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Record W1989704603 · doi:10.1097/mph.0b013e3181b27073

Comparison of Safety and Effectiveness of Two Different Transfusion Rates in Children With Severe Anemia

2009· article· en· W1989704603 on OpenAlexaff
Haşim Olgun, Mustafa Büyükavcı, Oğuzhan Sepetçigil, Zühal Keskin Yıldırım, Mehmet Karacan, Naci Cevi̇z

Bibliographic record

VenueJournal of Pediatric Hematology/Oncology · 2009
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsPediatric Oncology Group
Fundersnot available
KeywordsMedicineAnemiaBlood pressurePacked red blood cellsBlood transfusionHeart rateRegimenHeart failureVital signsAnesthesiaHemoglobinSurgeryInternal medicine

Abstract

fetched live from OpenAlex

We compared the safety and efficacy of 2 transfusion regimens in children with severe anemia (hemoglobin <5 g/dL) and without overt signs of congestive heart failure requiring transfusion of packed red blood cells (PRBCs). Forty-three patients were randomly divided into 2 groups: group A and group B. The transfusion regimens consisted of continuous infusion of PRBC at a rate of 1 mL/kg/h for group A and 3 mL/kg/h for group B. The patients were closely monitored for any clinical signs of heart failure throughout transfusion. Heart and respiratory rate, and arterial blood pressure were measured hourly for 6 hours during transfusion. None of the patients developed any signs of cardiac failure during or after the transfusion. The mean heart rate, respiratory rate, diastolic and systolic blood pressure were similar in both groups throughout transfusion. Group A needed significantly more PRBC units than group B to attain the same hemoglobin increase. Transfusion of PRBC at a rate of 3 mL/kg/h, and at a rate of 1 mL/kg/h, is a safe regimen for children with severe anemia of gradual onset requiring transfusion therapy.

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)0.002
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.011
GPT teacher head0.323
Teacher spread0.312 · 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

Citations9
Published2009
Admission routes1
Has abstractyes

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