To assess if the antecedent statin use was associated with all-cause death among COVID-19 patients enrolled in Medicaid.

Cohort study.

Mississippi Medicaid population.

This study included 10 792 Mississippi Medicaid-enrolled patients between 18 and 64 years of age with a confirmed COVID-19 diagnosis from March 2020 to June 2021.

Antecedent statin use, which was determined by a record of statin prescription in the 90-day period prior to the COVID diagnosis.

The outcomes of interest included mortality from all cause within 30 days, 60 days and 90 days after index.

A total of 10 792 patients with COVID-19 met the inclusion and exclusion criteria, with 13.1% of them being antecedent statin users. Statin users were matched 1:1 with non-users based on age, sex, race, comorbidities and medication use by propensity score matching. In total, the matched cohort consisted of 1107 beneficiaries in each group. Multivariable logistic regression showed that statin users were less likely to die within 30 days (adjusted OR: 0.51, 95% CI: 0.32 to 0.83), 60 days (OR: 0.56, 95% CI: 0.37 to 0.85) and 90 days (OR: 0.55, 95% CI: 0.37 to 0.82) after diagnosis of COVID-19. Those with low-intensity/moderate-intensity statin use had significantly lower mortality risk in the 60-day and the 90-day follow-up period, while the high intensity of statin use was only found to be significantly associated with a lower odd of mortality within 30 days post index.

After COVID infection, Medicaid beneficiaries who had taken statins antecedently could be at lower risk for death. For patients with chronic conditions, continuity of care is crucial when interruptions occur in their medical care. Further research is required to further investigate the potential mechanisms and optimal use of statins in COVID-19 treatment.

The English National Health Service (NHS) Diabetic Eye Screening Programme (DESP) performs around 2.3 million eye screening appointments annually, generating approximately 13 million retinal images that are graded by humans for the presence or severity of diabetic retinopathy. Previous research has shown that automated retinal image analysis systems, including artificial intelligence (AI), can identify images with no disease from those with diabetic retinopathy as safely and effectively as human graders, and could significantly reduce the workload for human graders. Some algorithms can also determine the level of severity of the retinopathy with similar performance to humans. There is a need to examine perceptions and concerns surrounding AI-assisted eye-screening among people living with diabetes and NHS staff, if AI was to be introduced into the DESP, to identify factors that may influence acceptance of this technology.

People living with diabetes and staff from the North East London (NEL) NHS DESP were invited to participate in two respective focus groups to codesign two online surveys exploring their perceptions and concerns around the potential introduction of AI-assisted screening.

Focus group participants were representative of the local population in terms of ages and ethnicity. Participants’ feedback was taken into consideration to update surveys which were circulated for further feedback. Surveys will be piloted at the NEL DESP and followed by semistructured interviews to assess accessibility, usability and to validate the surveys.

Validated surveys will be distributed by other NHS DESP sites, and also via patient groups on social media, relevant charities and the British Association of Retinal Screeners. Post-survey evaluative interviews will be undertaken among those who consent to participate in further research.

Ethical approval has been obtained by the NHS Research Ethics Committee (IRAS ID: 316631). Survey results will be shared and discussed with focus groups to facilitate preparation of findings for publication and to inform codesign of outreach activities to address concerns and perceptions identified.