Background
Some people with SARS‐CoV‐2 infection remain asymptomatic, whilst in others the infection can cause mild to moderate COVID‐19 disease and COVID‐19 pneumonia, leading some patients to ...require intensive care support and, in some cases, to death, especially in older adults. Symptoms such as fever or cough, and signs such as oxygen saturation or lung auscultation findings, are the first and most readily available diagnostic information. Such information could be used to either rule out COVID‐19 disease, or select patients for further diagnostic testing.
Objectives
To assess the diagnostic accuracy of signs and symptoms to determine if a person presenting in primary care or to hospital outpatient settings, such as the emergency department or dedicated COVID‐19 clinics, has COVID‐19 disease or COVID‐19 pneumonia.
Search methods
On 27 April 2020, we undertook electronic searches in the Cochrane COVID‐19 Study Register and the University of Bern living search database, which is updated daily with published articles from PubMed and Embase and with preprints from medRxiv and bioRxiv. In addition, we checked repositories of COVID‐19 publications. We did not apply any language restrictions.
Selection criteria
Studies were eligible if they included patients with suspected COVID‐19 disease, or if they recruited known cases with COVID‐19 disease and controls without COVID‐19. Studies were eligible when they recruited patients presenting to primary care or hospital outpatient settings. Studies including patients who contracted SARS‐CoV‐2 infection while admitted to hospital were not eligible. The minimum eligible sample size of studies was 10 participants. All signs and symptoms were eligible for this review, including individual signs and symptoms or combinations. We accepted a range of reference standards including reverse transcription polymerase chain reaction (RT‐PCR), clinical expertise, imaging, serology tests and World Health Organization (WHO) or other definitions of COVID‐19.
Data collection and analysis
Pairs of review authors independently selected all studies, at both title and stage and full‐text stage. They resolved any disagreements by discussion with a third review author. Two review authors independently extracted data and resolved disagreements by discussion with a third review author. Two review authors independently assessed risk of bias using the QUADAS‐2 checklist. Analyses were descriptive, presenting sensitivity and specificity in paired forest plots, in ROC (receiver operating characteristic) space and in dumbbell plots. We did not attempt meta‐analysis due to the small number of studies, heterogeneity across studies and the high risk of bias.
Main results
We identified 16 studies including 7706 participants in total. Prevalence of COVID‐19 disease varied from 5% to 38% with a median of 17%. There were no studies from primary care settings, although we did find seven studies in outpatient clinics (2172 participants), and four studies in the emergency department (1401 participants). We found data on 27 signs and symptoms, which fall into four different categories: systemic, respiratory, gastrointestinal and cardiovascular. No studies assessed combinations of different signs and symptoms and results were highly variable across studies. Most had very low sensitivity and high specificity; only six symptoms had a sensitivity of at least 50% in at least one study: cough, sore throat, fever, myalgia or arthralgia, fatigue, and headache. Of these, fever, myalgia or arthralgia, fatigue, and headache could be considered red flags (defined as having a positive likelihood ratio of at least 5) for COVID‐19 as their specificity was above 90%, meaning that they substantially increase the likelihood of COVID‐19 disease when present.
Seven studies carried a high risk of bias for selection of participants because inclusion in the studies depended on the applicable testing and referral protocols, which included many of the signs and symptoms under study in this review. Five studies only included participants with pneumonia on imaging, suggesting that this is a highly selected population. In an additional four studies, we were unable to assess the risk for selection bias. These factors make it very difficult to determine the diagnostic properties of these signs and symptoms from the included studies.
We also had concerns about the applicability of these results, since most studies included participants who were already admitted to hospital or presenting to hospital settings. This makes these findings less applicable to people presenting to primary care, who may have less severe illness and a lower prevalence of COVID‐19 disease. None of the studies included any data on children, and only one focused specifically on older adults. We hope that future updates of this review will be able to provide more information about the diagnostic properties of signs and symptoms in different settings and age groups.
Authors' conclusions
The individual signs and symptoms included in this review appear to have very poor diagnostic properties, although this should be interpreted in the context of selection bias and heterogeneity between studies. Based on currently available data, neither absence nor presence of signs or symptoms are accurate enough to rule in or rule out disease. Prospective studies in an unselected population presenting to primary care or hospital outpatient settings, examining combinations of signs and symptoms to evaluate the syndromic presentation of COVID‐19 disease, are urgently needed. Results from such studies could inform subsequent management decisions such as self‐isolation or selecting patients for further diagnostic testing. We also need data on potentially more specific symptoms such as loss of sense of smell. Studies in older adults are especially important.
Background
Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) and the resulting COVID‐19 pandemic present important diagnostic challenges. Several diagnostic strategies are available to ...identify or rule out current infection, identify people in need of care escalation, or to test for past infection and immune response. Point‐of‐care antigen and molecular tests to detect current SARS‐CoV‐2 infection have the potential to allow earlier detection and isolation of confirmed cases compared to laboratory‐based diagnostic methods, with the aim of reducing household and community transmission.
Objectives
To assess the diagnostic accuracy of point‐of‐care antigen and molecular‐based tests to determine if a person presenting in the community or in primary or secondary care has current SARS‐CoV‐2 infection.
