MétaCan
Menu
Back to cohort
Record W2554186032 · doi:10.1093/jscr/rjw188

Insulinoma or non-insulinoma pancreatogenous hypoglycemia? A diagnostic dilemma

2016· article· en· W2554186032 on OpenAlexafffund
Blaire Anderson, Jordan J. Nostedt, Safwat Girgis, Tara Dixon, Veena Agrawal, Edward Wiebe, Peter Senior, A. M. James Shapiro

Bibliographic record

VenueJournal of Surgical Case Reports · 2016
Typearticle
Languageen
FieldMedicine
TopicNeuroendocrine Tumor Research Advances
Canadian institutionsUniversity of Alberta
FundersJuvenile Diabetes Research Foundation United States of AmericaAlberta InnovatesDiabetes Research Institute Foundation
KeywordsInsulinomaMedicineHypoglycemiaHyperinsulinemic hypoglycemiaDiazoxideNesidioblastosisOccultHyperinsulinismRadiologyInternal medicinePancreasGastroenterologyInsulinPathology

Abstract

fetched live from OpenAlex

Insulinoma is the most common cause of endogenous hyperinsulinemic hypoglycemia in adults. An alternate etiology, non-insulinoma pancreatogenous hypoglycemia (NIPH), is rare. Clinically, NIPH is characterized by postprandial hyperinsulinemic hypoglycemia, negative 72-h fasts, negative preoperative localization studies for insulinoma and positive selective arterial calcium infusion tests. Histologically, diffuse islet hyperplasia with increased number and size of islet cells is present and confirms the diagnosis. Differentiating NIPH from occult insulinoma preoperatively is challenging. Partial pancreatectomy is the procedure of choice; however, recurrence of symptoms, although less debilitating, occurs commonly. Medical management with diazoxide, verapamil and octreotide can be used for persistent symptoms. Ultimately, near-total or total pancreatectomy may be necessary. We report a case of a 67-year-old male with hypoglycemia in whom preoperative workup, including computerized tomography abdomen, suggested insulinoma, but whose final diagnosis on pathology was NIPH instead.

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)0.003
metaresearch head score (Gemma)0.012
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 score0.008
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0020.004
Scholarly communication0.0030.006
Open science0.0030.003
Research integrity0.0080.007
Insufficient payload (model declined to judge)0.0020.002

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 head0.026
GPT teacher head0.315
Teacher spread0.289 · 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

Citations11
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Surgical Case ReportsSame topicNeuroendocrine Tumor Research AdvancesFrench-language works237,207