BACKGROUND Locally advanced rectal cancer(LARC)carries a substantial risk of recurrence,prompting the use of neoadjuvant chemoradiotherapy(nCRT)to improve tumor resectability and long-term outcomes.However,individual ...BACKGROUND Locally advanced rectal cancer(LARC)carries a substantial risk of recurrence,prompting the use of neoadjuvant chemoradiotherapy(nCRT)to improve tumor resectability and long-term outcomes.However,individual treatment responses vary considerably,highlighting the need for robust predictive tools to guide clinical decision-making.AIM To develop a nomogram model integrating clinical characteristics and biomarkers to predict the likelihood of poor response to nCRT in LARC.METHODS A retrospective analysis was performed on 178 patients with stage II-III LARC treated from January 2021 to December 2023.All patients underwent standardized nCRT followed by total mesorectal excision.Clinical data,inflammatory markers[C-reactive protein(CRP),interleukin-6(IL-6),tumor necrosis factoralpha],and tumor markers[carcinoembryonic antigen(CEA),carbohydrate antigen 19-9]were collected.Logistic regression was used to identify independent predictors of poor nCRT response.A nomogram was constructed using significant predictors and validated via concordance index(C-index),receiver operating characteristic curve,calibration plot,and decision curve analysis(DCA).RESULTS A total of 178 patients were enrolled,with 36(20.2%)achieving a good response and 142(79.8%)exhibiting a poor response to nCRT.Baseline factors,including age and comorbidities,showed no significant differences.However,poor responders more frequently had lymph node metastasis,advanced tumor node metastasis/T stage,larger tumor diameter,and elevated CRP,IL-6,and CEA levels.Logistic regression confirmed CRP,IL-6,and CEA as independent predictors of poor response.The nomogram demonstrated high accuracy(area under the curve=0.928),good calibration(Hosmer-Lemeshow P=0.928),and a sensitivity of 88.1%with 82.6%specificity.Internal validation via bootstrap resampling(n=1000)yielded an adjusted C-index of 0.716,and DCA confirmed substantial clinical utility.CONCLUSION A nomogram incorporating serum CRP,IL-6,and CEA accurately predicts poor nCRT response in patients with LARC.This model provides a valuable framework for individualized treatment planning,potentially improving clinical outcomes.展开更多
The prevalence of type 2 diabetes mellitus(T2DM)is rising,with hypertension as a common comorbidity that significantly increases cardiovascular and microva-scular risks.Accurate prediction of hypertension in T2DM is e...The prevalence of type 2 diabetes mellitus(T2DM)is rising,with hypertension as a common comorbidity that significantly increases cardiovascular and microva-scular risks.Accurate prediction of hypertension in T2DM is essential for early intervention and personalized management.In this editorial,we comment on a recent retrospective study by Zhao et al,which developed a nomogram model using a large cohort of 26850 patients to predict hypertension risk in patients with T2DM.The model incorporated key independent risk factors,including age,body mass index,duration of diabetes,low-density lipoprotein cholesterol and urine protein levels,demonstrating promising discriminative power and predictive accuracy in internal validation.However,its external applicability requires fur-ther confirmation.This editorial discusses the clinical value and limitations of the predictive model,highlighting the unfavorable impact of hypertension on T2DM patients.Future research should evaluate the potential contribution of other risk factors to enhance risk prediction and improve the management of T2DM co-morbidities.展开更多
