881 resultados para OPERATING CHARACTERISTIC CURVES


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Purpose: To evaluate retinal nerve fiber layer (RNFL), optic nerve head (ONH), and macular thickness measurements for glaucoma detection using the RTVue spectral domain optical coherence tomograph. Design: Diagnostic, case-control study. Participants: One hundred forty eyes of 106 glaucoma patients and 74 eyes of 40 healthy subjects from the Diagnostic Innovations in Glaucoma Study (DIGS). Methods: All patients underwent ocular imaging with the commercially available RTVue. Optic nerve head, RNFL thickness, and macular thickness scans were obtained during the same visit. Receiver operating characteristic (ROC) curves and sensitivities at fixed specificities (80% and 95%) were calculated for each parameter. Main Outcome Measures: Areas under the ROC curves (AUC) and sensitivities at fixed specificities of 80% and 95%. Results: The AUC for the RNFL parameter with best performance, inferior quadrant thickness, was significantly higher than that of the best-performing ONH parameter, inferior rim area (0.884 vs 0.812, respectively; P = 0.04). There was no difference between ROC curve areas of the best RNFL thickness parameters and the best inner macular thickness measurement, ganglion cell complex root mean square (ROC curve area = 0.870). Conclusions: The RTVue RNFL and inner retinal macular thickness measurements had good ability to detect eyes with glaucomatous visual field loss and performed significantly better than ONH parameters.

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PURPOSE. To evaluate and compare rates of change in neuro-retinal rim area (RA) and retinal nerve fiber layer thickness (RNFLT) measurements in glaucoma patients, those with suspected glaucoma, and normal subjects observed over time. METHODS. In this observational cohort study, patients recruited from two longitudinal studies (Diagnostic Innovations in Glaucoma Study-DIGS and African Descent and Evaluation Study-ADAGES) were observed with standard achromatic perimetry (SAP), optic disc stereophotographs, confocal scanning laser ophthalmoscopy (HRT-3; Heidelberg Engineering, Heidelberg, Germany), and scanning laser polarimetry (GDx-VCC; Carl Zeiss Meditec, Inc., Dublin, CA). Glaucoma progression was determined by the Guided Progression Analysis software for standard automated perimetry [SAP] and by masked assessment of serial optic disc stereophotographs by expert graders. Random-coefficients models were used to evaluate rates of change in average RNFLT and global RA measurements and their relationship with glaucoma progression. RESULTS. At baseline, 194 (31%) eyes were glaucomatous, 347 (55%) had suspected glaucoma, and 88 (14%) were normal. Forty-six (9%) eyes showed progression by SAP and/or stereophotographs, during an average follow-up of 3.3 (+/-0.7) years. The average rate of decline for RNFLT measurements was significantly higher in the progressing group than in the non-progressing group (-0.65 vs. -0.11 mu m/y, respectively; P < 0.001), whereas RA decline was not significantly different between these groups (-0.0058 vs. -0.0073 mm(2)/y, respectively; P = 0.727). The areas under the receiver operating characteristic (ROC) curves used to discriminate progressing versus nonprogressing eyes were 0.811 and 0.507 for the rates of change in the RNFLT and RA, respectively (P < 0.001). CONCLUSIONS. The ability to discriminate eyes with progressing glaucoma by SAP and/or stereophotographs from stable eyes was significantly greater for RNFLT than for RA measurements. (Invest Ophthalmol Vis Sci. 2010;51:3531-3539) DOI: 10.1167/iovs.09-4350

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OBJECTIVE. The purpose of the study was to investigate patient characteristics associated with image quality and their impact on the diagnostic accuracy of MDCT for the detection of coronary artery stenosis. MATERIALS AND METHODS. Two hundred ninety-one patients with a coronary artery calcification (CAC) score of <= 600 Agatston units (214 men and 77 women; mean age, 59.3 +/- 10.0 years [SD]) were analyzed. An overall image quality score was derived using an ordinal scale. The accuracy of quantitative MDCT to detect significant (>= 50%) stenoses was assessed using quantitative coronary angiography (QCA) per patient and per vessel using a modified 19-segment model. The effect of CAC, obesity, heart rate, and heart rate variability on image quality and accuracy were evaluated by multiple logistic regression. Image quality and accuracy were further analyzed in subgroups of significant predictor variables. Diagnostic analysis was determined for image quality strata using receiver operating characteristic (ROC) curves. RESULTS. Increasing body mass index (BMI) (odds ratio [OR] = 0.89, p < 0.001), increasing heart rate (OR = 0.90, p < 0.001), and the presence of breathing artifact (OR = 4.97, p = 0.001) were associated with poorer image quality whereas sex, CAC score, and heart rate variability were not. Compared with examinations of white patients, studies of black patients had significantly poorer image quality (OR = 0.58, p = 0.04). At a vessel level, CAC score (10 Agatston units) (OR = 1.03, p = 0.012) and patient age (OR = 1.02, p = 0.04) were significantly associated with the diagnostic accuracy of quantitative MDCT compared with QCA. A trend was observed in differences in the areas under the ROC curves across image quality strata at the vessel level (p = 0.08). CONCLUSION. Image quality is significantly associated with patient ethnicity, BMI, mean scan heart rate, and the presence of breathing artifact but not with CAC score at a patient level. At a vessel level, CAC score and age were associated with reduced diagnostic accuracy.

