目的:探索控制营养状况(Controlling Nutritional Status,CONUT)评分、WPCBAL评分、预后营养指数(Prognostic Nutritional Index,PNI)等3种预后评分系统对晚期肺癌患者生存时间的预测效能。方法:收集2018年12月—2021年12月在山东省第...目的:探索控制营养状况(Controlling Nutritional Status,CONUT)评分、WPCBAL评分、预后营养指数(Prognostic Nutritional Index,PNI)等3种预后评分系统对晚期肺癌患者生存时间的预测效能。方法:收集2018年12月—2021年12月在山东省第一医科大学附属肿瘤医院住院期间发生死亡,且具有评估所需全部数据的138例晚期肺癌患者的相关资料,进行回顾性分析。3个评分系统不同组别人群生存期差异的比较采用Log-rank检验,评估系统对终末期肺癌患者2周生存期的预测效能用受试者工作特征(ROC)曲线进行评价。结果:138例终末期肺癌患者的中位年龄为63.5岁,末次入院的中位生存时间为14 d,2周死亡率为51.4%。Log-rank检验结果显示,CONUT≥5分组的生存时间比CONUT<5分组更短,差异有统计学意义(11 d vs 16 d,P=0.046);WPCBAL≥5分组的生存时间比WPCBAL<5分组更短,差异有统计学意义(8 d vs 16 d,P=0.002)。ROC曲线显示,CONUT、WPCBAL对晚期肺癌患者2周生存状态的预测有一定价值,ROC曲线下面积分别为0.613、0.677。CONUT评分以5为截点时,预测晚期肺癌患者2周生存期的灵敏度、特异度分别为0.61、0.54;WPCBAL评分以5为截点时,预测晚期肺癌患者2周生存期的灵敏度、特异度分别为0.76、0.54。结论:CONUT评分、WPCBAL评分对预测晚期肺癌患者短期生存状态有一定价值,但特异度相对较低,仍需进一步研究。展开更多
目的评价术前CONUT评分在接受手术治疗的胃癌患者中的预后价值。方法计算机检索PubMed、Web of Science、Embase、Cochrane图书馆、中国期刊全文数据库(CNKI)、万方数据库等数据库,纳入关于术前CONUT评分与接受手术治疗胃癌患者预后的...目的评价术前CONUT评分在接受手术治疗的胃癌患者中的预后价值。方法计算机检索PubMed、Web of Science、Embase、Cochrane图书馆、中国期刊全文数据库(CNKI)、万方数据库等数据库,纳入关于术前CONUT评分与接受手术治疗胃癌患者预后的相关研究,检索时间为建库至2018年10月。按照纳入与排除标准筛选文献,提取数据并进行质量评价,采用Stata 12.0软件进行Meta分析。结果共纳入5篇英文文献,包含1822例Ⅰ~Ⅳ期胃癌患者。分析结果表明,术前CONUT评分与胃癌患者的总生存期(OS)显著相关,评分越高患者OS越短,差异有统计学意义(HR:1.71,95%CI:1.03~2.85,P=0.038)。亚组分析显示:在中国和截止值为3的研究中,术前CONUT评分与胃癌患者的OS明显缩短(中国,HR:1.44,95%CI:1.13~1.84,P=0.003;截止值为3,HR:3.27,95%CI:1.96~5.48,P<0.001)。但在日本和截止值不为3的研究中,术前CONUT评分与胃癌患者的OS无明显相关性(日本,HR:2.05,95%CI:0.68~6.18,P=0.203;截止值不为3,HR:1.16,95%CI:0.75~1.80,P=0.491)。结论术前CONUT评分与接受手术治疗胃癌患者的OS明显相关,可作为胃癌术后预后评估的潜在标记物。展开更多
Background:In-hospital mortality in patients with coronavirus disease 2019(COVID-19)is high.Simple prognostic indices are needed to identify patients at high-risk of COVID-19 health outcomes.We aimed to determine the ...Background:In-hospital mortality in patients with coronavirus disease 2019(COVID-19)is high.Simple prognostic indices are needed to identify patients at high-risk of COVID-19 health outcomes.We aimed to determine the usefulness of the CONtrolling NUTritional status(CONUT)index as a potential prognostic indicator of mortality in COVID-19 patients upon hospital admission.Methods:Our study design is of a retrospective observational study in a large cohort of COVID-19 patients.In addition to descriptive statistics,a Kaplan-Meier mortality analysis and a Cox regression were performed,as well as receiver operating curve(ROC).Results:From February 5,2020 to January 21,2021,there was a total of 2969 admissions for COVID-19 at our hospital,corresponding to 2844 patients.Overall,baseline(within 4 days of admission)CONUT index could be scored for 1627(57.2%)patients.Patients’age was 67.3±16.5 years and 44.9%were women.The