BACKGROUND The characteristics of cerebral hemodynamic indexes of patients with different types of auditory verbal hallucinations(AVHs)was not clear.AIM To explore the characteristics of cerebral hemodynamic indexes o...BACKGROUND The characteristics of cerebral hemodynamic indexes of patients with different types of auditory verbal hallucinations(AVHs)was not clear.AIM To explore the characteristics of cerebral hemodynamic indexes of patients with different types of AVHs and construct the risk nomogram prediction model of patients with different types of AVHs.METHODS Patients with different types of verbal hallucinations who visited Wenzhou Seventh People’s Hospital were retrospectively selected from March 2021 to March 2023,and these patients were classified into 117 cases of schizophrenia(SCZ)with AVHs,108 cases of post-traumatic stress disorder(PTSD)with AVHs,and 105 cases of recurrent depressive disorder with AVHs according to type.Transcranial doppler was performed to measure the hemodynamic parameters of the anterior cerebral artery(ACA),middle cerebral artery(MCA),posterior cerebral artery(PCA),basilar artery(BA)and vertebral artery(VA).Logistic regression modelling was used to explore the factors affecting patients with different types of AVHs and odds ratio,95%confidence interval(CI).A clinical prediction model was constructed,and the efficacy of the clinical prediction model was evaluated by using receiver operating characteristic,Hosmer-Lemeshow Goodness-of-Fit test,calibration curves and decision curve analysis.RESULTS The differences between the three groups of patients in mean velocity(Vm)-MCA,end-diastolic velocity(Vd)-MCA,Vm-ACA,pulsatility index(PI)-ACA,Vm-PCA,peak systolic velocity(Vs)-PCA,Vd-PCA,Vm-BA,Vs-BA,Vd-BA,PI-BA,resistance index(RI)-BA,Vm-VA,Vs-VA,Vd-VA,PI-VA,and RI-VA indexes were statistically significant.Rising Vm-ACA is an independent risk factor for SCZ with AVHs,and falling Vm-VA,Vd-MCA,and Vd-VA are independent risk factors for SCZ with AVHs.Rising Vm-ACA,Vm-PCA,Vs-PCA,Vd-PCA,Vm-BA,and Vs-BA are independent risk factors for PTSD with AVHs,and Vm-MCA,Vs-MCA,Vd-MCA,PI-PCA,and RIBA are independent protective factors for PTSD with AVHs.Elevated Vm-MCA,Vd-MCA,RI-BA,Vm-VA,and Vd-VA were independent risk factors,and elevated Vm-ACA,Vs-ACA,Vm-PCA,Vs-PCA,and Vd-PCA were independent protective factors.The areas under the curve of the three models were 0.82(95%CI:0.76-0.87),0.88(95%CI:0.83-0.92),and 0.81(95%CI:0.77-0.86),respectively;the Hosmer-Lemeshow Goodness-of-Fit test of the calibration curves of the three models suggests that P>0.05.CONCLUSION Monitoring the cerebral hemodynamic indexes of patients with AVHs is of practical significance in determining the type of mental disorder,which helps clinicians identify the type of AVHs and adopt more efficient treatment strategies to help patients recover.展开更多
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 nov...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.展开更多
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 stu...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.展开更多
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,patien...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.展开更多
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.Met...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.展开更多
Objective To develop and validate clinical predictive models for identifying poor short-term response to recombinant human growth hormone (rhGH) treatment in children with short stature.Methods A retrospective analysi...Objective To develop and validate clinical predictive models for identifying poor short-term response to recombinant human growth hormone (rhGH) treatment in children with short stature.Methods A retrospective analysis was conducted on 118 children diagnosed with growth hormone deficiency or idiopathic short stature who were treated at the First Affiliated Hospital of Zhengzhou University and two other hospitals between January 1,2020,and January 1,2024.展开更多
Objective To construct a nomogram prediction model for predicting hemoglobin A_(1)c(HbA_(1)c)failure in type 2 diabetes mellitus(T2DM)patients.Methods A total of 936 inpatients with T2DM admitted to the Department of ...Objective To construct a nomogram prediction model for predicting hemoglobin A_(1)c(HbA_(1)c)failure in type 2 diabetes mellitus(T2DM)patients.Methods A total of 936 inpatients with T2DM admitted to the Department of Endocrinology of the Affiliated Hospital of Shandong Second Medical University from January 2021to January 2022 were selected as the research subjects and divided into the non-standard group(HbA_(1)c≥7%,n=801)and the standard group(HbA_(1)c<7%,n=135).展开更多