Search methods
On 25 May 2020 we undertook electronic searches in the Cochrane COVID‐19 Study Register and the COVID‐19 Living Evidence Database from the University of Bern, which is updated daily with published articles from PubMed and Embase and with preprints from medRxiv and bioRxiv. In addition, we checked repositories of COVID‐19 publications. We did not apply any language restrictions.
Selection criteria
We included studies of people with suspected current SARS‐CoV‐2 infection, known to have, or not to have SARS‐CoV‐2 infection, or where tests were used to screen for infection. We included test accuracy studies of any design that evaluated antigen or molecular tests suitable for a point‐of‐care setting (minimal equipment, sample preparation, and biosafety requirements, with results available within two hours of sample collection). We included all reference standards to define the presence or absence of SARS‐CoV‐2 (including reverse transcription polymerase chain reaction (RT‐PCR) tests and established clinical diagnostic criteria).
Data collection and analysis
Two review authors independently screened studies and resolved any disagreements by discussion with a third review author. One review author independently extracted study characteristics, which were checked by a second review author. Two review authors independently extracted 2x2 contingency table data and assessed risk of bias and applicability of the studies using the QUADAS‐2 tool. We present sensitivity and specificity, with 95% confidence intervals (CIs), for each test using paired forest plots. We pooled data using the bivariate hierarchical model separately for antigen and molecular‐based tests, with simplifications when few studies were available. We tabulated available data by test manufacturer.
Main results
We included 22 publications reporting on a total of 18 study cohorts with 3198 unique samples, of which 1775 had confirmed SARS‐CoV‐2 infection. Ten studies took place in North America, two in South America, four in Europe, one in China and one was conducted internationally. We identified data for eight commercial tests (four antigen and four molecular) and one in‐house antigen test. Five of the studies included were only available as preprints.
We did not find any studies at low risk of bias for all quality domains and had concerns about applicability of results across all studies. We judged patient selection to be at high risk of bias in 50% of the studies because of deliberate over‐sampling of samples with confirmed COVID‐19 infection and unclear in seven out of 18 studies because of poor reporting. Sixteen (89%) studies used only a single, negative RT‐PCR to confirm the absence of COVID‐19 infection, risking missing infection. There was a lack of information on blinding of index test (n = 11), and around participant exclusions from analyses (n = 10). We did not observe differences in methodological quality between antigen and molecular test evaluations.
Antigen tests
Sensitivity varied considerably across studies (from 0% to 94%): the average sensitivity was 56.2% (95% CI 29.5 to 79.8%) and average specificity was 99.5% (95% CI 98.1% to 99.9%; based on 8 evaluations in 5 studies on 943 samples). Data for individual antigen tests were limited with no more than two studies for any test.
Rapid molecular assays
Sensitivity showed less variation compared to antigen tests (from 68% to 100%), average sensitivity was 95.2% (95% CI 86.7% to 98.3%) and specificity 98.9% (95% CI 97.3% to 99.5%) based on 13 evaluations in 11 studies of on 2255 samples. Predicted values based on a hypothetical cohort of 1000 people with suspected COVID‐19 infection (with a prevalence of 10%) result in 105 positive test results including 10 false positives (positive predictive value 90%), and 895 negative results including 5 false negatives (negative predictive value 99%).
Individual tests
We calculated pooled results of individual tests for ID NOW (Abbott Laboratories) (5 evaluations) and Xpert Xpress (Cepheid Inc) (6 evaluations). Summary sensitivity for the Xpert Xpress assay (99.4%, 95% CI 98.0% to 99.8%) was 22.6 (95% CI 18.8 to 26.3) percentage points higher than that of ID NOW (76.8%, (95% CI 72.9% to 80.3%), whilst the specificity of Xpert Xpress (96.8%, 95% CI 90.6% to 99.0%) was marginally lower than ID NOW (99.6%, 95% CI 98.4% to 99.9%; a difference of −2.8% (95% CI −6.4 to 0.8))
Authors' conclusions
This review identifies early‐stage evaluations of point‐of‐care tests for detecting SARS‐CoV‐2 infection, largely based on remnant laboratory samples. The findings currently have limited applicability, as we are uncertain whether tests will perform in the same way in clinical practice, and according to symptoms of COVID‐19, duration of symptoms, or in asymptomatic people. Rapid tests have the potential to be used to inform triage of RT‐PCR use, allowing earlier detection of those testing positive, but the evidence currently is not strong enough to determine how useful they are in clinical practice.
Prospective and comparative evaluations of rapid tests for COVID‐19 infection in clinically relevant settings are urgently needed. Studies should recruit consecutive series of eligible participants, including both those presenting for testing due to symptoms and asymptomatic people who may have come into contact with confirmed cases. Studies should clearly describe symptomatic status and document time from symptom onset or time since exposure. Point‐of‐care tests must be conducted on samples according to manufacturer instructions for use and be conducted at the point of care. Any future research study report should conform to the Standards for Reporting of Diagnostic Accuracy (STARD) guideline.
