scholarly journals Application of Receiver Operating Characteristic (ROC) Curve to Determine the Diagnostic Ability of A Validated Ten - Item Questionnaire (SS - 10) In Estimating the Prevalence of Sensitive Skin in Hong Kong Population

2019 ◽  
Vol 4 (07) ◽  
Author(s):  
Kam Tim Michael Chan ◽  
Amy Ho Nam Cheung
Keyword(s):  
Hong Kong ◽  
Roc Curve ◽  
Clinical Sample ◽  
Community Sample ◽  
Area Under The Curve ◽  
Operating Characteristics ◽  
Sensitive Skin ◽  
Diagnostic Ability ◽  
Cutoff Value ◽  
Receiver Operating

Sensitive skin is a complex skin condition with patients presented mainly subjective neurological symptoms. Prevalence of sensitive skin across populations vary from 13% in Chinese cities to a three-fold higher in American and European countries. Our study aims to develop a cutoff value using the Receiver Operating Characteristics curve in clinical sample in Hong Kong and examine the prevalence of sensitive skin in a community sample across five districts of Hong Kong. Method: The first group of participants consisted of a total of 1,111 new clinic attendees in a local clinic in Kowloon area of Hong Kong. The second group of data was collected from 500 community samples across 5 areas of Hong Kong, with the geographic characteristics ranging from highly to less populated. Participants filled in a questionnaire which contained their demographic information as well as the 10-item version of Sensitive Skin Scale (SS-10). For the clinical sample, a dermatologist diagnosed all the participants for sensitive skin and identified 84 cases (7.56%) of true sensitive skin. Results and conclusion: The Area Under the Curve (AUC) of 0.866 of the ROC curve suggested a good diagnostic ability of SS-10 in population of Hong Kong. A cutoff value of 25.5 with a sensitivity of 91.7% and specificity of 75.5% gave rise to 11.4% of prevalence of sensitive skin in the community sample, which is coherent with that in Mainland China. The study may have significant clinical implications for SS-10 to be a standardized and cost-effective screening tool in Asian populations.

scholarly journals Diagnostic Ability of Peguero-Lo Presti Electrocardiographic Left Ventricular Hypertrophy Criterion in Severe Aortic Stenosis

2021 ◽  
Vol 10 (13) ◽  
pp. 2864
Author(s):  
Aleksandra Gamrat ◽  
Katarzyna Trojanowicz ◽  
Michał A. Surdacki ◽  
Aleksandra Budkiewicz ◽  
Adrianna Wąsińska ◽  
...  
Keyword(s):  
Left Ventricular Hypertrophy ◽  
Aortic Stenosis ◽  
Roc Curve ◽  
Ventricular Hypertrophy ◽  
Severe Aortic Stenosis ◽  
Positive Likelihood Ratio ◽  
Left Ventricular ◽  
The Novel ◽  
Operating Characteristics ◽  
Diagnostic Ability

