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\"By presenting chapter-specific roadmaps, this book offers a behind-the-scenes chronology of the response to COVID-19 and provides a rubric for future pandemic response. Targeted at lay and scientific audiences, reflections and lessons learned grant the reader an opportunity to leverage this knowledge and improve the outcomes of future pandemics\"-- Provided by publisher.

Rapid microbiologic tests provide opportunities for antimicrobial stewardship programs to improve antimicrobial use and clinical and economic outcomes. Standard techniques for identification of organisms require at least 48–72 hours for final results, compared with rapid diagnostic tests that provide final organism identification within hours of growth. Importantly, rapid microbiologic tests are considered \"game changers\" and represent a significant advancement in the management of infectious diseases. This review focuses on currently available rapid diagnostic tests and, importantly, the impact of rapid testing in combination with antimicrobial stewardship on patient outcomes.

In recent years, a wide range of diagnostic tests has become available for use in resource-constrained settings. Accordingly, a huge number of guidelines, performance evaluations and implementation reports have been produced. However, this wealth of information is unstructured and of uneven quality, which has made it difficult for end-users, such as clinics, laboratories and health ministries, to determine which test would be best for improving clinical care and patient outcomes in a specific context. This paper outlines a six-step guide to the selection and implementation of in vitro diagnostic tests based on Médecins Sans Frontières' practical experience: (i) define the test's purpose; (ii) review the market; (iii) ascertain regulatory approval; (iv) determine the test's diagnostic accuracy under ideal conditions; (v) determine the test's diagnostic accuracy in clinical practice; and (vi) monitor the test's performance in routine use. Gaps in the information needed to complete these six steps and gaps in regulatory systems are highlighted. Finally, ways of improving the quality of diagnostic tests are suggested, such as establishing a model list of essential diagnostics, establishing a repository of information on the design of diagnostic studies and improving quality control and postmarketing surveillance.

BackgroundEating disorders affect upwards of 30 million people worldwide and often go undertreated and underdiagnosed. The purpose of this systematic review and meta-analysis was to evaluate the diagnostic accuracy of the Sick, Control, One, Fat and Food (SCOFF) questionnaire for DSM-5 eating disorders in the general population.MethodThe Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) were followed. A PubMed search was conducted among peer-reviewed articles. Information regarding validation of the SCOFF was required for inclusion. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool.ResultsThe final analysis included 25 studies. The validity of the SCOFF was high across samples with a pooled sensitivity of 0.86 (95% CI, 0.78–0.91) and specificity of 0.83 (95% CI, 0.77–0.88). Subgroup analyses were conducted to examine the impact of methodology, study quality, and clinical characteristics on diagnostic accuracy. Studies with the highest sensitivity tended to be case-control studies of young women with anorexia nervosa (AN) and bulimia nervosa (BN). Studies which included more men, included those diagnosed with binge eating disorder, and recruited from large community samples tended to have lower sensitivity. Few studies reported on BMI and race/ethnicity; thus, subgroups for these factors could not be examined. No studies used reference standards which assessed all DSM-5 eating disorders.ConclusionThis meta-analysis of 25 validation studies demonstrates that the SCOFF is a simple and useful screening tool for young women at risk for AN and BN. However, there is not enough evidence to support utilizing the SCOFF for screening for the range of DSM-5 eating disorders in primary care and community-based settings. Further examination of the validity of the SCOFF or development of a new screening tool, or multiple tools, to screen for the range of DSM-5 eating disorders heterogenous populations is warranted.Trial RegistrationThis study is registered online with PROSPERO (CRD42018089906).

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.

Background Delirium affects > 15% of hospitalised patients but is grossly underdetected, contributing to poor care. The 4 ‘A’s Test (4AT, www.the4AT.com ) is a short delirium assessment tool designed for routine use without special training. The primary objective was to assess the accuracy of the 4AT for delirium detection. The secondary objective was to compare the 4AT with another commonly used delirium assessment tool, the Confusion Assessment Method (CAM). Methods This was a prospective diagnostic test accuracy study set in emergency departments or acute medical wards involving acute medical patients aged ≥ 70. All those without acutely life-threatening illness or coma were eligible. Patients underwent (1) reference standard delirium assessment based on DSM-IV criteria and (2) were randomised to either the index test (4AT, scores 0–12; prespecified score of > 3 considered positive) or the comparator (CAM; scored positive or negative), in a random order, using computer-generated pseudo-random numbers, stratified by study site, with block allocation. Reference standard and 4AT or CAM assessments were performed by pairs of independent raters blinded to the results of the other assessment. Results Eight hundred forty-three individuals were randomised: 21 withdrew, 3 lost contact, 32 indeterminate diagnosis, 2 missing outcome, and 785 were included in the analysis. Mean age was 81.4 (SD 6.4) years. 12.1% (95/785) had delirium by reference standard assessment, 14.3% (56/392) by 4AT, and 4.7% (18/384) by CAM. The 4AT had an area under the receiver operating characteristic curve of 0.90 (95% CI 0.84–0.96). The 4AT had a sensitivity of 76% (95% CI 61–87%) and a specificity of 94% (95% CI 92–97%). The CAM had a sensitivity of 40% (95% CI 26–57%) and a specificity of 100% (95% CI 98–100%). Conclusions The 4AT is a short, pragmatic tool which can help improving detection rates of delirium in routine clinical care. Trial registration International standard randomised controlled trial number (ISRCTN) 53388093 . Date applied 30/05/2014; date assigned 02/06/2014.

