Prognostic analysis of related factors of adverse reactions to immunotherapy in advanced gastric cancer and establishment of a nomogram model

BACKGROUND Immunotherapy for advanced gastric cancer has attracted widespread attention in recent years.However,the adverse reactions of immunotherapy and its relationship with patient prognosis still need further study.In order to determine the association between adverse reaction factors and prognosis,the aim of this study was to conduct a systematic prognostic analysis.By comprehensively evaluating the clinical data of patients with advanced gastric cancer treated by immunotherapy,a nomogram model will be established to predict the survival status of patients more accurately.AIM To explore the characteristics and predictors of immune-related adverse reactions(irAEs)in advanced gastric cancer patients receiving immunotherapy with programmed death protein-1(PD-1)inhibitors and to analyze the correlation between irAEs and patient prognosis.METHODS A total of 140 patients with advanced gastric cancer who were treated with PD-1 inhibitors in our hospital from June 2021 to October 2023 were selected.Patients were divided into the irAEs group and the non-irAEs group according to whether or not irAEs occurred.Clinical features,manifestations,and prognosis of irAEs in the two groups were collected and analyzed.A multivariate logistic regression model was used to analyze the related factors affecting the occurrence of irAEs,and the prediction model of irAEs was established.The receiver operating characteristic(ROC)curve was used to evaluate the ability of different indicators to predict irAEs.A Kaplan-Meier survival curve was used to analyze the correlation between irAEs and prognosis.The Cox proportional risk model was used to analyze the related factors affecting the prognosis of patients.RESULTS A total of 132 patients were followed up,of whom 63(47.7%)developed irAEs.We looked at the two groups’clinical features and found that the two groups were statistically different in age≥65 years,Ki-67 index,white blood cell count,neutrophil count,and regulatory T cell(Treg)count(all P<0.05).Multivariate logistic regression analysis showed that Treg count was a protective factor affecting irAEs occurrence(P=0.030).The ROC curve indicated that Treg+Ki-67+age(≥65 years)combined could predict irAEs well(area under the curve=0.753,95%confidence interval:0.623-0.848,P=0.001).Results of the Kaplan-Meier survival curve showed that progressionfree survival(PFS)was longer in the irAEs group than in the non-irAEs group(P=0.001).Cox proportional hazard regression analysis suggested that the occurrence of irAEs was an independent factor for PFS(P=0.006).CONCLUSION The number of Treg cells is a separate factor that affects irAEs in advanced gastric cancer patients receiving PD-1 inhibitor immunotherapy.irAEs can affect the patients’PFS and result in longer PFS.Treg+Ki-67+age(≥65 years old)combined can better predict the occurrence of adverse reactions.

Prognostic value of a nomogram model for postoperative liver metastasis of colon cancer

BACKGROUND Colon cancer is one of the most common malignant tumors of the digestive system.Liver metastasis after colon cancer surgery is the primary cause of death in patients with colon cancer.AIM To construct a novel nomogram model including various factors to predict liver metastasis after colon cancer surgery.METHODS We retrospectively analyzed 242 patients with colon cancer who were admitted and underwent radical resection for colon cancer in Zhejiang Provincial People’s Hospital from December 2019 to December 2022.Patients were divided into liver metastasis and non-liver metastasis groups.Sex,age,and other general and clinicopathological data(preoperative blood routine and biochemical test indexes)were compared.The risk factors for liver metastasis were analyzed using singlefactor and multifactorial logistic regression.A predictive model was then constructed and evaluated for efficacy.RESULTS Systemic inflammatory index(SII),C-reactive protein/albumin ratio(CAR),red blood cell distribution width(RDW),alanine aminotransferase,preoperative carcinoembryonic antigen level,and lymphatic metastasis were different between groups(P<0.05).SII,CAR,and RDW were risk factors for liver metastasis after colon cancer surgery(P<0.05).The area under the curve was 0.93 for the column-line diagram prediction model constructed based on these risk factors to distinguish whether liver metastasis occurred postoperatively.The actual curve of the column-line diagram predicting the risk of postoperative liver metastasis was close to the ideal curve,with good agreement.The prediction model curves in the decision curve analysis showed higher net benefits for a larger threshold range than those in extreme cases,indicating that the model is safer.CONCLUSION Liver metastases after colorectal cancer surgery could be well predicted by a nomogram based on the SII,CAR,and RDW.

