843 resultados para Receiver operating characterictics
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BACKGROUND: Patients with chemotherapy-related neutropenia and fever are usually hospitalized and treated on empirical intravenous broad-spectrum antibiotic regimens. Early diagnosis of sepsis in children with febrile neutropenia remains difficult due to non-specific clinical and laboratory signs of infection. We aimed to analyze whether IL-6 and IL-8 could define a group of patients at low risk of septicemia. METHODS: A prospective study was performed to assess the potential value of IL-6, IL-8 and C-reactive protein serum levels to predict severe bacterial infection or bacteremia in febrile neutropenic children with cancer during chemotherapy. Statistical test used: Friedman test, Wilcoxon-Test, Kruskal-Wallis H test, Mann-Whitney U-Test and Receiver Operating Characteristics. RESULTS: The analysis of cytokine levels measured at the onset of fever indicated that IL-6 and IL-8 are useful to define a possible group of patients with low risk of sepsis. In predicting bacteremia or severe bacterial infection, IL-6 was the best predictor with the optimum IL-6 cut-off level of 42 pg/ml showing a high sensitivity (90%) and specificity (85%). CONCLUSION: These findings may have clinical implications for risk-based antimicrobial treatment strategies.
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PURPOSE: To evaluate whether proposed diagnostic criteria applied to magnetic resonance (MR) images of patients with laryngeal and hypopharyngeal carcinoma may be used to distinguish neoplastic from inflammatory involvement of the laryngeal cartilages. MATERIALS AND METHODS: The radiologic and histopathologic data in 121 consecutive patients with primary squamous cell carcinoma of the larynx (n = 63) or hypopharynx (n = 58) who underwent MR imaging before laryngectomy formed the basis of this retrospective study. Patient consent for retrospective chart review was waived by the institutional review board. All laryngectomy specimens were processed with a dedicated histopathologic whole-organ slice technique. MR images were evaluated by two readers according to established ("old") and proposed ("new") diagnostic criteria on the basis of the signal intensity behavior of cartilage on T2-weighted images and contrast material-enhanced T1-weighted images compared with that of the adjacent tumor. Specifically, with the new criteria, T2-weighted or postcontrast T1-weighted cartilage signal intensity greater than that of the adjacent tumor was considered to indicate inflammation, and signal intensity similar to that of the adjacent tumor was considered to indicate neoplastic invasion. The results of the MR image interpretation were compared with the histologic reference standard. RESULTS: The area under the receiver operating characteristic curve for the new criteria (0.94) was nominally but significantly larger than that for the old criteria (0.92) (P = .01). Overall specificity was significantly improved (82% for new vs 74% for old criteria, P < .001) and was greatest for the thyroid cartilage (75% for new vs 54% for old criteria, P < .001) with the new criteria. The sensitivities of the established and the proposed criteria were identical. CONCLUSION: The proposed MR imaging criteria enable improved differentiation of neoplastic cartilage invasion from peritumoral inflammation.
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OBJECTIVE: Meta-analysis of studies of the accuracy of diagnostic tests currently uses a variety of methods. Statistically rigorous hierarchical models require expertise and sophisticated software. We assessed whether any of the simpler methods can in practice give adequately accurate and reliable results. STUDY DESIGN AND SETTING: We reviewed six methods for meta-analysis of diagnostic accuracy: four simple commonly used methods (simple pooling, separate random-effects meta-analyses of sensitivity and specificity, separate meta-analyses of positive and negative likelihood ratios, and the Littenberg-Moses summary receiver operating characteristic [ROC] curve) and two more statistically rigorous approaches using hierarchical models (bivariate random-effects meta-analysis and hierarchical summary ROC curve analysis). We applied the methods to data from a sample of eight systematic reviews chosen to illustrate a variety of patterns of results. RESULTS: In each meta-analysis, there was substantial heterogeneity between the results of different studies. Simple pooling of results gave misleading summary estimates of sensitivity and specificity in some meta-analyses, and the Littenberg-Moses method produced summary ROC curves that diverged from those produced by more rigorous methods in some situations. CONCLUSION: The closely related hierarchical summary ROC curve or bivariate models should be used as the standard method for meta-analysis of diagnostic accuracy.