CONUT severity distribution was:194(11.9%)normal(0-1);769(47.2%)light(2-4);585(35.9%)moderate(5-8);and 79(4.9%)severe(9-12).Mortality of 30 days after admission was 3.1%in patients with normal risk CONUT,9.0%light,22.7%moderate,and 40.5%in those with severe CONUT(P<0.05).An increased risk of death associated with a greater baseline CONUT stage was sustained in a multivariable Cox regression model(P<0.05).An increasing baseline CONUT stage was associated with a longer duration of admission,a greater requirement for the use of non-invasive and invasive mechanical ventilation,and other clinical outcomes(all P<0.05).The ROC of CONUT for mortality had an area under the curve(AUC)and 95%confidence interval of 0.711(0.676-0746).Conclusion:The CONUT index upon admission is potentially a reliable and independent prognostic indicator of mortality and length of hospitalization in COVID-19 patients.展开更多
Objective:To investigate the predictive value of controlling nutritional status(CONUT)score for progression to chronic critical illness sepsis in elderly patients,and to construct a predictive model based on CONUT sco...Objective:To investigate the predictive value of controlling nutritional status(CONUT)score for progression to chronic critical illness sepsis in elderly patients,and to construct a predictive model based on CONUT score histogram.Methods:739 elderly patients with sepsis admitted from January 2020 to December 2022 were selected as the study objects,and were divided into chronic critical illness group(n=188)and non-chronic critical illness group(n=551)according to whether chronic critical illness disease occurred.Clinical data of the patients were collected and compared.The predictive value of CONUT score,PNI and NLR in the progression of senile sepsis to chronic severe disease was compared,and the optimal threshold value was determined,which was used to convert the numerical variables into binary variables.Through univariate analysis and multivariate Logistic regression analysis,the risk factors affecting the progression of elderly sepsis patients to chronic critical illness disease were screened out,and the prediction model was built based on the nomogram.The efficacy and clinical utility of the prediction model were evaluated by the area under the ROC curve(AUC),calibration curve and decision curve analysis(DCA).Results:The best cut-off value for CONUT score in predicting elderly sepsis progressing to chronic critical illness was 4 points.The predictive performance of CONUT score(AUC=0.739)was better than that of PNI(AUC=0.609)and NLR(AUC=0.582)in elderly sepsis progressing to chronic critical illness(CONUT score vs PNI:Z=5.960,P<0.001;CONUT score vs NLR:Z=6.119,P<0.001).Univariate analysis