Factors associated with visual outcomes after cataract surgery: A cross-sectional or retrospective study in Liberia

The Better Operative Outcomes Software Tool (BOOST) Prospective Study: Improving the Quality of Cataract Surgery Outcomes in Low-Resource Settings

PURPOSE

Post-operative vision impairment is common among patients who have undergone cataract surgery in low-resource settings, impacting quality of clinical outcomes and patient experience. This prospective, multisite, single-armed, pragmatic validation study aimed to assess whether receiving tailored recommendations via the free Better Operative Outcomes Software Tool (BOOST) app improved surgical outcomes, as quantified by post-operative unaided distance visual acuity (UVA) measured 1-3 days after surgery.

METHODS

During the baseline data collection round, surgeons in low and middle-income countries recorded clinical characteristics of 60 consecutive cataract cases in BOOST. Additional data on the causes of poor outcomes from 20 consecutive cases with post-operative UVA of <6/60 (4-12 weeks post-surgery) were entered to automatically generate tailored recommendations for improvement, before 60 additional consecutive cases were recorded during the follow-up study round. Average UVA was compared between cases recorded in the baseline study round and those recorded during follow-up.

RESULTS

Among 4,233 cataract surgeries performed by 41 surgeons in 18 countries, only 2,002 (47.3%) had post-operative UVA 6/12 or better. Among the 14 surgeons (34.1%) who completed both rounds of the study (1,680 cases total), there was no clinically significant improvement in post-operative average UVA (logMAR units ±SD) between baseline (0.50 ± 0.37) and follow-up (0.47 ± 0.36) rounds (mean improvement 0.03, p = 0.486).

CONCLUSIONS

Receiving BOOST-generated recommendations did not result in improved UVA beyond what could be expected from prospective monitoring of surgical outcomes alone. Additional research is required to assess whether targeted support to implement changes could potentiate the uptake of app-generated recommendations and improve outcomes.

Comparison of cataract surgery outcomes between a secondary and a tertiary eye hospital in Tamil Nadu, India

PURPOSE

To examine the difference in post-operative visual outcomes of cataract surgeries between a tertiary and secondary centre at Aravind Eye Hospitals in Tamil Nadu, India.

METHODS

Our retrospective cross-sectional study analysed cataract surgeries at a secondary centre and its associated tertiary centre in 2021. Our main outcome measures were postoperative best corrected visual acuity (BCVA), spherical equivalent, and intraoperative and postoperative complications. Two-sample proportion tests and logistic regression analyses were performed.

RESULTS

The analysis of 32,302 cataract surgeries in 2021 of which 4357 were performed at the secondary centre and 27,945 were performed at the tertiary centre showed that the tertiary centre operated on more advanced cataract condition (p < 0.001). Intraoperative (p < 0.001) and post-operative complication rates (p < 0.001) were higher in the tertiary centre. The odds of effective outcomes (BCVA > = 6/12) controlling for all covariates are poorer (p < 0.0001) in the tertiary centre for both phacoemulsification (phaco) and manual small incision cataract surgeries (MSICS).

CONCLUSION

World Health Organization recommendations for the effective outcome of cataract surgery are met by both the tertiary and secondary centres, but the odds of effective outcomes in the tertiary centre was lower after adjusting for all known factors. Further investigations of the causes of poor vision in both phaco and MSICS in the tertiary centre are needed to improve the situation.

Factors Influencing Visual Improvement after Phacoemulsification Surgery among Malaysian Cataract Patients

Blindness and visual impairment are part of the global burden of eye disease, with cataract being one of the leading causes of blindness. This study aimed to determine the factors affecting visual acuity (VA) improvement among cataract patients after phacoemulsification surgery in Malaysia. Cataract patients aged over 18 who underwent phacoemulsification surgery between January 2014 and December 2018 were included in this retrospective cohort study. Patients' sociodemographic, comorbidities, surgical, and related complication factors were extracted from the National Eye Database. The outcome was measured by the difference in visual acuity before and after the operation and was categorized as "improved", "no change", and "worse". A total of 180,776 patients were included in the final analysis. Multinomial logistic regression analysis showed "no changes in VA" was significantly higher in patients aged less than 40 years old (OR: 1.66; 95% CI: 1.22, 2.26), patients with ocular comorbidities (OR: 1.65; 95% CI: 1.53, 1.77), patients who had undergone surgery lasting more than 60 min (OR: 1.39; 95% CI: 1.14, 1.69), patients who had surgery without an intraocular lens (IOL) (OR: 1.64; 95% CI: 1.20, 2.26), and patients with postoperative complications (OR: 8.76; 95% CI: 8.13, 9.45). Worsening VA was significantly higher among male patients (OR: 1.11; 95% CI: 1.01, 1.22), patients who had ocular comorbidities (OR: 1.76; 95% CI: 1.59, 1.96), patients who had undergone surgery lasting more than 60 min (OR: 1.94; 95% CI: 1.57, 2.41), patients who had surgery without an IOL (OR: 2.03; 95% CI: 1.48, 2.80), and patients with postoperative complications (OR: 21.46; 95% CI: 19.35, 23.80). The factors impacting "no changes" in and "worsening" of VA after cataract surgery were the following: older age, male gender, ethnicity, ocular comorbidities, surgeon grade, absence of IOL, intraoperative complication, and postoperative problems.

Towards a Connected Mobile Cataract Screening System: A Future Approach

Advances in computing and AI technology have promoted the development of connected health systems, indirectly influencing approaches to cataract treatment. In addition, thanks to the development of methods for cataract detection and grading using different imaging modalities, ophthalmologists can make diagnoses with significant objectivity. This paper aims to review the development and limitations of published methods for cataract detection and grading using different imaging modalities. Over the years, the proposed methods have shown significant improvement and reasonable effort towards automated cataract detection and grading systems that utilise various imaging modalities, such as optical coherence tomography (OCT), fundus, and slit-lamp images. However, more robust and fully automated cataract detection and grading systems are still needed. In addition, imaging modalities such as fundus, slit-lamps, and OCT images require medical equipment that is expensive and not portable. Therefore, the use of digital images from a smartphone as the future of cataract screening tools could be a practical and helpful solution for ophthalmologists, especially in rural areas with limited healthcare facilities.

People to policy: The promise and challenges of big data for India

Big data holds great promise to help unravel insights to bridge the gap in human understanding. There has to be an emphasis on the quality of the data points being collected to ensure meaningful analysis. India has made significant strides to lay down a strong framework through the National Digital Health Blueprint and the National Health Stack for the future. There is a need to focus on the first important step of collection of a “good quality” data point through the implementation of electronic medical records by the health care providers. In India, 60 million individuals move below the poverty line every year because of the expenses related to unforeseen illness that adversely affects the individual's welfare and the nation's economic growth. With an out-of-pocket expense rate currently at 70% and the government's health budget at a mere 1.3% of its GDP (gross domestic product), data-driven decisions are the need of the hour for policy making and to ensure equitable, efficient, and excellent delivery of health care. There is a huge potential to harness the power of big data to generate insights to address the four big challenges of health care in India – availability, accessibility, affordability, and acceptability.