Serum cystatin C,monocyte/high-density lipoprotein-C ratio,and uric acid for the diagnosis of coronary heart disease and heart failure

BACKGROUND Coronary heart disease(CHD)and heart failure(HF)are the major causes of morbidity and mortality worldwide.Early and accurate diagnoses of CHD and HF are essential for optimal management and prognosis.However,conventional diagnostic methods such as electrocardiography,echocardiography,and cardiac biomarkers have certain limitations,such as low sensitivity,specificity,availability,and cost-effectiveness.Therefore,there is a need for simple,noninvasive,and reliable biomarkers to diagnose CHD and HF.AIM To investigate serum cystatin C(Cys-C),monocyte/high-density lipoprotein cholesterol ratio(MHR),and uric acid(UA)diagnostic values for CHD and HF.METHODS We enrolled 80 patients with suspected CHD or HF who were admitted to our hospital between July 2022 and July 2023.The patients were divided into CHD(n=20),HF(n=20),CHD+HF(n=20),and control groups(n=20).The serum levels of Cys-C,MHR,and UA were measured using immunonephelometry and an enzymatic method,respectively,and the diagnostic values for CHD and HF were evaluated using receiver operating characteristic(ROC)curve analysis.RESULTS Serum levels of Cys-C,MHR,and UA were significantly higher in the CHD,HF,and CHD+HF groups than those in the control group.The serum levels of Cys-C,MHR,and UA were significantly higher in the CHD+HF group than those in the CHD or HF group.The ROC curve analysis showed that serum Cys-C,MHR,and UA had good diagnostic performance for CHD and HF,with areas under the curve ranging from 0.78 to 0.93.The optimal cutoff values of serum Cys-C,MHR,and UA for diagnosing CHD,HF,and CHD+HF were 1.2 mg/L,0.9×10^(9),and 389μmol/L;1.4 mg/L,1.0×10^(9),and 449μmol/L;and 1.6 mg/L,1.1×10^(9),and 508μmol/L,respectively.CONCLUSION Serum Cys-C,MHR,and UA are useful biomarkers for diagnosing CHD and HF,and CHD+HF.These can provide information for decision-making and risk stratification in patients with CHD and HF.

Attribute-driven Fuzzy Fault Tree Model for Adaptive Lubricant Failure Diagnosis

Lubricant diagnosis serves as a crucial accordance for condition-based maintenance(CBM)involving oil changing and wear examination of critical parts in equipment.However,the accuracy of traditional end-to-end diagnosis models is often limited by the inconsistency and random fluctuations in multiple monitoring indicators.To address this,an attribute-driven adaptive diagnosis method is developed,involving three attributes:physicochemical,contamination,and wear.Correspondingly,a fuzzy fault tree(termed FFT)-based model is constructed containing the logic correlations from monitoring indicators to attributes and to lubricant failures.In particular,inference rules are integrated to mitigate conflicts arising from the reverse degradation of multiple indicators.With this model,the lubricant conditions can be accurately assessed through rule-based reasoning.Furthermore,to enhance its intelligence,the model is dynamically optimized with lubricant analysis knowledge and monitoring data.For verification,the developed model is tested with lubricant samples from both the fatigue experiment and actual aero-engines.Fatigue experiments reveal that the proposed model can improve the lubricant diagnosis accuracy from 73.4%to 92.6%compared with the existing methods.While for the engine lubricant test,a high accuracy of 90%was achieved.

Movement analysis in the diagnosis and management of Parkinson’s disease

Challenges in the diagnosis and treatment of Parkinson’s disease:Parkinson’s disease(PD)is an increasingly prevalent neurodegenerative disease,at first sight primarily characterized by motor symptoms,although non-motor symptoms also constitute a major part of the overall phenotype.Clinically,this disease cannot be diagnosed reliably until a large part of the vulnerable dopaminergic neurons has been irretrievably lost,and the disease progresses inexorably.New biological criteria for PD have been proposed recently and might eventually improve early diagnosis,but they require further validation,and their use will initially be restricted to a research environment(Darweesh et al.,2024).

Visualizing traumatic brain injury:ocular clues for diagnosis and assessment

Traumatic brain injury (TBI) is defined as damage to the brain resulting from an external sudden physical force or shock to the head.It is considered a silent public health epidemic causing significant death and disability globally.There were 64,000 TBI related deaths reported in the USA in 2020,with about US$76 billion in direct and indirect medical costs annually.