Background
The clinical implications of SARS‐CoV‐2 infection are highly variable. Some people with SARS‐CoV‐2 infection remain asymptomatic, whilst the infection can cause mild to moderate COVID‐19 ...and COVID‐19 pneumonia in others. This can lead to some people requiring intensive care support and, in some cases, to death, especially in older adults. Symptoms such as fever, cough, or loss of smell or taste, and signs such as oxygen saturation are the first and most readily available diagnostic information. Such information could be used to either rule out COVID‐19, or select patients for further testing. This is an update of this review, the first version of which published in July 2020.
Objectives
To assess the diagnostic accuracy of signs and symptoms to determine if a person presenting in primary care or to hospital outpatient settings, such as the emergency department or dedicated COVID‐19 clinics, has COVID‐19.
Search methods
For this review iteration we undertook electronic searches up to 15 July 2020 in the Cochrane COVID‐19 Study Register and the University of Bern living search database. In addition, we checked repositories of COVID‐19 publications. We did not apply any language restrictions.
Selection criteria
Studies were eligible if they included patients with clinically suspected COVID‐19, or if they recruited known cases with COVID‐19 and controls without COVID‐19. Studies were eligible when they recruited patients presenting to primary care or hospital outpatient settings. Studies in hospitalised patients were only included if symptoms and signs were recorded on admission or at presentation. Studies including patients who contracted SARS‐CoV‐2 infection while admitted to hospital were not eligible. The minimum eligible sample size of studies was 10 participants. All signs and symptoms were eligible for this review, including individual signs and symptoms or combinations. We accepted a range of reference standards.
Data collection and analysis
Pairs of review authors independently selected all studies, at both title and stage and full‐text stage. They resolved any disagreements by discussion with a third review author. Two review authors independently extracted data and resolved disagreements by discussion with a third review author. Two review authors independently assessed risk of bias using the Quality Assessment tool for Diagnostic Accuracy Studies (QUADAS‐2) checklist. We presented sensitivity and specificity in paired forest plots, in receiver operating characteristic space and in dumbbell plots. We estimated summary parameters using a bivariate random‐effects meta‐analysis whenever five or more primary studies were available, and whenever heterogeneity across studies was deemed acceptable.
Main results
We identified 44 studies including 26,884 participants in total. Prevalence of COVID‐19 varied from 3% to 71% with a median of 21%. There were three studies from primary care settings (1824 participants), nine studies from outpatient testing centres (10,717 participants), 12 studies performed in hospital outpatient wards (5061 participants), seven studies in hospitalised patients (1048 participants), 10 studies in the emergency department (3173 participants), and three studies in which the setting was not specified (5061 participants). The studies did not clearly distinguish mild from severe COVID‐19, so we present the results for all disease severities together.
Fifteen studies had a high risk of bias for selection of participants because inclusion in the studies depended on the applicable testing and referral protocols, which included many of the signs and symptoms under study in this review. This may have especially influenced the sensitivity of those features used in referral protocols, such as fever and cough. Five studies only included participants with pneumonia on imaging, suggesting that this is a highly selected population. In an additional 12 studies, we were unable to assess the risk for selection bias. This makes it very difficult to judge the validity of the diagnostic accuracy of the signs and symptoms from these included studies.
The applicability of the results of this review update improved in comparison with the original review. A greater proportion of studies included participants who presented to outpatient settings, which is where the majority of clinical assessments for COVID‐19 take place. However, still none of the studies presented any data on children separately, and only one focused specifically on older adults.
We found data on 84 signs and symptoms. Results were highly variable across studies. Most had very low sensitivity and high specificity. Only cough (25 studies) and fever (7 studies) had a pooled sensitivity of at least 50% but specificities were moderate to low. Cough had a sensitivity of 67.4% (95% confidence interval (CI) 59.8% to 74.1%) and specificity of 35.0% (95% CI 28.7% to 41.9%). Fever had a sensitivity of 53.8% (95% CI 35.0% to 71.7%) and a specificity of 67.4% (95% CI 53.3% to 78.9%). The pooled positive likelihood ratio of cough was only 1.04 (95% CI 0.97 to 1.11) and that of fever 1.65 (95% CI 1.41 to 1.93).
Anosmia alone (11 studies), ageusia alone (6 studies), and anosmia or ageusia (6 studies) had sensitivities below 50% but specificities over 90%. Anosmia had a pooled sensitivity of 28.0% (95% CI 17.7% to 41.3%) and a specificity of 93.4% (95% CI 88.3% to 96.4%). Ageusia had a pooled sensitivity of 24.8% (95% CI 12.4% to 43.5%) and a specificity of 91.4% (95% CI 81.3% to 96.3%). Anosmia or ageusia had a pooled sensitivity of 41.0% (95% CI 27.0% to 56.6%) and a specificity of 90.5% (95% CI 81.2% to 95.4%). The pooled positive likelihood ratios of anosmia alone and anosmia or ageusia were 4.25 (95% CI 3.17 to 5.71) and 4.31 (95% CI 3.00 to 6.18) respectively, which is just below our arbitrary definition of a 'red flag', that is, a positive likelihood ratio of at least 5. The pooled positive likelihood ratio of ageusia alone was only 2.88 (95% CI 2.02 to 4.09).