Traditional electrocardiographic (ECG) criteria for left ventricular hypertrophy (LVH), introduced in the pre-echocardiographic era of diagnosis, have a relatively low sensitivity (usually not exceeding 25–40%) in detecting LVH. A novel Peguero-Lo Presti ECG-LVH criterion was recently shown to exhibit a higher sensitivity than the traditional ECG-LVH criteria in hypertension. Our aim was to test the diagnostic ability of the novel Peguero-Lo Presti ECG-LVH criterion in severe aortic stenosis. We retrospectively analyzed 12-lead ECG tracings and echocardiographic records from the index hospitalization of 50 patients with isolated severe aortic stenosis (mean age: 77 ± 10 years; 30 women and 20 men). Exclusion criteria included QRS > 120 ms, bundle branch blocks or left anterior fascicular block, a history of myocardial infarction, more than mild aortic or mitral regurgitation, and significant LV dysfunction by echocardiography. We compared the agreement of the novel Peguero-Lo Presti criterion and traditional ECG-LVH criteria with echocardiographic LVH (LV mass index > 95 g/m2 in women and >115 g/m2 in men). Echocardiographic LVH was found in 32 out of 50 study patients. The sensitivity of the Peguero-Lo Presti criterion in detecting LVH was improved (55% vs. 9–34%) at lower specificity (72% vs. 78–100%) in comparison to 8 single traditional ECG-LVH criteria. Additionally, the positive predictive value (77% vs. 72%), positive likelihood ratio (2.0 vs. 1.5), and odds ratio (3.2 vs. 2.4) were higher for the Peguero-Lo Presti criterion versus the presence of any of these 8 traditional ECG-LVH criteria. Cohen’s Kappa, a measure of concordance between ECG and echocardiography with regard to LVH, was 0.24 for the Peguero-Lo Presti criterion, −0.01–0.13 for single traditional criteria, and 0.20 for any traditional criterion. However, by the receiver operating characteristics (ROC) curve analysis, the overall ability to discriminate between patients with and without LVH was insignificantly lower for the Peguero-Lo Presti versus Cornell voltage as a continuous variable (area under the ROC curve: 0.65 (95% CI, 0.48–0.81) vs. 0.71 (0.55–0.86), p = 0.5). In conclusion, our preliminary results suggest a slightly better, albeit still low, agreement of the novel Peguero-Lo Presti ECG criterion compared to the traditional ECG-LVH criteria with echocardiographic LVH in severe aortic stenosis.

Estimating the area under a receiver operating characteristic curve using partially ordered sets

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Ehsan Zamanzade ◽  
Xinlei Wang
Keyword(s):  
Roc Curve ◽  
Characteristic Curve ◽  
Partially Ordered Sets ◽  
Sampling Technique ◽  
Real Data ◽  
Cost Effective ◽  
Ordered Sets ◽  
Operating Characteristics ◽  
Partially Ordered ◽  
Receiver Operating

AbstractRanked set sampling (RSS), known as a cost-effective sampling technique, requires that the ranker gives a complete ranking of the units in each set. Frey (2012) proposed a modification of RSS based on partially ordered sets, referred to as RSS-t in this paper, to allow the ranker to declare ties as much as he/she wishes. We consider the problem of estimating the area under a receiver operating characteristics (ROC) curve using RSS-t samples. The area under the ROC curve (AUC) is commonly used as a measure for the effectiveness of diagnostic markers. We develop six nonparametric estimators of the AUC with/without utilizing tie information based on different approaches. We then compare the estimators using a Monte Carlo simulation and an empirical study with real data from the National Health and Nutrition Examination Survey. The results show that utilizing tie information increases the efficiency of estimating the AUC. Suggestions about when to choose which estimator are also made available to practitioners.

Sensitivity and specificity of Sirius indices in diagnosis of keratoconus and suspect keratoconus

2021 ◽  
pp. 112067212110601
Author(s):  
Abdelrahman Salman ◽  
Taym Darwish ◽  
Ali Ali ◽  
Marwan Ghabra ◽  
Rafea Shaaban
Keyword(s):  
Sensitivity And Specificity ◽  
Predictive Accuracy ◽  
Corneal Thickness ◽  
Case Series ◽  
Area Under The Curve ◽  
Receiver Operating Characteristics ◽  
Operating Characteristics ◽  
Symmetry Index ◽  
Case Series Study ◽  
Receiver Operating

