“…We identified 66 unique studies that met the inclusion criteria (Ablanedo‐Terrazas 2014; Al‐Ateah 2012; Arockiaraj 2017; Bahr 2015; Bahr 2017; Bera 2015; Bholla 2016; Biadglegne 2014; Blaich 2014; Causse 2011; Che 2017; Christopher 2013; Coetzee 2014; Dhasmana 2014; Dhooria 2016; Diallo 2016; Du 2015; Feasey 2013; Friedrich 2011; Ghariani 2015; Gu 2015; Gursoy 2016; Hanif 2011; Held 2014; Held 2016; Hillemann 2011; Ioannidis 2011; Iram 2015; Jing 2017; Kim 2015a; Li 2017; Ligthelm 2011; Lusiba 2014; Malbruny 2011; Massi 2017; Mazzola 2016; Meldau 2014; Nataraj 2016; Nhu 2014; Ozkutuk 2014; Pandey 2017; Pandie 2014; Patel 2013; Penata 2016; Pink 2016; Pohl 2016; Rufai 2015; Rufai 2017a; Rufai 2017b; Saeed 2017a; Safianowska 2012; Scott 2014; Sharma 2014; Sharma 2016; Solomons 2016; Suzana 2016; Tadesse 2015; Teo 2011; Tortoli 2012; Trajman 2014; Ullah 2017; Vadwa...…”
Section: Resultsmentioning
confidence: 99%
“…In the patient selection domain, we thought that 51 studies (77%) had low risk of bias, and six studies (9%) had high risk of bias for the following reasons: four studies selected participants by convenience (Bholla 2016; Ioannidis 2011; Malbruny 2011; Pandey 2017), and two studies had inappropriate exclusions (Saeed 2017a; Ullah 2017). We thought that nine studies (14%) had unclear risk of bias for the following reasons: the manner of patient selection was unclear ‐ eight studies (Diallo 2016; Gu 2015; Li 2017; Massi 2017; Rufai 2015; Rufai 2017a; Rufai 2017b; Zmak 2013), and it was unclear whether the study avoided inappropriate exclusions ‐ one study (Bera 2015). Regarding applicability (patient characteristics and setting), we thought that three studies (4%) had low concern because participants were evaluated in local hospitals or primary health settings (Bholla 2016; Pandie 2014; Trajman 2014); nine studies (14%) had high concern because participants were evaluated exclusively as inpatients at a tertiary care centre (Bahr 2015; Bahr 2017; Causse 2011; Che 2017; Du 2015; Feasey 2013; Gu 2015; Held 2014; Held 2016); and 54 studies had unclear concern because we could not tell the clinical setting.Figure 3Risk of bias and applicability concerns graph: review authors' judgements about each domain presented as percentages across included studies.Figure 4Risk of bias and applicability concerns summary: review authors' judgements about each domain for each included study.…”
Cochrane Database of Systematic Reviews Data collection and analysis Two review authors independently extracted data, assessed risk of bias and applicability using the QUADAS-2 tool. We determined pooled predicted sensitivity and specificity for TB, grouped by type of extrapulmonary specimen, and for rifampicin resistance. For TB detection, we used a bivariate random-e ects model. Recognizing that use of culture may lead to misclassification of cases of extrapulmonary TB as 'not TB' owing to the paucibacillary nature of the disease, we adjusted accuracy estimates by applying a latent class meta-analysis model. For rifampicin resistance detection, we performed univariate meta-analyses for sensitivity and specificity separately to include studies in which no rifampicin resistance was detected. We used theoretical populations with an assumed prevalence to provide illustrative numbers of patients with false positive and false negative results. Main results We included 66 unique studies that evaluated 16,213 specimens for detection of extrapulmonary TB and rifampicin resistance. We identified only one study that evaluated the newest test version, Xpert MTB/RIF Ultra (Ultra), for TB meningitis. Fi y studies (76%) took place in low-or middle-income countries. Risk of bias was low for patient selection, index test, and flow and timing domains and was high or unclear for the reference standard domain (most of these studies decontaminated sterile specimens before culture inoculation). Regarding applicability, in the patient selection domain, we scored high or unclear concern for most studies because either patients were evaluated exclusively as inpatients at tertiary care centres, or we were not sure about the clinical settings. Authors' conclusions In people presumed to have extrapulmonary TB, Xpert may be helpful in confirming the diagnosis. Xpert sensitivity varies across di erent extrapulmonary specimens, while for most specimens, specificity is high, the test rarely yielding a positive result for people without TB Xpert ® MTB/RIF assay for extrapulmonary tuberculosis and rifampicin resistance (Review)