Only two studies assessed combinations of different signs and symptoms, mostly combining fever and cough with other symptoms. These combinations had a specificity above 80%, but at the cost of very low sensitivity (< 30%).
Authors' conclusions
The majority of individual signs and symptoms included in this review appear to have very poor diagnostic accuracy, although this should be interpreted in the context of selection bias and heterogeneity between studies. Based on currently available data, neither absence nor presence of signs or symptoms are accurate enough to rule in or rule out COVID‐19. The presence of anosmia or ageusia may be useful as a red flag for COVID‐19. The presence of fever or cough, given their high sensitivities, may also be useful to identify people for further testing.
Prospective studies in an unselected population presenting to primary care or hospital outpatient settings, examining combinations of signs and symptoms to evaluate the syndromic presentation of COVID‐19, are still urgently needed. Results from such studies could inform subsequent management decisions.
Background
Accurate rapid diagnostic tests for SARS‐CoV‐2 infection would be a useful tool to help manage the COVID‐19 pandemic. Testing strategies that use rapid antigen tests to detect current ...infection have the potential to increase access to testing, speed detection of infection, and inform clinical and public health management decisions to reduce transmission. This is the second update of this review, which was first published in 2020.
Objectives
To assess the diagnostic accuracy of rapid, point‐of‐care antigen tests for diagnosis of SARS‐CoV‐2 infection. We consider accuracy separately in symptomatic and asymptomatic population groups. Sources of heterogeneity investigated included setting and indication for testing, assay format, sample site, viral load, age, timing of test, and study design.
Search methods
We searched the COVID‐19 Open Access Project living evidence database from the University of Bern (which includes daily updates from PubMed and Embase and preprints from medRxiv and bioRxiv) on 08 March 2021. We included independent evaluations from national reference laboratories, FIND and the Diagnostics Global Health website. We did not apply language restrictions.
Selection criteria
We included studies of people with either suspected SARS‐CoV‐2 infection, known SARS‐CoV‐2 infection or known absence of infection, or those who were being screened for infection. We included test accuracy studies of any design that evaluated commercially produced, rapid antigen tests. We included evaluations of single applications of a test (one test result reported per person) and evaluations of serial testing (repeated antigen testing over time). Reference standards for presence or absence of infection were any laboratory‐based molecular test (primarily reverse transcription polymerase chain reaction (RT‐PCR)) or pre‐pandemic respiratory sample.
Data collection and analysis
We used standard screening procedures with three people. Two people independently carried out quality assessment (using the QUADAS‐2 tool) and extracted study results. Other study characteristics were extracted by one review author and checked by a second. We present sensitivity and specificity with 95% confidence intervals (CIs) for each test, and pooled data using the bivariate model. We investigated heterogeneity by including indicator variables in the random‐effects logistic regression models. We tabulated results by test manufacturer and compliance with manufacturer instructions for use and according to symptom status.
Main results
We included 155 study cohorts (described in 166 study reports, with 24 as preprints). The main results relate to 152 evaluations of single test applications including 100,462 unique samples (16,822 with confirmed SARS‐CoV‐2). Studies were mainly conducted in Europe (101/152, 66%), and evaluated 49 different commercial antigen assays. Only 23 studies compared two or more brands of test.
Risk of bias was high because of participant selection (40, 26%); interpretation of the index test (6, 4%); weaknesses in the reference standard for absence of infection (119, 78%); and participant flow and timing 41 (27%). Characteristics of participants (45, 30%) and index test delivery (47, 31%) differed from the way in which and in whom the test was intended to be used. Nearly all studies (91%) used a single RT‐PCR result to define presence or absence of infection.
The 152 studies of single test applications reported 228 evaluations of antigen tests. Estimates of sensitivity varied considerably between studies, with consistently high specificities. Average sensitivity was higher in symptomatic (73.0%, 95% CI 69.3% to 76.4%; 109 evaluations; 50,574 samples, 11,662 cases) compared to asymptomatic participants (54.7%, 95% CI 47.7% to 61.6%; 50 evaluations; 40,956 samples, 2641 cases). Average sensitivity was higher in the first week after symptom onset (80.9%, 95% CI 76.9% to 84.4%; 30 evaluations, 2408 cases) than in the second week of symptoms (53.8%, 95% CI 48.0% to 59.6%; 40 evaluations, 1119 cases). For those who were asymptomatic at the time of testing, sensitivity was higher when an epidemiological exposure to SARS‐CoV‐2 was suspected (64.3%, 95% CI 54.6% to 73.0%; 16 evaluations; 7677 samples, 703 cases) compared to where COVID‐19 testing was reported to be widely available to anyone on presentation for testing (49.6%, 95% CI 42.1% to 57.1%; 26 evaluations; 31,904 samples, 1758 cases). Average specificity was similarly high for symptomatic (99.1%) or asymptomatic (99.7%) participants.
We observed a steady decline in summary sensitivities as measures of sample viral load decreased.