目的基于血清学标志物构建早产儿视网膜病变(ROP)患儿预后的Nomogram预测模型,并验证模型的预测价值。方法选取2022年1月至2024年1月河北医科大学第二医院收治的195例(390眼)ROP患儿,治疗后随访3个月,根据预后情况分为预后不良组(n=41)...目的基于血清学标志物构建早产儿视网膜病变(ROP)患儿预后的Nomogram预测模型,并验证模型的预测价值。方法选取2022年1月至2024年1月河北医科大学第二医院收治的195例(390眼)ROP患儿,治疗后随访3个月,根据预后情况分为预后不良组(n=41)、预后良好组(n=154)。比较两组患儿一般资料、治疗前血清学标志物[血管内皮生长因子(VEGF)、胰岛素样生长因子-1(IGF-1)、谷氨酸(Glu)、信号转导和转录激活因子3(STAT3)、低氧诱导因子3α(HIF-3α)]水平,通过LASSO-Logistic回归分析ROP患儿预后不良的影响因素,根据影响因素构建ROP患儿预后不良的Nomogram预测模型,通过受试者工作特征曲线、校准曲线及决策曲线验证模型的预测价值。结果预后不良组患儿1 min Apgar、5 min Apgar、病情程度重度占比、支气管肺发育不良占比、败血症占比及治疗前血清VEGF、Glu、STAT3、HIF-3α水平均高于预后良好组,胎龄、出生体重、血清IGF-1水平均低于预后良好组(均为P<0.05);LASSO-Logistic回归分析显示,胎龄、病情程度、支气管肺发育不良、败血症及治疗前血清VEGF、IGF-1、Glu、STAT3、HIF-3α水平均为ROP患儿预后不良的影响因素(均为P<0.05);根据影响因素构建ROP患儿预后不良的Nomogram预测模型,该模型预测ROP患儿预后不良的曲线下面积为0.943(95%CI:0.907~0.978),具有较高预测效能,该模型的校准度良好,预测结果与实际观测结果有较好的一致性,且在预测ROP患儿预后不良方面拥有良好的临床效用。结论血清VEGF、IGF-1、Glu、STAT3、HIF-3α水平均为ROP患儿预后的影响因素,基于以上血清学标志物构建的ROP患儿预后的Nomogram预测模型具有较高应用价值。展开更多
Zhao et al’s investigation on the assessment of inflammatory markers prognostic value for relapse-free survival in patients with gastrointestinal stromal tumor(GIST)using a nomogram-based approach is a scientific app...Zhao et al’s investigation on the assessment of inflammatory markers prognostic value for relapse-free survival in patients with gastrointestinal stromal tumor(GIST)using a nomogram-based approach is a scientific approach.This study explored the potential of an inflammatory marker-based nomograph model,highlighting the relapse-free survival-associated risk factors prognostic potential in patients with GIST.The author assessed 124 samples from patients with GIST to find an association between inflammatory markers and tumor size in a retrospective study using multivariate regression analysis.Further,a nomogram model was developed to identify the independent risk factors for the prognosis.GIST clinical treatment can use preoperative monocyte/lymphocyte ratio and platelet/lymphocyte ratio for relapse-free survival prognosis as independent factors.展开更多
BACKGROUND Post-stroke infection is the most common complication of stroke and poses a huge threat to patients.In addition to prolonging the hospitalization time and increasing the medical burden,post-stroke infection...BACKGROUND Post-stroke infection is the most common complication of stroke and poses a huge threat to patients.In addition to prolonging the hospitalization time and increasing the medical burden,post-stroke infection also significantly increases the risk of disease and death.Clarifying the risk factors for post-stroke infection in patients with acute ischemic stroke(AIS)is of great significance.It can guide clinical practice to perform corresponding prevention and control work early,minimizing the risk of stroke-related infections and ensuring favorable disease outcomes.AIM To explore the risk factors for post-stroke infection in patients with AIS and to construct a nomogram predictive model.METHODS The clinical data of 206 patients with AIS admitted to our hospital between April 2020 and April 2023 were retrospectively collected.Baseline data and post-stroke infection status of all study subjects were assessed,and the risk factors for poststroke infection in patients with AIS were analyzed.RESULTS Totally,48 patients with AIS developed stroke,with an infection rate of 23.3%.Age,diabetes,disturbance of consciousness,high National Institutes of Health Stroke Scale(NIHSS)score at admission,invasive operation,and chronic obstructive pulmonary disease(COPD)were risk factors for post-stroke infection in patients with AIS(P<0.05).A nomogram prediction model was constructed with a C-index of 0.891,reflecting the good potential clinical efficacy of the nomogram prediction model.The calibration