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Record W4388556770 · doi:10.1136/rmdopen-2023-003493

Association between infection and the onset of giant cell arteritis and polymyalgia rheumatica: a systematic review and meta-analysis

2023· review· en· W4388556770 on OpenAlexaboutno aff
L. Pacoureau, F. Barde, Raphaèle Séror, Yann Nguyen

Bibliographic record

VenueRMD Open · 2023
Typereview
Languageen
FieldMedicine
TopicVasculitis and related conditions
Canadian institutionsnot available
FundersUniversité Paris-SaclayFondation pour la Recherche MédicaleAgence Nationale de la Recherche
KeywordsMedicinePolymyalgia rheumaticaGiant cell arteritisMeta-analysisObservational studyInternal medicineEpidemiologyCohort studyOdds ratioVasculitisDisease

Abstract

fetched live from OpenAlex

OBJECTIVE: We aimed to analyse the association between infections and the subsequent risk of giant cell arteritis (GCA) and/or polymyalgia rheumatica (PMR) by a systematic review and a meta-analysis of observational studies. METHODS: Two databases (Medline and Embase) were systematically reviewed. Epidemiological studies studying the association between any prior infection and the onset of GCA/PMR were eligible. Risk of bias was assessed using the Newcastle-Ottawa quality assessment scale. Outcomes and pooled statistics were reported as OR and their 95% CI. RESULTS: (HZ) infections with pooled OR (95% CI) of 1.27 (1.18 to 1.37) and 1.20 (1.08 to 1.21), respectively. When analysed separately, hospital-treated and community-treated infections, were still significantly associated with the risk of GCA, but only when infections occurring within the year prior to diagnosis were considered (pooled OR (95% CI) 1.92 (1.67 to 2.21); 1.67 (1.54 to 1.82), respectively). This association was no longer found when infections occurring within the year prior to diagnosis were excluded. CONCLUSION: Our study showed a positive association between the risk of GCA and prior overall infections (occurring in the year before), and prior HZ infections. Infections might be the reflect of an altered immunity of GCA patients or trigger the disease. However, reverse causation cannot be excluded.CRD42023404089.

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)0.002
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: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.749
Threshold uncertainty score0.503

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0000.001
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 head0.075
GPT teacher head0.354
Teacher spread0.278 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations10
Published2023
Admission routes1
Has abstractyes

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