Quality Assessment Of Diagnostic Accuracy Studies Research Articles

Interferon-γ release assays for tuberculous meningitis diagnosis: a meta-analysis.

IntroductionTuberculous meningitis (TBM) is still a great challenge to global public health. As conventional diagnostic methods for TBM are unsatisfactory, interferon-γ release assays (IGRAs) have been introduced for TBM diagnosis tentatively. However, the role of IGRAs for diagnosing TBM remains unclear. Thus, we systematically evaluated the diagnostic performance of cerebrospinal fluid (CSF) and peripheral blood (PB) IGRAs in TBM to fill this blank.Material and methodsRelevant studies were systematically searched in both foreign and Chinese databases up to March 2018. Studies in which TBM diagnosis was based on microbiological or clinical criteria were included. The quality of the included studies was assessed through the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Main outcome measures, including sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR) and diagnostic odds ratio (DOR), were pooled statistically using random effects models. The potential heterogeneity was explored by threshold effect analysis, subgroup analyses and meta-regression. Funnel plots and Egger’s test were used to test the potential publication bias. Statistical analyses were performed using Stata and Meta-DiSc software.ResultsTwenty-six out of 656 publications were eligible for meta-analysis, including 1892 participants in total. The pooled estimates of PB IGRAs for TBM diagnosis are as follows: sensitivity: 0.81 (95% CI: 0.78–0.84); specificity: 0.76 (95% CI: 0.73–0.78); PLR: 4.23 (95% CI: 2.95–6.07); NLR: 0.24 (95% CI: 0.19–0.32) and DOR: 21.06 (11.91-37.24). The corresponding estimates for CSF IGRAs were obtained: sensitivity: 0.81 (95% CI: 0.76–0.85); specificity: 0.89 (95% CI: 0.86–0.92); PLR: 7.87 (95% CI: 4.98–12.46); NLR: 0.19 (95% CI: 0.13–0.29); and DOR: 47.74 (25.02–91.12).ConclusionsThe diagnostic performance of IGRAs is suboptimal. In terms of cost, turn-around time and accessibility, these assays are unsuitable for use as biomarkers for TBM diagnosis.

Machine learning with neuroimaging data to identify autism spectrum disorder: a systematic review and meta-analysis.

AutismSpectrum Disorder (ASD) is diagnosed through observation or interview assessments, which is time-consuming, subjective, and with questionable validity and reliability. Thus, we aimed to evaluate the role of machine learning (ML) with neuroimaging data to provide a reliable classification of ASD. A systematic search of PubMed, Scopus, and Embase was conducted to identify relevant publications. Quality Assessment of Diagnostic Accuracy Studies-2(QUADAS-2) was used to assess the studies' quality. A bivariate random-effects model meta-analysis was employed to evaluate the pooled sensitivity,the pooled specificity, and the diagnostic performance through the hierarchical summary receiver operating characteristic (HSROC) curveof ML with neuroimaging data inclassifying ASD. Meta-regression was also performed. Forty-four studies (5697 ASD and 6013 typically developing individuals [TD] in total) were included in the quantitative analysis. The pooled sensitivity for differentiating ASD from TD individuals was 86.25 95% confidence interval [CI] (81.24, 90.08), while the pooled specificity was 83.31 95% CI (78.12, 87.48) with a combined area under the HSROC (AUC) of 0.889. Higgins I2 (> 90%) and Cochran's Q (p < 0.0001) suggest a high degree of heterogeneity. In the bivariate model meta-regression, a higher pooled specificity was observed in studies not using a brain atlas (90.91 95% CI [80.67, 96.00], p = 0.032). In addition, a greater pooled sensitivity was seen in studies recruiting both males and females (89.04 95% CI [83.84, 92.72], p = 0.021), and combining imaging modalities (94.12 95% [85.43, 97.76], p = 0.036). ML with neuroimaging data is an exciting prospect in detecting individuals with ASD but further studiesarerequiredto improveits reliability for usage in clinical practice.

Overall diagnostic accuracy of different MR imaging sequences for detection of dysplastic nodules: a systematic review and meta-analysis.

