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Record W2149679046 · doi:10.1155/2010/876013

Understanding of Abdominal Compartment Syndrome among Pediatric Healthcare Providers

2010· article· en· W2149679046 on OpenAlexaboutno aff
Janeth C. Ejike, Jennifer Newcombe, Joanne Baerg, Khaled Bahjri, Mudit Mathur

Bibliographic record

VenueCritical Care Research and Practice · 2010
Typearticle
Languageen
FieldMedicine
TopicAbdominal Surgery and Complications
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineQuarter (Canadian coin)Health careFamily medicinePediatrics

Abstract

fetched live from OpenAlex

Background. The sparse reporting of abdominal compartment syndrome (ACS) in the pediatric literature may reflect inadequate awareness and recognition among pediatric healthcare providers (HCP). Purpose. To assess awareness of ACS, knowledge of the definition and intraabdominal pressure (IAP) measurement techniques used among pediatric HCP. Method. A written survey distributed at two pediatric critical care conferences. Results. Forty-seven percent of 1107 questionnaires were completed. Participants included pediatric intensivists, pediatric nurses, and others. Seventy-seven percent (n = 513) of participants had heard of ACS. Only 46.8% defined ACS correctly. The threshold IAP value used to define ACS was variable among participants. About one-quarter of participants (83/343), had never measured IAP. Conclusion. Twenty-three percent of HCP surveyed were unaware of ACS. Criteria used to define ACS were variable. Focused education on recognition of ACS and measuring IAP should be promoted among pediatric HCP.

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)0.001
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.367
GPT teacher head0.502
Teacher spread0.135 · 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 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

Citations39
Published2010
Admission routes1
Has abstractyes

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