Aim To estimate the sensitivity and specificity of topographic and tomographic corneal parameters as determined by Sirius (CSO, Florence, Italy) in discriminating keratoconus (KC) and suspect keratoconus from normal cornea. Method In this retrospective case-series study, keratoconus screening indices were measured using Sirius tomographer. Receiver operating characteristics (ROC) curves were used to determine the test's overall predictive accuracy (area under the curve) and to identify optimal cut-off points to maximize sensitivity and specificity in differentiating keratoconus and suspect keratoconus from normal corneas. Results Receiver operating characteristics (ROC) curve analyses showed high predictive accuracy for Symmetry Index back (SIb), Keratoconus Vertex front (KVf), Symmetry Index front (SIf), Keratoconus Vertex back (KVb), Apex Keratometry (Curve-Apex) and Minimum corneal Thickness (ThkMin) to distinguish keratoconus from normal (area under the curve > 0.9, all). Symmetry Index back was identified as the best diagnostic parameter for detecting suspect keratoconus with AUC of 0.86. Highest specificity to detect keratoconus and suspect keratoconus was seen for SIb, 99.87% and 84.66%, respectively. These values were associated with optimal cut-off points of 0.46 D for keratoconus and 0.12 D for suspect keratoconus. Conclusion Sirius parameters evaluated in the study were effective to differentiate keratoconus from normal corneas. However, Symmetry Index back was the index with the highest ability to detect suspect keratoconus.

Measurement of Whole Blood Platelet Aggregation by Multiplate® Aggregometry Before and during Aspirin Treatment.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 3895-3895
Author(s):  
Susanne B. Pedersen ◽  
Steen D. Kristensen ◽  
Anne-Mette Hvas
Keyword(s):  
Platelet Aggregation ◽  
Roc Curve ◽  
Area Under The Curve ◽  
Reference Method ◽  
Adenosine Diphosphate ◽  
Blood Platelet ◽  
Impedance Method ◽  
Healthy Individuals ◽  
Operating Characteristics ◽  
Normal Platelet

Abstract The inhibition of platelet aggregation by aspirin (ASA) is fundamental in treatment of ischemic heart disease (IHD). Several studies report findings of normal platelet aggregation despite ASA treatment in some individuals, referred to as ASA resistance (AR). It has been hypothesized that AR increases the risk of a future ischemic event. We evaluated a new impedance method for measurement of platelet aggregation, Multiplate® aggregometry (MA), and compared this method to light aggregometry ad modum Born (OPA), with reference to repeatability and detection of AR. Blood samples from 43 IHD patients and 21 healthy individuals treated with ASA 75 mg daily were analyzed in duplicate by MA and OPA on 4 consecutive days. An additional blood sample was obtained prior to ASA treatment in the group of healthy individuals. Compliance was confirmed by measurements of thromboxane B2 in serum. MA was performed with arachidonic acid (AA) in concentrations of 0.25 mM, 0.50 mM and 0.75 mM, and with adenosine diphosphate (ADP) in concentrations of 7.5 μM and 15 μM. OPA was performed with AA-concentrations of 0.5 mM, 1.0 mM and 1.5 mM, and with ADP-concentrations of 5 μM and 10 μM. Table 1. Area under the curve (AUC) measured by MA in patients and in healthy individuals before and during ASA treatment. Agonist AUC, aggregation units · min Healthy Before ASA HealthyDuring ASA PatientsDuring ASA Median Range Median Range Median Range AA, mM 0.25 520 402–999 38 12–83 41 8–110 0.50 574 461–976 51 20–112 56 17–187 0.75 551 434–889 68 21–333 98 18–418 ADP, μM 7.5 474 272–859 422 195–816 472 126–720 15 503 328–922 479 262–995 525 172–834 In healthy individuals, the AA-induced AUC was reduced significantly by ASA at all concentrations (88–93%, p=0.0001). The reduction of AUC was small and insignificant when using ADP (5–11%, p≥0.06). There was a trend towards a higher median AUC measured in patients than in healthy individuals during ASA (p=0.07). Table 2. Coefficients of variation (CV) of double measurements determined by MA and OPA in healthy individuals prior to ASA treatment and during ASA treatment. AA, mM MA AA, mM OPA CVBefore ASA, % CVDuring ASA, % CVBefore ASA, % CVDuring ASA, % 0.25 8 46 0.5 48 25 0.50 10 40 1.0 5 20 0.75 12 41 1.5 5 21 The CV of OPA was generally lower. The reference method was OPA with AA 1.0 mM and AR was defined as a residual platelet aggregation ≥ 20%. According to this definition 7 participants (16%) had AR. A receiver operating characteristics (ROC) analysis showed a sensitivity of MA using AA 0.75 mM of 100% at an AUC cut-point of 94 aggregation units (AU) · min, 71% at 135 AU · min and 29% at 212 AU · min. The specificity was 60, 81 and 93%, respectively. The area under the ROC-curve was 0.79 (95% CI 0.66–0.92). In conclusion, the large ASA-induced reduction in AUC of healthy individuals indicated that MA measures the effect of ASA efficiently when using AA. ADP seems less suitable, as the AUC was only slightly reduced by ASA. The CV of MA was high during ASA treatment, indicating that platelet aggregation during ASA was low and difficult to measure precisely with MA. The area under the ROC-curve was moderately satisfying, but of uncertain correctness due to the rather small number of observations.