To assess the overall diagnostic accuracy of different MR imaging sequences in the detection of the dysplastic nodule (DN). PubMed, Cochrane Library, and Web of Science were systematically searched. Study selection and data extraction were conducted by two authors independently. Quality assessment of diagnostic accuracy studies (QUADAS) 2 in RevMan software was used to score the included studies and assess their methodological quality. A random-effects model was used for statistical pooling by Meta-Disc. Subgroup analysis and sensitivity analysis were used to explore potential sources of heterogeneity. Fourteen studies (335 DN lesions in total) were included in our meta-analysis. The area under the curve (AUC) of summary receiver operating characteristic (SROC) of T2WI was 0.87. Pooled sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) of DWI were 0.81 (95%CI, 0.73-0.87), 0.90 (95%CI, 0.86-0.93), 7.04 (95%CI, 4.49-11.04), and 0.24 (95%CI, 0.17-0.33) respectively. In the arterial phase, pooled sensitivity, specificity, PLR, and NLR were 0.89 (0.84-0.93), 0.75 (0.72-0.79), 3.72 (2.51-5.51), and 0.17 (0.12-0.25), respectively. Pooled sensitivity, specificity, PLR, and NLR of the delayed phase were 0.78 (0.72-0.83), 0.60 (0.55-0.65), 2.19 (1.55-3.10), and 0.36 (0.23-0.55) separately. Pooled sensitivity, specificity, PLR, and NLR of the hepatobiliary phase were 0.77 (0.71-0.82), 0.92 (0.89-0.94), 8.74 (5.91-12.92), and 0.24 (0.14-0.41) respectively. Pooled sensitivity, specificity, and PLR were higher on DWI and hepatobiliary phase in diagnosing LGDN than HGDN. MR sequences, particularly DWI, arterial phase, and hepatobiliary phase imaging demonstrate high diagnostic accuracy for DN. • MRI has dramatically improved the detection and accurate diagnosis of DNs and their differentiation from hepatocellular carcinoma. • Overall diagnostic accuracy of different MRI sequences in the detection of DN has not been studied before. • Our meta-analysis demonstrates that MRI achieves a high diagnostic value for DN, especially when using DWI, arterial phase imaging, and hepatobiliary phase imaging.

Diagnostic tests for oral cancer and potentially malignant disorders in patients presenting with clinically evident lesions.

Squamous cell carcinoma is the most common form of malignancy of the oral cavity, and is often proceeded by oral potentially malignant disorders (OPMD). Early detection of oral cavity squamous cell carcinoma (oral cancer) can improve survival rates. The current diagnostic standard of surgical biopsy with histology is painful for patients and involves a delay in order to process the tissue and render a histological diagnosis; other diagnostic tests are available that are less invasive and some are able to provide immediate results. This is an update of a Cochrane Review first published in 2015. Primary objective: to estimate the diagnostic accuracy of index tests for the detection of oral cancer and OPMD, in people presenting with clinically evident suspicious and innocuous lesions. to estimate the relative accuracy of the different index tests. Cochrane Oral Health's Information Specialist searched the following databases: MEDLINE Ovid (1946 to 20 October 2020), and Embase Ovid (1980 to 20 October 2020). The US National Institutes of Health Ongoing Trials Register (ClinicalTrials.gov) and the World Health Organization International Clinical Trials Registry Platform were also searched for ongoing trials to 20 October 2020. No restrictions were placed on the language or date of publication when searching the electronic databases. We conducted citation searches, and screened reference lists of included studies for additional references. We selected studies that reported the diagnostic test accuracy of the following index tests when used as an adjunct to conventional oral examination in detecting OPMD or oral cavity squamous cell carcinoma: vital staining (a dye to stain oral mucosa tissues), oral cytology, light-based detection and oral spectroscopy, blood or saliva analysis (which test for the presence of biomarkers in blood or saliva). Two review authors independently screened titles and abstracts for relevance. Eligibility, data extraction and quality assessment were carried out by at least two authors, independently and in duplicate. Studies were assessed for methodological quality using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Meta-analysis was used to combine the results of studies for each index test using the bivariate approach to estimate the expected values of sensitivity and specificity. This update included 63 studies (79 datasets) published between 1980 and 2020 evaluating 7942 lesions for the quantitative meta-analysis. These studies evaluated the diagnostic accuracy of conventional oral examination with: vital staining (22 datasets), oral cytology (24 datasets), light-based detection or oral spectroscopy (24 datasets). Nine datasets assessed two combined index tests. There were no eligible diagnostic accuracy studies evaluating blood or salivary sample analysis. Two studies were classed as being at low risk of bias across all domains, and 33 studies were at low concern for applicability across the three domains, where patient selection, the index test, and the reference standard used were generalisable across the population attending secondary care. The summary estimates obtained from the meta-analysis were: - vital staining: sensitivity 0.86 (95% confidence interval (CI) 0.79 to 0.90) specificity 0.68 (95% CI 0.58 to 0.77), 20 studies, sensitivity low-certainty evidence, specificity very low-certainty evidence; - oral cytology: sensitivity 0.90 (95% CI 0.82 to 0.94) specificity 0.94 (95% CI 0.88 to 0.97), 20 studies, sensitivity moderate-certainty evidence, specificity moderate-certainty evidence; - light-based: sensitivity 0.87 (95% CI 0.78 to 0.93) specificity 0.50 (95% CI 0.32 to 0.68), 23 studies, sensitivity low-certainty evidence, specificity very low-certainty evidence; and - combined tests: sensitivity 0.78 (95% CI 0.45 to 0.94) specificity 0.71 (95% CI 0.53 to 0.84), 9 studies, sensitivity very low-certainty evidence, specificity very low-certainty evidence. At present none of the adjunctive tests can be recommended as a replacement for the currently used standard of a surgical biopsy and histological assessment. Given the relatively high values of the summary estimates of sensitivity and specificity for oral cytology, this would appear to offer the most potential. Combined adjunctive tests involving cytology warrant further investigation. Potentially eligible studies of blood and salivary biomarkers were excluded from the review as they were of a case-control design and therefore ineligible. In the absence of substantial improvement in the tests evaluated in this updated review, further research into biomarkers may be warranted.

