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Record W3181785310 · doi:10.1097/mpg.0000000000003218

Vascular Complications in Pediatric Pancreatitis

2021· article· en· W3181785310 on OpenAlexaff
Chinenye R. Dike, Gretchen A. Cress, Douglas S. Fishman, Tanja Gonska, Chee Y. Ooi, Emily R. Perito, David M. Troendle, Cynthia M. Tsai, Mark E. Lowe, Aliye Uç

Bibliographic record

VenueJournal of Pediatric Gastroenterology and Nutrition · 2021
Typearticle
Languageen
FieldMedicine
TopicPancreatitis Pathology and Treatment
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersNational Center for Advancing Translational SciencesNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsMedicinePancreatitisPseudoaneurysmThrombosisAcute pancreatitisVenous thrombosisSurgeryIncidence (geometry)SplanchnicVascular diseaseComplicationRadiologyBlood flow

Abstract

fetched live from OpenAlex

ABSTRACT: We reviewed INSPPIRE (International Study Group of Pediatric Pancreatitis: In Search for a Cure) database for splanchnic venous thrombosis or arterial pseudoaneurysms to determine the incidence, risk factors and outcomes of peripancreatic vascular complications in children with acute recurrent pancreatitis (ARP) or chronic pancreatitis (CP). Of 410 children with diagnostic imaging studies, vascular complications were reported in five (1.2%); two had ARP, three CP. The vascular events were reported during moderately severe or severe acute pancreatitis (AP) in four, mild AP in one. Venous thrombosis occurred in four, arterial pseudoaneurysm (left gastric artery) in one. Two patients with venous thrombosis were treated with anticoagulant, one achieved recanalization (splenic vein). In two patients who did not receive anticoagulants, one re-canalized. No adverse effects were observed with anticoagulants. The child with pseudoaneurysm underwent aneurysmal coiling. Anti-coagulants appear to be safe in children with acute pancreatitis, their long-term benefit needs to be further investigated.

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)0.000
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 score0.031
Threshold uncertainty score0.356

Codex and Gemma teacher scores by category

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

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 head0.253
Teacher spread0.242 · 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.

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

Citations10
Published2021
Admission routes1
Has abstractyes

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