Purpose: Microbial keratitis (MK) is a potentially blinding corneal disease caused by an array of microbial etiologies. However, the lack of early organism identification is a barrier to optimal care. We investigated clinician confidence in their diagnosis of organism type on initial presentation and the relationship between confidence and presenting features.
Methods: This research presents secondary data analysis of 72 patients from the Automated Quantitative Ulcer Analysis (AQUA) study. Cornea specialists reported their confidence in organism identification. Presenting sample characteristics were recorded including patient demographics, health history, infection morphology, symptoms, and circumstances of infection. The association between confidence and presenting characteristics was investigated with 2-sample t-tests, Wilcoxon tests, and Chi-square or Fisher's exact tests.
Results: Clinicians reported being "confident or very confident" in their diagnosis of the causal organism in MK infections for 39 patients (54%) and "not confident" for 33 patients (46%). Confidence was not significantly associated with patient demographics, morphologic features, or symptoms related to MK. MK cases where clinicians reported they were confident, versus not confident in their diagnosis, showed significantly smaller percentages of previous corneal disease (0% versus 15%, = 0.017), were not seen by an outside provider first (69% versus 94%, = 0.015), or had no prior labs drawn (8% versus 33%, = 0.046), and a significantly larger percentage of cases wore contact lenses (54% versus 28%, = 0.029).
Conclusion: In almost half of MK cases, cornea specialists reported lack of confidence in identifying the infection type. Confidence was related to ocular history and circumstances of infection but not by observable signs and symptoms or patient demographics. Tools are needed to assist clinicians with early diagnosis of MK infection type to expedite care and healing.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10922689 | PMC |
http://dx.doi.org/10.1080/02713683.2023.2288803 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!