ArticleJournal of clinical laboratory analysis2019
Optimization of
Article in Journal of clinical laboratory analysis, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
What it found
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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
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A comparative systematic review and meta-analysis on the diagnostic accuracy of non-invasive tests forFrontiers in medicine · 2023Pooled it
- Prevalence of Helicobacter pylori infection in the general population in Wuzhou, China: a cross-sectional study.Infectious agents and cancer · 2025Article
- The Aging Stomach: Clinical Implications ofInternational journal of molecular sciences · 2024Review
- Focusing onFrontiers in cellular and infection microbiology · 2023Review
- Helicobacter pylori Infection, Its Laboratory Diagnosis, and Antimicrobial Resistance: a Perspective of Clinical Relevance.Clinical microbiology reviews · 2022Review
- Synthetic biomarkers: a twenty-first century path to early cancer detection.Nature reviews. Cancer · 2021Review
- What Is New inJournal of clinical medicine · 2021Review
- Review
- Association betweenJournal of diabetes research · 2020Article
- Optimization ofJournal of clinical laboratory analysis · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThreshold values for
methodsConsecutive test samples collected at our central laboratory from patients undergoing a first-time 13C-UBT between 1 January 2010 and 31 December 2015 were included. The difference between values at 30 minutes and at baseline (T30-T0) was expressed as delta over baseline (DOB). Cluster analysis was performed on the 13C-UBT test results to determine the optimal cutoff point with minimal interclass variance.
resultsTwo lakhs thirty four thousand eight hundred thirty one patients (87 291 (37.2%) male, age 39.9 ± 19.9) underwent a first-time 13C-UBT, including 124 701 (53.1%) negative and 110 130 (46.9%) positive tests, using the manufacturer-recommended cutoff of 3.5 DOB. Cluster analysis determined an optimized cutoff of 2.74 DOB, representing an additional 2180 (0.93%) positive subjects who had been previously categorized as negative according to the manufacturer-specified cutoff of 3.5 DOB. Mean positive and negative DOB values were 19.54 ± 14.95 and 0.66 ± 0.51, respectively. The cutoffs for male and female subjects were 2.23 and 3.05 DOB, respectively. Threshold values for <45-year-olds, 45-60-year-olds and >60-year-olds were 2.67, 2.55, and 2.93 DOB, respectively. Of the 2180 (0.93%) patients with DOB 2.73-3.49, 289 (13.3%) performed a subsequent 13C-UBT and 140 (48.4%) remained positive when tested at 20.3 ± 14.4 months.
conclusionsMajor referral laboratories should optimize threshold values for 13C-UBT positivity for their geographical location. Different cutoff values should be applied for male and female subjects.
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