Systematic review with meta-analysis of the accuracy of diagnostic tests for COVID-19.
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ABSTRACT: Objective
To collate the evidence on the accuracy parameters of all available diagnostic methods for detecting SARS-CoV-2.Methods
A systematic review with meta-analysis was performed. Searches were conducted in Pubmed and Scopus (April 2020). Studies reporting data on sensitivity or specificity of diagnostic tests for COVID-19 using any human biological sample were included.Results
Sixteen studies were evaluated. Meta-analysis showed that computed tomography has high sensitivity (91.9% [89.8%-93.7%]), but low specificity (25.1% [21.0%-29.5%]). The combination of IgM and IgG antibodies demonstrated promising results for both parameters (84.5% [82.2%-86.6%]; 91.6% [86.0%-95.4%], respectively). For RT-PCR tests, rectal stools/swab, urine, and plasma were less sensitive while sputum (97.2% [90.3%-99.7%]) presented higher sensitivity for detecting the virus.Conclusions
RT-PCR remains the gold standard for the diagnosis of COVID-19 in sputum samples. However, the combination of different diagnostic tests is highly recommended to achieve adequate sensitivity and specificity.
SUBMITTER: Boger B
PROVIDER: S-EPMC7350782 | biostudies-literature | 2021 Jan
REPOSITORIES: biostudies-literature
Publications
Systematic review with meta-analysis of the accuracy of diagnostic tests for COVID-19.
Böger Beatriz B Fachi Mariana M MM Vilhena Raquel O RO Cobre Alexandre F AF Tonin Fernanda S FS Pontarolo Roberto R
American journal of infection control 20200710 1
<h4>Objective</h4>To collate the evidence on the accuracy parameters of all available diagnostic methods for detecting SARS-CoV-2.<h4>Methods</h4>A systematic review with meta-analysis was performed. Searches were conducted in Pubmed and Scopus (April 2020). Studies reporting data on sensitivity or specificity of diagnostic tests for COVID-19 using any human biological sample were included.<h4>Results</h4>Sixteen studies were evaluated. Meta-analysis showed that computed tomography has high sens ...[more]
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Project description:ObjectiveTo determine the diagnostic accuracy of serological tests for coronavirus disease-2019 (covid-19).DesignSystematic review and meta-analysis.Data sourcesMedline, bioRxiv, and medRxiv from 1 January to 30 April 2020, using subject headings or subheadings combined with text words for the concepts of covid-19 and serological tests for covid-19.Eligibility criteria and data analysisEligible studies measured sensitivity or specificity, or both of a covid-19 serological test compared with a reference standard of viral culture or reverse transcriptase polymerase chain reaction. Studies were excluded with fewer than five participants or samples. Risk of bias was assessed using quality assessment of diagnostic accuracy studies 2 (QUADAS-2). Pooled sensitivity and specificity were estimated using random effects bivariate meta-analyses.Main outcome measuresThe primary outcome was overall sensitivity and specificity, stratified by method of serological testing (enzyme linked immunosorbent assays (ELISAs), lateral flow immunoassays (LFIAs), or chemiluminescent immunoassays (CLIAs)) and immunoglobulin class (IgG, IgM, or both). Secondary outcomes were stratum specific sensitivity and specificity within subgroups defined by study or participant characteristics, including time since symptom onset.Results5016 references were identified and 40 studies included. 49 risk of bias assessments were carried out (one for each population and method evaluated). High risk of patient selection bias was found in 98% (48/49) of assessments and high or unclear risk of bias from performance or interpretation of the serological test in 73% (36/49). Only 10% (4/40) of studies included outpatients. Only two studies evaluated tests at the point of care. For each method of testing, pooled sensitivity and specificity were not associated with the immunoglobulin class measured. The pooled sensitivity of ELISAs measuring IgG or IgM was 84.3% (95% confidence interval 75.6% to 90.9%), of LFIAs was 66.0% (49.3% to 79.3%), and of CLIAs was 97.8% (46.2% to 100%). In all analyses, pooled sensitivity was lower for LFIAs, the potential point-of-care method. Pooled specificities ranged from 96.6% to 99.7%. Of the samples used for estimating specificity, 83% (10 465/12 547) were from populations tested before the epidemic or not suspected of having covid-19. Among LFIAs, pooled sensitivity of commercial kits (65.0%, 49.0% to 78.2%) was lower than that of non-commercial tests (88.2%, 83.6% to 91.3%). Heterogeneity was seen in all analyses. Sensitivity was higher at least three weeks after symptom onset (ranging from 69.9% to 98.9%) compared with within the first week (from 13.4% to 50.3%).ConclusionHigher quality clinical studies assessing the diagnostic accuracy of serological tests for covid-19 are urgently needed. Currently, available evidence does not support the continued use of existing point-of-care serological tests.Study registrationPROSPERO CRD42020179452.
