Determinants of persistent symptoms after treatment for Lyme borreliosis: a prospective observational cohort study
Bibliographic record
Abstract
BACKGROUND: Patients treated for Lyme borreliosis (LB) frequently report persistent symptoms. Little is known about risk factors and etiology. METHODS: In a prospective observational cohort study with a follow-up of one year, we assessed a range of microbiological, immunological, genetic, clinical, functional, epidemiological, psychosocial and cognitive-behavioral variables as determinants of persistent symptoms after treatment for LB. Between 2015 and 2018 we included 1135 physician-confirmed LB patients at initiation of antibiotic therapy, through clinical LB centers and online self-registration. Two reference cohorts of individuals without LB (n = 4000 and n = 2405) served as a control. Prediction analyses and association studies were used to identify determinants, as collected from online questionnaires (three-monthly) and laboratory tests (twice). FINDINGS: Main predictors of persistent symptoms were baseline poorer physical and social functioning, higher depression and anxiety scores, more negative illness perceptions, comorbidity, as well as fatigue, cognitive impairment, and pain in 295 patients with persistent symptoms. The primary prediction model correctly indicated persistent symptoms in 71.0% of predictions (AUC 0.79). In patients with symptoms at baseline, cognitive-behavioral responses to symptoms predicted symptom persistence. Of various microbiological, immunological and genetic factors, only lower IL-10 concentrations in ex vivo stimulation experiments were associated with persistent symptoms. Clinical LB characteristics did not contribute to the prediction of persistent symptoms. INTERPRETATION: Determinants of persistent symptoms after LB were mainly generic, including baseline functioning, symptoms and cognitive-behavioral responses. A potential role of host immune responses remains to be investigated. FUNDING: Netherlands Organisation for Health Research and Development (ZonMw); the Dutch Ministry of Health, Welfare and Sport (VWS).
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".