Pathogenesis, diagnosis, and treatment of epilepsy: electromagnetic stimulation-mediated neuromodulation therapy and new technologies

Epilepsy is a severe,relapsing,and multifactorial neurological disorder.Studies regarding the accurate diagnosis,prognosis,and in-depth pathogenesis are crucial for the precise and effective treatment of epilepsy.The pathogenesis of epilepsy is complex and involves alterations in variables such as gene expression,protein expression,ion channel activity,energy metabolites,and gut microbiota composition.Satisfactory results are lacking for conventional treatments for epilepsy.Surgical resection of lesions,drug therapy,and non-drug interventions are mainly used in clinical practice to treat pain associated with epilepsy.Non-pharmacological treatments,such as a ketogenic diet,gene therapy for nerve regeneration,and neural regulation,are currently areas of research focus.This review provides a comprehensive overview of the pathogenesis,diagnostic methods,and treatments of epilepsy.It also elaborates on the theoretical basis,treatment modes,and effects of invasive nerve stimulation in neurotherapy,including percutaneous vagus nerve stimulation,deep brain electrical stimulation,repetitive nerve electrical stimulation,in addition to non-invasive transcranial magnetic stimulation and transcranial direct current stimulation.Numerous studies have shown that electromagnetic stimulation-mediated neuromodulation therapy can markedly improve neurological function and reduce the frequency of epileptic seizures.Additionally,many new technologies for the diagnosis and treatment of epilepsy are being explored.However,current research is mainly focused on analyzing patients’clinical manifestations and exploring relevant diagnostic and treatment methods to study the pathogenesis at a molecular level,which has led to a lack of consensus regarding the mechanisms related to the disease.

MicroRNAs as potential biomarkers for diagnosis of post-traumatic stress disorder

Post-traumatic stress disorder is a mental disorder caused by exposure to severe traumatic life events.Currently,there are no validated biomarkers or laboratory tests that can distinguish between trauma survivors with and without post-traumatic stress disorder.In addition,the heterogeneity of clinical presentations of post-traumatic stress disorder and the overlap of symptoms with other conditions can lead to misdiagnosis and inappropriate treatment.Evidence suggests that this condition is a multisystem disorder that affects many biological systems,raising the possibility that peripheral markers of disease may be used to diagnose post-traumatic stress disorder.We performed a PubMed search for microRNAs(miRNAs)in post-traumatic stress disorder(PTSD)that could serve as diagnostic biomarkers and found 18 original research articles on studies performed with human patients and published January 2012 to December 2023.These included four studies with whole blood,seven with peripheral blood mononuclear cells,four with plasma extracellular vesicles/exosomes,and one with serum exosomes.One of these studies had also used whole plasma.Two studies were excluded as they did not involve microRNA biomarkers.Most of the studies had collected samples from adult male Veterans who had returned from deployment and been exposed to combat,and only two were from recently traumatized adult subjects.In measuring miRNA expression levels,many of the studies had used microarray miRNA analysis,miRNA Seq analysis,or NanoString panels.Only six studies had used real time polymerase chain reaction assay to determine/validate miRNA expression in PTSD subjects compared to controls.The miRNAs that were found/validated in these studies may be considered as potential candidate biomarkers for PTSD and include miR-3130-5p in whole blood;miR-193a-5p,-7113-5p,-125a,-181c,and-671-5p in peripheral blood mononuclear cells;miR-10b-5p,-203a-3p,-4488,-502-3p,-874-3p,-5100,and-7641 in plasma extracellular vesicles/exosomes;and miR-18a-3p and-7-1-5p in blood plasma.Several important limitations identified in the studies need to be taken into account in future studies.Further studies are warranted with war veterans and recently traumatized children,adolescents,and adults having PTSD and use of animal models subjected to various stressors and the effects of suppressing or overexpressing specific microRNAs.

