SynthesisPloS one2022
Cholera diagnosis in human stool and detection in water: A systematic review and meta-analysis.
Synthesis in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Cholera rages in Africa and the Middle East: A narrative review on challenges and solutions.Health science reports · 2024Review
- A stitch in time: The importance of water and sanitation services (WSS) infrastructure maintenance for cholera risk. A geospatial analysis in Harare, Zimbabwe.PLoS neglected tropical diseases · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 3 countries.
Funding
Abstract
backgroundCholera continues to pose a problem for low-resource, fragile and humanitarian contexts. Evidence suggests that 2.86 million cholera cases and 95,000 deaths due to cholera are reported annually. Without quick and effective diagnosis and treatment, case-fatality may be 50%. In line with the priorities of the Global Task Force on Cholera Control, we undertook a systematic review and meta-analysis of diagnostic test accuracy and other test characteristics of current tests for cholera detection in stool and water.
methodsWe searched 11 bibliographic and grey literature databases. Data was extracted on test sensitivity, specificity and other product information. Meta-analyses of sensitivity and specificity were conducted for tests reported in three or more studies. Where fewer studies reported a test, estimates were summarised through narrative synthesis. Risk of Bias was assessed using QUADAS-2.
resultsSearches identified 6,637 records; 41 studies reporting on 28 tests were included. Twenty-two tests had both sensitivities and specificities reported above 95% by at least one study, but there was, overall, wide variation in reported diagnostic accuracy across studies. For the three tests where meta-analyses were possible the highest sensitivity meta-estimate was found in the Cholera Screen test (98.6%, CI: 94.7%-99.7%) and the highest specificity meta-estimate in the Crystal VC on enriched samples (98.3%, CI: 92.8%-99.6%). There was a general lack of evidence regarding field use of tests, but where presented this indicated trends for lower diagnostic accuracy in field settings, with lesser-trained staff, and without the additional process of sample enrichment. Where reported, mean test turnaround times ranged from over 50% to 130% longer than manufacturer's specification. Most studies had a low to unclear risk of bias.
conclusionsCurrently available Rapid Diagnostic Tests can potentially provide high diagnostic and detection capability for cholera. However, stronger evidence is required regarding the conditions required to secure these levels of accuracy in field use, particularly in low-resource settings. REGISTRATION: PROSPERO (CRD42016048428).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.