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Receiver Operating Curve (receiver + operating_curve)
Selected AbstractsUse of the Brief Smell Identification Test for olfactory deficit in a Norwegian population with Alzheimer's diseaseINTERNATIONAL JOURNAL OF GERIATRIC PSYCHIATRY, Issue 10 2007Grete Kjelvik Abstract Aims Several studies have shown that Alzheimer's disease (AD) is associated with hyposmia. Olfactory identification may be a cheap and simple additional test in the assessment of early cognitive changes. The sense of smell is influenced by factors such as experience and culture and the aim of the present study was to assess the validity of the Brief Smell Identification Test (B-SIT) in distinguishing patients with AD from healthy gender and age-matched controls in a Norwegian population. Methods The study included 39 patients with a diagnosis of probable AD, and 52 gender and age-matched controls. Olfactory function was assessed with B-SIT, and a non-standardized olfactory identification task (freshly ground coffee). Results The difference in olfactory performance between patients and controls was highly significant, both for the whole AD patient group and the subgroup of patients with MMSE,,,24. Receiver operating curve (ROC) analyses indicated that B-SIT distinguished patients from controls with high sensitivity and specificity. All the odours in B-SIT with the exception of turpentine showed highly significant differences between patients and controls. AD-associated memory impairment did not seem to affect the answers given for B-SIT in this population. Conclusions For patients with AD, the Brief Smell Identification Test (B-SIT) appears to be well-suited for detecting a deficit in olfactory identification in a Norwegian population. Copyright © 2007 John Wiley & Sons, Ltd. [source] Electrocardiographic Activity before Onset of Postoperative Atrial Fibrillation in Cardiac Surgery PatientsPACING AND CLINICAL ELECTROPHYSIOLOGY, Issue 11 2008MIRELA OVREIU Ph.D. Background:Electrocardiographic (ECG) characteristics were analyzed in postoperative cardiac surgery patients in an attempt to predict development of new-onset postoperative atrial fibrillation (AF). Methods:Nineteen ECG characteristics were analyzed using computer-based algorithms. The parameters were retrospectively analyzed from ECG signals recorded in postoperative cardiac surgery patients while they were in the cardiovascular intensive care unit (CVICU) at our institution. ECG data from 99 patients (of whom 43 developed postoperative AF) were analyzed. A bootstrap variable selection procedure was applied to select the most important ECG parameters, and a multivariable logistic regression model was developed to classify patients who did and did not develop AF. Results:Premature atrial activity (PAC) was greater in AF patients (P < 0.01). Certain heart rate variability (HRV) and turbulence parameters also differed in patients who did and did not develop AF. In contrast, P-wave morphology was similar in patients with and without AF. Receiver operating curve (ROC) analysis applied to the model produced a C-statistic of 0.904. The model thus correctly classified AF patients with more than a 90% sensitivity and a 70% specificity. Conclusion:Among the 19 ECG parameters analyzed, PAC activity, frequency-domain HRV, and heart rate turbulence parameters were the best discriminators for postoperative AF. [source] Circulating levels of copeptin, a novel biomarker, in lower respiratory tract infectionsEUROPEAN JOURNAL OF CLINICAL INVESTIGATION, Issue 2 2007B. Müller Abstract Background, Vasopressin has haemodynamic as well as osmoregulatory effects, and reflects the individual stress response. Copeptin is cosynthesized with vasopressin, directly mirroring vasopressin levels, but is more stable in plasma and serum. Both levels are increased in patients with septic shock. Lower respiratory tract infections (LRTI) are a precursor of sepsis. Thus, we investigated circulating levels and the prognostic use of copeptin for the severity and outcome in patients with LRTI. Materials and methods, Five hundred and forty-five consecutive patients with LRTI and 50 healthy controls were evaluated. Serum copeptin levels were measured with a new chemiluminescens sandwich immunoassay. Results, Of the 545 patients, 373 had community-acquired pneumonia (CAP), 60 acute exacerbations of chronic obstructive pulmonary disease (COPD), 59 acute bronchitis, 13 exacerbations of asthma and 40 other final diagnoses. Copeptin levels were significantly higher in patients with LRTI as compared to controls (P < 0·001) with highest levels in patients with CAP. Copeptin levels increased with increasing severity of CAP, as classified