A Nomogram Model for Prediction of Mortality Risk of Patients with Dangerous Upper Gastrointestinal Bleeding:A Two-center Retrospective Study

Objective:This study aimed to establish a nomogram model to predict the mortality risk of patients with dangerous upper gastrointestinal bleeding(DUGIB),and identify high-risk patients who require emergent therapy.Methods:From January 2020 to April 2022,the clinical data of 256 DUGIB patients who received treatments in the intensive care unit(ICU)were retrospectively collected from Renmin Hospital of Wuhan University(n=179)and the Eastern Campus of Renmin Hospital of Wuhan University(n=77).The 179 patients were treated as the training cohort,and 77 patients as the validation cohort.Logistic regression analysis was used to calculate the independent risk factors,and R packages were used to construct the nomogram model.The prediction accuracy and identification ability were evaluated by the receiver operating characteristic(ROC)curve,C index and calibration curve.The nomogram model was also simultaneously externally validated.Decision curve analysis(DCA)was then used to demonstrate the clinical value of the model.Results:Logistic regression analysis showed that hematemesis,urea nitrogen level,emergency endoscopy,AIMS65,Glasgow Blatchford score and Rockall score were all independent risk factors for DUGIB.The ROC curve analysis indicated the area under curve(AUC)of the training cohort was 0.980(95%CI:0.962-0.997),while the AUC of the validation cohort was 0.790(95%CI:0.685-0.895).The calibration curves were tested for Hosmer-Lemeshow goodness of fit for both training and validation cohorts(P=0.778,P=0.516).Conclusion:The developed nomogram is an effective tool for risk stratification,early identification and intervention for DUGIB patients.

Establishment of a nomogram model for predicting therapy complications in patients with polycythemia and deep venous thrombosis

BACKGROUND Patients with deep venous thrombosis(DVT)residing at high altitudes can only rely on anticoagulation therapy,missing the optimal window for surgery or thrombolysis.Concurrently,under these conditions,patient outcomes can be easily complicated by high-altitude polycythemia(HAPC),which increases the difficulty of treatment and the risk of recurrent thrombosis.To prevent reaching this point,effective screening and targeted interventions are crucial.Thus,this study analyzes and provides a reference for the clinical prediction of thrombosis recurrence in patients with lower-extremity DVT combined with HAPC.AIM To apply the nomogram model in the evaluation of complications in patients with HAPC and DVT who underwent anticoagulation therapy.METHODS A total of 123 patients with HAPC complicated by lower-extremity DVT were followed up for 6-12 months and divided into recurrence and non-recurrence groups according to whether they experienced recurrence of lower-extremity DVT.Clinical data and laboratory indices were compared between the groups to determine the influencing factors of thrombosis recurrence in patients with lowerextremity DVT and HAPC.This study aimed to establish and verify the value of a nomogram model for predicting the risk of thrombus recurrence.RESULTS Logistic regression analysis showed that age,immobilization during follow-up,medication compliance,compliance with wearing elastic stockings,and peripheral blood D-dimer and fibrin degradation product levels were indepen-dent risk factors for thrombosis recurrence in patients with HAPC complicated by DVT.A Hosmer-Lemeshow goodness-of-fit test demonstrated that the nomogram model established based on the results of multivariate logistic regression analysis was effective in predicting the risk of thrombosis recurrence in patients with lowerextremity DVT complicated by HAPC(χ^(2)=0.873;P>0.05).The consistency index of the model was 0.802(95%CI:0.799-0.997),indicating its good accuracy and discrimination.CONCLUSION The column chart model for the personalized prediction of thrombotic recurrence risk has good application value in predicting thrombotic recurrence in patients with lower-limb DVT combined with HAPC after discharge.

Development and validation of a prediction model for early screening of people at high risk for colorectal cancer

BACKGROUND Colorectal cancer(CRC)is a serious threat worldwide.Although early screening is suggested to be the most effective method to prevent and control CRC,the current situation of early screening for CRC is still not optimistic.In China,the incidence of CRC in the Yangtze River Delta region is increasing dramatically,but few studies have been conducted.Therefore,it is necessary to develop a simple and efficient early screening model for CRC.AIM To develop and validate an early-screening nomogram model to identify individuals at high risk of CRC.METHODS Data of 64448 participants obtained from Ningbo Hospital,China between 2014 and 2017 were retrospectively analyzed.The cohort comprised 64448 individuals,of which,530 were excluded due to missing or incorrect data.Of 63918,7607(11.9%)individuals were considered to be high risk for CRC,and 56311(88.1%)were not.The participants were randomly allocated to a training set(44743)or validation set(19175).The discriminatory ability,predictive accuracy,and clinical utility of the model were evaluated by constructing and analyzing receiver operating characteristic(ROC)curves and calibration curves and by decision curve analysis.Finally,the model was validated internally using a bootstrap resampling technique.RESULTS Seven variables,including demographic,lifestyle,and family history information,were examined.Multifactorial logistic regression analysis revealed that age[odds ratio(OR):1.03,95%confidence interval(CI):1.02-1.03,P<0.001],body mass index(BMI)(OR:1.07,95%CI:1.06-1.08,P<0.001),waist circumference(WC)(OR:1.03,95%CI:1.02-1.03 P<0.001),lifestyle(OR:0.45,95%CI:0.42-0.48,P<0.001),and family history(OR:4.28,95%CI:4.04-4.54,P<0.001)were the most significant predictors of high-risk CRC.Healthy lifestyle was a protective factor,whereas family history was the most significant risk factor.The area under the curve was 0.734(95%CI:0.723-0.745)for the final validation set ROC curve and 0.735(95%CI:0.728-0.742)for the training set ROC curve.The calibration curve demonstrated a high correlation between the CRC high-risk population predicted by the nomogram model and the actual CRC high-risk population.CONCLUSION The early-screening nomogram model for CRC prediction in high-risk populations developed in this study based on age,BMI,WC,lifestyle,and family history exhibited high accuracy.