scholarly journals A DISCRETIZATION METHOD BASED ON MAXIMIZING THE AREA UNDER RECEIVER OPERATING CHARACTERISTIC CURVE

2013 ◽  
Vol 27 (01) ◽  
pp. 1350002 ◽  
Author(s):  
MURAT KURTCEPHE ◽  
H. ALTAY GÜVENIR
Keyword(s):  
Roc Curve ◽  
Naive Bayes ◽  
Characteristic Curve ◽  
Naïve Bayes ◽  
Machine Learning Algorithms ◽  
Discretization Method ◽  
Operating Characteristics ◽  
Discretization Methods ◽  
Real World Datasets ◽  
Receiver Operating

Many machine learning algorithms require the features to be categorical. Hence, they require all numeric-valued data to be discretized into intervals. In this paper, we present a new discretization method based on the receiver operating characteristics (ROC) Curve (AUC) measure. Maximum area under ROC curve-based discretization (MAD) is a global, static and supervised discretization method. MAD uses the sorted order of the continuous values of a feature and discretizes the feature in such a way that the AUC based on that feature is to be maximized. The proposed method is compared with alternative discretization methods such as ChiMerge, Entropy-Minimum Description Length Principle (MDLP), Fixed Frequency Discretization (FFD), and Proportional Discretization (PD). FFD and PD have been recently proposed and are designed for Naïve Bayes learning. ChiMerge is a merging discretization method as the MAD method. Evaluations are performed in terms of M-Measure, an AUC-based metric for multi-class classification, and accuracy values obtained from Naïve Bayes and Aggregating One-Dependence Estimators (AODE) algorithms by using real-world datasets. Empirical results show that MAD is a strong candidate to be a good alternative to other discretization methods.

scholarly journals Downregulation of Urinary microRNA-200c acts as a Promising Novel Bio-marker in the Diagnosis of Patients With Bladder Cancer

2020 ◽  
Author(s):  
Hao Zi ◽  
Wen-Lin Tao ◽  
Lei Gao ◽  
Zhao-Hua Yu ◽  
Xiao-Dong Bai ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Cancer Patients ◽  
Roc Curve ◽  
Area Under The Curve ◽  
Tumor Grade ◽  
Healthy Controls ◽  
Strongly Correlated ◽  
Operating Characteristics ◽  
Diagnostic Capacity ◽  
Pcr Method

Abstract BackgroundMicroRANs (miRNAs) have been reported to be involved in various human cancers. The aim of this study was to explore the diagnostic performance of urine miR-200c in bladder cancer. MethodsQuantitative real-time polymerase chain reaction (qRT-PCR) method was applied to measure the relative expression of urine miR-200c in bladder cancer patients. The relationship between urine miR-200c level and clinicopathological factors was analyzed using χ2 test. The diagnostic capacity of urine miR-200c was calculated using the receiver operating characteristics (ROC) curve analysis.ResultsUrinary level of miR-200c was significantly reduced in bladder cancer patients compared with healthy controls (P=0.000). Furthermore, urine miR-200c expression was strongly correlated with histologic grade (P=0.019), tumor grade (P=0.003), and lymph node metastasis (P=0.001). ROC curve showed that urine miR-200c could distinguish bladder cancer patients from healthy controls with an area under the curve of 0.844. The cutoff value of 1.235, with the sensitivity of 89.0% and the specificity of 70.7% respectively.ConclusionUrine miR-200c may act as a noninvasive diagnostic biomarker for bladder cancer.