| S-EPMC7327913 | biostudies-literature
Project description:ObjectiveTo determine the diagnostic accuracy of serological tests for coronavirus disease-2019 (COVID-19).MethodsPubMed, Embase and the Cochrane Library were searched from January 1 2020 to September 2 2022. We included studies that measured the sensitivity, specificity or both qualities of a COVID-19 serological test and a reference standard of a viral culture or reverse transcriptase polymerase chain reaction (RT-PCR). The risk of bias was assessed by using quality assessment of diagnostic accuracy studies 2 (QUADAS-2). The primary outcomes included overall sensitivity and specificity, as stratified by the methods of serological testing [enzyme-linked immunosorbent assays (ELISAs), lateral flow immunoassays (LFIAs) or chemiluminescent immunoassays (CLIAs)] and immunoglobulin classes (IgG, IgM, or both). Secondary outcomes were stratum-specific sensitivity and specificity within the subgroups, as defined by study or participant characteristics, which included the time from the onset of symptoms, testing via commercial kits or an in-house assay, antigen target, clinical setting, serological kit as the index test and the type of specimen for the RT-PCR reference test.ResultsEight thousand seven hundred and eighty-five references were identified and 169 studies included. Overall, we judged the risk of bias to be high in 47.9 % (81/169) of the studies, and a low risk of applicability concerns was found in 100% (169/169) of the studies. For each method of testing, the pooled sensitivity of the ELISAs ranged from 81 to 82%, with sensitivities ranging from 69 to 70% for the LFIAs and 77% to 79% for the CLIAs. Among the evaluated tests, IgG (80-81%)-based tests exhibited better sensitivities than IgM-based tests (66-68%). IgG/IgM-based CLIA had the highest sensitivity [87% (86-88%)]. All of the tests displayed high specificity (97-98%). Heterogeneity was observed in all of the analyses. The detection of nucleocapsid protein (77-80%) as the antigen target was found to offer higher sensitivity results than surface protein detection (66-68%). Sensitivity was higher in the in-house assays (78-79%) than in the commercial kits (47-48%).ConclusionAmong the evaluated tests, ELISA and CLIA tests performed better in terms of sensitivity than did the LFIA. IgG-based tests had higher sensitivity than IgM-based tests, and combined IgG/IgM test-based CLIA tests had the best overall diagnostic test accuracy. The type of sample, serological kit and timing of use of the specific tests were associated with the diagnostic accuracy. Due to the limitations of the serological tests, other techniques should be quickly approved to provide guidance for the correct diagnosis of COVID-19.