Sensitivity varied between brands. When tests were used according to manufacturer instructions, average sensitivities by brand ranged from 34.3% to 91.3% in symptomatic participants (20 assays with eligible data) and from 28.6% to 77.8% for asymptomatic participants (12 assays). For symptomatic participants, summary sensitivities for seven assays were 80% or more (meeting acceptable criteria set by the World Health Organization (WHO)). The WHO acceptable performance criterion of 97% specificity was met by 17 of 20 assays when tests were used according to manufacturer instructions, 12 of which demonstrated specificities above 99%. For asymptomatic participants the sensitivities of only two assays approached but did not meet WHO acceptable performance standards in one study each; specificities for asymptomatic participants were in a similar range to those observed for symptomatic people.
At 5% prevalence using summary data in symptomatic people during the first week after symptom onset, the positive predictive value (PPV) of 89% means that 1 in 10 positive results will be a false positive, and around 1 in 5 cases will be missed. At 0.5% prevalence using summary data for asymptomatic people, where testing was widely available and where epidemiological exposure to COVID‐19 was suspected, resulting PPVs would be 38% to 52%, meaning that between 2 in 5 and 1 in 2 positive results will be false positives, and between 1 in 2 and 1 in 3 cases will be missed.
Authors' conclusions
Antigen tests vary in sensitivity. In people with signs and symptoms of COVID‐19, sensitivities are highest in the first week of illness when viral loads are higher. Assays that meet appropriate performance standards, such as those set by WHO, could replace laboratory‐based RT‐PCR when immediate decisions about patient care must be made, or where RT‐PCR cannot be delivered in a timely manner. However, they are more suitable for use as triage to RT‐PCR testing. The variable sensitivity of antigen tests means that people who test negative may still be infected. Many commercially available rapid antigen tests have not been evaluated in independent validation studies.
Evidence for testing in asymptomatic cohorts has increased, however sensitivity is lower and there is a paucity of evidence for testing in different settings. Questions remain about the use of antigen test‐based repeat testing strategies. Further research is needed to evaluate the effectiveness of screening programmes at reducing transmission of infection, whether mass screening or targeted approaches including schools, healthcare setting and traveller screening.
Background
Invasive aspergillosis is the most common life‐threatening opportunistic invasive mycosis in immunocompromised patients. A test for invasive aspergillosis should neither be too invasive ...nor too great a burden for the already weakened patient. The serum galactomannan enzyme‐linked immunosorbent assay (ELISA) seems to have the potential to meet both requirements.
Objectives
To obtain summary estimates of the diagnostic accuracy of galactomannan detection in serum for the diagnosis of invasive aspergillosis.
Search methods
We searched MEDLINE, EMBASE and Web of Science with both MeSH terms and text words for both aspergillosis and the sandwich ELISA. We checked the reference lists of included studies and review articles for additional studies. We conducted the searches in February 2014.
Selection criteria
We included cross‐sectional studies, case‐control designs and consecutive series of patients assessing the diagnostic accuracy of galactomannan detection for the diagnosis of invasive aspergillosis in patients with neutropenia or patients whose neutrophils are functionally compromised. The reference standard was composed of the criteria given by the European Organization for Research and Treatment of Cancer (EORTC) and the Mycoses Study Group (MSG).
Data collection and analysis
Two review authors independently assessed quality and extracted data. We carried out meta‐analysis using the bivariate method. We investigated sources of heterogeneity by adding potential sources of heterogeneity to the model as covariates.
Main results
We included 54 studies in the review (50 in the meta‐analyses), containing 5660 patients, of whom 586 had proven or probable invasive aspergillosis. When using an optical density index (ODI) of 0.5 as a cut‐off value, the sensitivity of the test was 78% (70% to 85%) and the specificity was 85% (78% to 91%). At a cut‐off value of 1.0 ODI, the sensitivity was 71% (63% to 78%) and the specificity was 90% (86% to 93%). At a cut‐off value of 1.5 ODI, the sensitivity was 63% (49% to 78%) and the specificity was 93% (89% to 97%). None of the potential sources of heterogeneity had a statistically significant effect on either sensitivity or specificity.
Authors' conclusions
If we used the test at a cut‐off value of 0.5 ODI in a population of 100 patients with a disease prevalence of 11% (overall median prevalence), two patients who have invasive aspergillosis would be missed (sensitivity 78%, 22% false negatives), and 13 patients would be treated unnecessarily or referred unnecessarily for further testing (specificity 85%, 15% false negatives). If we used the test at a cut‐off value of 1.5 in the same population, that would mean that four invasive aspergillosis patients would be missed (sensitivity 61%, 39% false negatives), and six patients would be treated or referred for further testing unnecessarily (specificity 93%, 7% false negatives). These numbers should, however, be interpreted with caution because the results were very heterogeneous.
Background
Point‐of‐care (POC) tests for diagnosing schistosomiasis include tests based on circulating antigen detection and urine reagent strip tests. If they had sufficient diagnostic accuracy they ...could replace conventional microscopy as they provide a quicker answer and are easier to use.
Objectives
To summarise the diagnostic accuracy of: a) urine reagent strip tests in detecting active Schistosoma haematobium infection, with microscopy as the reference standard; and b) circulating antigen tests for detecting active Schistosoma infection in geographical regions endemic for Schistosoma mansoni or S. haematobium or both, with microscopy as the reference standard.