“…We identified 66 unique studies that met the inclusion criteria (Ablanedo‐Terrazas 2014; Al‐Ateah 2012; Arockiaraj 2017; Bahr 2015; Bahr 2017; Bera 2015; Bholla 2016; Biadglegne 2014; Blaich 2014; Causse 2011; Che 2017; Christopher 2013; Coetzee 2014; Dhasmana 2014; Dhooria 2016; Diallo 2016; Du 2015; Feasey 2013; Friedrich 2011; Ghariani 2015; Gu 2015; Gursoy 2016; Hanif 2011; Held 2014; Held 2016; Hillemann 2011; Ioannidis 2011; Iram 2015; Jing 2017; Kim 2015a; Li 2017; Ligthelm 2011; Lusiba 2014; Malbruny 2011; Massi 2017; Mazzola 2016; Meldau 2014; Nataraj 2016; Nhu 2014; Ozkutuk 2014; Pandey 2017; Pandie 2014; Patel 2013; Penata 2016; Pink 2016; Pohl 2016; Rufai 2015; Rufai 2017a; Rufai 2017b; Saeed 2017a; Safianowska 2012; Scott 2014; Sharma 2014; Sharma 2016; Solomons 2016; Suzana 2016; Tadesse 2015; Teo 2011; Tortoli 2012; Trajman 2014; Ullah 2017; Vadwa...…”
Section: Resultsmentioning
confidence: 99%
“…In the patient selection domain, we thought that 51 studies (77%) had low risk of bias, and six studies (9%) had high risk of bias for the following reasons: four studies selected participants by convenience (Bholla 2016; Ioannidis 2011; Malbruny 2011; Pandey 2017), and two studies had inappropriate exclusions (Saeed 2017a; Ullah 2017). We thought that nine studies (14%) had unclear risk of bias for the following reasons: the manner of patient selection was unclear ‐ eight studies (Diallo 2016; Gu 2015; Li 2017; Massi 2017; Rufai 2015; Rufai 2017a; Rufai 2017b; Zmak 2013), and it was unclear whether the study avoided inappropriate exclusions ‐ one study (Bera 2015). Regarding applicability (patient characteristics and setting), we thought that three studies (4%) had low concern because participants were evaluated in local hospitals or primary health settings (Bholla 2016; Pandie 2014; Trajman 2014); nine studies (14%) had high concern because participants were evaluated exclusively as inpatients at a tertiary care centre (Bahr 2015; Bahr 2017; Causse 2011; Che 2017; Du 2015; Feasey 2013; Gu 2015; Held 2014; Held 2016); and 54 studies had unclear concern because we could not tell the clinical setting.Figure 3Risk of bias and applicability concerns graph: review authors' judgements about each domain presented as percentages across included studies.Figure 4Risk of bias and applicability concerns summary: review authors' judgements about each domain for each included study.…”
Cochrane Database of Systematic Reviews Data collection and analysis Two review authors independently extracted data, assessed risk of bias and applicability using the QUADAS-2 tool. We determined pooled predicted sensitivity and specificity for TB, grouped by type of extrapulmonary specimen, and for rifampicin resistance. For TB detection, we used a bivariate random-e ects model. Recognizing that use of culture may lead to misclassification of cases of extrapulmonary TB as 'not TB' owing to the paucibacillary nature of the disease, we adjusted accuracy estimates by applying a latent class meta-analysis model. For rifampicin resistance detection, we performed univariate meta-analyses for sensitivity and specificity separately to include studies in which no rifampicin resistance was detected. We used theoretical populations with an assumed prevalence to provide illustrative numbers of patients with false positive and false negative results. Main results We included 66 unique studies that evaluated 16,213 specimens for detection of extrapulmonary TB and rifampicin resistance. We identified only one study that evaluated the newest test version, Xpert MTB/RIF Ultra (Ultra), for TB meningitis. Fi y studies (76%) took place in low-or middle-income countries. Risk of bias was low for patient selection, index test, and flow and timing domains and was high or unclear for the reference standard domain (most of these studies decontaminated sterile specimens before culture inoculation). Regarding applicability, in the patient selection domain, we scored high or unclear concern for most studies because either patients were evaluated exclusively as inpatients at tertiary care centres, or we were not sure about the clinical settings. Authors' conclusions In people presumed to have extrapulmonary TB, Xpert may be helpful in confirming the diagnosis. Xpert sensitivity varies across di erent extrapulmonary specimens, while for most specimens, specificity is high, the test rarely yielding a positive result for people without TB Xpert ® MTB/RIF assay for extrapulmonary tuberculosis and rifampicin resistance (Review)