Prevalence of freezing of gait in Parkinson's disease: a systematic review and meta-analysis.

Freezing of gait (FOG) is considered one of the most disturbing and least understood symptoms in Parkinson's disease (PD). The reported prevalence rates of FOG in PD vary widely, ranging from 5 to 85.9%. We conducted a systematic review and meta-analysis to provide a reliable estimate of the average point prevalence of FOG in PD, and we further investigated the study characteristics that might have influenced the estimate. We searched different databases to identify studies that report the prevalence of FOG in PD or include relevant raw data for further calculation. The last inclusion date was February 20, 2020. The modified Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool was used for the quality assessment, and articles that met the predefined criteria were included in the quantitative analysis. Sixty-six studies were selected from 3392 references. A weighted prevalence of 50.6% in 9072 PD patients experienced FOG based on the special questionnaires (the FOG-Q and NFOG-Q), which was about twice as high as that assessed by the specific items of the clinical rating scales (UPDRS item2.14 and MDS-UPDRS item3.11) (23.2%) or simple clinical questions (25.4%). The weighted prevalence was 37.9% for early stage (≤ 5years) and 64.6% for advanced stage (≥ 9years). Moreover, a higher prevalence was calculated from the population-based studies than that in multicenter and single-center studies (47.3% vs. 33.5% and 37.1%, respectively). The result from this systematic review confirms that FOG is very common in PD and its prevalence is usually underestimated in hospital settings. Importantly, a more accurate assessment of FOG in future clinical researches would involve the use of special FOG scale rather than a single item on a scale or a general clinical inquiry.

Diagnostic Accuracy of Procalcitonin for Bacterial Infection in Liver Failure: A Meta-Analysis.

The purpose of our studies was to systematically assess the accuracy and clinical value of plasma calcitonin in patients with liver failure complicated with bacterial infection. In this study, we included prospective observational studies or randomized controlled trials on PCT. The quality of the studies was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Heterogeneity, pooled diagnostic odds ratio (DOR), pooled sensitivity, pooled specificity, pooled positive likelihood ratio, pooled negative likelihood ratio, the area under the summary receiver operating characteristic curve (SROC), and metaregression analysis were performed using Stata16.0 software. Consequently, the studies revealed substantial heterogeneity (I2 = 96, 95% confidence interval (95% CI) = 94–99). The results of meta-analysis using random effect models suggested that the combined DOR was 10.67 (95% CI = 3.73–30.53). In addition, the threshold effect analysis showed that the threshold effect was 0.23 and the correlation coefficient was −0.48, indicating that there was no threshold effect. In the forest map, the DOR of each study and the combined DOR are not distributed along the same line, and Q = 2.2 × 1014, P ≤ 0.001. Furthermore, the metaregression analysis of PCT study design, bacterial infection site, and mean age displayed that the P values were >0.05. The combined sensitivity was 0.77 (95% CI = 0.54–0.90), the combined specificity was 0.76 (95% CI = 0.70–0.82), the combined positive likelihood ratio was 3.25 (95% CI = 2.33–4.52), the combined negative likelihood ratio was 0.30 (95% CI = 0.14–0.67), and the combined AUC was 0.80 (95% CI = 0.76–0.83). In conclusion, PCT has moderate diagnostic value for adult liver failure complicated with bacterial infection, and it is a better auxiliary diagnostic index for liver failure with bacterial infection. However, the results of procalcitonin must be carefully interpreted combined with medical history, physical examination, and microbiological assessment.

Performance and Limitation of Machine Learning Algorithms for Diabetic Retinopathy Screening: Meta-analysis.

