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Diagnostic accuracy of radiographs for detecting supraglottitis: a systematic review and meta-analysis.

ABSTRACT: Aim:To assess the diagnostic performance of lateral radiograph of the neck for supraglottitis in adults and children. Methods:Electronic database searches (including PubMed, EMBASE, CINAHL, Web of Science, and WHO International Clinical Trials Registry Platform) were carried out through July 2014. Citations of included studies and recent narrative reviews were searched. Studies that compared lateral radiograph of the neck with a reference standard of direct/indirect laryngoscopy were included. Two reviewers independently assessed the methodological quality of included studies by Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Results:Of 2,088 potentially relevant citations, two single-gate (cohort) studies and six two-gate (case-control) studies were identified. These included studies of design are at the moderate or high risk of bias in QUADAS-2. The pooled sensitivity from bivariate random-effects regression was 92.9% (95% confidence interval [CI], 88.5-95.9%) and the pooled specificity was 89.2% (95% CI, 85.9-91.9%), but the diagnostic value would be overestimated because of selection bias in the six two-gate studies. The sensitivity and specificity of the single-gate studies were 100.0% (95% CI, 92.2-100.0%) and 30.6% (95% CI, 15.5-35.6%) in children and 81.0% (95% CI, 78.2-93.2%) and 85.7% specificity (95% CI, 78.2-93.2%) in adults. Conclusion:This study determines that there are insufficient studies of lateral neck radiograph for detecting supraglottitis. Lateral radiograph of the neck seems to have moderate accuracy for detecting supraglottitis. Further approximately unbiased studies are needed to obtain more valid and reliable estimates of test accuracy.

SUBMITTER: Fujiwara T

PROVIDER: S-EPMC5667265 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Diagnostic accuracy of radiographs for detecting supraglottitis: a systematic review and meta-analysis.

Fujiwara Takashi T Miyata Toyohisa T Tokumasu Hironobu H Gemba Hiroko H Fukuoka Toshio T

Acute medicine & surgery 20161110 2

<h4>Aim</h4>To assess the diagnostic performance of lateral radiograph of the neck for supraglottitis in adults and children.<h4>Methods</h4>Electronic database searches (including PubMed, EMBASE, CINAHL, Web of Science, and WHO International Clinical Trials Registry Platform) were carried out through July 2014. Citations of included studies and recent narrative reviews were searched. Studies that compared lateral radiograph of the neck with a reference standard of direct/indirect laryngoscopy w ...[more]

PMID: 29123860

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Project description:BackgroundArtificial Intelligence (AI) holds considerable promise for diagnostics in the field of gastroenterology. This systematic review and meta-analysis aims to assess the diagnostic accuracy of AI models compared with the gold standard of experts and histopathology for the diagnosis of various gastrointestinal (GI) luminal pathologies including polyps, neoplasms, and inflammatory bowel disease.MethodsWe searched PubMed, CINAHL, Wiley Cochrane Library, and Web of Science electronic databases to identify studies assessing the diagnostic performance of AI models for GI luminal pathologies. We extracted binary diagnostic accuracy data and constructed contingency tables to derive the outcomes of interest: sensitivity and specificity. We performed a meta-analysis and hierarchical summary receiver operating characteristic curves (HSROC). The risk of bias was assessed using Quality Assessment for Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Subgroup analyses were conducted based on the type of GI luminal disease, AI model, reference standard, and type of data used for analysis. This study is registered with PROSPERO (CRD42021288360).FindingsWe included 73 studies, of which 31 were externally validated and provided sufficient information for inclusion in the meta-analysis. The overall sensitivity of AI for detecting GI luminal pathologies was 91.9% (95% CI: 89.0-94.1) and specificity was 91.7% (95% CI: 87.4-94.7). Deep learning models (sensitivity: 89.8%, specificity: 91.9%) and ensemble methods (sensitivity: 95.4%, specificity: 90.9%) were the most commonly used models in the included studies. Majority of studies (n = 56, 76.7%) had a high risk of selection bias while 74% (n = 54) studies were low risk on reference standard and 67% (n = 49) were low risk for flow and timing bias.InterpretationThe review suggests high sensitivity and specificity of AI models for the detection of GI luminal pathologies. There is a need for large, multi-center trials in both high income countries and low- and middle- income countries to assess the performance of these AI models in real clinical settings and its impact on diagnosis and prognosis.Systematic review registration[https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=288360], identifier [CRD42021288360].

