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Record W2171575717 · doi:10.1093/ndt/gfl265

Continuous renal replacement therapy (CRRT) in children using the AQUARIUS™

2006· article· en· W2171575717 on OpenAlexaffabout
Daljit K. Hothi, Cecilia St. George-Hyslop, Denis F. Geary, Desmond Bohn, Elizabeth Harvey

Bibliographic record

VenueNephrology Dialysis Transplantation · 2006
Typearticle
Languageen
FieldMedicine
TopicRenal function and acid-base balance
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineRenal replacement therapyIntensive care medicineHemodialysisSurgery

Abstract

fetched live from OpenAlex

1Division of Nephrology and 2Pediatric Critical Care Unit, Hospital for Sick Children, Toronto, Canada Continuous renal replacement therapy (CRRT) is the preferred choice for blood purification and volume control in critically ill children [1,2]. The reported overall survival rate for children requiring CRRT is 60% [3], and mortality in infants is comparable with that of older children and adolescents [4]. It is imperative in paediatric CRRT that equipment be adaptable to accommodate large variations in size (2–100 kg). Until recently at the Hospital for Sick Children, CRRT was provided using the PRISMA™ (Gambro AB, Stockholm, Sweden) circuits designed for adult use. A ‘Hot-Line™’(Smiths-Level 1 Inc., Rockland, MA) blood warmer prevented hypothermia but increased the extracorporeal circuit volume by 25 ml, which then exceeded 10% of the blood volume for patients weighing <15 kg. The PRISMA M10™, a 50 ml paediatric circuit, reduced the weight for a blood prime to ≤8 kg, but we elected not to use it given its limited functional capabilities based on product specifications. The PRISMA™ haemofilter AN69 membrane is associated with a ‘bradykinin release phenomenon’ on contact with acidotic blood including a blood prime [5], producing transient, but potentially life-threatening cardiovascular instability [6,7]. Protocols to overcome this, incorporating administration of large doses of alkali and calcium to the patient [8], are labour-intensive and were, in our experience, largely unsuccessful.

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 score0.217
Threshold uncertainty score0.403

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 head0.010
GPT teacher head0.249
Teacher spread0.239 · 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

Citations14
Published2006
Admission routes2
Has abstractyes

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