showed that age,CCI score,SOFA score,sepsis shock,serum Lac,CONUT score,mechanical ventilation(MV),and continuous renal replacement therapy(CRRT)treatment were related to elderly sepsis progressing to chronic critical illness(P<0.05).Multivariate logistic regression analysis showed that CONUT score≥4 points,age≥75 years,CCI score≥3 points,SOFA score>5 points,sepsis shock,and serum Lac≥4 mmol/L were independent risk factors for elderly sepsis progressing to chronic critical illness(P<0.05).The nomogram showed that CONUT score had the greatest contribution value in predicting elderly sepsis progressing to chronic critical illness.Based on this,the nomogram prediction model had an AUC of 0.846[95%CI(0.812~0.879)],with a sensitivity of 75.5%and specificity of 81.3%,indicating good predictive performance.The calibration curve was close to the ideal curve,and the DCA threshold had clinical utility advantages when ranging from 0.1 to 0.9.Conclusion:The nomographic prediction model based on CONUT score can effectively predict the risk probability of senile sepsis progressing to chronic critical illness,helpful for clinicians to identify the high risk group of chronic and severe senile sepsis,which is helpful for clinicians to identify high-risk populations of elderly sepsis with chronic critical illness.展开更多
文摘目的:探索控制营养状况(Controlling Nutritional Status,CONUT)评分、WPCBAL评分、预后营养指数(Prognostic Nutritional Index,PNI)等3种预后评分系统对晚期肺癌患者生存时间的预测效能。方法:收集2018年12月—2021年12月在山东省第一医科大学附属肿瘤医院住院期间发生死亡,且具有评估所需全部数据的138例晚期肺癌患者的相关资料,进行回顾性分析。3个评分系统不同组别人群生存期差异的比较采用Log-rank检验,评估系统对终末期肺癌患者2周生存期的预测效能用受试者工作特征(ROC)曲线进行评价。结果:138例终末期肺癌患者的中位年龄为63.5岁,末次入院的中位生存时间为14 d,2周死亡率为51.4%。Log-rank检验结果显示,CONUT≥5分组的生存时间比CONUT<5分组更短,差异有统计学意义(11 d vs 16 d,P=0.046);WPCBAL≥5分组的生存时间比WPCBAL<5分组更短,差异有统计学意义(8 d vs 16 d,P=0.002)。ROC曲线显示,CONUT、WPCBAL对晚期肺癌患者2周生存状态的预测有一定价值,ROC曲线下面积分别为0.613、0.677。CONUT评分以5为截点时,预测晚期肺癌患者2周生存期的灵敏度、特异度分别为0.61、0.54;WPCBAL评分以5为截点时,预测晚期肺癌患者2周生存期的灵敏度、特异度分别为0.76、0.54。结论:CONUT评分、WPCBAL评分对预测晚期肺癌患者短期生存状态有一定价值,但特异度相对较低,仍需进一步研究。
文摘目的评价术前CONUT评分在接受手术治疗的胃癌患者中的预后价值。方法计算机检索PubMed、Web of Science、Embase、Cochrane图书馆、中国期刊全文数据库(CNKI)、万方数据库等数据库,纳入关于术前CONUT评分与接受手术治疗胃癌患者预后的相关研究,检索时间为建库至2018年10月。按照纳入与排除标准筛选文献,提取数据并进行质量评价,采用Stata 12.0软件进行Meta分析。结果共纳入5篇英文文献,包含1822例Ⅰ~Ⅳ期胃癌患者。分析结果表明,术前CONUT评分与胃癌患者的总生存期(OS)显著相关,评分越高患者OS越短,差异有统计学意义(HR:1.71,95%CI:1.03~2.85,P=0.038)。亚组分析显示:在中国和截止值为3的研究中,术前CONUT评分与胃癌患者的OS明显缩短(中国,HR:1.44,95%CI:1.13~1.84,P=0.003;截止值为3,HR:3.27,95%CI:1.96~5.48,P<0.001)。但在日本和截止值不为3的研究中,术前CONUT评分与胃癌患者的OS无明显相关性(日本,HR:2.05,95%CI:0.68~6.18,P=0.203;截止值不为3,HR:1.16,95%CI:0.75~1.80,P=0.491)。结论术前CONUT评分与接受手术治疗胃癌患者的OS明显相关,可作为胃癌术后预后评估的潜在标记物。
基金The work is supported by a grant from the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement(No 101016216).