by the pneumonia severity index (PSI) (P < 0·001). In patients who died, copeptin levels on admission were significantly higher as compared to levels in survivors [70·0 (28·8,149·0) vs. 24·3 (10·8,43·8) pmol L,1, P < 0·001]. The area under the receiver operating curve (AUC) for survival was 0·75 for copeptin, which was significantly higher as compared to C-reactive protein (AUC 0·61, P = 0·01), leukocyte count (AUC 0·59, P = 0·01) and similar to procalcitonin (AUC 0·68, P = 0·21). Conclusions, Copeptin levels are increased with increasing severity of LRTI namely in patients with CAP and unfavourable outcome. Copeptin levels, as a novel biomarker, might be a useful tool in the risk stratification of patients with LRTI. [source] Relationship of serum fibrosis markers with liver fibrosis stage and collagen content in patients with advanced chronic hepatitis C,HEPATOLOGY, Issue 3 2008Robert J. Fontana This study determined the utility of a panel of serum fibrosis markers along with routine laboratory tests in estimating the likelihood of histological cirrhosis in a cohort of prior nonresponders with chronic hepatitis C. The relationship between serum markers and quantitative hepatic collagen content was also determined. Liver biopsy samples from 513 subjects enrolled in the HALT-C trial were assigned Ishak fibrosis scores. The collagen content of 386 sirius-red stained, nonfragmented biopsy samples was quantified using computerized morphometry. Serum tissue inhibitor of matrix metalloproteinase-1 (TIMP-1), amino-terminal peptide of type III procollagen (PIIINP), hyaluronic acid (HA), and YKL-40 levels were determined using commercially available assays. Sixty-two percent of patients had noncirrhotic fibrosis (Ishak stage 2-4) whereas 38% had cirrhosis (Ishak stage 5,6). Multivariate analysis identified a 3-variable model (HA, TIMP-1, and platelet count) that had an area under the receiver operating curve (AUROC) of 0.81 for estimating the presence of cirrhosis. This model was significantly better than that derived from the cirrhosis discriminant score (AUROC 0.70), the AST-to-platelet ratio (AUROC 0.73), and a prior model developed in HALT-C patients (AUROC 0.79). Multivariate analysis demonstrated that the serum fibrosis markers correlated substantially better with Ishak fibrosis scores than with the log hepatic collagen content (AUROC 0.84 versus 0.72). Conclusion: A 3-variable model consisting of serum HA, TIMP-1, and platelet count was better than other published models in identifying cirrhosis in HALT-C Trial subjects. The stronger correlation of the serum markers with Ishak scores suggests that serum fibrosis markers reflect the pattern of fibrosis more closely than the quantity of hepatic collagen. (HEPATOLOGY 2008.) [source] Platelet count is not a predictor of the presence or development of gastroesophageal varices in cirrhosis,HEPATOLOGY, Issue 1 2008Amir A. Qamar Current guidelines recommend esophagogastroduodenoscopy (EGD) in patients with cirrhosis to screen for gastroesophageal varices (GEV). Thrombocytopenia has been proposed as a noninvasive test to predict the presence of GEV. There is no agreement regarding a specific platelet count (PLT) that can reliably predict GEV. The present longitudinal study aims to (1) further investigate the relationship between varices and PLT at the time of endoscopy, (2) investigate whether changes in PLT from the baseline over time can predict the development of GEV, and (3) investigate whether changes in PLT correlate with the hepatic venous pressure gradient (HVPG). A secondary analysis was conducted for 213 subjects with compensated cirrhosis with portal hypertension but without GEV enrolled in a randomized, placebo-controlled, double-blind trial of a nonselective beta-blocker used to prevent GEV. PLTs were obtained every 3 months, and HVPG measurements and EGD were done annually. The PLTs were compared between subjects who did and did not develop GEV. In a median follow-up of 54.9 months, 84 patients developed GEV. PLT was greater than 150,000 in 15% of patients at the development of GEV. A receiver operating curve did not show any PLT with high sensitivity or specificity for the presence of GEV. Subjects with clinically insignificant portal hypertension (HVPG < 10 mm Hg) whose PLT remained greater than 100,000 had a 2-fold reduction in the occurrence of GEV (P = 0.0374). A significant correlation was found between HVPG and PLT at the baseline, year 1, and year 5 (P < 0.0001). Conclusion: Cross-sectional or longitudinal evaluations of PLTs are inadequate noninvasive markers for GEV. Patients with mild portal hypertension whose PLT remains greater than 100,000 have significantly less risk of GEV. Although HVPG