Objective: To determine the incidence of dry eye in patients undergoing clear cornea phacoemulsification and to investigate its effects on dry eye symptoms and tear function. Methods: This was a single-center, prospective, non-randomized study involving forty-nine (49) eyes from fortyfour (44) patients without preoperative dry eye, who underwent clear cornea phacoemulsification for age-related cataract. Main outcome measures were subjective grading of ocular discomfort, ocular surface disease index (OSDI), fluorescein tear break-up time (FTBUT), and Schirmer tests without anesthesia and with anesthesia. They were measured before surgery and 1 week, 1 month, and 3 months after surgery. Results: None of the patients qualified for the definition of dry eye disease before and after clear cornea phacoemulsification. Preoperative FTBUT (14.01 ± 0.56 seconds) decreased at 1 week (3.97 ± 0.21 seconds; p<0.001) and at 1 month (5.82 ± 0.32 seconds; p<0.001) after the surgery and gradually improved by 3 months (8.26 ± 0.54 seconds; p<0.001) after surgery. Preoperative Schirmer test without anesthesia (18.78 ± 1.17 mm) decreased at 1 week (14.02 ± 1.52 mm; p<0.001) and subsequently recovered by 3 months (16.31 ± 1.34 mm; p>0.05). Preoperative Schirmer test with anesthesia (14.24 ± 0.94 mm) decreased at 1 week (11.98 ± 1.00 mm; p=0.046) after surgery and went back to baseline levels by 3 months (13.80 ± 1.12 mm; p>0.05). Conclusion Patients without dry eye disease, who underwent clear cornea phacoemulsification, did not develop dry eye disease after the surgery. Temporary reduction in physiologic tear levels seen one week postsurgery gradually returned to near-normal baseline levels by the third postoperative month.
Dry Eye Syndromes ; Phacoemulsification

OBJECTIVE

To assess the diagnostic accuracy of point-of-care screening using Medios™ Artificial Intelligence (AI) in the diagnosis of diabetic retinopathy (DR).

METHODS

This is a multi-center, cross-sectional, instrument validation study among adult Filipinos with Type 2 diabetes seen at Endocrine specialty clinics from May to November 2021. Retinal images were captured by a minimally trained nurse using the Remedio Fundus on Phone (FOP). Images were interpreted separately by the Medios™ AI and three retina specialists. The primary outcome measure is the accuracy of Medios™™ AI in diagnosing DR compared to retina specialists’ findings using sensitivity and specificity, predictive values, and likelihood ratios.

RESULTS

A total of 182 subjects with Type 2 diabetes were included in the study. The sensitivity and specificity of the Medios™ AI in diagnosing any DR were 73.68% (95%CI, 57.99-85.03) and 83.74% (95%CI, 79.35-87.35), respectively, compared with the retinal specialists’ findings using the same images. The positive and negative predictive values were 34.57% (95%CI, 25.12-45.41) and 96.47% (95%CI, 93.62-98.07). The positive and negative likelihood ratios were 4.53 (95%CI, 4.26 4.82) and 0.31 (95%CI, 0.26-0.38). The overall diagnostic accuracy of Medios™ AI in detecting DR was 82.69% (95%CI, 78.47-86.23).

CONCLUSION

The Medios™ AI system showed acceptable diagnostic accuracy when used as a point-of-care screening tool in detecting DR among patients with Type 2 diabetes seen at Endocrine specialty clinics. This technology can be a useful screening tool for endocrinologists as it is relatively inexpensive, safe, and easily performed. It can also shorten the lead time from screening to referral and intervention.

Human ; Diabetes Mellitus ; Diabetic Retinopathy