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Diagnostic accuracy of clinical tools for assessment of acute stroke: a systematic review.

ABSTRACT: INTRODUCTION:Recanalisation therapy in acute ischaemic stroke is highly time-sensitive, and requires early identification of eligible patients to ensure better outcomes. Thus, a number of clinical assessment tools have been developed and this review examines their diagnostic capabilities. METHODS:Diagnostic performance of currently available clinical tools for identification of acute ischaemic and haemorrhagic strokes and stroke mimicking conditions was reviewed. A systematic search of the literature published in 2015-2018 was conducted using PubMed, EMBASE, Scopus and The Cochrane Library. Prehospital and in-hospital studies with a minimum sample size of 300 patients reporting diagnostic accuracy were selected. RESULTS:Twenty-five articles were included. Cortical signs (gaze deviation, aphasia and neglect) were shown to be significant indicators of large vessel occlusion (LVO). Sensitivity values for selecting subjects with LVO ranged from 23 to 99% whereas specificity was 24 to 97%. Clinical tools, such as FAST-ED, NIHSS, and RACE incorporating cortical signs as well as motor dysfunction demonstrated the best diagnostic accuracy. Tools for identification of stroke mimics showed sensitivity varying from 44 to 91%, and specificity of 27 to 98% with the best diagnostic performance demonstrated by FABS (90% sensitivity, 91% specificity). Hypertension and younger age predicted intracerebral haemorrhage whereas history of atrial fibrillation and diabetes were associated with ischaemia. There was a variation in approach used to establish the definitive diagnosis. Blinding of the index test assessment was not specified in about 50% of included studies. CONCLUSIONS:A wide range of clinical assessment tools for selecting subjects with acute stroke has been developed in recent years. Assessment of both cortical and motor function using RACE, FAST-ED and NIHSS showed the best diagnostic accuracy values for selecting subjects with LVO. There were limited data on clinical tools that can be used to differentiate between acute ischaemia and haemorrhage. Diagnostic accuracy appeared to be modest for distinguishing between acute stroke and stroke mimics with optimal diagnostic performance demonstrated by the FABS tool. Further prehospital research is required to improve the diagnostic utility of clinical assessments with possible application of a two-step clinical assessment or involvement of simple brain imaging, such as transcranial ultrasonography.

SUBMITTER: Antipova D

PROVIDER: S-EPMC6727516 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Diagnostic accuracy of clinical tools for assessment of acute stroke: a systematic review.

Antipova Daria D Eadie Leila L Macaden Ashish A Wilson Philip P

BMC emergency medicine 20190904 1

<h4>Introduction</h4>Recanalisation therapy in acute ischaemic stroke is highly time-sensitive, and requires early identification of eligible patients to ensure better outcomes. Thus, a number of clinical assessment tools have been developed and this review examines their diagnostic capabilities.<h4>Methods</h4>Diagnostic performance of currently available clinical tools for identification of acute ischaemic and haemorrhagic strokes and stroke mimicking conditions was reviewed. A systematic sear ...[more]

PMID: 31484499

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Project description:BackgroundDespite the rapidly growing number of digital assessment tools for screening and diagnosing mental health disorders, little is known about their diagnostic accuracy.ObjectiveThe purpose of this systematic review and meta-analysis is to establish the diagnostic accuracy of question- and answer-based digital assessment tools for diagnosing a range of highly prevalent psychiatric conditions in the adult population.MethodsThe Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) will be used. The focus of the systematic review is guided by the population, intervention, comparator, and outcome framework (PICO). We will conduct a comprehensive systematic literature search of MEDLINE, PsychINFO, Embase, Web of Science Core Collection, Cochrane Library, Applied Social Sciences Index and Abstracts (ASSIA), and Cumulative Index to Nursing and Allied Health Literature (CINAHL) for appropriate articles published from January 1, 2005. Two authors will independently screen the titles and abstracts of identified references and select studies according to the eligibility criteria. Any inconsistencies will be discussed and resolved. The two authors will then extract data into a standardized form. Risk of bias will be assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool, and a descriptive analysis and meta-analysis will summarize the diagnostic accuracy of the identified digital assessment tools.ResultsThe systematic review and meta-analysis commenced in November 2020, with findings expected by May 2021.ConclusionsThis systematic review and meta-analysis will summarize the diagnostic accuracy of question- and answer-based digital assessment tools. It will identify implications for clinical practice, areas for improvement, and directions for future research.Trial registrationPROSPERO International Prospective Register of Systematic Reviews CRD42020214724; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020214724.International registered report identifier (irrid)DERR1-10.2196/25382.