Search methods
We searched the electronic databases MEDLINE, EMBASE, BIOSIS, MEDION, and Health Technology Assessment (HTA) without language restriction up to 30 June 2014.
Selection criteria
We included studies that used microscopy as the reference standard: for S. haematobium, microscopy of urine prepared by filtration, centrifugation, or sedimentation methods; and for S. mansoni, microscopy of stool by Kato‐Katz thick smear. We included studies on participants residing in endemic areas only.
Data collection and analysis
Two review authors independently extracted data, assessed quality of the data using QUADAS‐2, and performed meta‐analysis where appropriate. Using the variability of test thresholds, we used the hierarchical summary receiver operating characteristic (HSROC) model for all eligible tests (except the circulating cathodic antigen (CCA) POC for S. mansoni, where the bivariate random‐effects model was more appropriate). We investigated heterogeneity, and carried out indirect comparisons where data were sufficient. Results for sensitivity and specificity are presented as percentages with 95% confidence intervals (CI).
Main results
We included 90 studies; 88 from field settings in Africa. The median S. haematobium infection prevalence was 41% (range 1% to 89%) and 36% for S. mansoni (range 8% to 95%). Study design and conduct were poorly reported against current standards.
Tests for S. haematobium
Urine reagent test strips versus microscopy
Compared to microscopy, the detection of microhaematuria on test strips had the highest sensitivity and specificity (sensitivity 75%, 95% CI 71% to 79%; specificity 87%, 95% CI 84% to 90%; 74 studies, 102,447 participants). For proteinuria, sensitivity was 61% and specificity was 82% (82,113 participants); and for leukocyturia, sensitivity was 58% and specificity 61% (1532 participants). However, the difference in overall test accuracy between the urine reagent strips for microhaematuria and proteinuria was not found to be different when we compared separate populations (P = 0.25), or when direct comparisons within the same individuals were performed (paired studies; P = 0.21).
When tests were evaluated against the higher quality reference standard (when multiple samples were analysed), sensitivity was marginally lower for microhaematuria (71% vs 75%) and for proteinuria (49% vs 61%). The specificity of these tests was comparable.
Antigen assay
Compared to microscopy, the CCA test showed considerable heterogeneity; meta‐analytic sensitivity estimate was 39%, 95% CI 6% to 73%; specificity 78%, 95% CI 55% to 100% (four studies, 901 participants).
Tests for S. mansoni
Compared to microscopy, the CCA test meta‐analytic estimates for detecting S. mansoni at a single threshold of trace positive were: sensitivity 89% (95% CI 86% to 92%); and specificity 55% (95% CI 46% to 65%; 15 studies, 6091 participants) Against a higher quality reference standard, the sensitivity results were comparable (89% vs 88%) but specificity was higher (66% vs 55%). For the CAA test, sensitivity ranged from 47% to 94%, and specificity from 8% to 100% (four studies, 1583 participants).
Authors' conclusions
Among the evaluated tests for S. haematobium infection, microhaematuria correctly detected the largest proportions of infections and non‐infections identified by microscopy.
The CCA POC test for S. mansoni detects a very large proportion of infections identified by microscopy, but it misclassifies a large proportion of microscopy negatives as positives in endemic areas with a moderate to high prevalence of infection, possibly because the test is potentially more sensitive than microscopy.
23 April 2019
No update planned
Other
Reliable evidence with clear conclusions. All eligible published studies found in the last search (30 Jun, 2014) were included.
Background
In children with urinary tract infection (UTI), only those with pyelonephritis (and not cystitis) are at risk for developing long‐term renal sequelae. If non‐invasive biomarkers could ...accurately differentiate children with cystitis from children with pyelonephritis, treatment and follow‐up could potentially be individualized.
Objectives
The objectives of this review were to 1) determine whether procalcitonin, C‐reactive protein (CRP), erythrocyte sedimentation rate (ESR) can replace the acute DMSA scan in the diagnostic evaluation of children with UTI; 2) assess the influence of patient and study characteristics on the diagnostic accuracy of these tests, and 3) compare the performance of the three tests to each other.
Search methods
We searched MEDLINE, EMBASE, DARE, Web of Science, and BIOSIS Previews for this review. The reference lists of all included articles and relevant systematic reviews were searched to identify additional studies not found through the electronic search.
Selection criteria
We only considered published studies that evaluated the results of an index test (procalcitonin, CRP, ESR) against the results of an acute‐phase DMSA scan (conducted within 30 days of the UTI) in children aged 0 to 18 years with a culture‐confirmed episode of UTI. The following cutoff values were used for the primary analysis: 0.5 ng/mL for procalcitonin, 20 mg/L for CRP and 30 mm/h for ESR.
Data collection and analysis
Two authors independently applied the selection criteria to all citations and independently ed data. We used the bivariate model to calculate pooled random‐effects pooled sensitivity and specificity values.