Autism spectrum disorder:difficulties in diagnosis and microRNA biomarkers

We performed a PubMed search for microRNAs in autism spectrum disorder that could serve as diagnostic biomarkers in patients and selected 17 articles published from January 2008 to December 2023,of which 4 studies were performed with whole blood,4 with blood plasma,5 with blood serum,1 with serum neural cell adhesion molecule L1-captured extracellular vesicles,1 with blood cells,and 2 with peripheral blood mononuclear cells.Most of the studies involved children and the study cohorts were largely males.Many of the studies had performed microRNA sequencing or quantitative polymerase chain reaction assays to measure microRNA expression.Only five studies had used real-time polymerase chain reaction assay to validate microRNA expression in autism spectrum disorder subjects compared to controls.The microRNAs that were validated in these studies may be considered as potential candidate biomarkers for autism spectrum disorder and include miR-500a-5p,-197-5p,-424-5p,-664a-3p,-365a-3p,-619-5p,-664a-3p,-3135a,-328-3p,and-500a-5p in blood plasma and miR-151a-3p,-181b-5p,-320a,-328,-433,-489,-572,-663a,-101-3p,-106b-5p,-19b-3p,-195-5p,and-130a-3p in blood serum of children,and miR-15b-5p and-6126 in whole blood of adults.Several important limitations were identified in the studies reviewed,and need to be taken into account in future studies.Further studies are warranted with children and adults having different levels of autism spectrum disorder severity and consideration should be given to using animal models of autism spectrum disorder to investigate the effects of suppressing or overexpressing specific microRNAs as a novel therapy.

APPLICATION OF MULTI-SENSOR DATA FUSION BASED ON FUZZY NEURAL NETWORK IN ROTA TING MECHANICAL FAILURE DIAGNOSIS

At present, multi-se nsor fusion is widely used in object recognition and classification, since this technique can efficiently improve the accuracy and the ability of fault toleranc e. This paper describes a multi-sensor fusion system, which is model-based and used for rotating mechanical failure diagnosis. In the data fusion process, the fuzzy neural network is selected and used for the data fusion at report level. By comparing the experimental results of fault diagnoses based on fusion data wi th that on original separate data,it is shown that the former is more accurate than the latter.

Comparative study of galectin-3 and B-type natriuretic peptide as biomarkers for the diagnosis of heart failure

Background Heart failure （HF） is a common disease with complex pathophysiological causes. The diagnosis of HF commonly relies on comprehensive analyses of medical history and symptoms, and results from echocardiography and biochemical tests. Galectin-3, a rela-tively new biomarker in HF, was approved by the US Food and Drug Administration in 2010 as a marker in the stratification of risk for HF. We assessed galectin-3 as a biomarker for HF diagnosis in patients with preserved ejection fraction （pEF） and compared its performance with that of B-type natriuretic peptide （BNP）. Methods Thirty-five pEF patients with HF （HFpEF group） and 43 pEF patients without HF （control group） were enrolled. Plasma levels of galectin-3 and BNP in HFpEF and control subjects were determined. Sensitivity, specificity, pre dictive values, and accuracy of galectin-3 and BNP as markers for HF diagnosis were calculated and compared. Results Levels of galec- tin-3 and BNP were 23.09 ±6.97 ng/mL and 270.46 ± 330.41 pg/mL in the HFpEF group, and 16.74 ± 2.75 ng/mL and 59.94 ± 29.93 pg/mL in the control group, respectively. Differences in levels of galectin-3 and BNP between the two groups were significant （P 〈 0.01）. As a bio- marker for HF diagnosis in study subjects, galectin-3 showed sensitivity and specificity of 94.3% and 65.1%, respectively, at a cutoff value of 17.8 ug/mL. BNP showed sensitivity and specificity of 77.1% and 90.7%, respectively, at a cutoff value of 100 pg/mL. Galectin-3 was a significantly more sensitive （P 〈 0.05） but less specific （P 〈 0.01） biomarker compared with BNP. Differences in positive predictive value, negative predictive value, and accuracy between galectin-3 and BNP markers were not significant （P 〉 0.05）. Areas under the receiver operating characteristic curve （95% confidence interval） were 0.891 （0.808-0.974） and 0.896 （0.809-0.984） for galectin-3 and BNP, respec- tively, with no significant difference between the two values （P 〉 0.05）. Conclusions The level of galectin-3 is significantly elevated in patients with HF. Galectin-3 and BNP are useful biomarkers for the diagnosis of HF in patients with pEF.

