Predictors of incomplete COVID-19 vaccine schedule among adults in Scotland: Two retrospective cohort analyses of the primary schedule and third dose

Deriving and validating a risk prediction model for long COVID: a population-based, retrospective cohort study in Scotland

OBJECTIVES

Using electronic health records, we derived and internally validated a prediction model to estimate risk factors for long COVID and predict individual risk of developing long COVID.

DESIGN

Population-based, retrospective cohort study.

SETTING

Scotland.

PARTICIPANTS

Adults (≥18 years) with a positive COVID-19 test, registered with a general medical practice between 1 March 2020 and 20 October 2022.

MAIN OUTCOME MEASURES

Adjusted odds ratios (aORs) with 95% confidence intervals (CIs) for predictors of long COVID, and patients' predicted probabilities of developing long COVID.

RESULTS

A total of 68,486 (5.6%) patients were identified as having long COVID. Predictors of long COVID were increasing age (aOR: 3.84; 95% CI: 3.66-4.03 and aOR: 3.66; 95% CI: 3.27-4.09 in first and second splines), increasing body mass index (BMI) (aOR: 3.17; 95% CI: 2.78-3.61 and aOR: 3.09; 95% CI: 2.13-4.49 in first and second splines), severe COVID-19 (aOR: 1.78; 95% CI: 1.72-1.84); female sex (aOR: 1.56; 95% CI: 1.53-1.60), deprivation (most versus least deprived quintile, aOR: 1.40; 95% CI: 1.36-1.44), several existing health conditions. Predictors associated with reduced long COVID risk were testing positive while Delta or Omicron variants were dominant, relative to when the Wild-type variant was dominant (aOR: 0.85; 95% CI: 0.81-0.88 and aOR: 0.64; 95% CI: 0.61-0.67, respectively) having received one or two doses of COVID-19 vaccination, relative to unvaccinated (aOR: 0.90; 95% CI: 0.86-0.95 and aOR: 0.96; 95% CI: 0.93-1.00).

CONCLUSIONS

Older age, higher BMI, severe COVID-19 infection, female sex, deprivation and comorbidities were predictors of long COVID. Vaccination against COVID-19 and testing positive while Delta or Omicron variants were dominant predicted reduced risk.

SARS-CoV-2 vaccine uptake and risks of severe COVID-19 disease among people prescribed opioid agonist therapy in Scotland

BACKGROUND

There is limited evidence quantifying the risk of severe COVID-19 disease among people with opioid dependence. We examined vaccine uptake and severe disease (admission to critical care or death with COVID-19) among individuals prescribed opioid agonist therapy (OAT).

METHOD

A case-control design was used to examine vaccine uptake in those prescribed OAT compared with the general population, and the association between severe disease and OAT. In both analyses, 10 controls from the general population were matched (to each OAT recipient and COVID-19 case, respectively) according to socio-demographic factors. Conditional logistic regression was used to estimate rate ratios (RR) for severe disease.

RESULTS

Vaccine uptake was markedly lower in the OAT cohort (dose 1: 67%, dose 2: 53% and dose 3: 31%) compared with matched controls (76%, 72% and 57%, respectively). Those prescribed OAT within the last 5 years, compared with those not prescribed, had increased risk of severe COVID-19 (RR 3.38, 95% CI 2.75 to 4.15), particularly in the fourth wave (RR 6.58, 95% CI 4.20 to 10.32); adjustment for comorbidity and vaccine status attenuated this risk (adjusted RR (aRR) 2.43, 95% CI 1.95 to 3.02; wave 4 aRR 3.78, 95% CI 2.30 to 6.20). Increased risk was also observed for those prescribed OAT previously (>3 months ago) compared with recently (aRR 1.74, 95% CI 1.11 to 2.71).

CONCLUSIONS

The widening gap in vaccine coverage for those prescribed OAT, compared with the general population, is likely to have exacerbated the risk of severe COVID-19 in this population over the pandemic. However, continued OAT use may have provided protection from severe COVID-19 among those with opioid dependence.