ReviewGalen medical journal2020
A Systematic Review of Screening Tests for Chronic Kidney Disease: An Accuracy Analysis.
Review in Galen medical journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Biomaterials for biomarker imaging and detection.Journal of advanced research · 2026Review
- Breath ammonia test for chronic kidney disease screening: impact of fasting on diagnostic accuracy.Clinical kidney journal · 2026Article
- Sudoscan's Effectiveness in Identifying Chronic Kidney Disease in Patients With Type 2 Diabetes.Cureus · 2024Article
- Potential Plasma Metabolite Biomarkers of Diabetic Nephropathy: Untargeted Metabolomics Study.Journal of personalized medicine · 2022Article
- The Effectiveness of Fluoride Varnish and Fissure Sealant in Elementary School Children: A Systematic Review and Meta-Analysis.Iranian journal of public health · 2022Review
- Cost-Effectiveness Analysis of Colorectal Cancer Screening: A Systematic Review.Risk management and healthcare policy · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This systematic review was conducted to assess the diagnostic accuracy of chronic kidney disease screening tests in the general population. MEDLINE, EMBASE, Web of Science, Scopus, The Cochrane Library and ProQuest databases were searched for English-language publications up to November 2016. Two reviewers independently screened studies and extracted study data in standardized tables. Methodological quality was assessed using the QUADAS-2 tool. Sensitivity and specificity of all available screening methods were identified through included studies. Ten out of 1349 screened records included for final analysis. Sensitivities of the dipstick test with a cutoff value of trace were ranged from 37.1% to 69.4% and specificities from 93.7% to 97.3% for the detection of ACR>30 mg/g. The diagnostic sensitivities of the UAC>10 mg/dL testing was shown to vary from 40% to 87%, and specificities ranged from 75% to 96%. While the sensitivities of ACR were fluctuating between 74% and 90%, likewise the specificities were between 77% and 88%. Sensitivities for C-G, Grubb and Larsson equations were 98.9%, 86.2%, and 70.1% respectively. In the meantime the study showed specificities of 84.8%, 84.2% and 90.5% respectively for these equations. Individual studies were highly heterogeneous in terms of target populations, type of screening tests, thresholds used to detect CKD and variations in design. Results pointed to the superiority of UAC and dipstick over the other tests in terms of all parameters involved. The diversity of methods and thresholds for detection of CKD, necessitate considering the cost parameter along with the effectiveness of tests to scale-up an efficient strategy.
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.