correlates somewhat with PLT, changes in PLT cannot be used as a surrogate for HVPG changes. (HEPATOLOGY 2008;47:153,159.) [source] Validation of a simple model for predicting liver fibrosis in HIV/hepatitis C virus-coinfected patientsHIV MEDICINE, Issue 6 2005H Al-Mohri Objectives Recently, several models incorporating laboratory measurements have been validated for use as surrogate markers for liver fibrosis in hepatitis C virus (HCV) mono-infection, the simplest of these being the aspartate aminotransferase (AST) to platelet ratio index (APRI). We evaluated how well the APRI predicts significant hepatic fibrosis in patients with HIV/HCV coinfection. Methods Forty-six HIV/HCV-coinfected patients who underwent liver biopsy and had concomitant laboratory measurements (±3 months) were included in the study. Significant fibrosis was defined as F2,F4 using Batt and Ludwig scoring (=3 Ishak). APRI=[(AST/upper limit of normal)/platelet count (109/L)] × 100. We used sas proc logistic (SAS Institute, Cary, NC) to calculate the area under the receiver operating curve (ROC) (AUC). Sensitivities, specificities, positive predictive value (PPV) and negative predictive value (NPV) were compared using cut-offs previously identified in the literature. Results Thirty-three of 46 patients (72%) had significant fibrosis on biopsy. For significant fibrosis, the area under the ROC for the APRI was 0.847±0.057. APRI scores >1.5 (the higher cut-off) were 100% specific and 52% sensitive; PPV was 100% and NPV 45%. Scores <0.5 (the lower cut-off) were 82% sensitive and 46% specific in ruling out significant fibrosis (PPV 79%; NPV 50%). Conclusions A simple model incorporating readily available laboratory data is highly predictive of significant fibrosis in HIV/HCV coinfection and could serve as a biopsy-sparing measure, thus making treatment more accessible for this population. [source] Prediction of respiratory insufficiency in Guillain-Barré syndromeANNALS OF NEUROLOGY, Issue 6 2010Christa Walgaard MD Objective Respiratory insufficiency is a frequent and serious complication of the Guillain-Barré syndrome (GBS). We aimed to develop a simple but accurate model to predict the chance of respiratory insufficiency in the acute stage of the disease based on clinical characteristics available at hospital admission. Methods Mechanical ventilation (MV) in the first week of admission was used as an indicator of acute stage respiratory insufficiency. Prospectively collected data from a derivation cohort of 397 GBS patients were used to identify predictors of MV. A multivariate logistic regression model was validated in a separate cohort of 191 GBS patients. Model performance criteria comprised discrimination (area under receiver operating curve [AUC]) and calibration (graphically). A scoring system for clinical practice was constructed from the regression coefficients of the model in the combined cohorts. Results In the derivation cohort, 22% needed MV in the first week of admission. Days between onset of weakness and admission, Medical Research Council sum score, and presence of facial and/or bulbar weakness were the main predictors of MV. The prognostic model had a good discriminative ability (AUC, 0.84). In the validation cohort, 14% needed MV in the first week of admission, and both calibration and discriminative ability of the model were good (AUC, 0.82). The scoring system ranged from 0 to 7, with corresponding chances of respiratory insufficiency from 1 to 91%. Interpretation This model accurately predicts development of respiratory insufficiency within 1 week in patients with GBS, using clinical characteristics available at admission. After further validation, the model may assist in clinical decision making, for example, on patient transfer to an intensive care unit. ANN NEUROL 2010;67:781,787 [source] The Impact of Injury Coding Schemes on Predicting Hospital Mortality After Pediatric InjuryACADEMIC EMERGENCY MEDICINE, Issue 7 2009Randall S. Burd MD Abstract Objectives:, Accurate adjustment for injury severity is needed to evaluate the effectiveness of trauma management. While the choice of injury coding scheme used for modeling affects performance, the impact of combining coding schemes on performance has not been evaluated. The purpose of this study was to use Bayesian logistic regression to develop models predicting hospital mortality in injured children and to compare the performance of models developed using different injury coding schemes. Methods:, Records of children (age < 15 years) admitted after injury were obtained from the National Trauma Data Bank (NTDB) and the National Pediatric Trauma Registry (NPTR) and used to train Bayesian logistic regression models predicting