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Customised 96-ocular TaqMan (iCAM) microarray PCR card for rapid diagnosis of microbial keratitis
Yunfei Yang1, Ahmed Roble2, Rashmi Deshmukh1
1Department of Ophthalmology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
BMJ Open Ophthalmology
|December 11, 2024
Summary
A new TaqMan PCR card (iCAM) accurately detects microbes causing microbial keratitis (MK) from a single corneal sample, offering faster results than traditional methods. This diagnostic tool shows promise for improving MK diagnosis and treatment.
Area of Science:
- Ophthalmology
- Microbiology
- Molecular Diagnostics
Background:
- Microbial keratitis (MK) is a significant cause of vision impairment.
- Accurate and rapid diagnosis of the causative microbe is crucial for effective treatment.
- Current diagnostic methods, including cultures, can be time-consuming.
Purpose of the Study:
- To validate the diagnostic performance of a custom 96-micro-organism TaqMan PCR card (iCAM) for detecting microbes in corneal epithelial samples.
- To compare the iCAM test's performance against conventional microbiological methods.
Main Methods:
- A prospective cohort study involving patients with MK was conducted.
- Corneal epithelial samples were analyzed using both the iCAM PCR test and conventional culture methods.
- Microbial detection rates and positive predictive values (PPV) were evaluated.
Main Results:
- The iCAM test identified a causative microbe in 44% of samples, comparable to conventional methods (44%).
- iCAM test processing time ranged from 6 to 24 hours, significantly faster than conventional tests (up to 7 days).
- The overall microbial detection rate was 65%, with a 62% correlation between methods; sensitivity was 56% and PPV was 60%.
Conclusions:
- The iCAM test effectively detects a broad range of microbial pathogens (bacteria, fungi, viruses, protozoa) from a single corneal sample.
- Limitations include a small patient cohort and sample volume constraints when split for multiple tests.
- A multicenter trial is planned to further validate the clinical impact of iCAM on diagnostic accuracy and patient outcomes.
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