| S-EPMC9800917 | biostudies-literature
Project description:BackgroundHaving a penicillin allergy label associates with a higher risk for antibiotic resistance and increased health care use.ObjectiveWe sought to assess the accuracy of skin tests and specific IgE quantification in the diagnostic evaluation of patients reporting a penicillin/β-lactam allergy.MethodsWe performed a systematic review and diagnostic accuracy meta-analysis, searching on MEDLINE, Scopus, and Web of Science. We included studies conducted in patients reporting a penicillin allergy and in whom skin tests and/or specific IgE quantification were performed and compared with drug challenge results. We quantitatively assessed the accuracy of diagnostic tests with bivariate random-effects meta-analyses. Meta-regression and subgroup analyses were performed to explore causes of heterogeneity. Studies' quality was evaluated using QUADAS-2 criteria.ResultsWe included 105 primary studies, assessing 31,761 participants. Twenty-seven studies were assessed by bivariate meta-analysis. Skin tests had a summary sensitivity of 30.7% (95% CI, 18.9%-45.9%) and a specificity of 96.8% (95% CI, 94.2%-98.3%), with a partial area under the summary receiver-operating characteristic curve of 0.686 (I2 = 38.2%). Similar results were observed for subanalyses restricted to patients reporting nonimmediate maculopapular exanthema or urticaria/angioedema. Specific IgE had a summary sensitivity of 19.3% (95% CI, 12.0%-29.4%) and a specificity of 97.4% (95% CI, 95.2%-98.6%), with a partial area under the summary receiver-operating characteristic curve of 0.420 (I2 = 8.5%). Projected predictive values mainly reflect the low frequency of true penicillin allergy.ConclusionsSkin tests and specific IgE quantification appear to have low sensitivity and high specificity. Because current evidence is insufficient for assessing the role of these tests in stratifying patients for delabeling, we identified key requirements needed for future studies.
| S-EPMC8019189 | biostudies-literature
Project description:BackgroundThe early detection of coronavirus disease (COVID-19) infection to improve disease management becomes the greatest challenge. Despite the high sensitivity of RT-PCR, not only it was reported that 20-67% of infected patients had false-negative results. Rapid diagnostic tests (RDTs) are widely used as a point-of-care test for SARS-CoV-2 detection in pharyngeal and blood specimens. It's more appealing since it's less time-consuming, doesn't seem to be as expensive, and doesn't need any specific training, but the poor sensitivity is the major limitation. Several reports indicated the rapid test of blood and pharyngeal samples has the same sensitivity as the RT-PCR, but some reports have lower sensitivity, especially in asymptomatic patients.MethodsIn the present survey, we investigate the eligible studies for the sensitivity and specificity of rapid tests and explore the factors that influence the result to help better diagnose COVID-19 infection. 20 studies met the inclusion criteria which imposed 33 different tests.ResultsOur findings showed the type of sample, the type of assay, the time of sampling, and the load of virus influence on the sensitivity of RDTs.ConclusionThis research extends our knowledge of how to improve the sensitivity of RDTs to better diagnose the infected patients to address the controlling COVID-19 pandemic.
| S-EPMC9005339 | biostudies-literature
Project description:Antigen detection rapid diagnostic tests (Ag-RDTs) used for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid protein are inexpensive, faster and easy to use alternative of Nucleic Acid Amplification Test (NAAT) for diagnosis of Coronavirus disease 2019 (COVID-19). In this systematic review and meta-analysis, we assessed the diagnostic accuracy of Ag-RDTs in low and middle-income countries (LMICs). We included studies that evaluated the diagnostic accuracy of Ag-RDTs (sensitivity and specificity) against reverse transcription-polymerase chain reaction (RT-PCR) as a reference standard. The study population comprised of people living in LMICs irrespective of age and gender, who had undergone testing for COVID-19. We included peer reviewed prospective or retrospective cohort studies, cross-sectional studies, case control studies, randomized clinical trials (RCTs) as well as non-randomized experimental studies which addressed the review question. A systematic search was conducted in PubMed, CINAHL, Embase, Scopus, and Google Scholar to identify studies published between 1 January, 2020 and 15 August, 2021. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 tool was used to assess the methodological quality of studies. The analysis was done using Review Manager 5.4 and R software 4.0.2. From the total of 12 diagnostic accuracy studies with 4,817 study participants, pooled sensitivity and specificity were 78.2% and 99.5% respectively. Sensitivity was marginally higher in subgroup analysis based on studies with low risk of bias and applicability concerns (78.9%) and studies using SD Biosensor Ag-RDT (79.4%). However, an inverse relation between cycle threshold (Ct) and sensitivity of Ag-RDT was not seen. The review demonstrated pooled sensitivity value approaching the minimum performance requirement for diagnosis of COVID-19 by WHO with specificity value meeting the specified requirement. Ag-RDTs, therefore have the potential to be used as a screening tool for SARS-CoV-2 detection in low resource settings where RT-PCR might not be readily accessible. However, false negative results need to be interpreted with caution.