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Making an accurate diagnosis is essential to ensure that a patient receives appropriate treatment and correct information regarding their prognosis. Characteristics of diagnostic tests are quantified in test accuracy studies, but many such studies have methodological flaws. The HSRC evidence-based diagnosis programme has focused on methods for systematic reviews of test accuracy studies, and the wider context in which tests are ordered and interpreted. We carried out a range of projects relating to literature searching, quality assessment, meta-analysis, presentation of results, and interactions between doctors and patients during the diagnostic process. We have shown that systematic reviews of test accuracy studies should search a range of databases and that current diagnostic filters do not have sufficient accuracy to be used in test accuracy reviews. Summary quality scores should not be used in test accuracy reviews; the Quality Assessment of Studies of Diagnostic Accuracy included in Systematic Reviews (QUADAS) tool for assessing test accuracy studies is acceptable for quality assessment. We have shown that the hierarchical summary receiver operating characteristic (HSROC) and bivariate models for meta-analysis of test accuracy are statistically equivalent in many circumstances, and have developed an add-on module for the statistical software package Stata that enables these statistically rigorous models to be fitted by those without expert statistical knowledge. Three areas that would benefit from further research are literature searching, synthesis of results from individual patient data and presentation of results.
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The municipality of San Juan La Laguna, Guatemala is home to approximately 5,200 people and located on the western side of the Lake Atitlán caldera. Steep slopes surround all but the eastern side of San Juan. The Lake Atitlán watershed is susceptible to many natural hazards, but most predictable are the landslides that can occur annually with each rainy season, especially during high-intensity events. Hurricane Stan hit Guatemala in October 2005; the resulting flooding and landslides devastated the Atitlán region. Locations of landslide and non-landslide points were obtained from field observations and orthophotos taken following Hurricane Stan. This study used data from multiple attributes, at every landslide and non-landslide point, and applied different multivariate analyses to optimize a model for landslides prediction during high-intensity precipitation events like Hurricane Stan. The attributes considered in this study are: geology, geomorphology, distance to faults and streams, land use, slope, aspect, curvature, plan curvature, profile curvature and topographic wetness index. The attributes were pre-evaluated for their ability to predict landslides using four different attribute evaluators, all available in the open source data mining software Weka: filtered subset, information gain, gain ratio and chi-squared. Three multivariate algorithms (decision tree J48, logistic regression and BayesNet) were optimized for landslide prediction using different attributes. The following statistical parameters were used to evaluate model accuracy: precision, recall, F measure and area under the receiver operating characteristic (ROC) curve. The algorithm BayesNet yielded the most accurate model and was used to build a probability map of landslide initiation points. The probability map developed in this study was also compared to the results of a bivariate landslide susceptibility analysis conducted for the watershed, encompassing Lake Atitlán and San Juan. Landslides from Tropical Storm Agatha 2010 were used to independently validate this study’s multivariate model and the bivariate model. The ultimate aim of this study is to share the methodology and results with municipal contacts from the author's time as a U.S. Peace Corps volunteer, to facilitate more effective future landslide hazard planning and mitigation.
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The aim of the present study was to evaluate the potential of diagnostic tests based on interferon-gamma inducible protein (IP)-10 and monocyte chemotactic protein (MCP)-2, and compare the performance with the QuantiFERON TB Gold In-Tube (QFT-IT; Cellestis, Carnagie, Australia) test. IP-10 and MCP-2 were determined in supernatants from whole blood stimulated with Mycobacterium tuberculosis-specific antigens. Samples were obtained from 80 patients with culture- and/or PCR-proven tuberculosis (TB), and 124 unexposed healthy controls: 86 high school students and 38 high school staff. IP-10 and MCP-2 test cut-offs were established based on receiver operating characteristic curve analysis. TB patients produced significantly higher levels (median) of IP-10 (2158 pg x mL(-1)) and MCP-2 (379 pg x mL(-1)) compared with interferon (IFN)-gamma (215 pg x mL(-1)). The QFT-IT, IP-10 and MCP-2 tests detected 81, 83 and 71% of the TB patients; 0, 3 and 0% of the high school students and 0, 16 and 3% of the staff, respectively. Agreement between tests was high (>89%). By combining IP-10 and IFN-gamma tests, the detection rate increased among TB patients to 90% without a significant increase in positive responders among the students. In conclusion, interferon-gamma inducible protein-10 and monocyte chemotactic protein-2 responses to Mycobacterium tuberculosis-specific antigens could be used to diagnose infection. Combining interferon-gamma inducible protein-10 and interferon-gamma may be a simple approach to increase the detection rate of the Mycobacterium tuberculosis-specific in vitro tests.