BackgroundDiabetic retinopathy (DR), whose standard diagnosis is performed by human experts, has high prevalence and requires a more efficient screening method. Although machine learning (ML)–based automated DR diagnosis has gained attention due to recent approval of IDx-DR, performance of this tool has not been examined systematically, and the best ML technique for use in a real-world setting has not been discussed.ObjectiveThe aim of this study was to systematically examine the overall diagnostic accuracy of ML in diagnosing DR of different categories based on color fundus photographs and to determine the state-of-the-art ML approach.MethodsPublished studies in PubMed and EMBASE were searched from inception to June 2020. Studies were screened for relevant outcomes, publication types, and data sufficiency, and a total of 60 out of 2128 (2.82%) studies were retrieved after study selection. Extraction of data was performed by 2 authors according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), and the quality assessment was performed according to the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Meta-analysis of diagnostic accuracy was pooled using a bivariate random effects model. The main outcomes included diagnostic accuracy, sensitivity, and specificity of ML in diagnosing DR based on color fundus photographs, as well as the performances of different major types of ML algorithms.ResultsThe primary meta-analysis included 60 color fundus photograph studies (445,175 interpretations). Overall, ML demonstrated high accuracy in diagnosing DR of various categories, with a pooled area under the receiver operating characteristic (AUROC) ranging from 0.97 (95% CI 0.96-0.99) to 0.99 (95% CI 0.98-1.00). The performance of ML in detecting more-than-mild DR was robust (sensitivity 0.95; AUROC 0.97), and by subgroup analyses, we observed that robust performance of ML was not limited to benchmark data sets (sensitivity 0.92; AUROC 0.96) but could be generalized to images collected in clinical practice (sensitivity 0.97; AUROC 0.97). Neural network was the most widely used method, and the subgroup analysis revealed a pooled AUROC of 0.98 (95% CI 0.96-0.99) for studies that used neural networks to diagnose more-than-mild DR.ConclusionsThis meta-analysis demonstrated high diagnostic accuracy of ML algorithms in detecting DR on color fundus photographs, suggesting that state-of-the-art, ML-based DR screening algorithms are likely ready for clinical applications. However, a significant portion of the earlier published studies had methodology flaws, such as the lack of external validation and presence of spectrum bias. The results of these studies should be interpreted with caution.

Machine Learning for the Prediction of Molecular Markers in Glioma on Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis.

Molecular characterization of glioma has implications for prognosis, treatment planning, and prediction of treatment response. Current histopathology is limited by intratumoral heterogeneity and variability in detection methods. Advances in computational techniques have led to interest in mining quantitative imaging features to noninvasively detect genetic mutations. To evaluate the diagnostic accuracy of machine learning (ML) models in molecular subtyping gliomas on preoperative magnetic resonance imaging (MRI). A systematic search was performed following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines to identify studies up to April 1, 2020. Methodological quality of studies was assessed using the Quality Assessment for Diagnostic Accuracy Studies (QUADAS)-2. Diagnostic performance estimates were obtained using a bivariate model and heterogeneity was explored using metaregression. Forty-four original articles were included. The pooled sensitivity and specificity for predicting isocitrate dehydrogenase (IDH) mutation in training datasets were 0.88 (95% CI 0.83-0.91) and 0.86 (95% CI 0.79-0.91), respectively, and 0.83 to 0.85 in validation sets. Use of data augmentation and MRI sequence type were weakly associated with heterogeneity. Both O6-methylguanine-DNA methyltransferase (MGMT) gene promoter methylation and 1p/19q codeletion could be predicted with a pooled sensitivity and specificity between 0.76 and 0.83 in training datasets. ML application to preoperative MRI demonstrated promising results for predicting IDH mutation, MGMT methylation, and 1p/19q codeletion in glioma. Optimized ML models could lead to a noninvasive, objective tool that captures molecular information important for clinical decision making. Future studies should use multicenter data, external validation and investigate clinical feasibility of ML models.

A systematic review of next-generation point-of-care stroke diagnostic technologies

Stroke is a leading cause of morbidity and mortality. Current diagnostic modalities include CT and MRI. Over the last decade, novel technologies to facilitate stroke diagnosis, with the hope of shortening time to treatment and reducing rates of morbidity and mortality, have been developed. The authors conducted a systematic review to identify studies reporting on next-generation point-of-care stroke diagnostic technologies described within the last decade. A systematic review was performed according to PRISMA guidelines to identify studies reporting noninvasive stroke diagnostics. The QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies-2) tool was utilized to assess risk of bias. PubMed, Web of Science, and Scopus databases were utilized. Primary outcomes assessed included accuracy and timing compared with standard imaging, potential risks or complications, potential limitations, cost of the technology, size/portability, and range/size of detection. Of the 2646 reviewed articles, 19 studies met the inclusion criteria and included the following modalities of noninvasive stoke detection: microwave technology (6 studies, 31.6%), electroencephalography (EEG; 4 studies, 21.1%), ultrasonography (3 studies, 15.8%), near-infrared spectroscopy (NIRS; 2 studies, 10.5%), portable MRI devices (2 studies, 10.5%), volumetric impedance phase-shift spectroscopy (VIPS; 1 study, 5.3%), and eddy current damping (1 study, 5.3%). Notable medical devices that accurately predicted stroke in this review were EEG-based diagnosis, with a maximum sensitivity of 91.7% for predicting a stroke, microwave-based diagnosis, with an area under the receiver operating characteristic curve (AUC) of 0.88 for differentiating ischemic stroke and intracerebral hemorrhage (ICH), ultrasound with an AUC of 0.92, VIPS with an AUC of 0.93, and portable MRI with a diagnostic accuracy similar to that of traditional MRI. NIRS offers significant potential for more superficially located hemorrhage but is limited in detecting deep-seated ICH (2.5-cm scanning depth). As technology and computational resources have advanced, several novel point-of-care medical devices show promise in facilitating rapid stroke diagnosis, with the potential for improving time to treatment and informing prehospital stroke triage.

