术、化疗、骨和肝转移是独立预后因素。基于独立预后因素的列线图预后模型C-index为0.686(95%CI 0.649-0.723)。 结论 下咽癌最易向肺转移。基于手术、化疗、有无骨转移和肝转移的列线图预后模型预测能力较好。     

Nomograms to predict recurrence and survival in stage IIIB and IIIC melanoma after therapeutic lymphadenectomy

BackgroundCurrent staging algorithms in melanoma patients undergoing therapeutic lymph node dissection (LND) fail to accurately distinguish long-term survivors from those at risk of rapid relapse. Our goal was to establish and validate nomograms for predicting both recurrence and survival after LND.MethodsA prospective cohort of stage IIIB and IIIC melanoma patients was ascertained from a tertiary hospital in Brisbane, Australia. Failure-time multivariate analysis identified key factors that, in adjusted combinations, generated nomograms to predict 2-year recurrence and 5-year melanoma-specific survival. The predictive value of these nomograms was further validated in a patient cohort from Rotterdam, The Netherlands.ResultsIn 494 Australian patients, number of positive lymph nodes, extra-capsular extension and nodular histopathological subtype were the main independent predictors of 2-year recurrence while age, number of positive nodes and extra-capsular extension were the independent predictors of survival. Predictive value was confirmed in The Netherlands cohort of 331 patients. The nomograms were able to classify patients according to their 2-year recurrence and 5-year survival rates even within each stage III sub-class.ConclusionsModels that include extra-capsular extension predict outcomes in patients with clinically involved lymph nodes. This tool may help tailor treatment and monitoring of this group of patients.     

Nomograms of total renal volume,urinary bladder volume and bladder wall thickness index in 3,376 children with a normal urinary tract

Background We have previously shown that urinary bladder volume index (BVI = length × width × depth of bladder) and bladder volume wall thickness index (BVWI = BVI at full bladder/average bladder wall thickness) are useful indicators of bladder dysfunction in children with enuresis and urinary tract infection. These indices show a good correlation with urodynamic studies. We have expanded the study to include normal paediatric subjects with a wide age range. We illustrate a simple sonography protocol with nomograms of different parameters, which provide useful references for functional assessment in children with urological abnormalities. Objective To construct nomograms of total renal volume, maximum BVI and BVWI based on a Chinese paediatric population with age range from newborn to adolescence. Materials and methods Sonography was performed in consecutive children with normal urinary tracts on imaging, using a standardized protocol. Data were collected for construction of nomograms for different parameters. Results Nomograms of total renal volume, BVI and BVWI were constructed based on 3,376 consecutive paediatric subjects. All parameters consistently increased with age. Conclusion Nomograms of total renal volume, BVI and BVWI could provide useful references for studying bladder dysfunction in children using noninvasive dynamic sonography.     

肺炎克雷伯菌尿路感染167例碳青霉烯耐药风险列线图预测模型的构建

目的 构建肺炎克雷伯菌尿路感染碳青霉烯耐药风险列线图预测模型。方法 回顾性分析2018年1月至2020年12月在秦皇岛市第一医院确诊为肺炎克雷伯菌尿路感染的成人住院病人167例临床资料,将尿液标本中检出耐碳青霉烯类肺炎克雷伯菌（CRKP）的62例病人设为CRKP组,非CRKP的105例病人设为非CRKP组。采用logistic回归分析发生CRKP尿路感染的独立危险因素,并将167例病人按照分层随机抽样以7∶3比例分为训练集（118例）和验证集（49例）,然后使用训练集根据独立危险因素建立CRKP尿路感染列线图风险预测模型。采用校准曲线和受试者操作特征曲线（ROC曲线）评估列线图预测模型的准确度和区分度。结果 CRKP组肺炎克雷伯菌对头孢呋辛、哌拉西林/他唑巴坦、美罗培南、阿米卡星耐药性分别为100%(62/62)、100%(62/62)、98.4%(61/62)、51.6%(32/62),明显高于非CRKP组的42.9%(45/105)、8.6%(9/105)、1.0%(1/105)、3.8%(4/105)。多因素logistic回归分析显示,入住重症监护室、两周内使用碳青霉烯和酶抑制...     