scholarly journals A Rapid Heparin Antibody Detection Assay Performs Better Than 4T's Score in Predicting HIT Diagnosis: A Single Community Medical Center Retrospective Analysis

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 1457-1457 ◽  
Author(s):  
Srikant Nannapaneni ◽  
Ishan Malhotra ◽  
Michael Simon ◽  
Phone Oo ◽  
Trishala Meghal ◽  
...  
Keyword(s):  
High Risk ◽  
Roc Curve ◽  
Predictive Value ◽  
Risk Groups ◽  
Low Risk ◽  
Receiver Operating Characteristics ◽  
Operating Characteristics ◽  
Test Result ◽  
4T Score ◽  
Receiver Operating

Abstract Introduction: The diagnosis of heparin induced thrombocytopenia (HIT) and thrombosis (HITT) is challenging due to poor availability of the gold standard serotonin releasing assay (SRA) and suboptimal positive predictive value from clinical scoring models such as 4T score. A common algorithm used for diagnosing HIT is: 4T's pretest probability score estimation in cases suspected of HIT; followed by HIT antibody test in the intermediate to high risk groups; followed by confirmation with SRA test in HIT antibody positive patients. Since 2011, a Particle Immune-Filtration Assay (PIFA) Heparin/Platelet Factor 4 Rapid Assay (HPF4-RA) (Akers Bioscience, Inc, Thorofare, NJ) became available in our medical center and test results were available on the same day. We observed that HPF4-RA test was being routinely ordered along with SRA test at the same time. We performed this retrospective analysis to evaluate and compare the predictive performance for SRA positive HIT diagnosis using 4T score or HPF4-RA. We applied a regression analysis model, to calculate area under receiver operating characteristics (ROC) curve. Methods: A list of all consecutive patients who had HIT antibody test and/or SRA test performed between January 2010 and June 2013 was obtained, which consisted of 402 patients. Patients with duplication of tests were deleted from analysis. 283 patients had results reported for both HPF4-RA (positive in n=42, negative in n=241) and SRA tests (positive in n=16 and negative in n=267); and these results were used for calculation of HPF4-RA prediction model. Two patients had HPF4-RA negative result but SRA positive test result. 4T's scores were calculated for 125 patients, consisting of all HPF4-RA positive patients (n=42), and patients randomly selected from the total HPF4-RA negative pool (n=83). Electronic medical records were reviewed for temporal trend of platelet counts, diagnosis, medication use, Doppler tests and competing causes of thrombocytopenia. Persons calculating the 4T's score were blinded to the laboratory test results. Results: Stratification of the patients with 4T's score analysis (n=125) revealed that the distribution of SRA positive patients (n=16) was 31.3% (n=5) in low risk, 31.3% (n=5) in intermediate risk, and 37.5% (n=6) in high risk groups; while the distribution of SRA negative patients (n=109) was 45.9% (n=50) in low risk, 43.1% (n=47) in intermediate risk and 11.0% (n=12) in high risk groups. The area under receiver operating characteristics (ROC) curve for 4T score as a continuous variable to predict SRA positive HIT was 0.659 (95% CI 0.516 - 0.802; p = 0.041), and the area under ROC curve for HPF4-RA to predict SRA positive HIT was 0.818 ( 95% CI 0.712 - 0.924; p = 0.00) (Figure 1). HPF4-RA test also showed better overall prediction parameters for HIT as shown in Table 1. A combination of HIT HPF4-RA positive result and a 4T score ≥ 4 did not increase the area under ROC curve for prediction of SRA positive HIT. Abstract 1457. Table1: Predictive performance of 4T's score and HPF4-RA for HIT (defined by positive SRA) Sensitivity (95% CI) Specificity (95% CI) PPV (95% CI) NPV (95% CI) Number of patients (%) 4T's score ≤ 3 (Low Risk) 0.31 (0.11 – 0.59) 0.72 (0.64 - 0.79) 0.11 (0.03 - 0.23) 0.91 (0.84 - 0.95) 56 (44.8) 4T's score ≥ 4 (Intermediate and High Risk) 0.69 (0.41-0.89) 0.39 (0.29 - 0.48) 0.14 (0.72 - 0.24) 0.89 (0.77 - 0.96) 69 (55.2) 4T's score ≥ 6 (High Risk) 0.37 (0.15-0.65) 0.82 (0.74 - 0.89) 0.24 (0.09 - 0.45) 0.90 (0.82 - 0.95) 17 (13.6) HPF4-RA Test 0.88 (0.62-0.98) 0.86 (0.81- 0.90) 0.26 (0.16 - 0.41) 0.99 (0.96 - 0.99) 283 PPV: Positive Predictive Value. NPV: Negative Predictive Value Figure 1: Receiver Operating Characteristics (ROC) curve of the 4T's score and HPF4-RA test result for determining the presence of HIT (defined by positive SRA). Figure 1:. Receiver Operating Characteristics (ROC) curve of the 4T's score and HPF4-RA test result for determining the presence of HIT (defined by positive SRA). Conclusions: Both 4T's score and HPF4-RA testing predict SRA positive HIT more than chance; however HPF4-RA testing predicts SRA positive HIT better than 4T's scores with higher sensitivity, specificity and NPV. This result challenges the pretesting algorithm for selecting patients for confirmatory SRA testing to diagnose HIT. Instead of using 4T's score as a screening tool for selecting patients for HPF4 antibody testing; rapid HPF4 antibody assays when available, should be considered as upfront screening tool and positive results considered for confirmatory SRA testing for diagnosis of HIT. Further studies are warranted to confirm this data. Disclosures No relevant conflicts of interest to declare.

