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Predicting factors and prediction model for discriminating between fungal infection and bacterial infection in severe microbial keratitis.

ABSTRACT: A retrospective medical record review including 344 patients who were admitted with severe microbial keratitis at Ramathibodi Hospital, Bangkok, Thailand, from January 2010 to December 2016 was conducted. Causative organisms were identified in 136 patients based on positive culture results, pathological reports and confocal microscopy findings. Eighty-six eyes (63.24%) were bacterial keratitis, while 50 eyes (36.76%) were fungal keratitis. Demographics, clinical history, and clinical findings from slit-lamp examinations were collected. We found statistically significant differences between fungal and bacterial infections in terms of age, occupation, contact lens use, underlying ocular surface diseases, previous ocular surgery, referral status, and duration since onset (p < 0.05). For clinical features, depth of lesions, feathery edge, satellite lesions and presence of endothelial plaque were significantly higher in fungal infection compared to bacterial infection with odds ratios of 2.97 (95%CI 1.43-6.15), 3.92 (95%CI 1.62-9.45), 6.27 (95%CI 2.26-17.41) and 8.00 (95%CI 3.45-18.59), respectively. After multivariate analysis of all factors, there were 7 factors including occupation, history of trauma, duration since onset, depth of lesion, satellite lesions, endothelial plaque and stromal melting that showed statistical significance at p < 0.05. We constructed the prediction model based on these 7 identified factors. The model demonstrated a favorable receiver operating characteristic curve (ROC = 0.79, 95%CI 0.72-0.86) with correct classification, sensitivity and specificity of 81.48%, 70% and 88.24%, respectively at the optimal cut-off point. In conclusion, we propose potential prediction factors and prediction model as an adjunctive tool for clinicians to rapidly differentiate fungal infection from bacterial infection in severe microbial keratitis patients.

SUBMITTER: Jongkhajornpong P

PROVIDER: S-EPMC6426210 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Predicting factors and prediction model for discriminating between fungal infection and bacterial infection in severe microbial keratitis.

Jongkhajornpong Passara P Nimworaphan Jirat J Lekhanont Kaevalin K Chuckpaiwong Varintorn V Rattanasiri Sasivimol S

PloS one 20190320 3

A retrospective medical record review including 344 patients who were admitted with severe microbial keratitis at Ramathibodi Hospital, Bangkok, Thailand, from January 2010 to December 2016 was conducted. Causative organisms were identified in 136 patients based on positive culture results, pathological reports and confocal microscopy findings. Eighty-six eyes (63.24%) were bacterial keratitis, while 50 eyes (36.76%) were fungal keratitis. Demographics, clinical history, and clinical findings fr ...[more]

PMID: 30893373

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Project description:Microbial keratitis is a major cause of blindness worldwide. An excessive host inflammatory response can occur even after adequate antimicrobial treatment. This results in tissue damage with corneal thinning and even perforation, which may require corneal transplantation. In this study we investigated the pathways involved in the pathophysiology of this disease by comparing the human transcriptome profile of tissue from culture-proven bacterial and fungal keratitis (n=7 and n=8 respectively) with normal non-infected cadaveric corneal tissue (C, n=12) using Illumina HT12 v4 microarrays. The causative organisms were Streptococcus pneumoniae (n=6) and Pseudomonas aeruginosa (n=1) for bacterial keratitis (BK). Fungal keratitis (FK) was caused by Fusarium sp. (n=5), Aspergillus sp. (n=2, A. flavus and terreus) and Lasiodiplodia sp. (n=1). Differential expression (DE) analysis revealed 2310 significantly altered probes in the BK v C comparison, and 1813 probes for FK v C. The most highly upregulated gene in both comparisons was MMP9 with fold changes (FC) of 64 (fdr-adjusted p<6 x10-11) for FK v C and 89 for BK v C (fdr-adjusted p<4 x10-11) respectively. Network co-expression analyses revealed the defense response, inflammatory response and extracellular matrix mechanisms to be the main functional pathways involved. Microarray results were validated by performing real-time quantitative PCR (RTqPCR) for 46 DE genes using RNA extracted from the same samples. There was a high correlation between log2 FC values from microarray and RTqPCR. Further studies are needed to evaluate the most highly differentially expressed genes as possible biomarkers of disease progression or therapeutic targets. Case - control study design. Corneal ulcer tissue from 8 bacterial and 9 fungal ulcers was excised at the time of corneal transplantation surgery and immediately preserved in RNALater. Non-infected corneal tissue from 13 cadaver corneas were the control tissue. Transcriptome profile generated using Illumina HT12 v4 beadchips. Differential expression analysis was performed with pairwise comparisons: bacterial ulcers versus controls, fungal ulcers versus controls and bacterial versus fungal ulcers. Microarray results validated with RTqPCR.

Dataset Information

Predicting factors and prediction model for discriminating between fungal infection and bacterial infection in severe microbial keratitis.

Publications

Predicting factors and prediction model for discriminating between fungal infection and bacterial infection in severe microbial keratitis.

Similar Datasets

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