scholarly journals Sputum Gram Stain for Bacterial Pathogen Diagnosis in Community-acquired Pneumonia: A Systematic Review and Bayesian Meta-analysis of Diagnostic Accuracy and Yield

2019 ◽  
Vol 71 (3) ◽  
pp. 499-513 ◽  
Author(s):  
Hiroaki Ogawa ◽  
Georgios D Kitsios ◽  
Mitsunaga Iwata ◽  
Teruhiko Terasawa
Keyword(s):  
Systematic Review ◽  
Diagnostic Accuracy ◽  
Latent Class ◽  
Meta Analysis ◽  
Latent Class Model ◽  
Reporting Quality ◽  
Credible Interval ◽  
Community Acquired Pneumonia ◽  
Gram Stain ◽  
Clinical Role

Abstract Background The clinical role of sputum Gram stain (SGS) in community-acquired pneumonia (CAP) diagnosis remains controversial. A 1996 meta-analysis of the diagnostic accuracy of SGS reported heterogeneous results. To update the available evidence, we performed a systematic review and a Bayesian standard and latent-class model meta-analysis. Methods We searched Medline, Embase, and Cochrane Central by 23 August 2018 to identify studies reporting on the diagnostic accuracy, yield (percentage of patients with any pathogen[s] correctly identified by SGS), and clinical outcomes of SGS in adult patients with CAP. Two reviewers extracted the data. We quantitatively synthesized the diagnostic accuracy and yield, and descriptively analyzed other outcomes. Results Twenty-four studies with 4533 patients were included. The methodological and reporting quality of the included studies was limited. When good-quality sputum specimens were selected, SGS had a summary sensitivity of 0.69 (95% credible interval [CrI], .56–.80) and specificity of 0.91 (CrI, .83–.96) for detecting Streptococcus pneumoniae, and a sensitivity of 0.76 (CrI, .60–.87) and specificity of 0.97 (CrI, .91–.99) for Haemophilus influenzae. Adjusted analyses accounting for imperfect reference standards provided higher-specificity estimates than the unadjusted analyses. Bacterial pathogens were identified in 73% (CrI, 26%–96%) of good-quality specimens, and 36% (CrI, 22%–53%) of all specimens regardless of quality. Evidence on other bacteria was sparse. Conclusions SGS was highly specific to diagnose S. pneumoniae and H. influenzae infections in patients with CAP. With good-quality specimens, SGS can provide clinically actionable information for pathogen-directed antibiotic therapies.

scholarly journals Reporting quality of diagnostic accuracy studies: a systematic review and meta-analysis of investigations on adherence to STARD

2013 ◽  
Vol 19 (2) ◽  
pp. 47-54 ◽  
Author(s):  
Daniël A Korevaar ◽  
W Annefloor van Enst ◽  
René Spijker ◽  
Patrick M M Bossuyt ◽  
Lotty Hooft
Keyword(s):  
Systematic Review ◽  
Diagnostic Accuracy ◽  
Meta Analysis ◽  
Reporting Quality

scholarly journals Usefulness of sputum gram stain for etiologic diagnosis in community-acquired pneumonia: a systematic review and meta-analysis

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Gaspar Del Rio-Pertuz ◽  
Juan F. Gutiérrez ◽  
Abel J. Triana ◽  
Jorge L. Molinares ◽  
Andrea B. Robledo-Solano ◽  
...  
Keyword(s):  
Systematic Review ◽  
Meta Analysis ◽  
Community Acquired Pneumonia ◽  
Gram Stain ◽  
Etiologic Diagnosis

scholarly journals Evidence assessing the diagnostic performance of medical smartphone apps: a systematic review and exploratory meta-analysis

BMJ Open ◽  
2017 ◽  
Vol 7 (12) ◽  
pp. e018280 ◽  
Author(s):  
Rahel Buechi ◽  
Livia Faes ◽  
Lucas M Bachmann ◽  
Michael A Thiel ◽  
Nicolas S Bodmer ◽  
...  
Keyword(s):  
Systematic Review ◽  
Diagnostic Accuracy ◽  
Quality Assessment ◽  
Meta Analysis ◽  
Reporting Quality ◽  
Diagnostic Value ◽  
Summary Estimate ◽  
Registration Number ◽  
Business Source Premier ◽  
Smartphone Sensors