Phosphocreatine (PCr) plays a vital role in neuron and myocyte energy homeostasis. Currently, there are no routine diagnostic tests to noninvasively map PCr distribution with clinically relevant spatial resolution and scan time. Here, we demonstrate that artificial neural network-based chemical exchange saturation transfer (ANNCEST) can be used to rapidly quantify PCr concentration with robust immunity to commonly seen MRI interferences. High-quality PCr mapping of human skeletal muscle, as well as the information of exchange rate, magnetic field and radio-frequency transmission inhomogeneities, can be obtained within 1.5 min on a 3 T standard MRI scanner using ANNCEST. For further validation, we apply ANNCEST to measure the PCr concentrations in exercised skeletal muscle. The ANNCEST outcomes strongly correlate with those from 31 P magnetic resonance spectroscopy ( R  = 0.813, p  < 0.001, t test). These results suggest that ANNCEST has potential as a cost-effective and widely available method for measuring PCr and diagnosing related diseases. Phosphocreatine plays a vital role in cellular energetic homeostasis, but there are no routine diagnostic tests to noninvasively map the distribution with clinically relevant spatial resolution. Here, the authors develop and validate a noninvasive approach for quantifying and imaging phosphocreatine, without contrast agents, on widely available clinical MRI scanners with artificial neural networks.

PurposeEarly clinical recognition of sepsis can be challenging. With the advancement of machine learning, promising real-time models to predict sepsis have emerged. We assessed their performance by carrying out a systematic review and meta-analysis.MethodsA systematic search was performed in PubMed, Embase.com and Scopus. Studies targeting sepsis, severe sepsis or septic shock in any hospital setting were eligible for inclusion. The index test was any supervised machine learning model for real-time prediction of these conditions. Quality of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology, with a tailored Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) checklist to evaluate risk of bias. Models with a reported area under the curve of the receiver operating characteristic (AUROC) metric were meta-analyzed to identify strongest contributors to model performance.ResultsAfter screening, a total of 28 papers were eligible for synthesis, from which 130 models were extracted. The majority of papers were developed in the intensive care unit (ICU, n = 15; 54%), followed by hospital wards (n = 7; 25%), the emergency department (ED, n = 4; 14%) and all of these settings (n = 2; 7%). For the prediction of sepsis, diagnostic test accuracy assessed by the AUROC ranged from 0.68–0.99 in the ICU, to 0.96–0.98 in-hospital and 0.87 to 0.97 in the ED. Varying sepsis definitions limit pooling of the performance across studies. Only three papers clinically implemented models with mixed results. In the multivariate analysis, temperature, lab values, and model type contributed most to model performance.ConclusionThis systematic review and meta-analysis show that on retrospective data, individual machine learning models can accurately predict sepsis onset ahead of time. Although they present alternatives to traditional scoring systems, between-study heterogeneity limits the assessment of pooled results. Systematic reporting and clinical implementation studies are needed to bridge the gap between bytes and bedside.

The Lateral Flow Immunoassay (LFIA) is by far one of the most successful analytical platforms to perform the on-site detection of target substances. LFIA can be considered as a sort of lab-in-a-hand and, together with other point-of-need tests, has represented a paradigm shift from sample-to-lab to lab-to-sample aiming to improve decision making and turnaround time. The features of LFIAs made them a very attractive tool in clinical diagnostic where they can improve patient care by enabling more prompt diagnosis and treatment decisions. The rapidity, simplicity, relative cost-effectiveness, and the possibility to be used by nonskilled personnel contributed to the wide acceptance of LFIAs. As a consequence, from the detection of molecules, organisms, and (bio)markers for clinical purposes, the LFIA application has been rapidly extended to other fields, including food and feed safety, veterinary medicine, environmental control, and many others. This review aims to provide readers with a 10-years overview of applications, outlining the trends for the main application fields and the relative compounded annual growth rates. Moreover, future perspectives and challenges are discussed.