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Project description:BackgroundThe global COVID-19 pandemic has led to extensive development in many fields, including the diagnosis of COVID-19 infection by mass spectrometry. The aim of this systematic review and meta-analysis was to assess the accuracy of mass spectrometry diagnostic tests developed so far, across a wide range of biological matrices, and additionally to assess risks of bias and applicability in studies published to date.Method23 retrospective observational cohort studies were included in the systematic review using the PRISMA-DTA framework, with a total of 2858 COVID-19 positive participants and 2544 controls. Risks of bias and applicability were assessed via a QUADAS-2 questionnaire. A meta-analysis was also performed focusing on sensitivity, specificity, diagnostic accuracy and Youden's Index, in addition to assessing heterogeneity.FindingsSensitivity averaged 0.87 in the studies reviewed herein (interquartile range 0.81-0.96) and specificity 0.88 (interquartile range 0.82-0.98), with an area under the receiver operating characteristic summary curve of 0.93. By subgroup, the best diagnostic results were achieved by viral proteomic analyses of nasopharyngeal swabs and metabolomic analyses of plasma and serum. The performance of other sampling matrices (breath, sebum, saliva) was less good, indicating that these protocols are currently insufficiently mature for clinical application.ConclusionsThis systematic review and meta-analysis demonstrates the potential for mass spectrometry and 'omics in achieving accurate test results for COVID-19 diagnosis, but also highlights the need for further work to optimize and harmonize practice across laboratories before these methods can be translated to clinical applications.
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Project description:To perform a meta-analysis to compare the diagnostic test accuracy (DTA) of deep learning (DL) in detecting coronavirus disease 2019 (COVID-19), and to investigate how network architecture and type of datasets affect DL performance. We searched PubMed, Web of Science and Inspec from January 1, 2020, to December 3, 2020, for retrospective and prospective studies on deep learning detection with at least reported sensitivity and specificity. Pooled DTA was obtained using random-effect models. Sub-group analysis between studies was also carried out for data source and network architectures. The pooled sensitivity and specificity were 91% (95% confidence interval [CI]: 88%, 93%; I2 = 69%) and 92% (95% CI: 88%, 94%; I2 = 88%), respectively for 19 studies. The pooled AUC and diagnostic odds ratio (DOR) were 0.95 (95% CI: 0.88, 0.92) and 112.5 (95% CI: 57.7, 219.3; I2 = 90%) respectively. The overall accuracy, recall, F1-score, LR+ and LR- are 89.5%, 89.5%, 89.7%, 23.13 and 0.13. Sub-group analysis shows that the sensitivity and DOR significantly vary with the type of network architectures and sources of data with low heterogeneity are (I2 = 0%) and (I2 = 18%) for ResNet architecture and single-source datasets, respectively. The diagnosis of COVID-19 via deep learning has achieved incredible performance, and the source of datasets, as well as network architectures, strongly affect DL performance.
| S-EPMC8445811 | biostudies-literature
Project description:Objective:To systematically evaluate the diagnostic accuracy of monofilament tests for detecting diabetic peripheral neuropathy. Methods:We searched EMBASE (OvidSP), MEDLINE (OvidSP), the Cochrane Library, and Web of Science to identify diagnostic accuracy trials of monofilament tests for detecting diabetic peripheral neuropathy. We used a hierarchical summary receiver operating characteristics (HSROC) model to conduct the meta-analysis of diagnostic accuracy of monofilament tests for detecting diabetic peripheral neuropathy. Results:A total of 19 comparative trials met the inclusion criteria and were part of the qualitative synthesis. Eight trials using nerve conduction studies as the reference standard were selected for the meta-analysis. The pooled sensitivity and specificity of monofilament tests for detecting diabetic peripheral neuropathy were 0.53 (95% confidence interval (CI) 0.32 to 0.74) and 0.88 (95% CI 0.78 to 0.94), respectively. The pooled positive likelihood ratio and negative likelihood ratio were 4.56 (95% CI 2.93 to 7.10) and 0.53 (95% CI 0.35 to 0.81), respectively. Conclusions:Our review indicated that monofilament tests had limited sensitivity for screening diabetic peripheral neuropathy. The clinical use of the monofilament test in the evaluation of diabetic peripheral neuropathy cannot be encouraged based on currently available evidence.
