Explore the vast range of titles available.

Diagnostic test accuracy (DTA) may vary among health-care settings, which among other reasons may be due to referral from primary to secondary care. The true magnitude and direction of any difference is not certain. We analyzed the results of meta-analyses of DTA to compare sensitivity and specificity between patients in nonreferred and referred care settings. We systematically searched EBSCOhost MEDLINE for systematic reviews that included at least ten original studies of the same diagnostic test, with at least three studies each performed in nonreferred and referred care. Random-effects models, with setting as a binary covariate, were used to calculate pooled sensitivity and specificity estimates per test. Sensitivity analyses were conducted limiting the analyses to studies from countries with gatekeeping systems only. In total, nine systematic reviews evaluating thirteen diagnostic tests were included. For signs and symptoms (seven tests), the differences in sensitivity and specificity ranged from +0.03 to +0.30 and from −0.12 to +0.03, respectively; for biomarkers (four tests) differences in sensitivity ranged from −0.11 to +0.21 and specificity from −0.01 to −0.19. Differences in sensitivity and specificity for one questionnaire test were +0.1 and −0.07 respectively and for one imaging test were −0.22 and −0.07. Sensitivity analyses limited to countries with gatekeeping health care systems produced similar results. Sensitivity and specificity vary in both direction and magnitude between nonreferred and referred settings, depending on the test and target condition, with no universal patterns governing performance differences. Doctors use diagnostic tests to help assess the likelihood if a patient has a certain condition. However, the accuracy of these tests may vary depending on where they are used—such as in primary care (where patients first seek help) or in specialist care (after being referred by a doctor). We wanted to find out how much test accuracy changes between these settings. To do this, we analyzed previous studies that reviewed the accuracy of different diagnostic tests. We compared how well these tests worked in patients who had not yet been referred to a specialist vs those who had. Our analysis included results from thirteen different diagnostic tests, covering symptoms, biomarkers (such as blood tests), a questionnaire, and an imaging test. We found that test accuracy varied depending on the type of test and the condition being diagnosed. Some tests had higher sensitivity (correctly identifying patients with the disease) or specificity (correctly identifying healthy individuals) in primary care, while in specialist care, the same test could perform better, worse, or similarly. There was no clear pattern that applied to all tests. This suggests that researchers should consider how test accuracy may differ across health-care settings when conducting and interpreting diagnostic test accuracy studies. •Sensitivity and specificity vary both in direction and magnitude between settings.•Differences do not follow a specific pattern; they vary across tests and conditions.•Differences in sensitivity were larger than those in specificity.•Consider the setting in diagnostic accuracy interpretation and research design.

Purpose Prone position (PP) improves oxygenation and outcome of acute respiratory distress syndrome (ARDS) patients with a PaO 2 /FiO 2 ratio <150 mmHg. Regional changes in lung aeration can be assessed by lung ultrasound (LUS). Our aim was to predict the magnitude of oxygenation response after PP using bedside LUS. Methods We conducted a prospective multicenter study that included adult patients with severe and moderate ARDS. LUS data were collected at four time points: 1 h before (baseline) and 1 h after turning the patient to PP, 1 h before and 1 h after turning the patient back to the supine position. Regional lung aeration changes and ultrasound reaeration scores were assessed at each time. Overdistension was not assessed. Results Fifty-one patients were included. Oxygenation response after PP was not correlated with a specific LUS pattern. The patients with focal and non-focal ARDS showed no difference in global reaeration score. With regard to the entire PP session, the patients with non-focal ARDS had an improved aeration gain in the anterior areas. Oxygenation response was not associated with aeration changes. No difference in PaCO 2 change was found according to oxygenation response or lung morphology. Conclusions In ARDS patients with a PaO 2 /FiO 2 ratio ≤150 mmHg, bedside LUS cannot predict oxygenation response after the first PP session. At the bedside, LUS enables monitoring of aeration changes during PP.

Disease activity measurement is a key component of rheumatoid arthritis (RA) management. Biomarkers that capture the complex and heterogeneous biology of RA have the potential to complement clinical disease activity assessment. To develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis. Candidate serum protein biomarkers were selected from extensive literature screens, bioinformatics databases, mRNA expression and protein microarray data. Quantitative assays were identified and optimized for measuring candidate biomarkers in RA patient sera. Biomarkers with qualifying assays were prioritized in a series of studies based on their correlations to RA clinical disease activity (e.g. the Disease Activity Score 28-C-Reactive Protein [DAS28-CRP], a validated metric commonly used in clinical trials) and their contributions to multivariate models. Prioritized biomarkers were used to train an algorithm to measure disease activity, assessed by correlation to DAS and area under the receiver operating characteristic curve for classification of low vs. moderate/high disease activity. The effect of comorbidities on the MBDA score was evaluated using linear models with adjustment for multiple hypothesis testing. 130 candidate biomarkers were tested in feasibility studies and 25 were selected for algorithm training. Multi-biomarker statistical models outperformed individual biomarkers at estimating disease activity. Biomarker-based scores were significantly correlated with DAS28-CRP and could discriminate patients with low vs. moderate/high clinical disease activity. Such scores were also able to track changes in DAS28-CRP and were significantly associated with both joint inflammation measured by ultrasound and damage progression measured by radiography. The final MBDA algorithm uses 12 biomarkers to generate an MBDA score between 1 and 100. No significant effects on the MBDA score were found for common comorbidities. We followed a stepwise approach to develop a quantitative serum-based measure of RA disease activity, based on 12-biomarkers, which was consistently associated with clinical disease activity levels.