The detection value of PD-L1 expression in biopsy specimens and surgical resection specimens in non-small cell lung cancer: a meta-analysis.

BackgroundThe detection value of different types of specimens for programmed death ligand-1 (PD-L1) expression remains controversial. As such, the purpose of this meta-analysis was to compare the detection value of biopsy specimens and surgical resection specimens for PD-L1 expression in patients with non-small cell lung cancer (NSCLC).MethodsPubMed and Web of Science were searched prior to December 2020 to identify studies that compared the detection value of biopsy specimens and surgical resection specimens for PD-L1 expression in NSCLC. Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 scale was used to evaluate the quality of the literature included. The detection value of different types of specimens for PD-L1 expression was then assessed. Besides, the relative risk (RR) with 95% CI were pooled using Review Manager 5.3 software and Stata 14.0 software.ResultsThe meta-analysis involved 12 articles and included 877 patients. There was no significant difference in the detection rate of PD-L1 at the 1% cutoff between biopsy specimens and surgical resection specimens (RR =0.89, 95% CI: 0.70–1.12, P=0.33). However, there was a significant difference between two groups when the cutoff is 50% (RR =0.69, 95% CI: 0.58–0.83, P<0.01). In addition, a subgroup analysis of the type of biopsy specimens and the PD-L1 qualitative immunohistochemistry (IHC) assays showed that the detection rate of PD-L1 in small biopsies and using the SP142 antibody were lower than in surgical specimens and using other antibodies for both the 1% and 50% cut-offs (P<0.01).ConclusionsCurrent evidence suggests that caution must be taken when using biopsy specimens from patients with advanced NSCLC to evaluate PD-L1 status eligible for immunotherapy, additional biopsy specimens sampling may be needed to minimize the risk of tumor misclassification. In addition, PD-L1 qualitative IHC assays and the type of biopsy specimens related to PD-L1 expression detection.

International HIV Dementia Scale for HIV-Associated Neurocognitive Disorders: A Systematic Review and Meta-Analysis.

The present study aims to systematically review the evidence on the accuracy of the International HIV Dementia Scale (IHDS) test for diagnosing human immunodeficiency virus (HIV)-associated neurocognitive disorders (HAND) and outline the quality and quantity of research evidence available on the accuracy of IHDS in people living with HIV. We conducted a systematic literature review, searching five databases from inception until July 2020. We extracted dichotomized positive and negative test results at various thresholds and calculated the sensitivity and specificity of IHDS. Quality assessment was performed according to the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) criteria. Fifteen cross-sectional studies, published between 2011 and 2018, met the inclusion criteria for meta-analysis. Overall, 3760 patients were included, but most studies recruited small samples. We assessed most studies as being applicable to the review question, though we had concerns about the selection of participants in three studies. The accuracy of IHDS was investigated at thirteen cut-off points (scores 6–12). The threshold of 10 is the most useful for optimal HAND screening (including asymptomatic neurocognitive disorder, symptomatic HAND, and HIV-associated dementia) with fair diagnostic accuracy.

Utility of the DECAF score for predicting survival of patients with COPD: a meta-analysis of diagnostic accuracy studies.

The DECAF (Dyspnea, Eosinopenia, Consolidation, Acidemia, Atrial Fibrillation) score is a widely used system for predicting the survival of patients with acute aggravation of chronic obstructive pulmonary disease (COPD). Evaluations of the predictive accuracy of DECAF have shown differing results. We performed this meta-analysis to evaluate the DECAF score as a survival predictor in patients with COPD. We have included the studies examining the accuracy of DECAF scoring system as index test with occurrence of events (mortality and need for invasive/non-invasive ventilation) as reference standards irrespective of the study design employed, type of participants and severity of the condition. We conducted a systematic search for all studies reporting the predictive accuracy of DECAF scores in the databases of PubMed Central, Scopus, Medline, Embase, and Cochrane from inception until September 2020. We have used the quality assessment of diagnostic accuracy studies-2 (QUADAS-2) tool to evaluate the risk of bias. We used the STATA software "midas" package to perform the meta-analysis. We included 21 studies with 6429 patients. Most studies included were prospective. Most studies were conducted in the United Kingdom. Most studies used a cut-off value of the DECAF score ≥3 to predict the in-hospital or 30-day mortality and need for mechanical ventilation. All the studies used the occurrence of in-hospital/30-day mortality or patient undergoing mechanical ventilation as the reference standards. The pooled sensitivity and specificity of the DECAF score for predicting in-hospital mortality among patients with acute exacerbation of COPD were 74% (95% CI, 67%-79%) and 76% (95% CI, 68%-82%), respectively; and those for the 30-day mortality were 72% (95% CI, 59%-82%) and 83% (95% CI, 67%-93%), respectively. The overall quality of the studies in our meta-analysis was high. We found no significant publication biases as per Deek's test and funnel plot. This review has certain strengths. It is the first meta-analysis assessing the predictive utility of the DECAF score for in-hospital mortality among patients with AECOPD. Most studies included were of high quality according to the QUADAS-2 tool. Despite these strengths, our review had some limitations. We found a significant between-study variability in our analysis that can limit its value for inferring or interpreting the pooled findings. The predictive accuracy of the scoring system depends on many factors such as the ethnicity of the participants or patients, the timing of the scoring system assessment, and the AECOPD severity. We could not assess the influence of these variables in our study. Despite these shortcomings, our findings provide valuable information and important implications for the clinical practice involving patients with AECOPD. We found that the DECAF score can predict in-hospital and 30-day mortalities with satisfactory sensitivity and specificity.