| S-EPMC5651135 | biostudies-literature
Project description:AimThis systematic review aimed to ascertain the diagnostic accuracy (sensitivity and specificity) of screening tests for early detection of type 2 diabetes and prediabetes in previously undiagnosed adults.MethodsThis systematic review included published studies that included one or more index tests (random and fasting tests, HbA1c) for glucose detection, with 75-gram Oral Glucose Tolerance Test (or 2-hour post load glucose) as a reference standard (PROSPERO ID CRD42018102477). Seven databases were searched electronically (from their inception up to March 9, 2020) accompanied with bibliographic and website searches. Records were manually screened and full text were selected based on inclusion and exclusion criteria. Subsequently, data extraction was done using standardized form and quality assessment of studies using QUADAS-2 tool. Meta-analysis was done using bivariate model using Stata 14.0. Optimal cut offs in terms of sensitivity and specificity for the tests were analysed using R software.ResultsOf 7,151 records assessed by title and abstract, a total of 37 peer reviewed articles were included in this systematic review. The pooled sensitivity, specificity, positive (LR+) and negative likelihood ratio (LR-) for diagnosing diabetes with HbA1c (6.5%; venous sample; n = 17 studies) were 50% (95% CI: 42-59%), 97.3% (95% CI: 95.3-98.4), 18.32 (95% CI: 11.06-30.53) and 0.51 (95% CI: 0.43-0.60), respectively. However, the optimal cut-off for diagnosing diabetes in previously undiagnosed adults with HbA1c was estimated as 6.03% with pooled sensitivity of 73.9% (95% CI: 68-79.1%) and specificity of 87.2% (95% CI: 82-91%). The optimal cut-off for Fasting Plasma Glucose (FPG) was estimated as 104 milligram/dL (mg/dL) with a sensitivity of 82.3% (95% CI: 74.6-88.1%) and specificity of 89.4% (95% CI: 85.2-92.5%).ConclusionOur findings suggest that at present recommended threshold of 6.5%, HbA1c is more specific and less sensitive in diagnosing the newly detected diabetes in undiagnosed population from community settings. Lowering of thresholds for HbA1c and FPG to 6.03% and 104 mg/dL for early detection in previously undiagnosed persons for screening purposes may be considered.
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Project description:The present systematic review and meta-analysis about the accuracy of diagnostic tests aim to describe the findings of literature over the last thirty years for the diagnosis of Chagas disease (CD). This work aimed to determine the accuracy of diagnostic techniques for CD in the disease's acute and chronic phases. The PubMed database was searched for studies published between 1990 and 2021 on CD diagnostics. Fifty-six published studies that met the criteria were analyzed and included in the meta-analysis, evaluating diagnostic accuracy through sensitivity and specificity. For Enzyme-Linked Immunosorbent Assay (ELISA), Fluorescent Antibody Technique (IFAT), Hemagglutination Test (HmT), Polymerase Chain Reaction (PCR), and Real-Time Polymerase Chain Reaction (qPCR) diagnosis methods, the sensitivity had a median of 99.0%, 78.0%, 75.0%, 76.0%, and 94.0%, respectively; while specificity presented a median of 99.0%, 99.0%, 99.0%, 98.0%, and 98.0%, respectively. This meta-analysis showed that ELISA and qPCR techniques had a higher performance compared to other methods of diagnosing CD in the chronic and acute phases, respectively. It was concluded utilizing the Area Under the Curve restricted to the false positive rates (AUCFPR), that the ELISA diagnostic test presents the highest performance in diagnosing acute and chronic CD, compared to serological and molecular tests. Future studies focusing on new CD diagnostics approaches should be targeted.
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