Luminance contrast sensitivity and colour vision are considered to have great predictive value in the evaluation of type 2 diabetic retinopathy. However, these two visual characteristics have seldom been investigated in the same group of patients. In the present study we measured contrast sensitivity and colour vision in a group of patients with type 2 diabetes and correlated the results with estimates of common metabolic markers for the disease. A subgroup of the patients had no clinical signs of retinopathy.

Ishihara test is a color vision test, whose results consider that all plates of the test have the same weighting. Rodriguez-Carmona et al. (Aviat Space Environ Med 83:19–29, 2012) proposed an equation to quantify the Ishihara test results (severity index), which took an account the rate of hits from the different plates of the test considering the performance of trichromat or colorblind population. We proposed a correction in Rodiguez-Carmona’s equation for the severity index. We evaluated 60 normal trichromats and 107 subjects with congenital color deficiency. We calculated three indexes to quantify the results of each subject: a non-weighted index, a weighted index similar to the Rodriguez-Carmona et al., and a weighted index modified which combined the hit frequency for each plate in a trichromat population and of the error reading frequency for each plate in color-blind populations. Compared to the non-weighted evaluation, the weighted index was reduced by 22.95%, 32.92%, and 35.38% from trichromats, protan and deutan groups, respectively. Receiver Operating Characteristics (ROC) analysis showed perfect performance of the classifier for all metrics to measure the Ishihara test results. The proposal correction changed significantly the value of the index, but the overall benefits were small.

Background: Cryptococcosis, a systemic mycosis, remains a neglected disease in Brazil due to the absence of systematic national surveillance. This study developed an interactive dashboard to analyze cryptococcosis-related deaths (2000–2022) and forecast trends through regional ARIMA modeling. Methodology: The Cross-Industry Standard Process for Data Mining framework was employed to extract mortality data from the Brazilian Mortality Information System, utilizing the microdatasus package in R Studio software, with R version 3.4.0. The records were then filtered using the International Classification of Diseases, Tenth Revision codes (B45 series) to identify primary and associated causes of death. After data extraction, a series of data preprocessing steps was implemented, including deduplication, variable recoding, and the management of missing values. The Shiny framework was employed to construct an interactive dashboard, incorporating Plotly and DT packages, with time-series visualizations, demographic variables, and multilingual support (Portuguese/English). Results: Among 12,308 deaths (2227 primary; 10,081 associated causes), most occurred in males aged 21–60 years. Data completeness was high for age/residence (100%) but lower for education (82%). The dashboard enables dynamic exploration of trends, demographic patterns, and open-data downloads. Regional ARIMA models revealed heterogeneous forecasts, with the Southeast projecting a decline (193 deaths in 2025; 95% CI: 146–240) and the South showing stability (141 deaths; 95% CI: 109–173). Conclusions: This tool bridges a critical gap in cryptococcosis surveillance, enabling dynamic mortality trend analysis, identification of high-risk demographics, and regional forecasting to guide public health resource allocation. While the absence of HIV serostatus data limits etiological analysis, the dashboard’s open-source framework supports adaptation for other neglected diseases.