Serum or plasma ferritin concentration as an index of iron deficiency and overload.

Serum or plasma ferritin concentration as an index of iron deficiency and overload.

Diagnostic Accuracy of 64-Slice Computed Tomography Angiography in Patients with Chest Pain vs. SPECT in the Assessment of Significant Coronary Artery Disease: A Systematic Review and Meta-analysis

Context: This systematic review and meta-analysis intended to investigate the diagnostic accuracy of computed tomography angiography (CTA) in comparison with single-photon emission computed tomography (SPECT) for the diagnosis of coronary artery disease (CAD) in chest pain patients with no history of cardiovascular diseases (CVDs).&#x0D; Methods: Invasive angiography was considered as the reference test with a stenosis threshold of ≥ 50%. Cochrane, Scopus, Science Direct, PubMed, and Embase databases were comprehensively searched from the time of inception of these databases to May 15, 2018. A manual search in Google Scholar, a reference review of the obtained studies, and a review of gray literature (including those presented in conferences and congresses) regarding diagnostic performances of CTA and SPECT techniques were performed independently by two researchers. A meta-analysis was performed to determine pooling estimates of sensitivity, specificity, diagnostic odds ratio, and positive as well as negative likelihood ratios in CTA and SPECT tests. According to the 2 × 2 contingency table of each study, at 0.95 confidence interval, the diagnostic accuracy of CTA and SPECT was meta-analyzed by pooling estimates of sensitivity, specificity, diagnostic odds ratio (DOR), and positive and negative likelihood ratios based on DerSimonian-Laird’s random-effects model. Heterogeneity was assessed by calculating I2. Analyses were performed using MetaDiSc version 1.4 and Stata version 11. The qualities of the selected studies were assessed independently by two researchers according to the quality assessment of diagnostic accuracy studies (QUADAS) questionnaire. Sensitivity analyses were performed by the Jackknife method. Publication bias was evaluated by Deeks’ funnel plot.&#x0D; Results: Fourteen studies related to CTA (1206 individuals) and 15 related to SPECT (1638 individuals) were eligible for meta-analysis. The pooled sensitivity and the specificity of CTA for CAD diagnosis were 91% (95% CI, 88% - 94%) and 87% (95% CI, 84% - 98%), respectively. The pooled positive and negative likelihood ratios, the diagnostic odds ratio, and the area under the ROC curve for CTA were 7.93 (95% CI, 5.11 - 12.29), 0.1 (95% CI, 0.06 - 0.17), 95.71 (95% CI, 59.81 - 153.15), and 0.96, respectively. The pooled sensitivity and the specificity of SPECT for CAD diagnosis were 81% (95% CI, 79% - 83%) and 74% (95% CI, 71% - 78%), respectively. The pooled positive and negative likelihood ratios, the diagnostic odds ratio, and the area under the ROC curve for SPECT were 3.03 (95% CI, 2.34 - 3.91), 0.25 (95% CI, 0.21 - 0.30), 13.56 (95% CI, 10.60 - 12.34), and 0.86, respectively. According to the sensitivity analyses, the removal of any single study at a time did not change the effect size of the remaining studies. We observed symmetry in the Deeks’ funnel plot, indicating that there was ignorable publication bias for CTA and SPECT studies.&#x0D; Conclusions: This study demonstrated that the diagnostic accuracies of CTA and SPECT tests lie in the ‘excellent’ and the ‘very good’ ranges, respectively. CTA is stronger evidence, than SPECT, to rule out CVDs in patients with low and intermediate risks of CAD with no history of cardiovascular diseases.

The Accuracy of 16S rRNA Polymerase Chain Reaction for the Diagnosis of Neonatal Sepsis: A Meta-Analysis.