Abstract 19569: High-sensitive Troponin T Cut-off Value for Myocardial Infarction After Vascular Surgery

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Danielle M Gualandro ◽  
Gisela B Llobet ◽  
Pai C Yu ◽  
Daniela Calderaro ◽  
Andre C Marques ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Vascular Surgery ◽  
Roc Curve ◽  
Troponin T ◽  
Curve Analysis ◽  
Operating Characteristics ◽  
Roc Curve Analysis ◽  
Cutoff Value ◽  
Coronary Syndrome ◽  
High Sensitive Troponin

Introduction: Isolated high sensitive cardiac troponin T (hsTnT) elevations after vascular surgery are frequent and may lead to over diagnosis of myocardial infarction (MI). The aim of our study was to determine the accuracy of the current hsTnT cut-off value in the setting of acute coronary syndrome (ACS) after vascular surgery. Methods: Between August 2012 and March 2014, we included 337 consecutive patients submitted to arterial vascular surgery for which cardiac perioperative evaluation was requested. Perioperative surveillance included 12-lead electrocardiogram and hsTnT measurements on the three days following surgery. Patients were followed-up by cardiologists until hospital discharge and monitored for ACS. A receiver operating characteristics (ROC) curve analysis was performed to determine the hsTnT cut-off value with better accuracy for the diagnosis of perioperative ACS. Results: Of the 337 patients included, 240 (71.2%) presented hsTnT elevation above the manufacturer-provided cut-off value (0.014 ng/ml), whereas 22 (6.5%) fulfilled criteria for ACS. Median post-operative peak hsTnT of ACS patients were 0.215 ng/ml (IQR 0.043-0.493 ng/ml), versus 0.02 ng/ml (IQR 0.012-0.038 ng/ml) in patients that did not have events (P<0.001). After performing a ROC curve analysis (AUC = 0.876), we found that the manufacture-provided cutoff hsTnT value yielded a sensitivity of 100% and specificity of only 35% for diagnosis of perioperative ACS. A new hsTnT cutoff value of 0.0415 ng/ml was obtained with 86.4% sensitivity and 77% specificity for the diagnosis of perioperative ACS. Ninety-two patients (27.3%) had hsTnT elevations above the proposed new cutoff. Conclusion: A different hsTnT cutoff value of 0.0415 ng/ml is proposed and could be more useful for the diagnosis of perioperative ACS.