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There is no accepted way of measuring prothrombin time without time loss for patients undergoing major surgery who are at risk of intraoperative dilution and consumption coagulopathy due to bleeding and volume replacement with crystalloids or colloids. Decisions to transfuse fresh frozen plasma and procoagulatory drugs have to rely on clinical judgment in these situations. Point-of-care devices are considerably faster than the standard laboratory methods. In this study we assessed the accuracy of a Point-of-care (PoC) device measuring prothrombin time compared to the standard laboratory method. Patients undergoing major surgery and intensive care unit patients were included. PoC prothrombin time was measured by CoaguChek XS Plus (Roche Diagnostics, Switzerland). PoC and reference tests were performed independently and interpreted under blinded conditions. Using a cut-off prothrombin time of 50%, we calculated diagnostic accuracy measures, plotted a receiver operating characteristic (ROC) curve and tested for equivalence between the two methods. PoC sensitivity and specificity were 95% (95% CI 77%, 100%) and 95% (95% CI 91%, 98%) respectively. The negative likelihood ratio was 0.05 (95% CI 0.01, 0.32). The positive likelihood ratio was 19.57 (95% CI 10.62, 36.06). The area under the ROC curve was 0.988. Equivalence between the two methods was confirmed. CoaguChek XS Plus is a rapid and highly accurate test compared with the reference test. These findings suggest that PoC testing will be useful for monitoring intraoperative prothrombin time when coagulopathy is suspected. It could lead to a more rational use of expensive and limited blood bank resources.
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BACKGROUND: Periodontitis is the major cause of tooth loss in adults and is linked to systemic illnesses, such as cardiovascular disease and stroke. The development of rapid point-of-care (POC) chairside diagnostics has the potential for the early detection of periodontal infection and progression to identify incipient disease and reduce health care costs. However, validation of effective diagnostics requires the identification and verification of biomarkers correlated with disease progression. This clinical study sought to determine the ability of putative host- and microbially derived biomarkers to identify periodontal disease status from whole saliva and plaque biofilm. METHODS: One hundred human subjects were equally recruited into a healthy/gingivitis group or a periodontitis population. Whole saliva was collected from all subjects and analyzed using antibody arrays to measure the levels of multiple proinflammatory cytokines and bone resorptive/turnover markers. RESULTS: Salivary biomarker data were correlated to comprehensive clinical, radiographic, and microbial plaque biofilm levels measured by quantitative polymerase chain reaction (qPCR) for the generation of models for periodontal disease identification. Significantly elevated levels of matrix metalloproteinase (MMP)-8 and -9 were found in subjects with advanced periodontitis with Random Forest importance scores of 7.1 and 5.1, respectively. The generation of receiver operating characteristic curves demonstrated that permutations of salivary biomarkers and pathogen biofilm values augmented the prediction of disease category. Multiple combinations of salivary biomarkers (especially MMP-8 and -9 and osteoprotegerin) combined with red-complex anaerobic periodontal pathogens (such as Porphyromonas gingivalis or Treponema denticola) provided highly accurate predictions of periodontal disease category. Elevated salivary MMP-8 and T. denticola biofilm levels displayed robust combinatorial characteristics in predicting periodontal disease severity (area under the curve = 0.88; odds ratio = 24.6; 95% confidence interval: 5.2 to 116.5). CONCLUSIONS: Using qPCR and sensitive immunoassays, we identified host- and bacterially derived biomarkers correlated with periodontal disease. This approach offers significant potential for the discovery of biomarker signatures useful in the development of rapid POC chairside diagnostics for oral and systemic diseases. Studies are ongoing to apply this approach to the longitudinal predictions of disease activity.