Current concept in the diagnosis,treatment and rehabilitation of patients with congestive heart failure

Heart failure(HF)is a major public health problem with a prevalence of 1%-2%in developed countries.The underlying pathophysiology of HF is complex and as a clinical syndrome is characterized by various symptoms and signs.HF is classified according to left ventricular ejection fraction(LVEF)and falls into three groups:LVEF≥50%-HF with preserved ejection fraction(HFpEF),LVEF<40%-HF with reduced ejection fraction(HFrEF),LVEF 40%-49%-HF with mid-range ejection fraction.Diagnosing HF is primarily a clinical approach and it is based on anamnesis,physical examination,echocardiogram,radiological findings of the heart and lungs and laboratory tests,including a specific markers of HF-brain natriuretic peptide or N-terminal pro-B-type natriuretic peptide as well as other diagnostic tests in order to elucidate possible etiologies.Updated diagnostic algorithms for HFpEF have been recommended(H2FPEF,HFA-PEFF).New therapeutic options improve clinical outcomes as well as functional status in patients with HFrEF(e.g.,sodium-glucose cotransporter-2-SGLT2 inhibitors)and such progress in treatment of HFrEF patients resulted in new working definition of the term“HF with recovered left ventricular ejection fraction”.In line with rapid development of HF treatment,cardiac rehabilitation becomes an increasingly important part of overall approach to patients with chronic HF for it has been proven that exercise training can relieve symptoms,improve exercise capacity and quality of life as well as reduce disability and hospitalization rates.We gave an overview of latest insights in HF diagnosis and treatment with special emphasize on the important role of cardiac rehabilitation in such patients.

Diagnosis and treatment of heart failure with preserved left ventricular ejection fraction

Nearly six million people in United States have heart failure.Fifty percent of these people have normal left ventricular(LV)systolic heart function but abnormal diastolic function due to increased LV myocardial stiffness.Most commonly,these patients are elderly women with hypertension,ischemic heart disease,atrial fibrillation,obesity,diabetes mellitus,renal disease,or obstructive lung disease.The annual mortality rate of these patients is 8%-12%per year.The diagnosis is based on the history,physical examination,laboratory data,echocardiography,and,when necessary,by cardiac catheterization.Patients with obesity,hypertension,atrial fibrillation,and volume overload require weight reduction,an exercise program,aggressive control of blood pressure and heart rate,and diuretics.Miniature devices inserted into patients for pulmonary artery pressure monitoring provide early warning of increased pulmonary pressure and congestion.If significant coronary heart disease is present,coronary revascularization should be considered.

Effectiveness of chest radiography,lung ultrasound and thoracic computed tomography in the diagnosis of congestive heart failure

Hydrostatic pulmonary edema is as an abnormal in-crease in extravascular water secondary to elevatedpressure in the pulmonary circulation, due to conges-tive heart failure or intravascular volume overload.Diagnosis of hydrostatic pulmonary edema is usuallybased on clinical signs associated to conventional ra-diography findings. Interpretation of radiologic signsof cardiogenic pulmonary edema are often question-able and subject. For a bedside prompt evaluation,lung ultrasound(LUS) may assess pulmonary conges-tion through the evaluation of vertical reverberationartifacts, known as B-lines. These artifacts are relatedto multiple minimal acoustic interfaces between smallwater-rich structures and alveolar air, as it happens incase of thickened interlobular septa due to increase of extravascular lung water. The number, diffusion and in-tensity of B lines correlates with both the radiologic andinvasive estimate of extravascular lung water. The inte-gration of conventional chest radiograph with LUS canbe very helpful to obtain the correct diagnosis. Com-puted tomography(CT) is of limited use in the work upof cardiogenic pulmonary edema, due to its high cost,little use in the emergencies and radiation exposure.However, a deep knowledge of CT signs of pulmonaryedema is crucial when other similar pulmonary condi-tions may occasionally be in the differential diagnosis.

Delayed diagnosis of alpha-1-antitrypsin deficiency following post-hepatectomy liver failure: A case report

Post-hepatectomy liver failure(PHLF) is a leading cause of morbidity and mortality following major liver resection. The development of PHLF is dependent on the volume of the remaining liver tissue and hepatocyte function. Without effective pre-operative assessment, patients with undiagnosed liver disease could be at increased risk of PHLF. We report a case of a 60-year-old male patient with PHLF secondary to undiagnosed alpha-1-antitrypsin deficiency(AATD) following major liver resection. He initially presented with acute large bowel obstruction secondary to a colorectal adenocarcinoma, which had metastasized to the liver. There was no significant past medical history apart from mild chronic obstructive pulmonary disease. After colonic surgery and liver directed neo-adjuvant chemotherapy, he underwent a laparoscopic partially extended right hepatectomy and radio-frequency ablation. Post-operatively he developed PHLF. The cause of PHLF remained unknown, prompting reanalysis of the histology, which showed evidence of AATD. He subsequently developed progressive liver dysfunction, portal hypertension, and eventually an extensive parastomal bleed, which led to his death; this was ultimately due to a combination of AATD and chemotherapy. This case highlights that formal testing for AATD in all patients with a known history of chronic obstructive pulmonary disease, heavy smoking, or strong family history could help prevent the development of PHLF in patients undergoing major liver resection.