ObjectiveThe number of mobile applications addressing health topics is increasing. Whether these apps underwent scientific evaluation is unclear. We comprehensively assessed papers investigating the diagnostic value of available diagnostic health applications using inbuilt smartphone sensors.MethodsSystematic Review—MEDLINE, Scopus, Web of Science inclusive Medical Informatics and Business Source Premier (by citation of reference) were searched from inception until 15 December 2016. Checking of reference lists of review articles and of included articles complemented electronic searches. We included all studies investigating a health application that used inbuilt sensors of a smartphone for diagnosis of disease. The methodological quality of 11 studies used in an exploratory meta-analysis was assessed with the Quality Assessment of Diagnostic Accuracy Studies 2 tool and the reporting quality with the ’STAndards for the Reporting of Diagnostic accuracy studies' (STARD) statement. Sensitivity and specificity of studies reporting two-by-two tables were calculated and summarised.ResultsWe screened 3296 references for eligibility. Eleven studies, most of them assessing melanoma screening apps, reported 17 two-by-two tables. Quality assessment revealed high risk of bias in all studies. Included papers studied 1048 subjects (758 with the target conditions and 290 healthy volunteers). Overall, the summary estimate for sensitivity was 0.82 (95 % CI 0.56 to 0.94) and 0.89 (95 %CI 0.70 to 0.97) for specificity.ConclusionsThe diagnostic evidence of available health apps on Apple’s and Google’s app stores is scarce. Consumers and healthcare professionals should be aware of this when using or recommending them.PROSPERO registration number42016033049.

scholarly journals The impact of emerging Plasmodium knowlesi on accurate diagnosis by light microscopy: a systematic review and modelling analysis

2021 ◽  
Author(s):  
John H. Huber ◽  
Margaret Elliott ◽  
Cristian Koepfli ◽  
T. Alex Perkins
Keyword(s):  
Systematic Review ◽  
Light Microscopy ◽  
Latent Class ◽  
Plasmodium Knowlesi ◽  
Meta Analysis ◽  
Latent Class Model ◽  
Malaria Diagnosis ◽  
Bayesian Hierarchical ◽  
Highly Correlated ◽  
The Impact

ABSTRACTBackgroundThe five Plasmodium spp. that cause human malaria appear similar under light microscopy, which raises the possibility that misdiagnosis could routinely occur in clinical settings. Assessing the extent of misdiagnosis is of particular importance for monitoring P. knowlesi, which co-circulates with the other Plasmodium spp.MethodsWe performed a systematic review and meta-analysis of studies comparing the performance of microscopy and PCR for diagnosing malaria in settings with co-circulation of the five Plasmodium spp. We assessed the extent to which co-circulation of Plasmodium parasites affects diagnostic outcomes. We fit a Bayesian hierarchical latent class model to estimate variation in microscopy sensitivity and specificity.ResultsMean sensitivity of microscopy was low, yet highly variable across Plasmodium spp., ranging from 41.7% (95% CI: 22.8 – 64.1%) for P. falciparum and 40.3% (22.0 – 61.5%) for P. vivax to 0.119% (0.0121 – 0.640%) for P. knowlesi, 7.57% (2.66 – 22.0%) for P. malariae, and 0.180% (0.00491 – 1.21%) for P. ovale. Observed PCR prevalence was positively correlated with estimated microscopic sensitivity and negatively correlated with estimated microscopic specificity, though the strength of the associations varied by species.ConclusionsOur analysis suggests that co-circulation of Plasmodium spp. undermines the accuracy of microscopy. Sensitivity was considerably lower for P. knowlesi, P. malariae, and P. ovale. The negative association between specificity and PCR prevalence imply that less frequently encountered species may be misdiagnosed as more frequently encountered species. Together, these results suggest that the burden of P. knowlesi, P. malariae, and P. ovale may be underappreciated in a clinical setting.SummaryCo-circulation of Plasmodium species parasites may limit the accuracy of malaria diagnosis by light microscopy. Variation in performance of light microscopy is highly correlated with the prevalence of the parasites in the epidemiological setting.

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