Objective To determine the accuracy of 16S rRNA polymerase chain reaction (PCR) for the diagnosis of neonatal sepsis through a systematic review and meta-analysis. Methods Studies involving 16S rRNA PCR tests for the diagnosis of neonatal sepsis were searched in the PubMed, Medline, Embase, and Cochrane Library databases. The methodological quality of the identified studies was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2), and the sensitivity, the specificity, the positive likelihood ratio (PLR), the negative likelihood ratio (NLR), the diagnostic odds ratio (DOR), and the area under the curve (AUC) of operator characteristic (SROC) curves were determined. Heterogeneity between studies was analyzed by metaregression. Stata 14.0 and Meta-disc 1.4 software were used for the analyses. Results This meta-analysis included 19 related studies. The analysis found a sensitivity of 0.98 (95% CI: 0.85-1), specificity of 0.94 (95% CI: 0.87-0.97), PLR of 16.0 (95% CI: 7.6-33.9), NLR of 0.02 (95% CI: 0.00-0.18), DOR of 674 (95% CI: 89-5100), and AUC of 0.99 (95% CI: 0.97-0.99). Metaregression analysis identified Asian countries, arterial blood in blood samples, and sample size > 200 as the main sources of heterogeneity. This meta-analysis did not uncover publication bias. Sensitivity analysis showed that the study was robust. Fagan's nomogram results showed clinical usability. Conclusions The results from this meta-analysis indicate that 16S rRNA PCR testing is effective for the rapid diagnosis of neonatal sepsis.

Diagnostic Accuracy of Ultrasonography Method of Graf in the detection of Developmental Dysplasia of the Hip: A Meta-Analysis and Systematic Review.

The present study aimed to perform a meta-analysis on the performance of Graf's ultrasonography method in the detection of developmental dysplasia of the hip (DDH). A query was conducted on electronic bibliographic databases until the end of October 2020. The inclusion criteria entailed: 1. the use of Graf method in less than 12 weeks of age, 2. the use of follow-up as reference test, and 3. provision of crude data. Pooled diagnostic performance measures were calculated. Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) checklist was utilized to assess the quality of the included studies. The hierarchical summary receiver-operating characteristic (HROC) curves were also drawn. Six articles (including seven populations, 11,012 patients) were considered eligible. The pooled sensitivity and specificity were obtained at 93% (95% CI: 0.57-0.99) and 97% (95% CI:0.86-0.99), respectively (area under curve= 0.99). The pooled positive and negative likelihood ratio, as well as diagnostic odds ratio, was reported as 28.4, 0.07, and 396, respectively. As evidenced by the obtained results, Graf's method is a useful ultrasonography technique with acceptable accuracy for screening DDH in neonates. However, there are uncertainties about the best population and age for screening. Furthermore, more attention should be paid to the proper training of this method to reduce the number of operator errors.

The value of glycosylated hemoglobin in the diagnosis of diabetic retinopathy:\xa0a systematic review and Meta-analysis

ObjectiveGlycosylated hemoglobin (HbA1c) has obvious clinical value in the diagnosis of diabetes, but the conclusions on the diagnostic value of diabetic retinopathy (DR) are not consistent. This study aims to comprehensively evaluate the accuracy of glycosylated hemoglobin in the diagnosis of diabetic retinopathy through the meta-analysis of diagnostic tests.MethodsCochrane Library, Embase, PubMed, Web of Science, China National Knowledge Infrastructure (CNKI), China Wanfang Database, Chinese Biomedical Literature Database (CBM) were searched until November, 2020. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was used to assess the quality of the included studies. The pooled sensitivity, specificity, positive likelihood ratio (+LR), negative likelihood ratio (-LR), diagnostic odds ratio (DOR) and areas under the receiver operating characteristic (ROC) curve were calculated by Stata 15.0 software.ResultsAfter screening, 18 high-quality papers were included. The results of meta-analysis showed that the combined DOR = 18.19 (95% CI: 10.99–30.11), the sensitivity= 0.81 (95% CI): 0.75 ~ 0.87), specificity = 0.81 (95%CI: 0.72 ~ 0.87), +LR = 4.2 (95%CI: 2.95 ~ 6.00), −LR = 0.23 (95%CI: 0.17 ~ 0.31), and the area under the Summary ROC curve was 0.88 (95%CI: 0.85 ~ 0.90).ConclusionThe overall accuracy of HbA1cC forin diagnosing diabetic retinopathy is good. As it is more stable than blood sugar and is not affected by meals, it may be a suitable indicator for diabetic retinopathy.

Diagnostic Accuracy of MRI for Differentiation of Benign and Malignant Pancreatic Cystic Lesions Compared to CT and Endoscopic Ultrasound: Systematic Review and Meta-analysis.

