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Record W2037146606 · doi:10.1159/000162700

Adenohypophysial Necrosis in Respirator-Maintained Patients

2008· article· en· W2037146606 on OpenAlexaff
Katalin J. Kovács, J. M. Bilbao

Bibliographic record

VenuePathologia et Microbiologia · 2008
Typearticle
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsNecrosisCoagulative necrosisMedicineIschemiaLesionInfarctionInternal medicineAutopsyIncidence (geometry)PathologyIntracranial pressureCirculatory systemCardiologyEndocrinologySurgeryMyocardial infarction

Abstract

fetched live from OpenAlex

Fourteen cases of acute adenohypophysial necrosis were found among 76 patients maintained on mechanical respirators, indicating an increased incidence of adenohypophysial necrosis in these patients (18.4%), compared with that of an unselected autopsy material (1.1 %). Histologically, the lesions corresponded to coagulative infarctions and were due to suppression of blood flow to the anterior lobe. In many cases severe and widespread alterations were noted in the brain which might have interfered with pituitary circulation and by resulting in adenohypophysial ischemia could have been responsible for the development of infarction. In some other cases, however, no significant abnormalities were demonstrated in the brain, indicating that cerebral lesions and the associated elevation of intracranial pressure are not the only causative factors leading to circulatory disturbance of the anterior pituitary. No correlation was found between the duration of respirator therapy, the incidence and extent of adenohypophysial necrosis. Thus, it appears that the role of mechanical respirators is that they ‘buy time’ and by prolonging life they allow the advancement of the lesion to histologically recognizable infarction.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.033
GPT teacher head0.260
Teacher spread0.227 · 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

Citations6
Published2008
Admission routes1
Has abstractyes

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