“… 20 Penz et al 14 described a pooled sensitivity and specificity of respectively 77% and 97% of Xpert in the detection of EPTB in a meta-analysis including 36 studies. Relatively homogeneous tested samples and less included studies, especially some describing comparatively low specificity, 25 , 26 may account for the reduced pooled specificity in our study. In addition, a pooled PLR of 10.90 and a pooled NLR of 0.22 indicate that patients with positive or negative Xpert results have a 10.90-fold higher or a 0.22-fold lower chance of suffering from musculoskeletal TB than not.…”
ObjectivesXpert MTB/RIF assay, a rapid and automated real-time nucleic acid amplification test, has been reported for the diagnosis of musculoskeletal tuberculosis (TB) in current years. This meta-analysis aims to determine the diagnostic accuracy of Xpert for the detection of musculoskeletal TB and rifampicin (RIF) resistance.MethodsWe searched PubMed, Embase, China National Knowledge Infrastructure, and Wanfang for original articles published up to 1st June 2017 to identify studies in which the Xpert assay was applied to diagnose musculoskeletal TB. Pooled estimates were calculated using a random-effects model or a fixed-effects model according to heterogeneity. Summary receiver operating characteristic curves and the area under the curve (AUC) were used to summarize overall diagnostic performance. Deeks’ test was performed to evaluate potential publication bias.ResultsTwelve studies were identified with a pooled sensitivity and specificity of respectively 0.81 (95% confidence interval [CI] 0.78–0.83) and 0.83 (95% CI 0.80–0.86) of Xpert for the diagnosis of musculoskeletal TB. Xpert was highly sensitive (0.89, 95% CI 0.79–0.95) and highly specific (0.96, 95% CI 0.92–0.98) in detecting RIF resistance. AUC (over 0.9) suggested a relatively high level of overall diagnostic accuracy of Xpert for detecting musculoskeletal TB and RIF resistance. Prevalence and reference standard were indicated to be sources of heterogeneity between studies. No publication bias was found.ConclusionThis study provides available evidence of the rapid and effective role of Xpert in diagnosing musculoskeletal TB and detecting RIF resistance.
“…The pooled sensitivity of Xpert MTB/RIF was 96% (I 2 = 91%; 95% CI, 90-98). The specificity of Xpert MTB/RIF ranged from 17% (95% CI, [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28] to 100% (95% CI, 99-100) and the pooled specificity was 85% (I 2 = 97%; 95% CI, 57-96) ( Fig 4). As expected, the sensitivity was improved, and the specificity was undervalued when compared to the culture.…”
Section: Diagnostic Accuracy Of Xpert Mtb/rif Assay For Bjtbmentioning
BackgroundThis study aimed to evaluate the accuracy of the Xpert MTB/RIF assay for the diagnosis of bone and joint tuberculosis.
MethodsWe searched databases from their inception to May 7, 2019 for published articles and reviewed them to assess the accuracy of Xpert MTB/RIF with respect to a composite reference standard (CRS) and mycobacterial culture. Meta-analyses were performed using a bivariate random-effects model, and the sources of heterogeneity were assessed via subgroup analysis and meta-regression.
ResultsNineteen independent (9 prospective, 5 retrospective, and 5 case-control) studies that compared Xpert MTB/RIF with the CRS and 14 (6 prospective, 7 retrospective, and 1 case-control) studies that compared it with culture were included. The pooled sensitivity and specificity of Xpert MTB/RIF were 81% (95% confidence interval [CI], 77-84) and 99% (95% CI, 97-100) compared to the CRS, respectively, and 96% (95% CI, 90-98) and 85% (95% CI, 57-96) compared to culture, respectively. The pooled sensitivity and specificity using pus samples vs. the CRS were 82% (95% CI, 76-86) and 99% (95% CI, 95-100), respectively. The proportions obtained while working with tissue samples vs. the CRS were 84% (95% CI, 76-90) and 98% (95% CI, 94-99), respectively. There was no significant difference in diagnostic accuracy among the types of specimens.
ConclusionsXpert MTB/RIF demonstrates good diagnostic accuracy for bone and joint tuberculosis, the results of which are not related to the type of specimen.
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