Main results
A total of 24 studies met our inclusion criteria. Seventeen studies provided data for the primary analysis: six studies (434 children) included data on procalcitonin, 13 studies (1638 children) included data on CRP, and six studies (1737 children) included data on ESR (some studies had data on more than one test). The summary sensitivity estimates (95% CI) for the procalcitonin, CRP, ESR tests at the aforementioned cutoffs were 0.86 (0.72 to 0.93), 0.94 (0.85 to 0.97), and 0.87 (0.77 to 0.93), respectively. The summary specificity values for procalcitonin, CRP, and ESR tests at these cutoffs were 0.74 (0.55 to 0.87), 0.39 (0.23 to 0.58), and 0.48 (0.33 to 0.64), respectively.
Authors' conclusions
The ESR test does not appear to be sufficiently accurate to be helpful in differentiating children with cystitis from children with pyelonephritis. A low CRP value (< 20 mg/L) appears to be somewhat useful in ruling out pyelonephritis (decreasing the probability of pyelonephritis to < 20%), but unexplained heterogeneity in the data prevents us from making recommendations at this time. The procalcitonin test seems better suited for ruling in pyelonephritis, but the limited number of studies and the marked heterogeneity between studies prevents us from reaching definitive conclusions. Thus, at present, we do not find any compelling evidence to recommend the routine use of any of these tests in clinical practice.
Thoracic imaging tests for the diagnosis of COVID‐19 McInnes, Matthew DF; Salameh, Jean-Paul; Leeflang, Mariska MG ...
Cochrane database of systematic reviews,
09/2020, Letnik:
2020, Številka:
9
Journal Article
Recenzirano
Odprti dostop
Background
The diagnosis of infection by the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) presents major challenges. Reverse transcriptase polymerase chain reaction (RT‐PCR) testing ...is used to diagnose a current infection, but its utility as a reference standard is constrained by sampling errors, limited sensitivity (71% to 98%), and dependence on the timing of specimen collection. Chest imaging tests are being used in the diagnosis of COVID‐19 disease, or when RT‐PCR testing is unavailable.
Objectives
To determine the diagnostic accuracy of chest imaging (computed tomography (CT), X‐ray and ultrasound) in people with suspected or confirmed COVID‐19.
Search methods
We searched the COVID‐19 Living Evidence Database from the University of Bern, the Cochrane COVID‐19 Study Register, and The Stephen B. Thacker CDC Library. In addition, we checked repositories of COVID‐19 publications. We did not apply any language restrictions. We conducted searches for this review iteration up to 5 May 2020.
Selection criteria
We included studies of all designs that produce estimates of test accuracy or provide data from which estimates can be computed. We included two types of cross‐sectional designs: a) where all patients suspected of the target condition enter the study through the same route and b) where it is not clear up front who has and who does not have the target condition, or where the patients with the target condition are recruited in a different way or from a different population from the patients without the target condition. When studies used a variety of reference standards, we included all of them.
Data collection and analysis
We screened studies and extracted data independently, in duplicate. We also assessed the risk of bias and applicability concerns independently, in duplicate, using the QUADAS‐2 checklist and presented the results of estimated sensitivity and specificity, using paired forest plots, and summarised in tables. We used a hierarchical meta‐analysis model where appropriate. We presented uncertainty of the accuracy estimates using 95% confidence intervals (CIs).
Main results
We included 84 studies, falling into two categories: studies with participants with confirmed diagnoses of COVID‐19 at the time of recruitment (71 studies with 6331 participants) and studies with participants suspected of COVID‐19 (13 studies with 1948 participants, including three case‐control studies with 549 cases and controls). Chest CT was evaluated in 78 studies (8105 participants), chest X‐ray in nine studies (682 COVID‐19 cases), and chest ultrasound in two studies (32 COVID‐19 cases). All evaluations of chest X‐ray and ultrasound were conducted in studies with confirmed diagnoses only. Twenty‐five per cent (21/84) of all studies were available only as preprints, 15/71 studies in the confirmed cases group and 6/13 of the studies in the suspected group.
Among 71 studies that included confirmed cases, 41 studies had included symptomatic cases only, 25 studies had included cases regardless of their symptoms, five studies had included asymptomatic cases only, three of which included a combination of confirmed and suspected cases. Seventy studies were conducted in Asia, 2 in Europe, 2 in North America and one in South America. Fifty‐one studies included inpatients while the remaining 24 studies were conducted in mixed or unclear settings. Risk of bias was high in most studies, mainly due to concerns about selection of participants and applicability.
Among the 13 studies that included suspected cases, nine studies were conducted in Asia, and one in Europe. Seven studies included inpatients while the remaining three studies were conducted in mixed or unclear settings.
In studies that included confirmed cases the pooled sensitivity of chest CT was 93.1% (95%CI: 90.2 ‐ 95.0 (65 studies, 5759 cases); and for X‐ray 82.1% (95%CI: 62.5 to 92.7 (9 studies, 682 cases). Heterogeneity judged by visual assessment of the ROC plots was considerable. Two studies evaluated the diagnostic accuracy of point‐of‐care ultrasound and both reported zero false negatives (with 10 and 22 participants having undergone ultrasound, respectively). These studies only reported True Positive and False Negative data, therefore it was not possible to pool and derive estimates of specificity.
In studies that included suspected cases, the pooled sensitivity of CT was 86.2% (95%CI: 71.9 to 93.8 (13 studies, 2346 participants) and specificity was 18.1% (95%CI: 3.71 to 55.8). Heterogeneity judged by visual assessment of the forest plots was high.