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The aim of this study was to compare the performance of the DIAGNOdent 2095 with visual examination for occlusal caries detection in permanent and primary molars. The sample comprised 148 permanent human molars and 179 primary human molars. The samples were measured and visually examined three times by two examiners. After measurement, the teeth were histologically prepared and assessed for caries extension. Sensitivity, specificity, accuracy and area under the receiver operating characteristics (ROC) curve were calculated. Intra-class correlation (ICC), unweighted kappa and the Bland and Altman method were used to assess inter- and intra-examiner reproducibility. DIAGNOdent showed higher specificity and lower sensitivity than did visual examination. The ICC values indicated an excellent agreement between the examinations. Kappa values varied from good to excellent for DIAGNOdent but from poor to good for visual examination. In conclusion, the DIAGNOdent may be a useful adjunct to conventional methods for occlusal caries detection.
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Objective: Suicide attempts are common in patients being treated for alcohol-use disorders (AUDs). However, clinical assessment of suicide risk is difficult. In this Swiss multisite study, we propose a decision tree to facilitate identification of profiles of AUD patients at high risk for suicidal behavior. Method: In this retrospective study, we used a sample of 700 patients (243 female), attending 1 of 12 treatment programs for AUDs in the German-speaking part of Switzerland. Sixty-nine patients who reported a suicide attempt in the 3 months before the index treatment were compared using risk factors with 631 patients without a suicide attempt. Receiver operating characteristic (ROC) analyses were used to identify patients at risk of having had a suicide attempt in the previous 3 months. Results: Consistent with previous empirical findings in AUD patients, a prior history of attempted suicide and severe symptoms of depression and aggression considerably increased the risk of a suicide attempt and, in combination, raised the likelihood of a prior suicide attempt to 52%. In addition, one third of AUD patients who had a history of suicide attempts and previous inpatient psychiatric treatment, or who were male and had previous inpatient psychiatric treatment, also reported a suicide attempt. Conclusions: The empirically supported decision tree helps to identify profiles of suicidal AUD patients in Switzerland and supplements clinicians' judgments in making triage decisions for suicide management.
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OBJECTIVE: To evaluate the association between arterial blood pressure (ABP) during the first 24 h and mortality in sepsis. DESIGN: Retrospective cohort study. SETTING: Multidisciplinary intensive care unit (ICU). PATIENTS AND PARTICIPANTS: A total of 274 septic patients. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: Hemodynamic, and laboratory parameters were extracted from a PDMS database. The hourly time integral of ABP drops below clinically relevant systolic arterial pressure (SAP), mean arterial pressure (MAP), and mean perfusion pressure (MPP = MAP - central venous pressure) levels was calculated for the first 24 h after ICU admission and compared with 28-day-mortality. Binary and linear regression models (adjusted for SAPS II as a measure of disease severity), and a receiver operating characteristic (ROC) analysis were applied. The areas under the ROC curve were largest for the hourly time integrals of ABP drops below MAP 60 mmHg (0.779 vs. 0.764 for ABP drops below MAP 55 mmHg; P < or = 0.01) and MPP 45 mmHg. No association between the hourly time integrals of ABP drops below certain SAP levels and mortality was detected. One or more episodes of MAP < 60 mmHg increased the risk of death by 2.96 (CI 95%, 1.06-10.36, P = 0.04). The area under the ROC curve to predict the need for renal replacement therapy was highest for the hourly time integral of ABP drops below MAP 75 mmHg. CONCLUSIONS: A MAP level > or = 60 mmHg may be as safe as higher MAP levels during the first 24 h of ICU therapy in septic patients. A higher MAP may be required to maintain kidney function.
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BACKGROUND: The estimation of physiologic ability and surgical stress (E-PASS) has been used to produce a numerical estimate of expected mortality and morbidity after elective gastrointestinal surgery. The aim of this study was to validate E-PASS in a selected cohort of patients requiring liver resections (LR). METHODS: In this retrospective study, E-PASS predictor equations for morbidity and mortality were applied to the prospective data from 243 patients requiring LR. The observed rates were compared with predicted rates using Fisher's exact test. The discriminative capability of E-PASS was evaluated using receiver-operating characteristic (ROC) curve analysis. RESULTS: The observed and predicted overall mortality rates were both 3.3% and the morbidity rates were 31.3 and 26.9%, respectively. There was a significant difference in the comprehensive risk scores for deceased and surviving patients (p = 0.043). However, the scores for patients with or without complications were not significantly different (p = 0.120). Subsequent ROC curve analysis revealed a poor predictive accuracy for morbidity. CONCLUSIONS: The E-PASS score seems to effectively predict mortality in this specific group of patients but is a poor predictor of complications. A new modified logistic regression might be required for LR in order to better predict the postoperative outcome.