scholarly journals AB0226 USING 3 TESLA MRI WITH A HIGH-RESOLUTION 16-CHANNEL HAND COIL TO DIFFERENTIATE BETWEEN RHEUMATOID AND PSORIATIC ARTHRITIS: A PILOT STUDY

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1412.3-1413
Author(s):  
P. Sewerin ◽  
D. Abrar ◽  
A. Lautwein ◽  
S. Vordenbäumen ◽  
R. Brinks ◽  
...  
Keyword(s):  
Roc Curve ◽  
Area Under The Curve ◽  
Operating Characteristics ◽  
Research Support ◽  
Fat Saturation ◽  
3T Mri ◽  
Deutschland Gmbh ◽  
Bone Edema ◽  
Inflammatory Changes ◽  
Flexor Tenosynovitis

Background:The differentiation between rheumatoid arthritis (RA) and psoriatic arthritis (PsA) is sometimes a challenge for rheumatologists in daily clinical practice. Imaging techniques such as MRI could be a helpful tool for this purpose.Objectives:To examine the value of 3 Tesla (T) magnetic resonance imaging (MRI) with a high-resolution 16-channel hand coil for the differentiation between RA and PsA.Methods:A total of 17 patients with active PsA and 27 patients with active RA were evaluated by 3T MRI. Images were analyzed by three readers according to the outcome measures for RA clinical trials (OMERACT) and RA and PsA MRI scores for the presence and intensity of the following MRI features: synovitis, flexor tenosynovitis, bone edema, bone erosion, periarticular inflammation, bone proliferation, and joint space narrowing. A receiver operating characteristics (ROC) curve was established for a calculated prediction model comprising age, gender, and the imaging features ‘periarticular inflammation’ and ‘erosion’ of the metacarpophalangeal (MCP) joint of the 5th finger.Results:PsA could be differentiated from RA by extracapsular inflammatory changes (PsAMRIS sub-score ‘periarticular inflammation’), with a minimal odds ratio (OR) for the outcome ‘not RA’ of 0.06 (p< 0.01) at all MCP joints. The calculated ROC curve had an area under the curve (AUC) of 98.1%.Conclusion:3T MRI showed a strong association of extracapsular inflammatory changes with PsA at the MCP joint level, and consequently allowed differentiation between PsA and RA.Figure 1.Receiver operating characteristics (ROC) curve with different thresholds for the calculated prediction model for the outcome RA. Area under the curve (AUC) = 98.1%.Figure 2.51-year-old female patient with PsA. MR images show flexor tenosynovitis (FS), synovitis (Syn), and periarticular inflammation (PI). A. Sagittal PD fat-saturation of D5. PI at the volar and dorsal aspects at the MCP, PIP, and DIP levels. FS at the PIP and DIP joint levels. Black asterisks indicate PI. Black arrow points to FS. B. Coronal STIR with bone edema (BE) at the proximal portion of PIP3 and 5 accompanied by PI at PIP3 and MCP, PIP and DIP5. Asterisks indicate BE. Arrowheads point to PI. C. Transversal T2 fat-saturation with FS and PI at MCP5. Arrowhead indicates FS, arrow points to volar PI. D. Transversal T1 fat-saturation following iv contrast, with FS and PI at MCP5. Arrowhead indicates FS, arrows points to volar PI.Disclosure of Interests:Philipp Sewerin Grant/research support from: AbbVie Deutschland GmbH & Co. KGBristol-Myers Squibb Celgene GmbHLilly Deutschland GmbHNovartis Pharma GmbH Pfizer Deutschland GmbHRheumazentrum Rhein-Ruhr, Consultant of: AMGEN GmbH AbbVie Deutschland GmbH & Co. KG Biogen GmbHBristol-Myers Squibb Celgene GmbH Chugai Pharma arketing Ltd. / Chugai Europe GmbHHexal Pharma Janssen-CilagGmbH Johnson & Johnson Deutschland GmbHLilly Deutschland GmbH / Lilly Europe / Lilly Global Novartis Pharma GmbH Pfizer Deutschland GmbH Roche Pharma Rheumazentrum Rhein-Ruhr Sanofi-Genzyme Deutschland GmbH Swedish Orphan Biovitrum GmbH UCB Pharma GmbH, Speakers bureau: AMGEN GmbH AbbVie Deutschland GmbH & Co. KG Biogen GmbHBristol-Myers Squibb Celgene GmbH Chugai Pharma arketing Ltd. / Chugai Europe GmbHHexal Pharma Janssen-CilagGmbH Johnson & Johnson Deutschland GmbHLilly Deutschland GmbH / Lilly Europe / Lilly Global Novartis Pharma GmbH Pfizer Deutschland GmbH Roche Pharma Rheumazentrum Rhein-Ruhr Sanofi-Genzyme Deutschland GmbH Swedish Orphan Biovitrum GmbH UCB Pharma GmbH, Daniel Abrar: None declared, Alexander Lautwein: None declared, Stefan Vordenbäumen: None declared, Ralph Brinks: None declared, Christine Goertz: None declared, Miriam Frenken: None declared, Matthias Schneider Grant/research support from: GSK, UCB, Abbvie, Consultant of: Abbvie, Alexion, Astra Zeneca, BMS, Boehringer Ingelheim, Gilead, Lilly, Sanofi, UCB, Speakers bureau: Abbvie, Astra Zeneca, BMS, Chugai, GSK, Lilly, Pfizer, Sanofi, Benedikt Ostendorf: None declared, Christoph Schleich: None declared