Role of Ultrasound Lung Comets in the Diagnosis of Acute Heart Failure in Emergency Department: A Systematic Review and Meta-analysis

Objective A new technique of transthoracic lung ultrasonography(TLS) has emerged and demonstrated promising results in acute heart failure diagnosis at an early stage. However, the diagnostic value of ultrasound lung comets(ULCs) for acute heart failure(AHF) performed in busy emergency department(ED) is uncertain. The present meta-analysis aimed to assess the diagnostic efficiency of ULCs in AHF. Methods We conducted a search on online journal databases to collect the data on TLS performed for diagnosing AHF published up to the end of July 2017. The sensitivity, specificity, positive likelihood ratio(PLR), negative likelihood ratio(NLR), and summary receiver operating characteristic(SROC) curve were calculated. The post-test probability of AHF was calculated by using Bayes analysis. Results We enrolled a total of 15 studies involving 3,309 patients. The value of sensitivity, specificity, PLR, NLR, DOR, area under the SROC curve, and Q* index was 85%, 91%, 8.94, 0.14, 67.24, 0.9587, and 0.9026, respectively. We detected significant heterogeneity among included studies, and therefore, all these results were analyzed under the random-effect model. We also explored possible sources of heterogeneity among the studies by using meta-regression analysis. Results suggest that the time interval between patient’s admission to bedside TLS examination was closely related to TLS accuracy. Conclusion This meta-analysis demonstrated that detecting ULCs is a convenient bedside tool and has high accuracy for early AHF diagnosis in ED. TLS could be recommended to be applied for early diagnosis of AHF in ED.

Post-Obstructive Diuresis: Physiopathology, Diagnosis and Management after Urological Treatment of Obstructive Renal Failure

Obstructive acute renal failure is both a medical and a surgical emergency. The first treatment modality is urological by relief of obstruction. Post-obstructive diuresis is an abnormal condition of prolonged polyuria, involving both excessive solute and water loss, after acute drainage of obstructed urinary tract system. Physiopathology mechanisms are multiples. In most patients, diuresis will resolve once the kidneys normalize the volume and solute status and homeostasis is achieved. Post-obstructive diuresis can occur in up to 50% of patients with substantial urinary tract obstruction and can be life-threatening if it becomes pathologic. It can be detected by hourly monitoring of diuresis. Medical treatment of post-obstructive diuresis consists of oral or intravenous fluids adjusted to the findings of clinical examination, diuresis (volume and electrolytes) and close monitoring of patient. Fluid compensation should be tapered off over several days. Patients at high risk of post-obstructive diuresis should be identified and appropriately monitored.

Electrocardiogram-based artificial intelligence for the diagnosis of heart failure:a systematic review and meta-analysis

BACKGROUND The electrocardiogram(ECG)is an inexpensive and easily accessible investigation for the diagnosis of cardiovascular diseases including heart failure(HF).The application of artificial intelligence(AI)has contributed to clinical practice in terms of aiding diagnosis,prognosis,risk stratification and guiding clinical management.The aim of this study is to systematically review and perform a meta-analysis of published studies on the application of AI for HF detection based on the ECG.METHODS We searched Embase,PubMed and Web of Science databases to identify literature using AI for HF detection based on ECG data.The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2(QUADAS-2)criteria.Random-effects models were used for calculating the effect estimates and hierarchical receiver operating characteristic curves were plotted.Subgroup analysis was performed.Heterogeneity and the risk of bias were also assessed.RESULTS A total of 11 studies including 104,737 subjects were included.The area under the curve for HF diagnosis was 0.986,with a corresponding pooled sensitivity of 0.95(95%CI:0.86–0.98),specificity of 0.98(95%CI:0.95–0.99)and diagnostic odds ratio of 831.51(95%CI:127.85–5407.74).In the patient selection domain of QUADAS-2,eight studies were designated as high risk.CONCLUSIONS According to the available evidence,the incorporation of AI can aid the diagnosis of HF.However,there is heterogeneity among machine learning algorithms and improvements are required in terms of quality and study design.

