ArticleTranslational vision science & technology2022
Assessment of Keratitis Severity Using Quantitative Image Analysis in an In Vivo Murine Model of Staphylococcus aureus Bacterial Keratitis.
Article in Translational vision science & technology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed, 5 citations in OpenAlex.
- Deep Learning-Based Classification of Slit-Lamp Photograph Quality in Microbial Keratitis.Ophthalmology science · 2026Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
Abstract
Purpose: Bacterial keratitis (BK) severity in murine models has traditionally been measured by subjective clinical grading or quantification of ocular bacterial burden. This investigation explores an objective and repeatable quantification of slit lamp photography (SLP) images to measure BK severity. Methods: BALB/c strain mice underwent three parallel scratches of the right cornea with subsequent inoculation of 107Staphylococcus aureus cells. SLP imaging and clinical severity grading were performed at 48 hours post-infection. Stromal infiltrate (SI) area on SLP images were quantified. Bacterial burden was determined after enucleation and homogenization. Spearman rank correlations (rs) were used to estimate associations between SI area, clinical severity grades, and bacterial burden. Results: BALB/c strain mice (n = 14) were evaluated with an average SI area of 0.92 mm2 (standard deviation, SD = 0.65) and average bacterial burden of 3.16 × 105 colony forming units per milliliter (CFU/mL) (SD = 8.3 × 105). Clinical severity grade positively correlated with SI area (rs = 0.59, p = 0.0276) and bacterial burden (rs = 0.66, p = 0.0106). There was a trend towards positive association between SI area and bacterial burden (rs = 0.51, p = 0.0543). Conclusions: SLP annotation of SI area is correlated with clinical severity and may provide an objective, quantitative, and repeatable assessment of BK disease severity. Translational Relevance: SLP annotation of SI area is a novel quantitative method to evaluate bacterial keratitis severity longitudinally in mouse models which may be a powerful tool to better understand BK pathogenesis and response to treatments.
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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.