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Record W4389059995 · doi:10.1016/j.ebiom.2023.104825

Determinants of persistent symptoms after treatment for Lyme borreliosis: a prospective observational cohort study

2023· article· en· W4389059995 on OpenAlexaff
Hedwig D. Vrijmoeth, Jeanine Ursinus, Margriet Harms, Anna D. Tulen, M E Baarsma, Freek R. van de Schoor, Stefanie A. Gauw, Tizza P. Zomer, Yolande M. Vermeeren, José A. Ferreira, Hein Sprong, Kristin Kremer, Hans Knoop, Leo A. B. Joosten, Bart Jan Kullberg, Joppe W. Hovius, Cees C. van den Wijngaard

Bibliographic record

VenueEBioMedicine · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsInstitute of Infection and Immunity
FundersMinisterie van Volksgezondheid, Welzijn en SportZonMw
KeywordsMedicinePsychosocialObservational studyDepression (economics)Prospective cohort studyAnxietyCohortCohort studyPsychiatryInternal medicineClinical psychologyPediatrics

Abstract

fetched live from OpenAlex

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).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.560

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.293
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations36
Published2023
Admission routes1
Has abstractyes

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