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Aim of this paper is to evaluate the diagnostic contribution of various types of texture features in discrimination of hepatic tissue in abdominal non-enhanced Computed Tomography (CT) images. Regions of Interest (ROIs) corresponding to the classes: normal liver, cyst, hemangioma, and hepatocellular carcinoma were drawn by an experienced radiologist. For each ROI, five distinct sets of texture features are extracted using First Order Statistics (FOS), Spatial Gray Level Dependence Matrix (SGLDM), Gray Level Difference Method (GLDM), Laws' Texture Energy Measures (TEM), and Fractal Dimension Measurements (FDM). In order to evaluate the ability of the texture features to discriminate the various types of hepatic tissue, each set of texture features, or its reduced version after genetic algorithm based feature selection, was fed to a feed-forward Neural Network (NN) classifier. For each NN, the area under Receiver Operating Characteristic (ROC) curves (Az) was calculated for all one-vs-all discriminations of hepatic tissue. Additionally, the total Az for the multi-class discrimination task was estimated. The results show that features derived from FOS perform better than other texture features (total Az: 0.802+/-0.083) in the discrimination of hepatic tissue.
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Quantitative characterisation of carotid atherosclerosis and classification into symptomatic or asymptomatic is crucial in planning optimal treatment of atheromatous plaque. The computer-aided diagnosis (CAD) system described in this paper can analyse ultrasound (US) images of carotid artery and classify them into symptomatic or asymptomatic based on their echogenicity characteristics. The CAD system consists of three modules: a) the feature extraction module, where first-order statistical (FOS) features and Laws' texture energy can be estimated, b) the dimensionality reduction module, where the number of features can be reduced using analysis of variance (ANOVA), and c) the classifier module consisting of a neural network (NN) trained by a novel hybrid method based on genetic algorithms (GAs) along with the back propagation algorithm. The hybrid method is able to select the most robust features, to adjust automatically the NN architecture and to optimise the classification performance. The performance is measured by the accuracy, sensitivity, specificity and the area under the receiver-operating characteristic (ROC) curve. The CAD design and development is based on images from 54 symptomatic and 54 asymptomatic plaques. This study demonstrates the ability of a CAD system based on US image analysis and a hybrid trained NN to identify atheromatous plaques at high risk of stroke.
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Dual energy X-ray absorptiometry (DXA) is widely accepted as the reference method for diagnosis and monitoring of osteoporosis and for assessment of fracture risk, especially at hip. However, axial-DXA is not suitable for mass screening, because it is usually confined to specialized centers. We propose a two-step diagnostic approach to postmenopausal osteoporosis: the first step, using an inexpensive, widely available screening technique, aims at risk stratification in postmenopausal women; the second step, DXA of spine and hip is applied only to potentially osteoporotic women preselected on the basis of the screening measurement. In a group of 110 healthy postmenopausal woman, the capability of various peripheral bone measurement techniques to predict osteoporosis at spine and/or hip (T-score < -2.5SD using DXA) was tested using receiver operating characteristic (ROC) curves: radiographic absorptiometry of phalanges (RA), ultrasonometry at calcaneus (QUS. CALC), tibia (SOS.TIB), and phalanges (SOS.PHAL). Thirty-three women had osteoporosis at spine and/or hip with DXA. Areas under the ROC curves were 0.84 for RA, 0.83 for QUS.CALC, 0.77 for SOS.PHAL (p < 0.04 vs RA) and 0.74 for SOS.TIB (p < 0.02 vs RA and p = 0.05 vs QUS.CALC). For levels of sensitivity of 90%, the respective specificities were 67% (RA), 64% (QUS.CALC), 48% (SOS.PHAL), and 39% (SOS.TIB). In a cost-effective two-step, the price of the first step should not exceed 54% (RA), 51% (QUS.CALC), 42% (SOS.PHAL), and 25% (SOS.TIB). In conclusion, RA, QUS.CALC, SOS.PHAL, and SOS.TIB may be useful to preselect postmenopausal women in whom axial DXA is indicated to confirm/exclude osteoporosis at spine or hip.