curve also showed good consistency between the actual observations and nomogram predictions.The area under the receiver operating characteristic curve was 0.891(95%confidence interval:0.839–0.942),showing predictive value for post-stroke infection.When the optimal cutoff value was selected,the sensitivity and specificity were 87.5%and 79.7%,respectively.CONCLUSION Age,diabetes,disturbance of consciousness,NIHSS score at admission,invasive surgery,and COPD are risk factors for post-stroke infection following AIS.The nomogram prediction model established based on these factors exhibits high discrimination and accuracy.展开更多
文摘BACKGROUND Locally advanced rectal cancer(LARC)carries a substantial risk of recurrence,prompting the use of neoadjuvant chemoradiotherapy(nCRT)to improve tumor resectability and long-term outcomes.However,individual treatment responses vary considerably,highlighting the need for robust predictive tools to guide clinical decision-making.AIM To develop a nomogram model integrating clinical characteristics and biomarkers to predict the likelihood of poor response to nCRT in LARC.METHODS A retrospective analysis was performed on 178 patients with stage II-III LARC treated from January 2021 to December 2023.All patients underwent standardized nCRT followed by total mesorectal excision.Clinical data,inflammatory markers[C-reactive protein(CRP),interleukin-6(IL-6),tumor necrosis factoralpha],and tumor markers[carcinoembryonic antigen(CEA),carbohydrate antigen 19-9]were collected.Logistic regression was used to identify independent predictors of poor nCRT response.A nomogram was constructed using significant predictors and validated via concordance index(C-index),receiver operating characteristic curve,calibration plot,and decision curve analysis(DCA).RESULTS A total of 178 patients were enrolled,with 36(20.2%)achieving a good response and 142(79.8%)exhibiting a poor response to nCRT.Baseline factors,including age and comorbidities,showed no significant differences.However,poor responders more frequently had lymph node metastasis,advanced tumor node metastasis/T stage,larger tumor diameter,and elevated CRP,IL-6,and CEA levels.Logistic regression confirmed CRP,IL-6,and CEA as independent predictors of poor response.The nomogram demonstrated high accuracy(area under the curve=0.928),good calibration(Hosmer-Lemeshow P=0.928),and a sensitivity of 88.1%with 82.6%specificity.Internal validation via bootstrap resampling(n=1000)yielded an adjusted C-index of 0.716,and DCA confirmed substantial clinical utility.CONCLUSION A nomogram incorporating serum CRP,IL-6,and CEA accurately predicts poor nCRT response in patients with LARC.This model provides a valuable framework for individualized treatment planning,potentially improving clinical outcomes.
基金Supported by National Natural Science Foundation of China,No.82170327 and No.82370332Tianjin Key Medical Discipline(Specialty)Construction Project,No.TJYXZDXK-029A.
文摘The prevalence of type 2 diabetes mellitus(T2DM)is rising,with hypertension as a common comorbidity that significantly increases cardiovascular and microva-scular risks.Accurate prediction of hypertension in T2DM is essential for early intervention and personalized management.In this editorial,we comment on a recent retrospective study by Zhao et al,which developed a nomogram model using a large cohort of 26850 patients to predict hypertension risk in patients with T2DM.The model incorporated key independent risk factors,including age,body mass index,duration of diabetes,low-density lipoprotein cholesterol and urine protein levels,demonstrating promising discriminative power and predictive accuracy in internal validation.However,its external applicability requires fur-ther confirmation.This editorial discusses the clinical value and limitations of the predictive model,highlighting the unfavorable impact of hypertension on T2DM patients.Future research should evaluate the potential contribution of other risk factors to enhance risk prediction and improve the management of T2DM co-morbidities.
