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Record W3118631287 · doi:10.1097/mpg.0000000000003036

Management of Central Venous Access in Children With Intestinal Failure

2020· article· en· W3118631287 on OpenAlexaff
Danielle Wendel, Ethan A. Mezoff, Vikram Raghu, Sivan Kinberg, Jason Soden, Yaron Avitzur, Jeffrey A. Rudolph, Michelle Gniadek, Valeria Cohran, Robert S. Venick, Conrad R. Cole

Bibliographic record

VenueJournal of Pediatric Gastroenterology and Nutrition · 2020
Typearticle
Languageen
FieldHealth Professions
TopicCentral Venous Catheters and Hemodialysis
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsMedicineIntestinal failureReferralIntensive care medicineVenous accessHepatologyShort bowel syndromeCentral venous catheterPopulationCentral lineInternal medicineParenteral nutritionSurgeryCatheterFamily medicineEnvironmental health

Abstract

fetched live from OpenAlex

ABSTRACT: Intestinal failure requires the placement and maintenance of a long-term central venous catheter for the provision of fluids and/or nutrients. Complications associated with this access contribute to significant morbidity and mortality, while the loss of access is an increasingly common reason for intestinal transplant referral. As more emphasis has been placed on the prevention of central line-associated bloodstream infections and new technologies have developed, care for central lines has improved; however, because care has evolved independently in local centers, care of central venous access varies significantly in this vulnerable population. The present position paper from the Intestinal Failure Special Interest Group of the North American Society for Pediatric Gastroenterology, Hepatology, and Nutrition (NASPGHAN) reviews current evidence and provides recommendations for central line management in children with intestinal failure.

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 score0.004
Threshold uncertainty score0.284

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 head0.020
GPT teacher head0.294
Teacher spread0.275 · 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

Citations59
Published2020
Admission routes1
Has abstractyes

Explore more

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