Nugent score is a grading system that evaluates bacterial populations in vaginal samples to diagnose bacterial vaginosis. It helps standardize the identification of bacterial imbalances based on Gram-stained slides.
The Nugent score identifies shifts in vaginal microbiota by analyzing bacterial types like Lactobacilli, Gardnerella, and Mobiluncus. It assigns a score to determine whether the sample indicates normal flora, intermediate flora, or bacterial vaginosis.
The system focuses on Lactobacilli (Gram-positive rods), Gardnerella vaginalis (Gram-variable rods), and Mobiluncus species (Gram-negative curved rods). These bacteria are graded to assess the vaginal microbiota balance.
Manual Nugent scoring requires expertise to classify bacterial morphologies accurately. Challenges include subjectivity, variability in interpretation, and potential for human error in assessing Gram-stained slides.
Nugent score interpretation depends heavily on the examiner's experience and skill. Variability in training or technique can lead to inconsistent results, affecting diagnostic reliability.
Automation standardizes the scoring process by using AI to classify bacterial morphologies and calculate scores, reducing human error and variability. This improves accuracy and speeds up analysis.
AI automates the identification and classification of bacteria in Gram-stained images, providing consistent Nugent scores. It also streamlines the process, making it faster and less reliant on manual interpretation.
CarbConnect uses AI-powered image analysis to automate Nugent score calculations. It enables efficient scoring and secure sharing of results, supporting both clinical diagnostics assistant and microbiology research.