文摘BACKGROUND The characteristics of cerebral hemodynamic indexes of patients with different types of auditory verbal hallucinations(AVHs)was not clear.AIM To explore the characteristics of cerebral hemodynamic indexes of patients with different types of AVHs and construct the risk nomogram prediction model of patients with different types of AVHs.METHODS Patients with different types of verbal hallucinations who visited Wenzhou Seventh People’s Hospital were retrospectively selected from March 2021 to March 2023,and these patients were classified into 117 cases of schizophrenia(SCZ)with AVHs,108 cases of post-traumatic stress disorder(PTSD)with AVHs,and 105 cases of recurrent depressive disorder with AVHs according to type.Transcranial doppler was performed to measure the hemodynamic parameters of the anterior cerebral artery(ACA),middle cerebral artery(MCA),posterior cerebral artery(PCA),basilar artery(BA)and vertebral artery(VA).Logistic regression modelling was used to explore the factors affecting patients with different types of AVHs and odds ratio,95%confidence interval(CI).A clinical prediction model was constructed,and the efficacy of the clinical prediction model was evaluated by using receiver operating characteristic,Hosmer-Lemeshow Goodness-of-Fit test,calibration curves and decision curve analysis.RESULTS The differences between the three groups of patients in mean velocity(Vm)-MCA,end-diastolic velocity(Vd)-MCA,Vm-ACA,pulsatility index(PI)-ACA,Vm-PCA,peak systolic velocity(Vs)-PCA,Vd-PCA,Vm-BA,Vs-BA,Vd-BA,PI-BA,resistance index(RI)-BA,Vm-VA,Vs-VA,Vd-VA,PI-VA,and RI-VA indexes were statistically significant.Rising Vm-ACA is an independent risk factor for SCZ with AVHs,and falling Vm-VA,Vd-MCA,and Vd-VA are independent risk factors for SCZ with AVHs.Rising Vm-ACA,Vm-PCA,Vs-PCA,Vd-PCA,Vm-BA,and Vs-BA are independent risk factors for PTSD with AVHs,and Vm-MCA,Vs-MCA,Vd-MCA,PI-PCA,and RIBA are independent protective factors for PTSD with AVHs.Elevated Vm-MCA,Vd-MCA,RI-BA,Vm-VA,and Vd-VA were independent risk factors,and elevated Vm-ACA,Vs-ACA,Vm-PCA,Vs-PCA,and Vd-PCA were independent protective factors.The areas under the curve of the three models were 0.82(95%CI:0.76-0.87),0.88(95%CI:0.83-0.92),and 0.81(95%CI:0.77-0.86),respectively;the Hosmer-Lemeshow Goodness-of-Fit test of the calibration curves of the three models suggests that P>0.05.CONCLUSION Monitoring the cerebral hemodynamic indexes of patients with AVHs is of practical significance in determining the type of mental disorder,which helps clinicians identify the type of AVHs and adopt more efficient treatment strategies to help patients recover.
基金reviewed and approved by the Institutional Review Board of Zhejiang Provincial People’s Hospital(Approval No.2023-338).
文摘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.
基金Our study has been approved by Medical Research Ethics Approval Committee(2023010122HN11C).
文摘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.
基金Supported by Guiding Project of Qinghai Provincial Health Commission,No.2021-wjzdx-89.
文摘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.
基金supported by Wuhan Scientific Research Project(No.EX20B05)National Nature Science Foundation of China(No.82000521).
文摘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.
文摘Objective To develop and validate clinical predictive models for identifying poor short-term response to recombinant human growth hormone (rhGH) treatment in children with short stature.Methods A retrospective analysis was conducted on 118 children diagnosed with growth hormone deficiency or idiopathic short stature who were treated at the First Affiliated Hospital of Zhengzhou University and two other hospitals between January 1,2020,and January 1,2024.
文摘Objective To construct a nomogram prediction model for predicting hemoglobin A_(1)c(HbA_(1)c)failure in type 2 diabetes mellitus(T2DM)patients.Methods A total of 936 inpatients with T2DM admitted to the Department of Endocrinology of the Affiliated Hospital of Shandong Second Medical University from January 2021to January 2022 were selected as the research subjects and divided into the non-standard group(HbA_(1)c≥7%,n=801)and the standard group(HbA_(1)c<7%,n=135).