scholarly journals Screening for Sleep Apnoea in Mild Cognitive Impairment: The Utility of the Multivariable Apnoea Prediction Index

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Georgina Wilson ◽  
Zoe Terpening ◽  
Keith Wong ◽  
Ron Grunstein ◽  
Louisa Norrie ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Roc Curve ◽  
Area Under The Curve ◽  
Sleep Apnoea ◽  
Self Report ◽  
Screening Tools ◽  
Operating Characteristics ◽  
Roc Curve Analysis ◽  
Obstructive Sleep

Purpose. Mild cognitive impairment (MCI) is considered an “at risk” state for dementia and efforts are needed to target modifiable risk factors, of which Obstructive sleep apnoea (OSA) is one. This study aims to evaluate the predictive utility of the multivariate apnoea prediction index (MAPI), a patient self-report survey, to assess OSA in MCI.Methods. Thirty-seven participants with MCI and 37 age-matched controls completed the MAPI and underwent polysomnography (PSG). Correlations were used to compare the MAPI and PSG measures including oxygen desaturation index and apnoea-hypopnoea index (AHI). Receiver-operating characteristics (ROC) curve analyses were performed using various cut-off scores for apnoea severity.Results. In controls, there was a significant moderate correlation between higher MAPI scores and more severe apnoea (AHI:r=0.47,P=0.017). However, this relationship was not significant in the MCI sample. ROC curve analysis indicated much lower area under the curve (AUC) in the MCI sample compared to the controls across all AHI severity cut-off scores.Conclusions. In older people, the MAPI moderately correlates with AHI severity but only in those who are cognitively intact. Development of further screening tools is required in order to accurately screen for OSA in MCI.

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