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Record W1930277236 · doi:10.1111/hdi.12275

Renal involvement in mushroom poisoning: The case of <scp>O</scp>rellanus syndrome

2015· article· en· W1930277236 on OpenAlexvenueno aff
Pasquale Esposito, Edoardo La Porta, Marta Calatroni, Stefania Bianzina, Carmelo Libetta, Marilena Gregorini, Teresa Rampino, Antonio Dal Canton

Bibliographic record

VenueHemodialysis International · 2015
Typearticle
Languageen
FieldMedicine
TopicSilymarin and Mushroom Poisoning
Canadian institutionsnot available
Fundersnot available
KeywordsMushroom poisoningMedicineMushroomIngestionRenal injuryHemodialysisInterstitial nephritisToxinCrush syndromeAcute kidney injuryInternal medicineKidneyIntensive care medicineRenal replacement therapySurgeryPoison controlFood scienceEmergency medicineBiologyMicrobiology

Abstract

fetched live from OpenAlex

Although mushroom poisoning is a rare cause of acute renal injury, in some cases it may lead to the development of a severe and irreversible renal failure. Orellanus syndrome is the most important example of organic renal damage related to mushroom consumption. It is caused by the ingestion of orellanine, the main toxin of different types of Cortinarius mushrooms (Cortinarius speciosissimus, C. orellanus, C. orellanoides, etc.), and it is characterized by progressive clinical phases with a predominant kidney involvement, finally requiring renal replacement therapy in about 10% of cases. Renal damage is often late and associated with a histological picture of interstitial nephritis. Diagnosis is essentially clinical and no specific therapy has been shown to be effective in preventing and treating renal damage. Here, we describe the case of a patient with mixed wild mushroom poisoning, presenting the typical clinical signs and course of the Orellanus syndrome. This case offers us the opportunity to review the main clinical features of this severe and little-known intoxication.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.447
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.037
GPT teacher head0.291
Teacher spread0.255 · 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

Citations12
Published2015
Admission routes1
Has abstractyes

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