维持性血液透析尿毒症患者动静脉内瘘急性血栓形成的危险因素分析及Nomogram预测模型构建

目的探讨维持性血液透析(MHD)尿毒症患者动静脉内瘘急性血栓形成的危险因素及Nomogram预测模型构建。方法选择2020年12月至2022年12月于新乡医学院第三附属医院门诊行MHD治疗的418例尿毒症患者为研究对象。根据动静脉内瘘是否形成急性血栓将患者分为急性血栓组(n=32)与非急性血栓组(n=386)。应用单因素及多因素logistic回归分析影响行MHD的尿毒症患者动静脉内瘘急性血栓形成的影响因素;根据尿毒症患者动静脉内瘘急性血栓形成的独立危险因素建立Nomogram预测模型,并应用Bootstrap来验证Nomogram模型的有效性。结果急性血栓组患者合并糖尿病患、合并低血压、透析时穿刺失败占比、钙磷乘积、超敏C反应蛋白(hs-CRP)、总胆固醇(TC)、低密度脂蛋白胆固醇(LDL-C)水平均显著高于非急性血栓组(P<0.05);logistic回归分析显示,糖尿病、低血压、透析时穿刺失败、钙磷乘积升高、高水平hs-CRP、高水平LDL-C是影响行MHD的尿毒症患者动静脉内瘘急性血栓形成的独立危险因素(P<0.05);依据6个独立危险因素构建了Nomogram预测模型,该模型的一致性指数为0.893(95%置信区间:0.833~0.928);且其校正曲线和标准曲线拟合较好,曲线下面积为0.918。结论糖尿病、低血压、透析时穿刺失败、钙磷乘积升高、高水平hs-CRP和LDL-C是行MHD的尿毒症患者动静脉内瘘急性血栓形成的危险因素,依据独立危险因素构建的Nomogram模型预测行MHD的尿毒症患者动静脉内瘘急性血栓形成的效果较好,有助于临床急性血栓形成患者的早期筛查。

脓毒症患者并发急性肾损伤的危险因素分析及Nomogram预测模型的构建

目的分析脓毒症患者并发急性肾损伤的危险因素,并构建列线图(Nomogram)预测模型。方法选取2020年3月至2022年9月就诊的180例脓毒症患者为研究对象,根据患者是否并发急性肾损伤将其分为急性肾损伤组(n=75)和非急性肾损伤组(n=105)。采用受试者工作特征(ROC)曲线分析连续性变量的预测价值;采用logistic回归分析影响脓毒症患者并发急性肾损伤的危险因素;采用内部数据验证Nomogram模型临床效能。结果两组患者在年龄等一般资料的比较中,差异无统计学意义(P>0.05)。与非急性肾损伤组相比,急性肾损伤组患者男性较多,肺部感染者较多,平均动脉压(MAP)、前降钙素水平较低,乳酸、白细胞计数、多器官功能衰竭(MODS)评分水平较高(P<0.05)。MAP、乳酸、前降钙素、白细胞计数、MODS评分的ROC曲线下面积(AUC)为0.823、0.921、0.663、0.948、0.946,最佳截断值为89 mmHg、2.13 mmol/L、13.22μg/L、15×10^(9)·L^(-1)、6分。性别(男)、肺部感染(是)、MAP(≤89 mmHg)、乳酸(>2.13 mmol/L)、白细胞计数(>15×10^(9)·L^(-1))、MODS评分(>6分)均为影响脓毒症患者并发急性肾损伤的危险因素(P<0.05)。内部验证结果显示,Nomogram模型预测脓毒症患者并发急性肾损伤的风险C-index为0.763(95%CI:0.651~0.832);模型预测脓毒症患者并发急性肾损伤的风险阈值>0.07,Nomogram模型提供临床净收益。结论性别(男)、肺部感染(是)、MAP(≤89 mmHg)、乳酸(>2.13 mmol/L)、白细胞计数(>15×10^(9)·L^(-1))、MODS评分(>6分)均为影响脓毒症患者并发急性肾损伤的危险因素,且基于以上变量构建的Nomogram模型可以对患者并发急性肾损伤进行较好的预测。