Exploring impedance spectrum for lithium-ion batteries diagnosis and prognosis:A comprehensive review

Lithium-ion batteries have extensive usage in various energy storage needs,owing to their notable benefits of high energy density and long lifespan.The monitoring of battery states and failure identification are indispensable for guaranteeing the secure and optimal functionality of the batteries.The impedance spectrum has garnered growing interest due to its ability to provide a valuable understanding of material characteristics and electrochemical processes.To inspire further progress in the investigation and application of the battery impedance spectrum,this paper provides a comprehensive review of the determination and utilization of the impedance spectrum.The sources of impedance inaccuracies are systematically analyzed in terms of frequency response characteristics.The applicability of utilizing diverse impedance features for the diagnosis and prognosis of batteries is further elaborated.Finally,challenges and prospects for future research are discussed.

Plasma metabolomics combined with personalized diagnosis guided by Chinese medicine reveals subtypes of chronic heart failure

Background:Chronic heart failure(CHF)is characterized by insufficient blood supply from heart to meet the body’s metabolic demands.Integrating Western and traditional Chinese medicine to treat CHF has proved a validated therapeutic approach.In recent years,metabolomics has been regarded as a potential platform to provide biomarkers for diseasesubtypes.Objective:To examine 38 patients,combined NMR plasma metabolomics and traditional Chinese medicine diagnosis in order to identify diagnostic biomarkers for two CHF syndrome subtypes.Methods:After processing the spectra,orthogonal partial least square discriminant analysis was performed,and the contributing NMR signals were analyzed using Y-scrambling statistical validation with good reliability.Results:Plasma metabolic patterns of yin deficiency and yang deficiency patients were clearly discriminated.The yin-deficiency group had increased level of lactate,glycoprotein,lipoprotein and lower levels of glucose,valine and proline.The yang-deficiency group had higher levels of lactate,glycoprotein and pyruvic acid,and lower levels of glucose and lipoprotein.Potential biomarkers of CHF based on the two traditional Chinese medicine syndromes indicated alternative modes of metabolites and metabolic pathways in the disease,e.g.dysfunction of energy utilization and disturbance in fatty acids,amino acids.Conclusion:This study suggests that combining metabolomics with traditional Chinese medicine diagnosis can reveal metabolic signatures for CHF syndrome subtypes.The plasma metabolites identified might be of special clinical relevance for subtypes of CHF,which could lead to further understanding of mechanisms involved and an improvement in personalized treatment for CHF.

Development of a novel score for the diagnosis of bacterial infection in patients with acute-on-chronic liver failure

BACKGROUND The diagnosis of bacterial infection is difficult in patients with acute-on-chronic liver failure(ACLF).AIM To evaluate the diagnostic accuracy of widely used parameters for bacterial infection in ACLF and to develop a simple scoring system to improve diagnostic efficiency.METHODS This was a retrospective study.Procalcitonin(PCT),white blood cells(WBC),proportion of neutrophils(N%),and C-reactive protein(CRP)were examined.Logistic regression was used to select variables for the scoring models and receiver operating characteristic curve(ROC)analysis was used to evaluate the diagnostic value of different indices.RESULTS This study included 386 patients with ACLF,169(43.78%)of whom had bacterial infection on admission.The area under the ROC(AUROC)of PCT,CRP,WBC and N%for the diagnosis of bacterial infection ranged from 0.637 to 0.692,with no significant difference between them.Logistic regression showed that only N%,PCT,and CRP could independently predict infection.A novel scoring system(infection score)comprised of N%,PCT and CRP was developed.The AUROC of the infection score was 0.740,which was significantly higher than that for the other four indices(infection score vs N%,PCT,CRP,and WBC,P=0.0056,0.0001,0.0483 and 0.0008,respectively).The best cutoff point for the infection score was 4 points,with a sensitivity of 78.05%,a specificity of 55.29%,a positive predictive value of 57.91%and a negative predictive value of 76.16%.CONCLUSION The infection score is a simple and useful tool for discriminating bacterial infection in ACLF.

Robust Diagnosis for Sensor Failure

An approach for sensor fault diagnosis in stochasitc control system is proposed. Fault detection is realized on the basis of Kalman filter innovation. The location of sensor fault is obtained by utilizing the decision function of error estimation. Simulation results indicate that the approach is feasible and efficient.