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Diagnosis of autoimmune hepatitis (AIH) may be challenging. However, early diagnosis is important because immunosuppression is life-saving. Diagnostic criteria of the International Autoimmune Hepatitis Group (IAIHG) were complex and purely meant for scientific purposes. This study of the IAIHG aims to define simplified diagnostic criteria for routine clinical practice. Candidate criteria included sex, age, autoantibodies, immunoglobutins, absence of viral hepatitis, and histology. The training set included 250 AIH patients and 193 controls from 11 centers worldwide. Scores were built from variables showing predictive ability in univariate analysis. Diagnostic value of each score was assessed by the area under the receiver operating characteristic (ROC) curve. The best score was validated using data of an additional 109 AIH patients and 284 controls. This score included autoantibodies, immunoglobulin G, histology, and exclusion of viral hepatitis. The area under the curve for prediction of AIH was 0.946 in the training set and 0.91 in the validation set. Based on the ROC curves, two cutoff points were chosen. The score was found to have 88% sensitivity and 97% specificity (cutoff >= 6) and 81% sensitivity and 99% specificity (cutoff 2:7) in the validation set. Conclusion: A reliable diagnosis of AIH can be made using a very simple diagnostic score. We propose the diagnosis of probable AIH at a cutoff point greater than 6 points and definite AIH 7 points or higher.

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PURPOSE: To compare the abilities of scanning laser polarimetry (SLP) with enhanced corneal compensation (ECC) and variable corneal compensation (VCC) modes for detection of retinal nerve fiber layer (RNFL) loss in eyes with band atrophy (BA) of the optic nerve. DESIGN. Cross-sectional study. METHODS: Thirty-seven eyes from 37 patients with BA and temporal visual field defect from chiasmal compression and 40 eyes from 40 healthy subjects were studied. Subjects underwent standard automated perimetry and RNFL measurements using an SLP device equipped with VCC and ECC. Receiver operating characteristic (ROC) curves were calculated for each parameter. Pearson correlation coefficients were obtained to evaluate the relationship between RNFL thickness parameters and severity of visual field loss, as assessed by the temporal mean defect. RESULTS: All RNFL thickness parameters were significantly lower in eyes with BA compared with normal eyes with both compensation modes. However, no statistically significant differences were observed in the areas under the ROC curves for the different parameters between GDx VCC and ECC (Carl Zeiss Meditec, Inc, Dublin, California, USA). Structure-function relationships also were similar for both compensation modes. CONCLUSIONS: No significant differences were found between the diagnostic accuracy of GDx ECC and that of VCC for detection of BA of the optic nerve. The use of GDx ECC does not seem to provide a better evaluation of RNFL loss on the temporal and nasal sectors of the peripapillary retina in subjects with BA of the optic nerve.