股骨粗隆间骨折术后下肢深静脉血栓并发症影响因素分析及Nomogram模型建立

目的探讨股骨粗隆间骨折手术后早期发生下肢深静脉血栓的危险因素,并进行Nomogram模型构建。方法选取2018年1月—2020年12月于华北石油管理局总医院行股骨粗隆间骨折手术的120例患者,术后早期发生下肢深静脉血栓13例。按照术后住院期间是否发生下肢深静脉血栓分为并发症组和无并发症组。采用多因素Logistics分析术后发生并发症的风险并构建Nomogram模型。结果并发症组患者住院时长、术后住院时间、治疗总费用均高于对照组,差异有统计学意义(P<0.05)。单因素分析显示,骨折类型、合并慢性病种类、贫血输血、骨折发病时长是术后下肢深静脉血栓的潜在影响因素,差异有统计学意义(P<0.05)。将单因素有统计学差异的变量进行Logistics多因素分析,合并慢性病种类、贫血输血、骨折发病时长是股骨粗隆间骨折术后下肢深静脉血栓的独立危险因素(P<0.05)。采用内部数据进行验证,C-index为0.746(95%CI:0.596~0.935),该Nomogram模型预测与实际观测结果吻合度较好。结论术前合并慢性病≥3种、贫血输血、骨折发病时长>1 d是股骨粗隆间骨折术后下肢深静脉血栓的独立危险因素。本研究构建的Nomogram模型有助于指导医师完善个性化围手术期治疗方案。

基于25⁃羟基维生素D、血清学因子等对老年类风湿性关节炎合并间质性肺疾病Nomogram预测模型的构建和评价

目的基于25-羟基维生素D[25-(OH)D]、血清学因子等构建老年类风湿性关节炎合并间质性肺疾病(RA-ILD)的Nomogram预测模型,并进行模型评价。方法选取2020年5月—2022年10月收治的老年类风湿性关节炎(RA)220例,根据是否合并间质性肺疾病将其分为RA-ILD组(51例)和单纯RA组(169例)2组,比较2组一般资料和实验室相关指标[类风湿因子(RF)、抗环瓜氨酸抗体(anti-CCP)、抗角蛋白抗体(AKA)、类风湿关节炎活动度评分(DAS28)]、25-(OH)D、血清学因子[白细胞介素-33(IL-33)、白细胞介素-35(IL-35)、赖氨酰氧化酶样蛋白-2(LOXL-2)、涎液化糖链抗原-6(KL-6)、基质金属蛋白酶-8(MMP-8)]水平,分析老年RA患者25-(OH)D与各血清学因子的相关性,探讨老年RA-ILD发生的影响因素,根据影响因素、25-(OH)D及血清学因子构建老年RA-ILD的Nomogram预测模型,并对该模型进行评价。结果RA-ILD组和单纯RA组RF、DAS28比较差异有统计学意义(P<0.01);RA-ILD组25-(OH)D、IL-35、KL-6低于单纯RA组,IL-33、LOXL-2、MMP-8高于单纯RA组(P<0.05,P<0.01)。老年RA患者25-(OH)D与IL-35、KL-6呈正相关,与IL-33、LOXL-2、MMP-8呈负相关(P<0.05)。25-(OH)D、IL-35、KL-6、IL-33、LOXL-2、MMP-8、RF和DAS28均为老年RA-ILD发生的影响因素(P<0.01)。在Nomogram预测模型中直接获取各预测因素对应得分,得分之和对应的预测概率即为该老年患者RA-ILD发生的风险概率,该模型对老年RA-ILD发生具有良好预测效能,且具有良好校准度。结论基于25-(OH)D、血清学因子等构建老年RA-ILD发生的Nomogram预测模型,预测效能较高、校准度良好。

基于多中心的老年OSAHS合并冠心病患者不良预后的Nomogram预测模型构建

目的基于多中心分析老年阻塞性睡眠呼吸暂停低通气综合征(OSAHS)合并冠心病患者不良预后的影响因素并构建Nomogram预测模型。方法于2020年3月至2022年3月选取江苏省中医院共357例老年OSAHS合并冠心病患者,按照7∶3比例将纳入患者分为建模组(n=250)及验证组(n=107)。对患者进行为期1年的随访,根据患者预后将建模组分为预后良好组(n=215)和预后不良组(n=35)。单因素及多因素Logistic回归分析影响老年OSAHS合并冠心病患者不良预后的因素,并根据此结果构建Nomogram预测模型,再以H-L拟合度曲线评估模型的有效性,以受试者工作特征(ROC)曲线评估模型的区分度。结果单因素分析结果显示,体重指数、睡眠呼吸暂停低通气指数(AHI)、睡眠平均氧饱和度(SaO_(2))、超敏C反应蛋白(hs-CRP)及白细胞介素-6(IL-6)为老年OSAHS合并冠心病患者不良预后的影响因素(P<0.05)。多因素Logistic回归分析显示,体重指数较高、AHI水平较高、hs-CRP水平较高、低水平的睡眠平均SaO_(2)为老年OSAHS合并冠心病患者不良预后的影响因素(P<0.05)。验证模型显示,建模组χ^(2)=6.125,P=0.421,ROC曲线下面积AUC为0.958(95%CI:0.926~0.980),敏感度及特异度分别为82.86%、96.28%;验证组χ^(2)=5.754,P=0.311,AUC为0.932(95%CI:0.893~0.960),敏感度及特异度分别为85.70%、88.40%。结论体重指数较高、AHI水平较高、hs-CRP水平较高、低水平的睡眠平均SaO_(2)为老年OSAHS合并冠心病患者不良预后的影响因素,以此构建的Nomogram预测模型具有较好的区分度及有效性,可帮助临床预测患者不良预后的发生风险,具有较高的临床价值。