Project description:BackgroundComputerized migraine diagnostic tools have been developed and validated since 1960. We conducted a systematic review to summarize and critically appraise the quality of all published studies involving computerized migraine diagnostic tools.MethodsWe performed a systematic literature search using PubMed, Web of Science, Scopus, snowballing, and citation searching. Cutoff date for search was 1 June 2021. Published articles in English that evaluated a computerized/automated migraine diagnostic tool were included. The following summarized each study: publication year, digital tool name, development basis, sample size, sensitivity, specificity, reference diagnosis, strength, and limitations. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool was applied to evaluate the quality of included studies in terms of risk of bias and concern of applicability.ResultsA total of 41 studies (median sample size: 288 participants, median age = 43 years; 77% women) were included. Most (60%) tools were developed based on International Classification of Headache Disorders criteria, half were self-administered, and 82% were evaluated using face-to-face interviews as reference diagnosis. Some of the automated algorithms and machine learning programs involved case-based reasoning, deep learning, classifier ensemble, ant-colony, artificial immune, random forest, white and black box combinations, and hybrid fuzzy expert systems. The median diagnostic accuracy was concordance = 89% [interquartile range (IQR) = 76-93%; range = 45-100%], sensitivity = 87% (IQR = 80-95%; range = 14-100%), and specificity = 90% (IQR = 77-96%; range = 65-100%). Lack of random patient sampling was observed in 95% of studies. Case-control designs were avoided in all studies. Most (76%) reference tests exhibited low risk of bias and low concern of applicability. Patient flow and timing showed low risk of bias in 83%.ConclusionDifferent computerized and automated migraine diagnostic tools are available with varying accuracies. Random patient sampling, head-to-head comparison among tools, and generalizability to other headache diagnoses may improve their utility.

Project description:Background: Pain is a common problem after stroke and is associated with poor outcomes. There is no consensus on the optimal method of pain assessment in stroke. A review of the properties of tools should allow an evidence based approach to assessment. Objectives: We aimed to systematically review published data on pain assessment tools used in stroke, with particular focus on classical test properties of: validity, reliability, feasibility, responsiveness. Methods: We searched multiple, cross-disciplinary databases for studies evaluating properties of pain assessment tools used in stroke. We assessed risk of bias using the Quality Assessment of Diagnostic Accuracy Studies tool. We used a modified harvest plot to visually represent psychometric properties across tests. Results: The search yielded 12 relevant articles, describing 10 different tools (n = 1,106 participants). There was substantial heterogeneity and an overall high risk of bias. The most commonly assessed property was validity (eight studies) and responsiveness the least (one study). There were no studies with a neuropathic or headache focus. Included tools were either scales or questionnaires. The most commonly assessed tool was the Faces Pain Scale (FPS) (6 studies). The limited number of papers precluded meaningful meta-analysis at level of pain assessment tool or pain syndrome. Even where common data were available across papers, results were conflicting e.g., two papers described FPS as feasible and two described the scale as having feasibility issues. Conclusion: Robust data on the properties of pain assessment tools for stroke are limited. Our review highlights specific areas where evidence is lacking and could guide further research to identify the best tool(s) for assessing post-stroke pain. Improving feasibility of assessment in stroke survivors should be a future research target. Systematic Review Registration Number: PROSPERO CRD42019160679 Available online at: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019160679.

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Diagnostic accuracy of clinical tools for assessment of acute stroke: a systematic review.

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Diagnostic accuracy of clinical tools for assessment of acute stroke: a systematic review.

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