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Background: Acute kidney injury (AKI) is a frequent complication in hospitalized patients, especially in those in intensive care units (ICU). The RIFLE classification might be a valid prognostic factor for critically ill cancer patients. The present study aims to evaluate the discriminatory capacity of RIFLE versus other general prognostic scores in predicting hospital mortality in critically ill cancer patients. Methods: This is a single-center study conducted in a cancer-specialized ICU in Brazil. All of the 288 patients hospitalized from May 2006 to June 2008 were included. RIFLE classification, APACHE II, SOFA, and SAPS II scores were calculated and the area under receiver operating characteristic (AROC) curves and logistic multiple regression were performed using hospital mortality as the outcome. Results: AKI, defined by RIFLE criteria, was observed in 156 (54.2%) patients. The distribution of patients with any degree of AKI was: risk, n = 96 (33.3%); injury, n = 30 (10.4%), and failure, n = 30 (10.4%). Mortality was 13.6% for non-AKI patients, 49% for RIFLE `R` patients, 62.3% for RIFLE `I` patients, and 86.8% for RIFLE `F` patients (p = 0.0006). Logistic regression analysis showed that RIFLE criteria, APACHE II, SOFA, and SAPS II were independent factors for mortality in this population. The discrimination of RIFLE was good (AROC 0.801, 95% CI 0.748-0.854) but inferior compared to those of APACHE II (AROC 0.940, 95% CI 0.915-0.966), SOFA (AROC 0.910, 95% CI 0.876-0.943), and SAPS II (AROC 0.869, 95% CI 0.827-0.912). Conclusion: AKI is a frequent complication in ICU patients with cancer. RIFLE was inferior to commonly used prognostic scores for predicting mortality in this cohort of patients. Copyright (C) 2011 S. Karger AG, Basel

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Evaluation of the performance of the APACHE III (Acute Physiology and Chronic Health Evaluation) ICU (intensive care unit) and hospital mortality models at the Princess Alexandra Hospital, Brisbane is reported. Prospective collection of demographic, diagnostic, physiological, laboratory, admission and discharge data of 5681 consecutive eligible admissions (1 January 1995 to 1 January 2000) was conducted at the Princess Alexandra Hospital, a metropolitan Australian tertiary referral medical/surgical adult ICU. ROC (receiver operating characteristic) curve areas for the APACHE III ICU mortality and hospital mortality models demonstrated excellent discrimination. Observed ICU mortality (9.1%) was significantly overestimated by the APACHE III model adjusted for hospital characteristics (10.1%), but did not significantly differ from the prediction of the generic APACHE III model (8.6%). In contrast, observed hospital mortality (14.8%) agreed well with the prediction of the APACHE III model adjusted for hospital characteristics (14.6%), but was significantly underestimated by the unadjusted APACHE III model (13.2%). Calibration curves and goodness-of-fit analysis using Hosmer-Lemeshow statistics, demonstrated that calibration was good with the unadjusted APACHE III ICU mortality model, and the APACHE III hospital mortality model adjusted for hospital characteristics. Post hoc analysis revealed a declining annual SMR (standardized mortality rate) during the study period. This trend was present in each of the non-surgical, emergency and elective surgical diagnostic groups, and the change was temporally related to increased specialist staffing levels. This study demonstrates that the APACHE III model performs well on independent assessment in an Australian hospital. Changes observed in annual SMR using such a validated model support an hypothesis of improved survival outcomes 1995-1999.

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Background: A common task in analyzing microarray data is to determine which genes are differentially expressed across two (or more) kind of tissue samples or samples submitted under experimental conditions. Several statistical methods have been proposed to accomplish this goal, generally based on measures of distance between classes. It is well known that biological samples are heterogeneous because of factors such as molecular subtypes or genetic background that are often unknown to the experimenter. For instance, in experiments which involve molecular classification of tumors it is important to identify significant subtypes of cancer. Bimodal or multimodal distributions often reflect the presence of subsamples mixtures. Consequently, there can be genes differentially expressed on sample subgroups which are missed if usual statistical approaches are used. In this paper we propose a new graphical tool which not only identifies genes with up and down regulations, but also genes with differential expression in different subclasses, that are usually missed if current statistical methods are used. This tool is based on two measures of distance between samples, namely the overlapping coefficient (OVL) between two densities and the area under the receiver operating characteristic (ROC) curve. The methodology proposed here was implemented in the open-source R software. Results: This method was applied to a publicly available dataset, as well as to a simulated dataset. We compared our results with the ones obtained using some of the standard methods for detecting differentially expressed genes, namely Welch t-statistic, fold change (FC), rank products (RP), average difference (AD), weighted average difference (WAD), moderated t-statistic (modT), intensity-based moderated t-statistic (ibmT), significance analysis of microarrays (samT) and area under the ROC curve (AUC). On both datasets all differentially expressed genes with bimodal or multimodal distributions were not selected by all standard selection procedures. We also compared our results with (i) area between ROC curve and rising area (ABCR) and (ii) the test for not proper ROC curves (TNRC). We found our methodology more comprehensive, because it detects both bimodal and multimodal distributions and different variances can be considered on both samples. Another advantage of our method is that we can analyze graphically the behavior of different kinds of differentially expressed genes. Conclusion: Our results indicate that the arrow plot represents a new flexible and useful tool for the analysis of gene expression profiles from microarrays.