文摘Background:In-hospital mortality in patients with coronavirus disease 2019(COVID-19)is high.Simple prognostic indices are needed to identify patients at high-risk of COVID-19 health outcomes.We aimed to determine the usefulness of the CONtrolling NUTritional status(CONUT)index as a potential prognostic indicator of mortality in COVID-19 patients upon hospital admission.Methods:Our study design is of a retrospective observational study in a large cohort of COVID-19 patients.In addition to descriptive statistics,a Kaplan-Meier mortality analysis and a Cox regression were performed,as well as receiver operating curve(ROC).Results:From February 5,2020 to January 21,2021,there was a total of 2969 admissions for COVID-19 at our hospital,corresponding to 2844 patients.Overall,baseline(within 4 days of admission)CONUT index could be scored for 1627(57.2%)patients.Patients’age was 67.3±16.5 years and 44.9%were women.The CONUT severity distribution was:194(11.9%)normal(0-1);769(47.2%)light(2-4);585(35.9%)moderate(5-8);and 79(4.9%)severe(9-12).Mortality of 30 days after admission was 3.1%in patients with normal risk CONUT,9.0%light,22.7%moderate,and 40.5%in those with severe CONUT(P<0.05).An increased risk of death associated with a greater baseline CONUT stage was sustained in a multivariable Cox regression model(P<0.05).An increasing baseline CONUT stage was associated with a longer duration of admission,a greater requirement for the use of non-invasive and invasive mechanical ventilation,and other clinical outcomes(all P<0.05).The ROC of CONUT for mortality had an area under the curve(AUC)and 95%confidence interval of 0.711(0.676-0746).Conclusion:The CONUT index upon admission is potentially a reliable and independent prognostic indicator of mortality and length of hospitalization in COVID-19 patients.
基金Natural Science Foundation of Hainan Provincial(No.819MS128)。
文摘Objective:To investigate the predictive value of controlling nutritional status(CONUT)score for progression to chronic critical illness sepsis in elderly patients,and to construct a predictive model based on CONUT score histogram.Methods:739 elderly patients with sepsis admitted from January 2020 to December 2022 were selected as the study objects,and were divided into chronic critical illness group(n=188)and non-chronic critical illness group(n=551)according to whether chronic critical illness disease occurred.Clinical data of the patients were collected and compared.The predictive value of CONUT score,PNI and NLR in the progression of senile sepsis to chronic severe disease was compared,and the optimal threshold value was determined,which was used to convert the numerical variables into binary variables.Through univariate analysis and multivariate Logistic regression analysis,the risk factors affecting the progression of elderly sepsis patients to chronic critical illness disease were screened out,and the prediction model was built based on the nomogram.The efficacy and clinical utility of the prediction model were evaluated by the area under the ROC curve(AUC),calibration curve and decision curve analysis(DCA).Results:The best cut-off value for CONUT score in predicting elderly sepsis progressing to chronic critical illness was 4 points.The predictive performance of CONUT score(AUC=0.739)was better than that of PNI(AUC=0.609)and NLR(AUC=0.582)in elderly sepsis progressing to chronic critical illness(CONUT score vs PNI:Z=5.960,P<0.001;CONUT score vs NLR:Z=6.119,P<0.001).Univariate analysis showed that age,CCI score,SOFA score,sepsis shock,serum Lac,CONUT score,mechanical ventilation(MV),and continuous renal replacement therapy(CRRT)treatment were related to elderly sepsis progressing to chronic critical illness(P<0.05).Multivariate logistic regression analysis showed that CONUT score≥4 points,age≥75 years,CCI score≥3 points,SOFA score>5 points,sepsis shock,and serum Lac≥4 mmol/L were independent risk factors for elderly sepsis progressing to chronic critical illness(P<0.05).The nomogram showed that CONUT score had the greatest contribution value in predicting elderly sepsis progressing to chronic critical illness.Based on this,the nomogram prediction model had an AUC of 0.846[95%CI(0.812~0.879)],with a sensitivity of 75.5%and specificity of 81.3%,indicating good predictive performance.The calibration curve was close to the ideal curve,and the DCA threshold had clinical utility advantages when ranging from 0.1 to 0.9.Conclusion:The nomographic prediction model based on CONUT score can effectively predict the risk probability of senile sepsis progressing to chronic critical illness,helpful for clinicians to identify the high risk group of chronic and severe senile sepsis,which is helpful for clinicians to identify high-risk populations of elderly sepsis with chronic critical illness.
