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Record W2771241464 · doi:10.3389/fmed.2017.00224

The Clinical, Symptom, and Quality-of-Life Characterization of a Well-Defined Group of Patients with Posttreatment Lyme Disease Syndrome

2017· article· en· W2771241464 on OpenAlexaboutno aff
Alison W. Rebman, Kathleen T. Bechtold, Ting Yang, Erica A. Mihm, Mark J. Soloski, Cheryl B. Novak, John N. Aucott

Bibliographic record

VenueFrontiers in Medicine · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsnot available
FundersSteven and Alexandra Cohen FoundationGlobal Lyme Alliance
KeywordsMedicineLyme diseasePittsburgh Sleep Quality IndexInternal medicineQuality of life (healthcare)Depression (economics)Incidence (geometry)Borrelia burgdorferiPhysical therapyPsychiatryImmunologySleep qualityInsomnia

Abstract

fetched live from OpenAlex

Background: The increased incidence and geographic expansion of Lyme disease has made it the most common vector-borne infection in North America. Post-treatment Lyme disease syndrome (PTLDS) represents a subset of patients who remain ill following standard antibiotic therapy for Lyme disease. The spectrum of symptoms and their impact on quality of life remain largely unexplored among patients with well-documented PTLDS. Objective: To characterize a case series of patients with well-documented PTLDS compared to a sample of healthy controls. Methods: Sixty-one participants met the proposed case definition for PTLDS. Twenty-six healthy controls had neither a clinical history of Lyme disease nor current antibodies to B. burgdorferi. Participants with PTLDS and controls were evaluated by physical exam, clinical laboratory testing, standardized questionnaires, and a 36-item current symptom list. Results: Compared to controls, participants with PTLDS reported significantly greater fatigue, pain, sleep disturbance, and depression (Fatigue Severity Scale: 50.0+/-10.6 vs.19.9+/-8.6; Short Form McGill Pain Questionnaire: 13.8+/-8.3 vs. 0.8+/-1.9; Pittsburgh Sleep Quality Index: 10.1+/-4.7 vs. 4.1+/-2.1; Beck Depression Inventory-II: 15.1+/-7.7 vs. 2.2+/-3.2; p<0.001 for each), and significantly lower quality of life (SF-36 Physical Component Score: 33.9+/-9.7 vs. 55.1+/-6.2; Mental Component Score: 42.9+/-10.1 vs. 54.2+/-5.4; p<0.001 for each). Nineteen non-PTLDS-defining symptoms were found to be significantly more severe among participants with PTLDS than controls, including sleep difficultly and visual complaints. Initial delayed or misdiagnosis was characterized in 59.0% of participants with PTLDS, and 32.2% had abnormal vibratory sense. Conclusions: Although physical exam and clinical laboratory tests showed few objective abnormalities, standardized symptom questionnaires revealed that patients with PTLDS are highly and clinically significantly symptomatic, with poor health-related quality of life. PTLDS patients exhibited levels of fatigue, musculoskeletal pain, sleep disturbance, and depression which were both clinically relevant and statistically significantly higher than controls. Our study shows that PTLDS can be successfully identified using a systematic approach to diagnosis and symptom measurement. As the prevalence of PTLDS continues to rise, there will be an increased need for physician education to more effectively identify and manage PTLDS as part of integrated patient care.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.286
Teacher spread0.267 · 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 source (direct Gemma or distilled Codex), 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

Citations125
Published2017
Admission routes1
Has abstractyes

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