创伤性胫骨平台骨折术后感染的危险因素分析及Nomogram预测模型构建

目的 分析创伤性胫骨平台骨折术后感染的危险因素,并构建Nomogram预测模型。方法 2019年10月~2021年8月行手术治疗的创伤性胫骨平台骨折病人148例,根据术后是否出现感染分为感染组(20例)和未感染组(128例)。比较两组病人的一般资料;采用单因素分析及多因素Logistic回归分析影响创伤性胫骨平台骨折术后感染的危险因素;采用ROC分析有统计学意义的连续性变量的预测价值;采用内部数据验证Nomogram模型预测效能。结果 两组病人年龄、性别等一般资料比较,差异无统计学意义(P>0.05),与未感染组相比,感染组病人糖尿病、开放型骨折类型、骨筋膜室综合征占比较高,手术时间和住院时间较长(P<0.05);糖尿病(是)、骨折类型(开放型)、骨筋膜室综合征(有)、手术时间(>3小时)是影响创伤性胫骨平台骨折术后感染的危险因素;手术时间和住院时间的AUC为0.792、0.651;最佳截断值为3小时、13天(P<0.05);Nomogram模型预测创伤性胫骨平台骨折术后感染风险的C-index为0.744(0.651~0.807);模型预测创伤性胫骨平台骨折术后感染风险的阈值>0.09。结论 糖尿病(是)、骨折类型(开放型)、骨筋膜室综合征(有)、手术时间(>3小时)是影响创伤性胫骨平台骨折术后感染的危险因素,且基于以上变量构建的Nomogram模型有较好的预测价值。

Nomogram模型在新生儿耐碳青霉烯类肺炎克雷伯菌肠道定植风险评估中的应用

目的建立一种有效的Nomogram模型,用以评估新生儿耐碳青霉烯类肺炎克雷伯菌(CRKP)肠道定植风险,运用建立的Nomogram模型得出新生儿CRKP具体的定植概率大小,采取个体化的预防策略,减少定植的发生,降低新生儿CRKP继发感染的可能性。方法选取入院后48 h新生儿进行直肠拭子/大便培养及药敏鉴定为CRKP定植患者187例,在同期入院的经检测为非CRKP定植患儿中随机抽取187例为非定植组,共374例进行回顾性研究。通过R语言(R 4.2.1)的caret软件包对374例总样本按建模组∶验证组=3∶1进行随机分组。模型建立:对建模组数据运用R 4.2.1的glmnet包进行LASSO回归分析确定最终用于建模的预测因素,rms软件包进行Nomogram模型的构建。模型验证:R 4.2.1 pROC和rms软件包对建模组和验证组数据分别进行一致性指数(Cindex)、受试者工作特征曲线(ROC)及其曲线下面积(AUC)、校准曲线对Nomogram模型的效能进行内部验证和外部验证。结果运用LASSO回归分析,从研究的35个可能影响新生儿CRKP定植的项目中确定了8个预测因子,分别是性别、剖宫产、母乳喂养、鼻胃管、灌肠、碳青霉烯类、益生菌和总住院时间。使用这8个预测变量构建的Nomogram模型显示出中等预测能力,ROC曲线下面积为建模组0.835、验证组0.800。Hos-mer-Lemeshow检验显示,预测概率与实际概率高度一致(建模组,P=0.678>0.05;验证组,P=0.208>0.05)显示出非常好的拟合度。结论在Nomogram模型中引入性别、剖宫产、母乳喂养、鼻胃管、灌肠、使用碳青霉烯类抗生素、口服益生菌、总住院时间可以提高其预测新生儿CRKP定植风险的能力。根据Nomogram模型预测的定植概率的大小不同,采取个体化的预防措施,减少新生儿CRKP定植的发生,降低新生儿CRKP继发感染的发生率。

