Incidence of Lyme disease in the United Kingdom and association with fatigue: a population-based, historical cohort study
Bibliographic record
Abstract
Abstract Objectives To evaluate incidence rates of Lyme disease in the UK and to investigate a possible association with subsequent fatigue Design Population-based historical cohort study with a comparator cohort matched by age, sex, and general practice Setting Patients treated in UK general practices contributing to IQVIA Medical Research Data Participants 2,130 patients with a first diagnosis of Lyme disease between 2000 and 2018, and 8,510 randomly-sampled matched comparators, followed-up for a median time of 3 years and 8 months. Main outcome measures Time from Lyme disease diagnosis to consultation for any fatigue-related symptoms or diagnosis and for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Adjusted hazard ratios (HRs) were estimated from Cox models. Results Average incidence rate for Lyme disease across the UK was 5.18 per 100,000 py between 2000 and 2018, increasing from 2.55 in 2000 to 9.33 in 2018. In total 929 events of any types of fatigue were observed, i.e. an incidence rate of 307.90 per 10,000 py in the Lyme cohort (282 events) and 165.60 in the comparator cohort (647 events). Effect of Lyme disease on any subsequent fatigue varied by index season with highest adjusted HRs in autumn [3.14 (95%CI: 1.92 to 5.13)] and winter [2.23 (1.21 to 4.11)]. Incidence rates of ME/CFS were 11.16 per 10,000 py in Lyme patients (12 events) and 1.20 in comparators (5 events), corresponding to an adjusted HR of 16.95 (5.17 to 55.60). Effect on any types of fatigue and ME/CFS was attenuated 6 months after diagnosis but still clearly visible. Conclusions UK primary care records provided strong evidence that Lyme disease was associated with acute and chronic fatigue. Albeit weaker, these effects persisted beyond 6 months, suggesting that patients and healthcare providers should remain alert to fatigue symptoms months to years following Lyme disease diagnosis. Key messages box What is already known on this topic Incidence rates of Lyme disease in the UK are increasing but estimations vary according to data sources used. Reports investigating the association between Lyme disease and long-term fatigue are contradictory. What this study adds Average incidence rate for Lyme disease across the UK was estimated at 5.18 per 100,000 py between 2000 and 2018, and followed an increasing trend. In patients with Lyme disease, a 2- and 3-fold increase in any subsequent fatigue was observed in winter and autumn, respectively, and a 16-fold increase in ME/CFS (all seasons combined), compared to a non-Lyme cohort matched by sex, age, and general practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".