mortality using three injury coding schemes (International Classification of Disease-9th revision [ICD-9] injury codes, the Abbreviated Injury Scale [AIS] severity scores, and the Barell matrix) and their combinations. Model performance was evaluated using independent data from the NTDB and the Kids' Inpatient Database 2003 (KID). Results:, Discrimination was optimal when modeling both ICD-9 and AIS severity codes (area under the receiver operating curve [AUC] = 0.921 [NTDB] and 0.967 [KID], Hosmer-Lemeshow [HL] h-statistic = 115 [NTDB] and 147 [KID]), while calibration was optimal when modeling coding based on the Barell matrix (AUC = 0.882 [NTDB] and 0.936 [KID], HL h-statistic = 19 [NTDB] and 69 [KID]). When compared to models based on ICD-9 codes alone, models that also included AIS severity scores and coding from the Barell matrix showed improved discrimination and calibration. Conclusions:, Mortality models that incorporate additional injury coding schemes perform better than those based on ICD-9 codes alone in the setting of pediatric trauma. Combining injury coding schemes may be an effective approach for improving the predictive performance of empirically derived estimates of injury mortality. [source] Reporting outcomes in clinical trials for bipolar disorder: a commentary and suggestions for changeBIPOLAR DISORDERS, Issue 5 2008Anabel Martinez-Arán Objective:, Newer outcome measures and statistical reporting that better translate efficacy data to evidence-based psychiatric care are needed when evaluating clinical trials for bipolar disorder. Using efficacy studies as illustrations, the authors review and recommend changes in the reporting of traditional clinical outcomes both in the acute and maintenance phases of bipolar disorder. Methods:, Definitions of response, remission, relapse, recovery, and recurrence are reviewed and recommendations for change are made. These suggestions include reporting the numbers needed to treat or harm (NNT or NNH), and a ratio of the two, likelihood of help or harm (LHH), as an important element of the effect size (ES). Moreover, models of prediction that conduct sensitivity or specificity analyses and utilize decision trees to help predict positive and negative outcomes of interest (for instance, excessive weight gain, or time to remission) using positive or negative predictive values (PPV or NPV) are reviewed for potential value to clinicians. Finally, functional and cognitive assessments are recommended for maintenance studies of bipolar disorder. Results:, The examples provided in this manuscript underscore that reporting the NNT or NNH, or alternative effect sizes, or using PPV or NPV may be of particular value to clinicians. Such reports are likely to help translate efficacy-driven clinical data to information that will more readily guide clinicians on the benefits and risks of specific interventions in bipolar disorder. Conclusions:, The authors opine that reporting these newer outcomes, such as NNT or NNH, area under the receiver operating curve (AUC), or PPV or NPV will help translate the results of clinical trials into a language that is more readily understood by clinicians. Moreover, assessing and evaluating functional and cognitive outcomes will not only inform clinicians about potential differences among therapeutic options, but likely will make it easier to communicate such differences to persons with bipolar illness or to their families. Finally, we hope such scientific and research efforts will translate to optimism for recovery-based outcomes in persons with bipolar disorder. [source] Body mass index is weakly associated with, and not a helpful predictor of, disease progression in men with clinically localized prostate carcinoma treated with radical prostatectomyCANCER, Issue 10 2005Kozhaya N. Mallah M.D. Abstract BACKGROUND Several studies have recently suggested an association between body mass index (BMI) and disease progression after radical prostatectomy. In the current study, the authors examined this association and that between the reciprocal of BMI (INVBMI, 1/BMI) and progression-free probability in men treated with radical retropubic prostatectomy (RRP) for clinically localized prostate carcinoma. METHODS The authors retrospectively studied 2210 patients who underwent RRP at Memorial Sloan-Kettering Cancer Center between September 1986 and May 2003. Clinicopathologic variables analyzed included BMI (kg/m2), preoperative serum prostate-specific antigen level (ng/mL), clinical T classification, year of surgery, race, biopsy-derived primary and secondary Gleason grades, and INVBMI, known to better correlate with percent body fat than BMI. Cox regression analysis was used to examine the possible