预测宫颈癌合并糖尿病患者术后切口感染风险的Nomogram模型建立

目的旨在构建预测宫颈癌合并糖尿病患者根治性子宫切除术术后切口感染风险的列线图模型,并进行模型评估。方法选取在本院接受根治性子宫切除术治疗的宫颈癌合并糖尿病患者267例作为研究对象,其中发生术后切口感染(感染组)97例,未发生术后切口感染(未感染组)170例。采用单因素和多因素Logistic回归筛选与术后切口感染相关的独立影响因素。采用R软件和相关程序包绘制列线图模型。结果与未感染组相比,感染组年龄≥55岁、体重指数(body mass index,BMI)≥25、引流管留置时间≥7 d、住院时间≥14 d、血清白蛋白<30 g/L的患者比例明显增加(P<0.05)。与未感染组相比,感染组血清白细胞介素6(interleukin-6,IL-6)、肿瘤坏死因子α(tumor necrosis factor-α,TNF-α)、C反应蛋白(C-reactive protein,CRP)和降钙素原(procalcitonin,PCT)水平显著升高(P<0.05)。多变量Logistic回归分析表明,年龄≥55岁、BMI≥25、引流管留置时间≥7 d、住院时间≥14 d,以及血清IL-6、TNF-α、CRP和PCT水平升高均是术后切口感染发生的独立危险因素(P<0.05)。用于评估宫颈癌合并糖尿病患者术后切口感染发生风险的列线图具有良好的预测准确性(C指数为0.947)、区分度(受试者工作特征曲线下面积为0.947)、一致性(Hosmer-Lemeshow拟合优度检验平均绝对误差为0.011)和临床效能。结论本研究基于围手术期特征构建了预测宫颈癌合并糖尿病患者术后切口感染的列线图模型,该模型可能有助于加强感染控制意识,为根治性子宫切除术后高危患者的管理提供参考。

肺癌化疗病人发生PICC相关上肢静脉血栓风险Nomogram模型的构建

目的:探究肺癌化疗病人发生经外周静脉置入中心静脉导管(PICC)相关上肢静脉血栓的危险因素,构建其风险Nomogram模型,并进一步验证该模型的预测价值。方法:回顾性分析2014年1月—2020年12月南昌大学第一附属医院呼吸内科收治的391例原发性肺癌化疗病人,比较病人的临床资料,并采用多因素Logistic回归模型分析肺癌化疗病人发生PICC相关上肢静脉血栓的独立危险因素,R软件整合独立危险因素并构建Nomogram模型。结果:89例(22.76%)肺癌化疗病人出现PICC相关上肢静脉血栓。体质指数(≥27.49 kg/m^(2))、糖尿病(是)、纤维蛋白原(FIB)(≥3.60 g/L)、活化部分凝血活酶时间(APTT)(≥33 s)、D-二聚体(≥0.90 mg/L)以及C反应蛋白(CRP)(≥5.80 mg/L)是肺癌化疗病人发生PICC相关上肢静脉血栓的独立危险因素(P<0.05)。该Nomogram模型预测与实际观测结果的吻合度较好,一致性指数(C-index)为0.832[95%CI(0.793,0.866)],当高风险阈值>0.05时,此Nomogram模型在预测肺癌化疗病人PICC相关上肢静脉血栓高风险的方面可提供高于单个独立危险因素的额外临床净收益。结论:基于体质指数、糖尿病、纤维蛋白原、活化部分凝血活酶时间、D-二聚体以及C反应蛋白独立危险因素构建的Nomogram模型在预测肺癌化疗病人发生PICC相关上肢静脉血栓具备可行性,可为临床风险分层及制定护理策略提供重要参考。

老年重症肺炎患者病情转归不良的风险预测Nomogram模型建立及验证

目的构建老年重症肺炎(SP)患者病情转归不良的风险预测Nomogram模型,并验证其预测效能。方法回顾性分析2022年1月~2023年6月本院重症监护病房收治的432例老年SP患者,随机分为训练集(n=288)和验证集(n=144)。根据患者入住ICU后28天病情转归将其分为转归不良组和转归良好组。采用Logistic回归分析筛选患者病情转归不良的影响因素,构建其风险预测Nomogram模型,以受试者工作特征(ROC)曲线和校准曲线评估模型的区分度和准确性,以决策曲线分析(DCA)评估模型的临床净获益。结果老年SP患者病情转归不良发生率为24.77%;肺炎严重程度(PSI)评分、白细胞计数(WBC)、纤维蛋白原(FIB)、降钙素原(PCT)是患者病情转归不良的影响因素(OR=1.677、1.619、1.435、1.935,P均<0.05);训练集与验证集的一致性指数(C-index)分别为0.874、0.839;ROC曲线下面积(AUC)分别为0.929、0.891;决策曲线(DCA)显示在训练集及验证集中模型预测病情转归不良的最大净获益值阈值概率区间分别在0~0.91和0~0.90。结论PSI评分、WBC、FIB、PCT是老年SP患者病情转归不良的影响因素,以此为基础构建的风险预测Nomogram模型具有良好预测效能与临床应用价值。

