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Record W2801998873 · doi:10.1111/hdi.12628

Atypical familial Mediterranean fever developed in a long‐term hemodialysis patient

2018· article· en· W2801998873 on OpenAlexvenueno aff
Toshiyuki Makino, Yoshitatsu Ohara, Namiko Kobayashi, Yohei Kono, Ayumu Nomizu, M. Ichijo, Yutaro Mori, Noriaki Matsui, Dai Kishida, Takayuki Toda

Bibliographic record

VenueHemodialysis International · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammasome and immune disorders
Canadian institutionsnot available
Fundersnot available
KeywordsFamilial Mediterranean feverMedicineSerositisHemodialysisColchicineFever of unknown originPediatricsAmyloidosisSurgeryDiseaseDermatologyInternal medicine

Abstract

fetched live from OpenAlex

Familial Mediterranean Fever (FMF) is usually an autosomal recessive autoinflammatory disease characterized by recurrent attacks of fever and serositis. FMF develops before the age of 20 years in 90% of patients. It has intervals of 1 week to several years between attacks, which leads to renal dysfunction-amyloidosis. We report a case of atypical FMF that developed in a long-term hemodialysis patient. A 65-year-old Japanese female undergoing hemodialysis for 32 years was referred to our hospital with a fever of unknown origin (FUO) following cervical laminoplasty. The fever occurred as recurrent attacks accompanied by oligoarthralgia of the left hip and knee. We suspected FMF because of recurrent self-limited febrile attacks, although the patient showed atypical clinical features such as late-onset and highly frequent attacks. After receiving treatment, she achieved a complete response to colchicine. Therefore, a diagnosis of FMF was made based on the Tel-Hashomer criteria, which was confirmed by genetic testing. The case suggests that FMF may be of note in long-term hemodialysis patients developing FUO.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.012
GPT teacher head0.260
Teacher spread0.248 · 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 designCase report
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

Citations1
Published2018
Admission routes1
Has abstractyes

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