文摘目的基于血清学标志物构建早产儿视网膜病变(ROP)患儿预后的Nomogram预测模型,并验证模型的预测价值。方法选取2022年1月至2024年1月河北医科大学第二医院收治的195例(390眼)ROP患儿,治疗后随访3个月,根据预后情况分为预后不良组(n=41)、预后良好组(n=154)。比较两组患儿一般资料、治疗前血清学标志物[血管内皮生长因子(VEGF)、胰岛素样生长因子-1(IGF-1)、谷氨酸(Glu)、信号转导和转录激活因子3(STAT3)、低氧诱导因子3α(HIF-3α)]水平,通过LASSO-Logistic回归分析ROP患儿预后不良的影响因素,根据影响因素构建ROP患儿预后不良的Nomogram预测模型,通过受试者工作特征曲线、校准曲线及决策曲线验证模型的预测价值。结果预后不良组患儿1 min Apgar、5 min Apgar、病情程度重度占比、支气管肺发育不良占比、败血症占比及治疗前血清VEGF、Glu、STAT3、HIF-3α水平均高于预后良好组,胎龄、出生体重、血清IGF-1水平均低于预后良好组(均为P<0.05);LASSO-Logistic回归分析显示,胎龄、病情程度、支气管肺发育不良、败血症及治疗前血清VEGF、IGF-1、Glu、STAT3、HIF-3α水平均为ROP患儿预后不良的影响因素(均为P<0.05);根据影响因素构建ROP患儿预后不良的Nomogram预测模型,该模型预测ROP患儿预后不良的曲线下面积为0.943(95%CI:0.907~0.978),具有较高预测效能,该模型的校准度良好,预测结果与实际观测结果有较好的一致性,且在预测ROP患儿预后不良方面拥有良好的临床效用。结论血清VEGF、IGF-1、Glu、STAT3、HIF-3α水平均为ROP患儿预后的影响因素,基于以上血清学标志物构建的ROP患儿预后的Nomogram预测模型具有较高应用价值。
文摘Zhao et al’s investigation on the assessment of inflammatory markers prognostic value for relapse-free survival in patients with gastrointestinal stromal tumor(GIST)using a nomogram-based approach is a scientific approach.This study explored the potential of an inflammatory marker-based nomograph model,highlighting the relapse-free survival-associated risk factors prognostic potential in patients with GIST.The author assessed 124 samples from patients with GIST to find an association between inflammatory markers and tumor size in a retrospective study using multivariate regression analysis.Further,a nomogram model was developed to identify the independent risk factors for the prognosis.GIST clinical treatment can use preoperative monocyte/lymphocyte ratio and platelet/lymphocyte ratio for relapse-free survival prognosis as independent factors.
基金Shandong Province Grassroots Health Technology Innovation Program Project,No.JCK22007.
文摘BACKGROUND Post-stroke infection is the most common complication of stroke and poses a huge threat to patients.In addition to prolonging the hospitalization time and increasing the medical burden,post-stroke infection also significantly increases the risk of disease and death.Clarifying the risk factors for post-stroke infection in patients with acute ischemic stroke(AIS)is of great significance.It can guide clinical practice to perform corresponding prevention and control work early,minimizing the risk of stroke-related infections and ensuring favorable disease outcomes.AIM To explore the risk factors for post-stroke infection in patients with AIS and to construct a nomogram predictive model.METHODS The clinical data of 206 patients with AIS admitted to our hospital between April 2020 and April 2023 were retrospectively collected.Baseline data and post-stroke infection status of all study subjects were assessed,and the risk factors for poststroke infection in patients with AIS were analyzed.RESULTS Totally,48 patients with AIS developed stroke,with an infection rate of 23.3%.Age,diabetes,disturbance of consciousness,high National Institutes of Health Stroke Scale(NIHSS)score at admission,invasive operation,and chronic obstructive pulmonary disease(COPD)were risk factors for post-stroke infection in patients with AIS(P<0.05).A nomogram prediction model was constructed with a C-index of 0.891,reflecting the good potential clinical efficacy of the nomogram prediction model.The calibration curve also showed good consistency between the actual observations and nomogram predictions.The area under the receiver operating characteristic curve was 0.891(95%confidence interval:0.839–0.942),showing predictive value for post-stroke infection.When the optimal cutoff value was selected,the sensitivity and specificity were 87.5%and 79.7%,respectively.CONCLUSION Age,diabetes,disturbance of consciousness,NIHSS score at admission,invasive surgery,and COPD are risk factors for post-stroke infection following AIS.The nomogram prediction model established based on these factors exhibits high discrimination and accuracy.