老年骨折并发急性脑血管创伤预后调查分析及Nomogram预测模型构建

目的探讨老年骨折并发急性脑血管创伤患者的预后,调查分析其危险因素并构建Nomogram预测模型。方法纳入2021年1月—2023年1月于唐山市第二医院接受治疗的98例老年骨折患者的临床资料,将老年骨折患者并发急性脑血管创伤者纳入观察组,未并发急性脑血管创伤者纳入对照组,比较两组基线资料和实验室指标,采用Logistic回归分析明确老年骨折并发急性脑血管创伤的独立影响因素,将获得的独立影响因素纳入Nomogram预测模型构建,采用R软件中C指数、受试者工作特征(ROC)曲线及校准曲线评价老年骨折并发急性脑血管创伤风险的Nomogram模型的预测效能。结果两组性别、年龄、身体质量指数(BMI)、骨折时间、高血压、吸烟史以及饮酒史对比无统计学差异(P>0.05);观察组高血糖患者比例明显多于对照组(P<0.05)。两组实验室指标对比中,收缩压、舒张压、空腹血糖(FPG)、总胆固醇(TC)、红细胞计数(RBC)、白细胞计数(WBC)、三酯甘油(TG)、钠离子、钾离子、钙离子以及D-二聚体无统计学差异(P>0.05);观察组RBC低于对照组,观察组血小板、纤维蛋白原(FIB)和C-反应蛋白(CRP)高于对照组(P<0.05)。Logistics回归分析显示,RBC是老年骨折并发急性脑血管创伤的独立保护因素(OR<1,P<0.05);高血糖、血小板、FIB和CRP是老年骨折并发急性脑血管创伤的独立危险因素(均OR>1,均P<0.05)。ROC曲线分析结果显示,高血糖、RBC、血小板、FIB以及CRP的AUC值均>0.700,表明上述指标对于老年骨折是否并发急性脑血管创伤具有较好的预测价值。基于以上影响因素构建Nomogram风险模型,校准曲线C-index值为0.964,说明该Nomogram模型具备较好的区分度,ROC曲线建模组和验证组的AUC值分别为0.964和0.939,说明该Nomogram模型具有良好的预测效能。结论基于老年骨折并发急性脑血管创伤的独立影响因素构建的Nomogram预测模型,能直观地预测老年骨折并发急性脑血管创伤的概率。

个体化预测老年妇科恶性肿瘤术中急性压力性损伤风险Nomogram模型的构建及验证

目的:构建个体化预测老年妇科恶性肿瘤患者术中急性压力性损伤的风险Nomogram模型,并验证模型的预测能力。方法:选取2018年6月至2023年6月于江苏省人民医院行手术治疗的505例老年妇科恶性肿瘤患者,其中术中发生急性压力性损伤51例(损伤组)。采用单因素和多因素logistic回归分析老年妇科恶性肿瘤发生术中急性压力性损伤的危险因素,并建立相关Nomogram预测模型。结果:损伤组和非损伤组患者的肿瘤分期、术前Munro量表评分、术前ALB、术前血红蛋白(Hb)、手术时间、术中出血量和术中体温波动情况比较,差异有统计学意义(P<0.05)。多因素logistic回归分析显示,Ⅲ~Ⅳ期肿瘤、术前Munro量表评分高、术前白蛋白(ALB)<35g/L、术前Hb<110g/L、手术时间≥180min、术中出血量≥500mL和术中体温波动较大是老年妇科恶性肿瘤患者发生术中急性压力性损伤的独立危险因素(P<0.05)。Nomogram模型验证结果,C-index指数为0.809(95%CI为0.781~0.836),Hosmer-Lemeshoe拟合优度检验显示,模型拟合较好(χ^(2)=4.308,P=0.117),ROC曲线的AUC为0.811(95%CI为0.783~0.839),在1%~80%的列线图可预测范围内,模型获益值均为正值。结论:老年妇科恶性肿瘤患者发生术中急性压力性损伤的危险因素包括Ⅲ~Ⅳ期肿瘤、术前Munro量表评分高、术前ALB<35g/L、术前Hb<110g/L、手术时间≥180min、术中出血量≥500mL和术中体温波动较大,基于上述因素构建的Nomogram模型对老年妇科恶性肿瘤患者术中急性压力性损伤发生风险具有较高的预测价值。

老年全膝关节置换后谵妄的危险因素分析及nomogram预测模型建立

背景:术后谵妄是全膝关节置换术后严重并发症之一,通常发生在术后1-5 d,以意识混乱、认知障碍等为主要表现,不利于老年患者术后关节功能恢复。目前针对影响老年全膝关节置换术后谵妄的危险因素尚不明确,亦缺乏将其直观呈现以便推广应用的临床预测研究。目的:探究老年患者全膝关节置换术后谵妄的危险因素,并建立列线图(nomogram)预测模型。方法:回顾性分析2019年1月至2021年12月在江西中医药大学附属赣州市中医院诊治的116例接受全膝关节置换老年患者的病历资料,其中29例术后发生谵妄的患者作为观察组,余下87例术后未发生谵妄的患者作为对照组。比较两组患者术前一般临床资料、实验室检查结果以及手术资料,多因素Logistic回归分析影响老年患者全膝关节置换术后谵妄的危险因素,采用受试者工作特征曲线分析独立危险因素并获得最佳截断值,通过R软件构建nomogram模型。结果与结论:①两组患者年龄、脑血管意外病史、术前住院时间、术前白蛋白、血红蛋白、美国麻醉医师协会分级、手术时间、麻醉时间以及术中输血量比较差异有显著性意义(P<0.05);②由多因素Logistic回归分析可知,高龄、术前住院时间长、高美国麻醉医师协会分级以及手术时间过长是老年膝关节置换患者术后发生谵妄的危险因素,高白蛋白以及高血红蛋白是老年膝关节置换患者术后发生谵妄的保护因素;③年龄、术前住院时间、白蛋白、血红蛋白、美国麻醉医师协会分级、手术时间的曲线下面积分别为0.784,0.706,0.853,0.762,0.617,0.542,最佳截断值分别为75岁、7 d、40 g/L、125 g/L、3、200 min;④采用内部数据进行验证,一致性指数为0.974,该模型的实际曲线与理想曲线的吻合度较好;⑤提示基于高龄、术前住院时间长、高美国麻醉医师协会分级、低白蛋白、低血红蛋白以及手术时间过长所构建的nomogram模型对老年患者全膝关节置换术后谵妄发生风险的早期识别、预警与诊断有着深远的临床意义。

