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Record W4385511089 · doi:10.1051/ject/202153007

International Pediatric Perfusion Practice: 2016 Survey Results

2021· article· en· W4385511089 on OpenAlexaboutno aff
Thomas Klein, Jordan Voss, Vincent Olshove, Rajeev Gupta, Luiz Fernando Canêo, Robert C. Groom

Bibliographic record

VenueJournal of ExtraCorporeal Technology · 2021
Typearticle
Languageen
FieldEngineering
TopicMechanical Circulatory Support Devices
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePerfusionClinical PracticeEmergency medicineCardiologyFamily medicine

Abstract

fetched live from OpenAlex

New cardiopulmonary bypass device techniques emerge and are reported in the scientific literature. The extent to which they are actually adopted into clinical practice is not well known. Since 1989, we have periodically surveyed pediatric cardiac centers to ascertain practice patterns. In December 2016, a 186-question perfusion survey was distributed to pediatric cardiac surgery centers all over the world using a Web-based survey tool. Responses were received from 93 North American (NA) centers (the United States and Canada) and 67 non–NA (NNA) centers, representing 19,645 cumulative annual procedures in NA and 27,776 in NNA centers on patients <18 years. Wide variation in practice was evident across geographic regions. However, the most common pediatric circuit consisted of a hard-shell (open) venous reservoir, an arterial roller pump, and a hollow-fiber membrane oxygenator with a separate or integrated arterial filter. Compared with our previous surveys, there was increased utilization of all types of safety devices. The use of an electronic perfusion record was reported by 50% of NA centers and 31% of NNA centers. There was wide regional variation in cardioplegia delivery systems and cardioplegia solutions. Seventy-nine percent of the centers reported the use of some form of modified ultrafiltration. The survey demonstrated that there remains variation in perfusion practice for pediatric patients. Future surveys will be useful to evaluate the adoption of emerging perfusion practice guidelines.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.562
Threshold uncertainty score0.537

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.018
GPT teacher head0.269
Teacher spread0.251 · 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 designNot applicable
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

Citations23
Published2021
Admission routes1
Has abstractyes

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