Purpose: Corneal ulcer remains a major, ongoing health issue worldwide as it leads to blindness. The study analyzed the epidemiological patterns, microbiological profiles, antimicrobial resistance, and therapeutic outcomes trends across two time periods to assess changes associated with expanded diagnostic capacity. Methods: A 10-year retrospective research was conducted at Dr. Cipto Mangunkusumo Hospital, Jakarta (2015–2019, 2022– 2024). Clinical, microbiological, and treatment data were analyzed using chi-square tests and multivariable regression with propensity score matching to identify predictors of improvement. Results: A total of 1,100 eyes were examined. About two-thirds of patients were male, and the majority were aged 41 to 60 years, with trauma as the leading risk factor. Diagnostic testing increased markedly after 2022, revealing predominantly bacterial infections, most commonly Pseudomonas aeruginosa and coagulase-negative Staphylococci, with greater culture positivity and organism diversity. Antimicrobial resistance rose substantially, particularly to fluoroquinolones and aminoglycosides, whereas vancomycin (Gram-positive) and ceftazidime (Gram-negative) remained most effective. Clinical outcomes improved significantly in 2022–2024. Chi-square analysis showed ulcer location, size, depth, severity, and anterior chamber reaction were associated with improvement. Multivariable regression identified ulcer size, severity, surgical treatment, and later period as independent predictors of better outcomes, whereas antibiotic class did not independently influence healing. Conclusions Infectious corneal ulcer at our center remains predominantly bacterial, with evolving pathogen profiles and resistance patterns. Improved diagnostic access and standardized therapeutic protocols contributed to better outcomes. Routine culture testing and adherence to local resistance data are essential for guiding empiric therapy.

BACKGROUND : Diabetic retinopathy (DR) is a leading cause of preventable blindness. However, Indonesia lacks a comprehensive screening program. Artificial intelligence (AI)-assisted screening in primary health care (PHC) is a promising solution. Patient satisfaction is crucial for ensuring the participation and sustainability of such programs. This study aimed to adapt Indonesian version of evaluate client satisfaction questionnaire-18 (CSQ-18) and evaluate its acceptability. METHODS : This study was conducted from August 5–29, 2024 at 2 public PHCs in Jakarta. Patients with diabetes underwent DR screening, which included fundus photography and an AI-based grading system (RADR). Referable cases were graded secondarily by ophthalmologists. Satisfaction was assessed from November 10–20, 2024 using the Indonesian-translated CSQ-18, adapted through forward-backward translation, expert review, and pilot testing. Reliability was assessed using Cronbach’s alpha, validity was evaluated using Pearson’s correlation, and satisfaction scores were summarized as descriptive statistics. RESULTS : Of 300 selected participants, 216 completed telephone or in-person interviews. The Indonesian CSQ-18 demonstrated a strong internal consistency (Cronbach’s alpha = 0.886). All items showed acceptable item-total correlations. The mean (SD) satisfaction score was 60.19 (5.50) of 72, with a median of 59, indicating high patient satisfaction. Most participants expressed positive perceptions of screening duration, accessibility, and provider competence, although awareness-related items scored slightly lower. Potential interviewer bias and nonresponse may have affected the findings. CONCLUSIONS The Indonesian CSQ-18 is a reliable tool for assessing patient satisfaction with DR screening. These findings confirm the feasibility and acceptability of AI-assisted DR screening at the PHC level, supporting its potential for broader implementation in Indonesia.
artificial intelligence ; diabetic retinopathy ; patient satisfaction ; primary health care ; surveys and questionnaires