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Alzheimer Disease (AD) is characterized by progressive cognitive decline and dementia. Earlier diagnosis and classification of different stages of the disease are currently the main challenges and can be assessed by neuroimaging. With this work we aim to evaluate the quality of brain regions and neuroimaging metrics as biomarkers of AD. Multimodal Imaging Brain Connectivity Analysis (MIBCA) toolbox functionalities were used to study AD by T1weighted, Diffusion Tensor Imaging and 18FAV45 PET, with data obtained from the AD Neuroimaging Initiative database, specifically 12 healthy controls (CTRL) and 33 patients with early mild cognitive impairment (EMCI), late MCI (LMCI) and AD (11 patients/group). The metrics evaluated were gray-matter volume (GMV), cortical thickness (CThk), mean diffusivity (MD), fractional anisotropy (FA), fiber count (FiberConn), node degree (Deg), cluster coefficient (ClusC) and relative standard-uptake-values (rSUV). Receiver Operating Characteristic (ROC) curves were used to evaluate and compare the diagnostic accuracy of the most significant metrics and brain regions and expressed as area under the curve (AUC). Comparisons were performed between groups. The RH-Accumbens/Deg demonstrated the highest AUC when differentiating between CTRLEMCI (82%), whether rSUV presented it in several brain regions when distinguishing CTRL-LMCI (99%). Regarding CTRL-AD, highest AUC were found with LH-STG/FiberConn and RH-FP/FiberConn (~100%). A larger number of neuroimaging metrics related with cortical atrophy with AUC>70% was found in CTRL-AD in both hemispheres, while in earlier stages, cortical metrics showed in more confined areas of the temporal region and mainly in LH, indicating an increasing of the spread of cortical atrophy that is characteristic of disease progression. In CTRL-EMCI several brain regions and neuroimaging metrics presented AUC>70% with a worst result in later stages suggesting these indicators as biomarkers for an earlier stage of MCI, although further research is necessary.

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INTRODUCTION: A growing body of evidence shows the prognostic value of oxygen uptake efficiency slope (OUES), a cardiopulmonary exercise test (CPET) parameter derived from the logarithmic relationship between O(2) consumption (VO(2)) and minute ventilation (VE) in patients with chronic heart failure (CHF). OBJECTIVE: To evaluate the prognostic value of a new CPET parameter - peak oxygen uptake efficiency (POUE) - and to compare it with OUES in patients with CHF. METHODS: We prospectively studied 206 consecutive patients with stable CHF due to dilated cardiomyopathy - 153 male, aged 53.3±13.0 years, 35.4% of ischemic etiology, left ventricular ejection fraction 27.7±8.0%, 81.1% in sinus rhythm, 97.1% receiving ACE-Is or ARBs, 78.2% beta-blockers and 60.2% spironolactone - who performed a first maximal symptom-limited treadmill CPET, using the modified Bruce protocol. In 33% of patients an cardioverter-defibrillator (ICD) or cardiac resynchronization therapy device (CRT-D) was implanted during follow-up. Peak VO(2), percentage of predicted peak VO(2), VE/VCO(2) slope, OUES and POUE were analyzed. OUES was calculated using the formula VO(2) (l/min) = OUES (log(10)VE) + b. POUE was calculated as pVO(2) (l/min) / log(10)peakVE (l/min). Correlation coefficients between the studied parameters were obtained. The prognosis of each variable adjusted for age was evaluated through Cox proportional hazard models and R2 percent (R2%) and V index (V6) were used as measures of the predictive accuracy of events of each of these variables. Receiver operating characteristic (ROC) curves from logistic regression models were used to determine the cut-offs for OUES and POUE. RESULTS: pVO(2): 20.5±5.9; percentage of predicted peak VO(2): 68.6±18.2; VE/VCO(2) slope: 30.6±8.3; OUES: 1.85±0.61; POUE: 0.88±0.27. During a mean follow-up of 33.1±14.8 months, 45 (21.8%) patients died, 10 (4.9%) underwent urgent heart transplantation and in three patients (1.5%) a left ventricular assist device was implanted. All variables proved to be independent predictors of this combined event; however, VE/VCO2 slope was most strongly associated with events (HR 11.14). In this population, POUE was associated with a higher risk of events than OUES (HR 9.61 vs. 7.01), and was also a better predictor of events (R2: 28.91 vs. 22.37). CONCLUSION: POUE was more strongly associated with death, urgent heart transplantation and implantation of a left ventricular assist device and proved to be a better predictor of events than OUES. These results suggest that this new parameter can increase the prognostic value of CPET in patients with CHF.