association between BMI or its reciprocal with disease progression after controlling for the effects of common prognostic factors. The areas under the receiver operating curve (AUC) for models with and without INVBMI were calculated RESULTS Of the 2210 patients analyzed, 251 experienced disease progression in a median follow-up time of 25.9 months (range, 0,143 months). After adjusting for all clinical variables, both BMI (P = 0.071; hazards ratio [HR] = 1.027) and INVBMI (P = 0.041; HR < 0.001) were associated with disease progression. However, the areas under AUC for models with and without INVBMI were similar (range, 0.794,0.798). CONCLUSIONS Although conflicting evidence has been reported regarding the link between obesity and an increased risk of developing prostate carcinoma, as well as an increased risk of developing aggressive disease and prostate carcinoma-related mortality, the authors found weak associations with disease progression for both BMI and INVBMI. These variables were of negligible prognostic value in men who received surgery. Studies with longer follow-up, that examine alternative end points, and that follow treatment(s) besides surgery are needed. Cancer 2005. © 2005 American Cancer Society. [source] Bayesian Logistic Injury Severity Score: A Method for Predicting Mortality Using International Classification of Disease-9 CodesACADEMIC EMERGENCY MEDICINE, Issue 5 2008Randall S. Burd MD Abstract Objectives:, Owing to the large number of injury International Classification of Disease-9 revision (ICD-9) codes, it is not feasible to use standard regression methods to estimate the independent risk of death for each injury code. Bayesian logistic regression is a method that can select among a large numbers of predictors without loss of model performance. The purpose of this study was to develop a model for predicting in-hospital trauma deaths based on this method and to compare its performance with the ICD-9,based Injury Severity Score (ICISS). Methods:, The authors used Bayesian logistic regression to train and test models for predicting mortality based on injury ICD-9 codes (2,210 codes) and injury codes with two-way interactions (243,037 codes and interactions) using data from the National Trauma Data Bank (NTDB). They evaluated discrimination using area under the receiver operating curve (AUC) and calibration with the Hosmer-Lemeshow (HL) h-statistic. The authors compared performance of these models with one developed using ICISS. Results:, The discrimination of a model developed using individual ICD-9 codes was similar to that of a model developed using individual codes and their interactions (AUC = 0.888 vs. 0.892). Inclusion of injury interactions, however, improved model calibration (HL h-statistic = 2,737 vs. 1,347). A model based on ICISS had similar discrimination (AUC = .855) but showed worse calibration (HL h-statistic = 45,237) than those based on regression. Conclusions:, A model that incorporates injury interactions had better predictive performance than one based only on individual injuries. A regression approach to predicting injury mortality based on injury ICD-9 codes yields models with better predictive performance than ICISS. [source] Neuroprotein s-100B , a useful parameter in paediatric patients with mild traumatic brain injury?ACTA PAEDIATRICA, Issue 10 2009C Castellani Abstract Aims:, To examine the correlation of S-100B to cranial computerized tomography (CCT) scan results in children after mild traumatic brain injury (MTBI). Methods:, One hundred and nine paediatric patients (0,18 years) with MTBI were included in this prospective single-centre study. Serum was collected within 6 h of trauma for determination of serum S-100B. The upper reference of S-100B was set to 0.16 ,g/L. A CCT scan was performed in all patients and the results were correlated to the S-100B values. Results:, Computerized tomography was abnormal in 36 patients showing intracerebral haemorrhages and/or skull fractures. Serum S-100B level was significantly higher in patients with a pathological condition as shown in CT scan results (p = 0.003). There were no false negative, but 42 false positive test results for S-100B. This resulted in a sensitivity of 1.00, specificity of 0.42, positive predictive value of 0.46 and negative predictive value of 1.00. An area under the receiver operating curve of 0.68 was calculated. Conclusion:, S-100B is a valuable tool to rule out patients with pathological CCT findings in a collective of paediatric patients with MTBI. Elevations of S-100B do not necessarily lead to a pathological finding in the CT scan, but values below the cut-off safely rule out the evidence of intracranial lesions. [source] | ||||||||||