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Accuracy of potential diagnostic indicators for coeliac disease: a systematic review protocol

ABSTRACT: Introduction Coeliac disease (CD) is a systemic immune-mediated disorder triggered by gluten in genetically predisposed individuals. CD is diagnosed using a combination of serology tests and endoscopic biopsy of the small intestine. However, because of non-specific symptoms and heterogeneous clinical presentation, diagnosing CD is challenging. Early detection of CD through improved case-finding strategies can improve the response to a gluten-free diet, patients’ quality of life and potentially reduce the risk of complications. However, there is a lack of consensus in which groups may benefit from active case-finding. Methods and analysis We will perform a systematic review to determine the accuracy of diagnostic indicators (such as symptoms and risk factors) for CD in adults and children, and thus can help identify patients who should be offered CD testing. MEDLINE, Embase, Cochrane Library and Web of Science will be searched from 1997 until 2020. Screening will be performed in duplicate. Data extraction will be performed by one and checked by a second reviewer. Disagreements will be resolved through discussion or referral to a third reviewer. We will produce a narrative summary of identified prediction models. Studies, where 2×2 data can be extracted or reconstructed, will be treated as diagnostic accuracy studies, that is, the diagnostic indicators are the index tests and CD serology and/or biopsy is the reference standard. For each diagnostic indicator, we will perform a bivariate random-effects meta-analysis of the sensitivity and specificity. Ethics and dissemination Results will be reported in peer-reviewed journals, academic and public presentations and social media. We will convene an implementation panel to advise on the optimum strategy for enhanced dissemination. We will discuss findings with Coeliac UK to help with dissemination to patients. Ethical approval is not applicable, as this is a systematic review and no research participants will be involved. PROSPERO registration number CRD42020170766.

SUBMITTER: Elwenspoek M

PROVIDER: S-EPMC7537462 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Project description:Background and aimsAlcohol-related liver disease is the most frequent cause of cirrhosis and a major indication for liver transplantation. Several alcohol use biomarkers have been developed in recent years and are already in use in several centers. However, in patients with liver disease their diagnostic performance might be influenced by altered biomarker formation by hepatic damage, altered excretion by kidney dysfunction and diuretics use, and altered deposition in hair and nails. We systematically reviewed studies on the diagnostic accuracy of biomarkers of alcohol use in patients with liver disease and performed a detailed study quality assessment.MethodsA structured search in PubMed/Medline/Embase databases was performed for relevant studies, published until April 28, 2019. The risk of bias and applicability concerns was assessed according to the adapted quality assessment of diagnostic accuracy studies-2 (QUADAS-2) checklist.ResultsTwelve out of 6,449 studies met inclusion criteria. Urinary ethyl glucuronide and urinary ethyl sulfate showed high sensitivity (70 to 89 and 73 to 82%, respectively) and specificity (93 to 99 and 86 to 89%, respectively) for assessing any amount of alcohol use in the past days. Serum carbohydrate-deficient transferrin showed low sensitivity but higher specificity (40 to 79 and 57 to 99%, respectively) to detect excessive alcohol use in the past weeks. Whole blood phosphatidylethanol showed high sensitivity and specificity (73 to 100 and 90 to 96%, respectively) to detect any amount of alcohol use in the previous weeks. Scalp hair ethyl glucuronide showed high sensitivity (85 to 100%) and specificity (97 to 100%) for detecting chronic excessive alcohol use in the past 3 to 6 months. Main limitations of the current evidence are the lack of an absolute gold standard to assess alcohol use, heterogeneous study populations, and the paucity of studies.ConclusionsUrinary and scalp hair ethyl glucuronide are currently the most validated alcohol use biomarkers in patients with liver disease with good diagnostic accuracies. Phosphatidylethanol is a highly promising alcohol use biomarker, but so far less validated in liver patients. Alcohol use biomarkers can complement each other regarding diagnostic time window. More validation studies on alcohol use biomarkers in patients with liver disease are needed.

Project description:BackgroundSystematic review is an indispensable tool for optimal evidence collection and evaluation in evidence-based medicine. However, the explosive increase of the original literatures makes it difficult to accomplish critical appraisal and regular update. Artificial intelligence (AI) algorithms have been applied to automate the literature screening procedure in medical systematic reviews. In these studies, different algorithms were used and results with great variance were reported. It is therefore imperative to systematically review and analyse the developed automatic methods for literature screening and their effectiveness reported in current studies.MethodsAn electronic search will be conducted using PubMed, Embase, ACM Digital Library, and IEEE Xplore Digital Library databases, as well as literatures found through supplementary search in Google scholar, on automatic methods for literature screening in systematic reviews. Two reviewers will independently conduct the primary screening of the articles and data extraction, in which nonconformities will be solved by discussion with a methodologist. Data will be extracted from eligible studies, including the basic characteristics of study, the information of training set and validation set, and the function and performance of AI algorithms, and summarised in a table. The risk of bias and applicability of the eligible studies will be assessed by the two reviewers independently based on Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). Quantitative analyses, if appropriate, will also be performed.DiscussionAutomating systematic review process is of great help in reducing workload in evidence-based practice. Results from this systematic review will provide essential summary of the current development of AI algorithms for automatic literature screening in medical evidence synthesis and help to inspire further studies in this field.Systematic review registrationPROSPERO CRD42020170815 (28 April 2020).

Project description:Objectives: Genital Ulcer Disease (GUD) carries a significant disease burden globally. With limited access to diagnostics, the 2001 World Health Organization (WHO) sexually transmitted illnesses (STI) guidelines proposed a syndromic management algorithm that required a clinical decision to determine the management of GUD. We assessed the diagnostic accuracy of this algorithm. Methods: We conducted a systematic review (Prospero: CRD42020153294) using eight databases for publications between 1995 and January 2021 that reported primary data on the diagnostic accuracy of clinical diagnosis to identify aetiological agents of GUD. Titles and abstracts were independently assessed for eligibility, and data were extracted from full texts for sensitivity/specificity. A hierarchical logistic regression model was used to derive pooled sensitivity and specificity. We used GRADE to evaluate the certainty of evidence. Results: Of 24,857 articles, 151 full texts were examined and 29 included in the analysis. The majority were from middle-income countries [(14/29 (48%) lower middle, 10/29 (34%) upper middle)]. We pooled studies where molecular testing was using to confirm the aetiology of GUD: 9 studies (12 estimates) for herpes, 4 studies (7 estimates) for syphilis, and 7 studies (10 estimates) for chancroid. The pooled sensitivity and specificity of GUD for the detection of herpes was 43.5% [95% confidence interval (CI): 26.2-62.4], and 88.0% (95% CI: 67.0-96.3), respectively (high certainty evidence); and for syphilis were 52.8% (95% CI: 23.0-80.7), and 72.1% (95% CI: 28.0-94.5) (moderate certainty evidence); and for chancroid were 71.9% (95% CI: 45.9-88.5) and 53.1% (95% CI: 36.6-68.9) (moderate certainty evidence), respectively. Conclusion: Algorithms requiring a clinical diagnosis to determine and treat the aetiology of GUD have poor sensitivities for syphilis and herpes simplex virus, resulting in significant numbers of missed cases. There is an urgent need to improve access to affordable and efficient diagnostics (e.g., point-of-care tests) to be incorporated into GUD algorithms to better guide appropriate management. Systematic Review Registration: PROSPERO, identifier: CRD42020153294.

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Accuracy of potential diagnostic indicators for coeliac disease: a systematic review protocol

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