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Intramuscular Autotransplantation of Pancreatic Islets in a 7-Year-Old Child: A 2-Year Follow-Up

2008· article· en· W1585770671 on OpenAlexaff
Ehab Rafael, Annika Tibell, Mikael Rydén, Torbjörn Lundgren, Lars Sävendahl, Bengt Borgström, Urban Arnelo, B. Isaksson, Bo Nilsson, Olle Korsgren, Johan Permert

Bibliographic record

VenueAmerican Journal of Transplantation · 2008
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsPediatric Oncology Group
FundersVetenskapsrådet
KeywordsMedicineAutotransplantationIsletSurgeryTransplantationInternal medicineInsulin

Abstract

fetched live from OpenAlex

A 7-year-old girl with severe hereditary pancreatitis underwent total pancreatectomy. A total of 160,000 islet equivalents (6400 islet/kg) were transplanted to the brachioradialis muscle of the right forearm. Her plasma C-peptide level was undetectable after pancreatectomy but increased to 1.37 ng/mL after 17 days; at this time point, her insulin requirement was 0.75 units of insulin/kg/day. At 5- and 27-months, her hemoglobin A1c (HbA1c) and insulin requirements were 4.5 and 5.3% and 0.3 and 0.18 units/kg/day, respectively. Basal and stimulated C-peptide levels were 0.67 +/- 0.07 and 3.36 +/- 1.37 ng/mL, respectively. Stimulated insulin levels were 30% higher in the islet-bearing arm compared to the contralateral arm after glucagon stimulation. After surgery and islet transplantation, the quality of life improved dramatically and she gained 8 kg of weight. In summary, a normal HbA1c, a low insulin requirement and the absence of recurrent hypoglycemia and the gradient of insulin between the arms indicate that the intramuscularly transplanted islets contribute to a long-term clinically significant metabolic control.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0020.001
Science and technology studies0.0030.002
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.009
GPT teacher head0.233
Teacher spread0.225 · 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

Citations153
Published2008
Admission routes1
Has abstractno

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