Chest CT may give approximately the same proportion of positive results for patients with and without a SARS‐CoV‐2 infection: the chances of getting a positive CT result are 86% (95% CI: 72 to 94) in patient with a SARS‐CoV‐2 infection and 82% (95% CI: 44 to 96) in patients without.
Authors' conclusions
The uncertainty resulting from the poor study quality and the heterogeneity of included studies limit our ability to confidently draw conclusions based on our results. Our findings indicate that chest CT is sensitive but not specific for the diagnosis of COVID‐19 in suspected patients, meaning that CT may not be capable of differentiating SARS‐CoV‐2 infection from other causes of respiratory illness. This low specificity could also be the result of the poor sensitivity of the reference standard (RT‐PCR), as CT could potentially be more sensitive than RT‐PCR in some cases. Because of limited data, accuracy estimates of chest X‐ray and ultrasound of the lungs for the diagnosis of COVID‐19 should be carefully interpreted.
Future diagnostic accuracy studies should avoid cases‐only studies and pre‐define positive imaging findings. Planned updates of this review will aim to: increase precision around the accuracy estimates for CT (ideally with low risk of bias studies); obtain further data to inform accuracy of chest X rays and ultrasound; and continue to search for studies that fulfil secondary objectives to inform the utility of imaging along different diagnostic pathways.
Timely diagnosis of influenza can help clinical management.
To examine the accuracy of rapid influenza diagnostic tests (RIDTs) in adults and children with influenza-like illness and evaluate factors ...associated with higher accuracy.
PubMed and EMBASE through December 2011; BIOSIS and Web of Science through March 2010; and citations of articles, guidelines, reviews, and manufacturers.
Studies that compared RIDTs with a reference standard of either reverse transcriptase polymerase chain reaction (first choice) or viral culture.
Reviewers abstracted study data by using a standardized form and assessed quality by using Quality Assessment of Diagnostic Accuracy Studies criteria.
159 studies evaluated 26 RIDTs, and 35% were conducted during the H1N1 pandemic. Failure to report whether results were assessed in a blinded manner and the basis for patient recruitment were important quality concerns. The pooled sensitivity and specificity were 62.3% (95% CI, 57.9% to 66.6%) and 98.2% (CI, 97.5% to 98.7%), respectively. The positive and negative likelihood ratios were 34.5 (CI, 23.8 to 45.2) and 0.38 (CI, 0.34 to 0.43), respectively. Sensitivity estimates were highly heterogeneous, which was partially explained by lower sensitivity in adults (53.9% CI, 47.9% to 59.8%) than in children (66.6% CI, 61.6% to 71.7%) and a higher sensitivity for influenza A (64.6% CI, 59.0% to 70.1%) than for influenza B (52.2% CI, 45.0% to 59.3%).
Incomplete reporting limited the ability to assess the effect of important factors, such as specimen type and duration of influenza symptoms, on diagnostic accuracy.
Influenza can be ruled in but not ruled out through the use of RIDTs. Sensitivity varies across populations, but it is higher in children than in adults and for influenza A than for influenza B.
Canadian Institutes of Health Research.
During pregnancy, malaria infection with Plasmodium falciparum or Plasmodium vivax is related to adverse maternal health and poor birth outcomes. Diagnosis of malaria, during pregnancy, is ...complicated by the absence or low parasite densities in peripheral blood. Diagnostic methods, other than microscopy, are needed for detection of placental malaria. Therefore, the diagnostic accuracy of rapid diagnostic tests (RDTs), detecting antigen, and molecular techniques (PCR), detecting DNA, for the diagnosis of Plasmodium infections in pregnancy was systematically reviewed.
MEDLINE, EMBASE and Web of Science were searched for studies assessing the diagnostic accuracy of RDTs, PCR, microscopy of peripheral and placental blood and placental histology for the detection of malaria infection (all species) in pregnant women.
The results of 49 studies were analysed in metandi (Stata), of which the majority described P. falciparum infections. Although both placental and peripheral blood microscopy cannot reliably replace histology as a reference standard for placental P. falciparum infection, many studies compared RDTs and PCR to these tests. The proportion of microscopy positives in placental blood (sensitivity) detected by peripheral blood microscopy, RDTs and PCR are respectively 72% 95% CI 62-80, 81% 95% CI 55-93 and 94% 95% CI 86-98. The proportion of placental blood microscopy negative women that were negative in peripheral blood microscopy, RDTs and PCR (specificity) are 98% 95% CI 95-99, 94% 95% CI 76-99 and 77% 95% CI 71-82. Based on the current data, it was not possible to determine if the false positives in RDTs and PCR are caused by sequestered parasites in the placenta that are not detected by placental microscopy.
The findings suggest that RDTs and PCR may have good performance characteristics to serve as alternatives for the diagnosis of malaria in pregnancy, besides any other limitations and practical considerations concerning the use of these tests. Nevertheless, more studies with placental histology as reference test are urgently required to reliably determine the accuracy of RDTs and PCR for the diagnosis of placental malaria. P. vivax-infections have been neglected in diagnostic test accuracy studies of malaria in pregnancy.
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