Differentiation of benign and malignant pancreatic cystic lesions on MRI, computed tomography (CT), and endoscopic ultrasound (EUS) is critical for determining management. To perform a systematic review evaluating the diagnostic accuracy of MRI for diagnosing malignant pancreatic cystic lesions, and to compare the accuracy of MRI to CT and EUS. Systematic review and meta-analysis. MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, Web of Science, and Scopus were searched until February 2020 for studies reporting MRI accuracy for assessing pancreatic cystic lesions. 1.5T or 3.0T. Methodologic and outcome data were extracted by two reviewers (AU and MA, 2 years of experience each). All studies of pancreatic cystic lesions on MRI were identified. Studies with incomplete MRI technique were excluded. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 tool. Sensitivity/specificity was pooled using bivariate random-effects meta-analysis with 95% confidence intervals (95%CI). Pairwise-comparison of MRI to CT and EUS was performed. The impact of gadolinium-based contrast agents, mucinous lesions, and risk of bias were explored using meta-regression. MRI pooled sensitivity was 76% (95%CI 67% to 84%) and specificity was 80% (95%CI 74% to 85%) for distinguishing benign and malignant lesions. MRI and CT had similar sensitivity (P=0.822) and specificity (P=0.096), but MRI was more specific than EUS (80% vs. 75%, P < 0.05). Studies including only contrast-enhanced MRI were more sensitive than those including unenhanced exams (P < 0.05). MRI sensitivity and specificity did not differ for mucinous lesions (P=0.537 and P=0.384, respectively) or for studies at risk of bias (P=0.789 and P=0.791, respectively). MRI and CT demonstrate comparable accuracy for diagnosing malignant pancreatic cystic lesions. EUS is less specific than MRI, which suggests that, in some cases, management should be guided by MRI findings rather than EUS. 3 TECHNICAL EFFICACY STAGE: 2.

Interleukin-27 as a Diagnostic Biomarker for Patients with Sepsis: A Meta-Analysis.

Background The present study was aimed to investigate the value of blood interleukin-27 (IL-27) as a diagnostic biomarker of sepsis. Methods We searched PubMed, EMBASE, the Cochrane Library, and the reference lists of relevant articles. All studies published up to October 21, 2020, which evaluated the accuracy of IL-27 levels for the diagnosis of sepsis were included. All the selected papers were assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). We used a bivariate random effects model to estimate sensitivity, specificity, diagnostic odds ratios (DOR), and a summary receiver operating characteristic curve (SROC). Deeks' funnel plot was used to illustrate the potential presence of publication bias. Results This meta-analysis included seven articles. The pooled sensitivity, specificity, and DOR were 0.85 (95% CI, 0.72-0.93), 0.72 (95% CI, 0.42-0.90), and 15 (95% CI, 3-72), respectively. The area under the summary receiver operating characteristic curve was 0.88 (95% CI, 0.84-0.90). The pooled I2 statistic was 96.05 for the sensitivity and 96.65 for the specificity in the heterogeneity analysis. Deeks' funnel plot indicated no publication bias in this meta-analysis (P = 0.07). Conclusions The present results showed that IL-27 is a reliable diagnostic biomarker of sepsis, but it should be investigated in combination with other clinical tests and results.

Accuracy of quantitative diffusion-weighted imaging for differentiating benign and malignant pancreatic lesions: a systematic review and meta-analysis.

A variety of imaging techniques can be used to evaluate diffusion characteristics to differentiate malignant and benign pancreatic lesions. The diagnostic performance of diffusion parameters has not been systematic assessed. We aimed to investigate the diagnostic efficacy of quantitative diffusion-weighted imaging (DWI) for pancreatic lesions. A literature search was conducted using the PubMed, Embase, and Cochrane Library databases for studies from inception to March 30, 2020, which involves the quantitative diagnostic performance of diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) in the pancreas. Studies were reviewed according to inclusion and exclusion criteria. The quality of articles was evaluated by the Quality Assessment of Diagnostic Accuracy Studies-2 (QUATAS-2). A bivariate random-effects model was used to evaluate pooled sensitivities and specificities. Univariable meta-regression analysis was used to test the effects of factors that contributed to the heterogeneity. A total of 31 studies involving 1558 patients were ultimately eligible for data extraction. The lowest heterogeneity was found in specificity of perfusion fraction (f) with the I2 value was 17.97% and Cochran p value was 0.28. However, high heterogeneities were found for the other parameters (all I2 > 50%). There was no publication bias found in funnel plot (p = 0.30) for the apparent diffusion coefficient (ADC) parameter. The pooled sensitivities for ADC, f, pure diffusion coefficient (D), and pseudo diffusivity coefficient (D*) were 83%, 81%, 76%, and 84%, respectively. The pooled specificities for ADC, f, D, and D* were 87%, 83%, 69%, and 81% respectively. The areas under the curves for ADC, f, D, and D* were 0.92, 0.87, 0.79, and 0.87 respectively. Quantitative DWI and IVIM have a good diagnostic performance for differentiating malignant and benign pancreatic lesions. • IVIM has high sensitivity and specificity (84% and 83%, respectively) for differential diagnosis of pancreatic lesions, which is comparable to that of the ADC (83% and 87%, respectively). • The ADC has an excellent diagnostic performance for differentiating malignant from benign IPMNs (sensitivity, 0.83; specificity, 0.92); the f has the best diagnostic performance for differentiating pancreatic carcinoma from PNET (sensitivity, 0.85; specificity, 0.85). • For the ADC, using a maximal b value < 800 s/mm2 has a higher diagnostic accuracy than ≥ 800 s/mm2; performing in a high field strength (3.0 T) system has a higher diagnostic accuracy than a low field strength (1.5 T) for pancreatic lesions.