TIPS术治疗的肝硬化并发EVB患者医院内死亡风险预测模型的构建与应用

目的 构建肝硬化门静脉高压症并发食管胃底静脉曲张破裂出血(EVB)患者医院内死亡的风险预测模型。方法 2018年6月～2020年6月我院收治的107例肝硬化门静脉高压症并发EVB患者,均接受经颈静脉肝内门体静脉分流术(TIPS)治疗。应用Logistic回归分析影响患者死亡的危险因素,基于独立影响因素构建医院内死亡的风险预测模型,应用Bootstrap法对预测模型进行内部验证,应用受试者工作特征曲线(ROC)下面积(AUC)评估预测模型的预测效能。结果 本组患者医院内死亡25例(23.4%),生存82例;单因素分析显示,死亡患者Child-Pugh分级、出血部位、门静脉内径、肝性脑病和失血性休克发生率等与生存患者比,均存在显著性差异(P<0.05),多因素Logistic回归分析显示,门静脉内径(OR=2.201,95%CI:1.544～3.139)、肝性脑病(OR=3.093,95%CI:1.731～5.524)和失血性休克(OR=1.101,95%CI:1.040～1.165)是影响患者医院内死亡的独立危险因素(P<0.05);对所构建的列线图预测模型,经内部验证,其C...     

基于影像学特征对骨质疏松性椎体压缩骨折病人经皮椎体成形术后同椎体再发骨折的预测研究

目的 探讨基于影像学特征对骨质疏松性椎体压缩骨折（OVCF）病人经皮椎体成形术（PVP）后的列线图模型预测术椎椎体再发骨折的价值。方法 回顾性纳入急性OVCF并行PVP后的病人93例。所有病人均行X线及MRI检查,根据椎体再发骨折诊断标准将病人分为再发骨折组（48例）和无再发骨折组（45例）。采用t检验和卡方检验比较2组间临床资料及影像特征的差异,对差异有统计学意义的指标进行多因素Logistic回归分析,获取再发骨折的独立危险因素,采用R软件建立列线图模型并绘制其校准曲线。采用受试者操作特征（ROC）曲线评估模型的预测效能,计算ROC曲线下面积（AUC）。应用校准曲线对列线图模型进行验证。结果 再发骨折组的椎体高度恢复率、延伸至终板的骨折线、椎体内裂隙（IVC）、骨水泥周围积液及骨水泥-终板未接触（NPEC）与无再发骨折组的差异均有统计学意义（均P<0.05）;多因素Logistic回归分析显示延伸至终板的骨折线[优势比（OR）=3.232]、存在IVC(OR=27.117)和NPEC(OR=1.993)及较高的椎体高度恢复率（OR=2.943）为同椎体再发骨折的独立危险因素（...     

术前外周血炎症指标对舌鳞状细胞癌预后预测价值的分析

目的探讨术前外周血炎症指标对舌鳞状细胞癌（TSCC）患者预后的预测价值。方法回顾性分析2010年1月至2017年12月于郑州大学第一附属医院因TSCC行根治性切除术的210例患者的临床病理资料，应用临床诊断性能曲线确定血小板/淋巴细胞比值（PLR）、中性粒细胞/淋巴细胞比值（NLR）的最佳截断值。生存单因素分析应用Kaplan-Meier法和Log-rank检验，多因素分析应用Cox比例风险回归模型，基于Cox回归模型筛选的独立危险因素构建Nomogram模型。结果单因素分析显示，PLR、NLR、肿瘤分化程度、T分期、N分期和TNM分期为影响TSCC预后的危险因素（P<0.05）；多因素分析显示，PLR、N分期和TNM分期为独立危险因素（P<0.05）。Nomogram模型的C指数为0.701（95%CI：0.651~0.752），校准曲线表明Nomogram模型预测无进展生存率与实际无进展生存率具有较好的一致性。结论术前外周血炎症指标对TSCC术后患者的预后可能有一定的预测作用。