Long COVID demographic and secondary care referral characteristics in primary care: analysis of anonymised primary care data from a multiethnic, deprived urban area in the UK

Main findings

The key drivers to secondary care referral in our study were: older age (increased referrals); mixed ethnicity (reduced referrals); born in the UK (increased referrals); anxiety (increased referrals); diabetes (reduced referrals). Although Black ethnicity (reduced referrals) and female gender (increased referrals) had large AORs, these were uncertain given our sample size (not statistically significant).

Comparison with literature

In March 2023, the Office for National Statistics estimated that 1.9 million people in the UK (2.9% of the population) were experiencing self-reported Long COVID symptoms8. In terms of symptoms, fatigue was the most commonly reported symptom (72%) followed by difficulty concentrating (51%), muscle ache (49%) and shortness of breath (48%). These estimates were based on a household survey sent to almost 270,000 individuals and face-to-face interviews of selected samples. In a population study from Scotland, Long Covid prevalence, after adjustment for confounding, was 6.6% at 6 months in those with a history of acute infection9.

Studies of community prevalence are always likely to reveal higher prevalence estimates than studies conducted in primary care as a proportion of patients seek alternatives to primary care such as self-management approaches10. However, doubts have been raised about the clinical coding of Long COVID in UK primary care, suggesting substantial under-coding11. Based on a study of OpenSAFELY primary care data, the recorded prevalence of Long COVID in the London region was 55.6 per 100,000 (0.06%), much lower than in community estimates with just over a quarter of all practices reporting no diagnostic codes for Long COVID codes implying lack of coding rather than zero prevalence. In our study of an inner London, deprived and multiethnic borough, the prevalence was 0.36% and all practices had Long COVID codings. This higher rate than the London average probably represents higher acute COVID infection rates associated with the known acute Covid risk factors of social deprivation and multi-ethnicity12.

Strengths and weaknesses

Our findings relate to the secondary care referral characteristics of patients with a primary care diagnosis of Long COVID. The demographic characteristics of those patients referred with Long COVID may suggest health inequalities based on unequal referral thresholds for different sectors of the population. Alternatively, they may represent gradations of Long COVID severity or variable symptom patterns with some symptoms more likely than others to trigger referral13. This study based on Long COVID and co-morbidity diagnostic data was unable to determine disease severity and it is possible that, for example, Long COVID severity was greater in older patients with anxiety.

In our analysis, older age was a predictor of referral. However, age was skewed with small numbers of much older age Long Covid patients which may have distorted the regression model, resulting in an overestimate of the effect of age. Further research is needed on the differential effect of age categories, although our sample size in older patients was not sufficient for such analysis.

We included a variable in the regression analysis, ‘acute Covid: suspected/confirmed’. This variable was intended as a proxy indicator to capture those patients more engaged with primary care, since confirmation of an acute Covid diagnosis often relied on patients notifying their GP of the results of self-testing at home. However, this variable was not a significant predictor of Long Covid referral implying that help-seeking for acute Covid was not associated with secondary care help-seeking.

There may also have been differences in ‘coding threshold’ whereby GPs varied in their readiness to attach a Long COVID diagnostic label to a patient’s symptoms. However, our data shows no significant differences in referral thresholds between the three localities included in our study, implying few geographical differences between practices.

The overall prevalence estimate for Long COVID depended on identifying relevant SNOMED-CT codes, ensuring that no commonly used codes were omitted. Patients were only included if they had a formal diagnostic coding, and symptom coding based on the most commonly recorded Long COVID symptoms14 was not included. This could have substantially increased the estimated prevalence although records of symptom duration are less reliably obtained from electronic health records and therefore this was not included in our study.

Implications

Long COVID patients seen in secondary care services may be a selected population unrepresentative of the demographic characteristics of Long COVID in primary care. Epidemiological Long COVID studies need to consider a broader remit than secondary care populations. Further study is needed on the epidemiological characteristics of Long Covid in primary care, particularly in areas where our study may not translate so effectively, such as suburban or rural communities.

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