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Record W3207288546 · doi:10.1530/ec-21-0386

Baseline MRI findings as predictors of hypopituitarism in patients with non-functioning pituitary adenomas

2021· article· en· W3207288546 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEndocrine Connections · 2021
Typearticle
Languageen
FieldMedicine
TopicPituitary Gland Disorders and Treatments
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsHypopituitarismPituitary adenomaPituitary stalkOptic chiasmaLogistic regressionAdenomaReceiver operating characteristicMagnetic resonance imaging

Abstract

fetched live from OpenAlex

Hypopituitarism tends to occur in large pituitary adenomas. However, similar tumors could present with strikingly different hormonal deficiencies. In this study, we looked at MRI characteristics in non-functioning pituitary adenomas (NFPA), which could predict secondary adrenal insufficiency (SAI) and central hypothyroidism (CHT). We reviewed the files of patients with NFPA attending our clinic. Tumor size, invasiveness, MR-signal intensity, and gadolinium enhancement in preoperative MRI were recorded along with documented presurgical hypopituitarism profile. Logistic regression was used to predict SAI, CHT, or both (SAI/CHT) based on MRI and demographic parameters. Receiver operating characteristic curves were used to determine their diagnostic utility. One hundred twenty-one patients were included in the study. Older age (P = 0.021), male sex (P = 0.043), stalk deviation (P < 0.0001), contrast enhancement (P = 0.029), and optic chiasma compression (P = 0.012) were associated with SAI/CHT. Adenoma vertical height, largest diameter, and estimated volume were also strongly associated with SAI/CHT (P < 0.0001). These associations remained significant in a multivariate analysis. No tumor smaller than 12 mm in vertical height, 17 mm in largest diameter, or 0.9 cm3 in volume was associated with SAI/CHT. At cut-off ≥18 mm for vertical height, ≥23 mm for largest diameter, and ≥3.2 cm3 the sensitivity was around 90-92% for detecting SAI/CHT. Only vertical height was significantly associated with any one or more pituitary hormonal deficit (P = 0.001). In conclusion, adenoma size, independent of the measurement used, remains the best predictor of SAI/CHT in NFPA. Dynamic testing to rule out SAI is probably indicated in adenomas larger than 18 mm vertical height, 23 mm largest diameter and 3.2 cm3 adenoma volume.

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.

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 score0.013
Threshold uncertainty score0.675

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.222
Teacher spread0.217 · 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