Project description:ObjectivesTo determine the diagnostic accuracy of different endometrial sampling tests for detecting endometrial carcinoma.DesignSystematic review and meta-analysis of studies of diagnostic accuracy.Data sourcesCochrane Library, MEDLINE/PubMed, CINAHL, Web of Science and Scopus, from the date of inception of the databases to 18 January 2023. Additionally, the reference lists of included studies and other systematic reviews were thoroughly searched.Eligibility criteriaWe included published cross-sectional studies that evaluated any endometrial sampling test (index tests) in women (participants) with clinical suspicion of endometrial carcinoma (target condition) in comparison with histopathology of hysterectomy specimens (reference standard). We excluded case-control and case series studies. No restrictions on language or date of publication were applied.Data extraction and synthesisTwo independent reviewers extracted study data and assessed study quality using the revised quality assessment tool for diagnostic accuracy studies (QUADAS-2). We used bivariate diagnostic random-effects meta-analysis and presented the results in a summary receiver operating characteristic curve. We assessed the certainty of evidence as recommended by the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) approach.ResultsTwelve studies (1607 participants), published between 1986 and 2022, contributed data to the meta-analysis results. Seven studies were judged to be at a low risk of bias in all domains and all studies had low applicability concerns. The most studied index tests were Pipelle and conventional dilation and curettage (D&C). The sensitivity, specificity, positive likelihood ratio and negative likelihood ratio (95% CIs) for Pipelle were 0.774 (0.565 to 0.900), 0.985 (0.927 to 0.997), 97.000 (14.000 to 349.000) and 0.241 (0.101 to 0.442) and for conventional D&C were 0.880 (0.281 to 0.993), 0.984 (0.956 to 0.995), 59.300 (14.200 to 153.000) and 0.194 (0.007 to 0.732), respectively.ConclusionHigh certainty evidence indicates that endometrial sampling using Pipelle or conventional D&C is accurate in diagnosing endometrial cancer. Studies assessing other endometrial sampling tests were sparse.Trial registration numberhttps://osf.io/h8e9z.

Project description:BackgroundMost of national schistosomiasis elimination programmes in Asia are relying on stool examination, particularly Kato Katz stool examination technique for regular transmission monitoring. However, the Kato-Katz technique has shown low sensitivity for the detection of light-intensity infections, and therefore highly sensitive diagnostic tools are urgently required to monitor prevalence of infection in low transmission settings. The objective of this systematic review was to evaluate and synthesize the performance of diagnostic tests for detecting Schistosoma japonicum and S. mekongi infection in people living in endemic areas.Methodology/principal findingsWe comprehensively searched these nine electronic databases and other resources until July 2019, with no language or publication limits: PubMed, EMBASE, MEDLINE, Web of Science, BIOSIS Citation Index, HTA, CINAHL PLUS, The Cochrane Library, and PsycINFO. We included original studies that assessed diagnostic performance using antibody, antigen, and molecular tests with stool examination test as a reference standard. Two reviewers independently extracted a standard set of data and assessed study quality. We estimated the pooled estimates of sensitivity and specificity for each index test. We used diagnostic odds ratio to determine the overall accuracy and hierarchical summary receiver operating characteristics (HSROC) curve to assess the index tests performance. Fifteen studies (S. japonicum [n = 13] and S. mekongi [n = 2]) testing 15,303 participants were included in the review. Five studies reported performance of enzyme-linked immunosorbent assay (ELISA), seven studies reported indirect hemagglutination assay (IHA), and four studies reported polymerase chain reaction (PCR) for detecting S. japonicum. The pooled sensitivity and specificity were 0.93 (95% CI: 0.84-0.98) and 0.40 (95% CI: 0.29-0.53) for ELISA, 0.97 (95% CI: 0.90-0.99) and 0.66 (95% CI: 0.58-0.73) for IHA, and 0.89 (95% CI: 0.71-0.96) and 0.49 (95% CI: 0.29-0.69) for PCR respectively. A global summary indicated the best performance for IHA, closely followed by ELISA. We were unable to perform meta-analysis for S. mekongi due to insufficient number of studies.Conclusions/significanceIHA showed the highest detection accuracy for S. japonicum. Further studies are needed to determine the suitable diagnostic methods to verify the absence of transmission of S. mekongi and also to compare detection accuracy against more sensitive reference standards such as PCR.

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Diagnostic accuracy of radiographs for detecting supraglottitis: a systematic review and meta-analysis.

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Diagnostic accuracy of radiographs for detecting supraglottitis: a systematic review and meta-analysis.

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