Background Resuscitation can sometimes be futile and making a do-not-resuscitate(DNR)decision is in the best interest of the patient.The electronic poor outcome screening(ePOS)score was developed to predict 6-month po...Background Resuscitation can sometimes be futile and making a do-not-resuscitate(DNR)decision is in the best interest of the patient.The electronic poor outcome screening(ePOS)score was developed to predict 6-month poor outcomes of critically ill patients.We explored the diagnostic accuracy of the ePOS score in predicting DNR decisions in the intensive care unit(ICU).Methods This study was conducted at the ICU of a tertiary referral hospital in Saudi Arabia between March and May 2023.Prospectively,we calculated ePOS scores for all eligible consecutive admissions after 48 h in the ICU and recorded the DNR orders.The ability of the score to predict DNR was explored using logistic regression.Youden's ideal cut-off value was calculated using the DeLong method,and different diagnostic accuracy measures were generated with corresponding 95%confidence intervals(CIs).Results We enrolled 857 patients,125 received a DNR order and 732 did not.The average ePOS score of DNR and non-DNR patients was 28.2±10.7 and 15.2±9.7,respectively.ePOS score,as a predictor of DNR order,had an area under receiver operator characteristic(AUROC)curve of 81.8%(95%CI:79.0 to 84.3,P<0.001).Youden's ideal cut-off value>17 was associated with a sensitivity of 87.2(95%CI:80.0 to 92.5,P<0.001),specificity of 63.9(95%CI:60.3 to 67.4,P<0.001),positive predictive value of 29.2(95%CI:24.6 to 33.8,P<0.001),negative predictive value of 96.7(95%CI:95.1 to 98.3,P<0.001),and diagnostic odds ratio 12.1(95%CI:7.0 to 20.8,P<0.001).Conclusions In this study,the ePOS score performed well as a diagnostic test for patients who will be labeled as DNR during their ICU stay.A cut-off score>17 may help guide clinical decisions to withhold or commence resuscitative measures.展开更多
Model-based fault diagnosis serves as an efficient and powerful technique in addressing fault detection and isolation(FDI)issues for control systems.However,the standard methods and their modifications still encounter...Model-based fault diagnosis serves as an efficient and powerful technique in addressing fault detection and isolation(FDI)issues for control systems.However,the standard methods and their modifications still encounter some difficulties in algorithm design and application for complex higher-order systems.To avoid these difficulties,a novel fault diagnosis framework based on multiple performance indicators of closed-loop control system is proposed.Under this framework,a socalled performance residual vector is constructed to measure the differences between the real system and the nominal model in terms of system stability,accuracy,and rapidity(SAR)respectively.The criteria for quantification,normalization of the SAR residuals and the explicit mappings between the thresholds and the required performance are given.FDI can be easily achieved simultaneously by monitoring the normalized residual vector length and direction in the SAR performance residual space.A case study on electro-hydraulic servo control system of turbofan engine is adopted to demonstrate the effectiveness of the proposed method.展开更多
文摘Background Resuscitation can sometimes be futile and making a do-not-resuscitate(DNR)decision is in the best interest of the patient.The electronic poor outcome screening(ePOS)score was developed to predict 6-month poor outcomes of critically ill patients.We explored the diagnostic accuracy of the ePOS score in predicting DNR decisions in the intensive care unit(ICU).Methods This study was conducted at the ICU of a tertiary referral hospital in Saudi Arabia between March and May 2023.Prospectively,we calculated ePOS scores for all eligible consecutive admissions after 48 h in the ICU and recorded the DNR orders.The ability of the score to predict DNR was explored using logistic regression.Youden's ideal cut-off value was calculated using the DeLong method,and different diagnostic accuracy measures were generated with corresponding 95%confidence intervals(CIs).Results We enrolled 857 patients,125 received a DNR order and 732 did not.The average ePOS score of DNR and non-DNR patients was 28.2±10.7 and 15.2±9.7,respectively.ePOS score,as a predictor of DNR order,had an area under receiver operator characteristic(AUROC)curve of 81.8%(95%CI:79.0 to 84.3,P<0.001).Youden's ideal cut-off value>17 was associated with a sensitivity of 87.2(95%CI:80.0 to 92.5,P<0.001),specificity of 63.9(95%CI:60.3 to 67.4,P<0.001),positive predictive value of 29.2(95%CI:24.6 to 33.8,P<0.001),negative predictive value of 96.7(95%CI:95.1 to 98.3,P<0.001),and diagnostic odds ratio 12.1(95%CI:7.0 to 20.8,P<0.001).Conclusions In this study,the ePOS score performed well as a diagnostic test for patients who will be labeled as DNR during their ICU stay.A cut-off score>17 may help guide clinical decisions to withhold or commence resuscitative measures.
基金co-supported by the National Science and Technology Major Project of China(Nos.2017-V-0011-0062,2017-V-0010-0060)National Natural Science Foundation of China(51875014)the Academic Excellence Foundation of BUAA for PhD Students。
文摘Model-based fault diagnosis serves as an efficient and powerful technique in addressing fault detection and isolation(FDI)issues for control systems.However,the standard methods and their modifications still encounter some difficulties in algorithm design and application for complex higher-order systems.To avoid these difficulties,a novel fault diagnosis framework based on multiple performance indicators of closed-loop control system is proposed.Under this framework,a socalled performance residual vector is constructed to measure the differences between the real system and the nominal model in terms of system stability,accuracy,and rapidity(SAR)respectively.The criteria for quantification,normalization of the SAR residuals and the explicit mappings between the thresholds and the required performance are given.FDI can be easily achieved simultaneously by monitoring the normalized residual vector length and direction in the SAR performance residual space.A case study on electro-hydraulic servo control system of turbofan engine is adopted to demonstrate the effectiveness of the proposed method.