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Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

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Tese de Doutoramento em Engenharia Industrial e de Sistemas

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OBJECTIVE: To compare the accuracy of 4 different indices of cardiac risk currently used for predicting perioperative cardiac complications. METHODS: We studied 119 patients at a university-affiliated hospital whose cardiac assessment had been required for noncardiac surgery. Predictive factors of high risk for perioperative cardiac complications were assessed through clinical history and physical examination, and the patients were followed up after surgery until the 4th postoperative day to assess the occurrence of cardiac events. All patients were classified according to 4 indices of cardiac risk: the Goldman risk-factor index, Detsky modified risk index, Larsen index, and the American Society of Anesthesiologists' physical status classification and their compared accuracies, examining the areas under their respective receiver operating characteristic (ROC) curves. RESULTS: Cardiac complications occurred in 16% of the patients. The areas under the ROC curves were equal for the Goldman risk-factor index, the Larsen index, and the American Society of Anesthesiologists' physical status classification: 0.48 (SEM ± 0.03). For the Detsky index, the value found was 0.38 (SEM ± 0.03). This difference in the values was not statistically significant. CONCLUSION: The cardiac risk indices currently used did not show a better accuracy than that obtained randomly. None of the indices proved to be significantly better than the others. Studies to improve our ability to predict such complications are still required.

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OBJECTIVE: To develop a simple prognostic model to predict outcome at 1 month after acute basilar artery occlusion (BAO) with readily available predictors. METHODS: The Basilar Artery International Cooperation Study (BASICS) is a prospective, observational, international registry of consecutive patients who presented with an acute symptomatic and radiologically confirmed BAO. We considered predictors available at hospital admission in multivariable logistic regression models to predict poor outcome (modified Rankin Scale [mRS] score 4-5 or death) at 1 month. We used receiver operator characteristic curves to assess the discriminatory performance of the models. RESULTS: Of the 619 patients, 429 (69%) had a poor outcome at 1 month: 74 (12%) had a mRS score of 4, 115 (19%) had a mRS score of 5, and 240 (39%) had died. The main predictors of poor outcome were older age, absence of hyperlipidemia, presence of prodromal minor stroke, higher NIH Stroke Scale (NIHSS) score, and longer time to treatment. A prognostic model that combined demographic data and stroke risk factors had an area under the receiver operating characteristic curve (AUC) of 0.64. This performance improved by including findings from the neurologic examination (AUC 0.79) and CT imaging (AUC 0.80). A risk chart showed predictions of poor outcome at 1 month varying from 25 to 96%. CONCLUSION: Poor outcome after BAO can be reliably predicted by a simple model that includes older age, absence of hyperlipidemia, presence of prodromal minor stroke, higher NIHSS score, and longer time to treatment.

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Some forensic and clinical circumstances require knowledge of the frequency of drug use. Care of the patient, administrative, and legal consequences will be different if the subject is a regular or an occasional cannabis smoker. To this end, 11-nor-9-carboxy-Δ9-tetrahydrocannabinol (THCCOOH) has been proposed as a criterion to help to distinguish between these two groups of users. However, to date this indicator has not been adequately assessed under experimental conditions. We carried out a controlled administration study of smoked cannabis with a placebo. Cannabinoid levels were determined in whole blood using tandem mass spectrometry. Significantly high differences in THCCOOH concentrations were found between the two groups when measured during the screening visit, prior to the smoking session, and throughout the day of the experiment. Receiver operating characteristic (ROC) curves were determined and two threshold criteria were proposed in order to distinguish between these groups: a free THCCOOH concentration below 3 µg/L suggested an occasional consumption (≤ 1 joint/week) while a concentration higher than 40 µg/L corresponded to a heavy use (≥ 10 joints/month). These thresholds were tested and found to be consistent with previously published experimental data. The decision threshold of 40 µg/L could be a cut-off for possible disqualification for driving while under the influence of cannabis. A further medical assessment and follow-up would be necessary for the reissuing of a driving license once abstinence from cannabis has been demonstrated. A THCCOOH level below 3 µg/L would indicate that no medical assessment is required. Copyright © 2013 John Wiley & Sons, Ltd.