基于超声检查、肿瘤细胞因子构建儿童肾母细胞瘤的Nomogram诊断模型

目的:基于超声检查、肿瘤细胞因子构建儿童肾母细胞瘤的Nomogram诊断模型,以提高对肾母细胞瘤的临床诊断效能。方法:选取2019年1月至2023年1月我院收治的82例肾母细胞瘤患儿为研究组,另选取同期82例囊肿性肾病患儿为对照组,均经手术病理证实。术前均行超声检查,比较两组超声特征、临床资料。通过Logistic分析肾母细胞瘤发生的影响因素,根据影响因素构建肾母细胞瘤的Nomogram诊断模型。采用受试者工作特征(ROC)曲线、校准曲线进行Nomogram诊断模型验证。结果:两组肿块性质、内部回声、邻近结构侵犯及转移、伴下腔静脉瘤栓、伴同侧肾静脉血栓、动脉期峰值流速、血流阻力指数、肾体积局部增大、基质金属蛋白酶-9(MMP-9)、血管内皮生长因子(VEGF)比较,差异有统计学意义(P<0.05);LASSO回归分析显示,可使模型性能优良且影响因素最少的最佳惩罚系数λ下诊断肾母细胞瘤的变量数为6个:即肿块性质、内部回声、邻近结构侵犯及转移、伴同侧肾静脉血栓、VEGF、MMP-9;Logistic回归分析显示,肿块性质、内部回声、邻近结构侵犯及转移、伴同侧肾静脉血栓、VEGF、MMP-9是肾母细胞瘤的相关危险因素(P<0.05);运用R语言绘制肾母细胞瘤诊断模型显示,其C-index为0.939,诊断肾母细胞瘤的AUC为0.939。结论:肿块性质、内部回声、邻近结构侵犯及转移、伴同侧肾静脉血栓、VEGF、MMP-9与肾母细胞瘤发生有关,基于超声检查和肿瘤细胞因子所构建的诊断模型具有较高区分度、校准度以及诊断效能,可为肾母细胞瘤临床诊断提供参考。

基于血清标志物构建预测老年重症肺炎预后的Nomogram模型

目的:探究血清标志物Nomogram预测模型对老年重症肺炎(SP)预后的预测价值。方法:选取2022年1月至2023年1月武汉市红十字会医院收治的310例老年SP患者,按7∶3比例随机分为建模人群(n=217)与验证人群(n=93)。比较建模人群、验证人群入院28 d内预后情况,血清可溶性髓系细胞表达的触发受体-1(sTREM-1)、基质金属蛋白酶抑制剂-1(TIMP-1)、可溶性白细胞分化抗原14亚型(Presepsin)、N末端脑钠肽前体(NT-proBNP)、C反应蛋白(CRP)、饥饿素(Ghrelin)、降钙素原(PCT)、中性粒细胞与淋巴细胞比值(NLR)、肿瘤坏死因子-α(TNF-α)和白介素-6(IL-6)水平,Lasso-logistic回归分析老年SP预后不良的预测因素,并构建预后不良Nomogram预测模型,在验证人群中对Nomogram预测模型进行外部验证。结果:建模人群入院28 d内死亡78例(35.94%),验证人群入院28 d内死亡34例(36.56%),两组病死率比较无统计学差异(P>0.05)。建模人群、验证人群中,不同预后患者血清sTREM-1、NT-proBNP、TIMP-1、Presepsin、PCT、Ghrelin、CRP、IL-6、NLR、TNF-α水平比较,差异有统计学意义(P<0.05)。Lasso回归筛选预测因素,logistic回归分析显示,血清sTREM-1、TIMP-1、NT-proBNP、Presepsin、Ghrelin、PCT、NLR水平为老年SP预后不良的影响因素(P<0.05)。基于Lasso-logistic回归预测因素构建预测模型,验证人群受试者工作特征(ROC)曲线、临床决策曲线(DCA)显示,该预测模型具有良好的临床效用。结论:血清sTREM-1、TIMP-1、NT-proBNP、Presepsin、Ghrelin、PCT、NLR水平为老年SP患者预后不良的预测因子,基于以上因素构建Nomogram预测模型具有一定的临床价值。