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Record W7044063040

Volume-dependent relationship of fresh compared to standard red blood cells in critically ill adults: a subgroup analysis of the age of blood evaluation trial

2017· dissertation· en· W7044063040 on OpenAlexaff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2017
Typedissertation
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsSubgroup analysisHazard ratioIntensive care unitCritically illBlood transfusionRandomized controlled trialProportional hazards modelClinical trial
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Red blood cells (RBCs) preserved for transfusion accumulate multiple changes over time, collectively termed the storage lesion. Stored RBCs have been associated with deleterious clinical outcomes, including increased risk of death, in non-randomized studies, however recent randomized trials have not shown a clinical benefit with fresh compared to standard RBCs. It is unclear if the effect of the storage lesion is associated with the volume of RBCs transfused. OBJECTIVE: To determine if the effect of fresh compared to standard RBC units on mortality in critically ill adults is volume-dependent. METHODS: Sub-group analysis of the Age of Blood Evaluation (ABLE) trial, a multi-center study that randomized adult patients admitted to the Intensive Care Unit (ICU) to receive fresh (stored ≤7 days) or standard-issue RBCs (distributed according to a first-in, first-out policy), was performed. In a pre-planned analysis, the hazard of death and adjusted survival at 90 days was compared between treatment arms for subjects receiving up to 3 RBCs, and subjects receiving more than 3 RBCs using Cox proportional hazards regression. Hazard ratios (HR) were adjusted for age, sex, number of RBCs transfused, APACHE II score and MODS at randomization, comorbid conditions, reason for admission to ICU, ICU type (trauma, medical, or surgical), type of admission (emergency or elective), co-transfusions, and duration of supportive care. Similar analyses were done for secondary endpoints of mortality at 28 days, 180 days, in-ICU, and in-hospital. The dose response was further explored using subgroups defined by smaller transfusion increments. RESULTS: Complete follow-up was available for 2430 patients (≤3 RBCs: 789 standard arm vs. 754 fresh arm; >3 RBCs: 430 standard arm vs. 457 fresh arm). The HR for 90-day mortality was 1.08 (95% CI 0.94-1.25) overall, 1.20 (95% CI 0.99-1.42) for patients transfused ≤3 RBCs, and 0.90 (95% CI 0.69-1.10) for patients transfused >3 RBCs. Similar trends were seen for other mortality endpoints. There was evidence of statistical interaction between the storage age and number of RBC units transfused on mortality at 90 and 180 days. The exploratory analysis suggested a dose-effect of fresh compared to standard blood, with lower hazard of death at all time-points for patients receiving 6 or more fresh RBC units. CONCLUSIONS: In the pre-planned subgroup analysis, there was a non-significant trend favouring standard RBCs in patients transfused ≤3 RBC units, while fresh RBCs were favoured in patients transfused >3 RBC units. More detailed analyses demonstrated a trend of increased hazard of death with fresh compared to standard RBC units for patients transfused up to 3 RBC units, and decreased hazard of death with fresh compared to standard RBCs for patients transfused more than 5 RBC units. Interaction between storage age and number of transfusions was statistically significant for mortality at 90 and 180 days. These findings suggest a volume-dependent effect of fresh RBCs on mortality in critically ill adults, although the findings should be interpreted cautiously as this subgroup analysis was primarily exploratory. The findings should be confirmed in other randomized trials.

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)0.005
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 score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.006
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.292
Teacher spread0.266 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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