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Record W2887722431 · doi:10.1093/rap/rky026

Long-term outcomes of patients with Takayasu arteritis and renal artery involvement: a cohort study

2018· article· en· W2887722431 on OpenAlexaffabout
Corisande Baldwin, Aladdin J Mohammad, Claire Cousins, Simon Carette, Christian Pagnoux, David Jayne

Bibliographic record

VenueRheumatology Advances in Practice · 2018
Typearticle
Languageen
FieldMedicine
TopicVasculitis and related conditions
Canadian institutionsUniversity of TorontoUniversity of Calgary
FundersNIHR Cambridge Biomedical Research CentreReumatikerförbundetSvenska Läkaresällskapet
KeywordsMedicineInterquartile rangeRenal functionRenal arteryTakayasu's arteritisRetrospective cohort studyCohortArteritisSurgeryTakayasu arteritisDemographicsInternal medicineKidneyVasculitis

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe the long-term outcomes of patients with Takayasu arteritis (TAK) and renal artery involvement (RAI). METHODS: A retrospective review of 122 patients with TAK at three tertiary centres in Canada, Sweden and the UK. Data on demographics, laboratory and clinical parameters, medications and angiography findings were collected. Non-renal and renal parameters were compared at baseline and follow-up. RESULTS: . Five underwent endovascular intervention and three required surgical interventions. Among the 33 patients with radiologic follow-up, 23 (69%) had persistent RAI and 10 (30%) had resolution of RAI. One (6%) patient with unilateral RAI developed bilateral RAI and three (19%) with bilateral RAI regressed to unilateral RAI. Over time, 23 (62%) patients had stable renal function, 7 (19%) had improvement and 4 had a decline in renal function; no patient developed end-stage renal disease (ESRD). CONCLUSION: In this series of TAK patients with RAI, long-term non-renal and renal outcomes were favourable. No patient experienced ESRD or died.

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 score0.005
Threshold uncertainty score0.429

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 communication0.0000.001
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 head0.008
GPT teacher head0.293
Teacher spread0.286 · 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

Citations15
Published2018
Admission routes2
Has abstractyes

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