Multiple biomarker testing is necessary to facilitate individualized treatment of lung cancer patients. More than 80% of lung cancers are diagnosed based on very small tumor samples. Often there is not enough tissue for molecular analysis. We compared three minimal invasive sampling methods with respect to RNA quantity for molecular testing. 106 small biopsies were prospectively collected by three different methods forceps biopsy, endobronchial ultrasound (EBUS) guided transbronchial needle aspiration (TBNA), and CT-guided core biopsy. Samples were split into two halves. One part was formalin fixed and paraffin embedded for standard pathological evaluation. The other part was put in RNA later for immediate RNA/DNA extraction. If the pathologist confirmed the diagnosis of non-small cell lung cancer(NSCLC), the following molecular markers were tested: EGFR mutation, ERCC1, RRM1 and BRCA1. Overall, RNA-extraction was possible in 101 out of 106 patients (95.3%). We found 49% adenocarcinomas, 38% squamouscarcinomas, and 14% non-otherwise-specified(NOS). The highest RNA yield came from endobronchial ultrasound guided needle aspiration, which was significantly higher than bronchoscopy (37.74 ± 41.09 vs. 13.74 ± 15.53 ng respectively, P = 0.005) and numerically higher than CT-core biopsy (37.74 ± 41.09 vs. 28.72 ± 44.27 ng respectively, P = 0.244). EGFR mutation testing was feasible in 100% of evaluable patients and its incidence was 40.8%, 7.9% and 14.3% in adenocarcinomas, squamouscarcinomas and NSCLC NOS subgroup respectively. There was no difference in the feasibility of molecular testing between the three sampling methods with feasibility rates for ERCC1, RRM1 and BRCA1 of 91%, 87% and 81% respectively. All three methods can provide sufficient tumor material for multiple biomarkers testing from routinely obtained small biopsies in lung cancer patients. In our study EBUS guided needle aspiration provided the highest amount of tumor RNA compared to bronchoscopy or CT guided core biopsy. Thus EBUS should be considered as an acceptable option for tissue acquisition for molecular testing.

BackgroundIncreasing numbers of patients with active implantable medical devices (AIMDs) require magnetic resonance (MR) examinations. The manufacturers are continuing to improve the MR compatibility of their AIMDs. To this end, a variety of measurement methods and numerical simulations are used to evaluate the risks associated with magnetic resonance imaging (MRI).ObjectiveIn this article, test methods used to investigate interactions between AIMDs with radio frequency fields and time-varying magnetic gradient fields are reviewed.Materials and methodsA literature review of known test methods for radio frequency and gradient field exposure of AIMDs with leads, in particular for neurostimulators, cochlear implants, and implanted infusion pumps, is presented. The state of the art and promising methods are discussed.ResultsISO/TS 10974 describes the design of high frequency and gradient injection setups to test conductive materials. A large number of sensor designs have been published to measure the induced voltages and currents through radio frequency and gradient fields and for monitoring AIMDs during MR examinations in in vitro tests.ConclusionThe test methods should be planned to be as conservative as possible to cover the worst case scenario. However, in vitro measurements and computer simulation are far from being able to cover all possible configurations in their complexity and uniqueness. For safer MR examinations, current research recommends in vivo testing prior to MR, parallel radiofrequency transmission techniques, and new sequences with reduced energy input in the presence of AIMDs.

The purpose was to assess the clinical utility of diagnostic tests for identifying malignancy within a solitary pulmonary nodule (SPN), and to create a nomogram or “look-up” table using clinical data and non-invasive radiology (positive) test results to estimate post-test probability of malignancy. Studies that examined computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET) and single photon emission computed tomography (SPECT) for the evaluation of SPN. Two reviewers independently abstracted data and assessed study quality. Study-specific and overall positive likelihood ratios (LRs) for each diagnostic test confirming a diagnosis of malignancy and negative LR for each diagnostic test excluding a diagnosis of malignancy within an SPN were calculated. Forty-four of 242 articles were included. Positive LRs for diagnostic tests were: CT 3.91 (95% confidence interval 2.42, 5.40), MRI 4.57 (3.03, 6.1), PET 5.44 (3.56, 7.32) and SPECT 5.16 (4.03, 6.30). Negative LRs were: CT 0.10 (0.03, 0.16), MRI 0.08 (0.03, 0.12), PET 0.06 (0.02, 0.09) and SPECT 0.06 (0.04, 0.08). Differences in performance for all tests were negligible; therefore, the clinician may confidently use any of the four tests presented in further evaluating an SPN. Given the low cost and prevalence of the technology, SPECT appears to be the leading choice for additional testing in SPN evaluation.