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Record W2427056634 · doi:10.1017/cjn.2016.191

P.089 Recovery from chronic secondary adrenal insufficiency in patients with pituitary disorders

2016· article· en· W2427056634 on OpenAlexvenueaboutno aff
Vicki Munro, Barna Tugwell, Steve Doucette, DB Clarke, André Lacroix, SA Imran

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2016
Typearticle
Languageen
FieldMedicine
TopicAdrenal Hormones and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGlucocorticoidAdrenal insufficiencyPituitary disorderInternal medicineSurgeryHormone

Abstract

fetched live from OpenAlex

Background: Patients with pituitary disorders may be placed on steroid replacement for secondary adrenal insufficiency (SAI), generally after pituitary surgery; however, data regarding recovery of long-term SAI are lacking. We conducted a study to assess the longer term recovery rate of SAI in patients with pituitary disorders. M ethods: We identified all SAI patients from prospectively entered data in the Halifax Neuropituitary Database from November 1, 2005 to September 30, 2014, who had required glucocorticoid therapy for >3 months, and a minimum follow-up of 6 months. Exclusion: ACTH-secreting adenomas; peri-operative glucocorticoid treatment only; glucocorticoids for non-pituitary conditions. Results: 55 patients fulfilled the criteria, 41 (75%) of which had transsphenoidal surgery. Nine (16.4%) patients had complete recovery of SAI over a median of 20 months (range: 8–51). Smaller tumour size and initial cortisol >175 nmol/L had increased likelihood of recovery; those with secondary hypogonadism or growth hormone deficiency were less likely to recover. Conclusions: This is the first study to examine long-term recover of SAI in patients with pituitary disorders: approximately 1 in 6 patients recover adrenal function, up to 5 years after diagnosis. Consequently, patients with SAI should undergo regular testing to prevent unnecessary chronic glucocorticoid therapy.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.166
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.006
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.220
Teacher spread0.209 · 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.

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

Citations0
Published2016
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences NeurologiquesSame topicAdrenal Hormones and DisordersFrench-language works237,207