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Record W2003150160 · doi:10.1097/ccm.0000000000000675

Male-Predominant Plasma Transfusion Strategy for Preventing Transfusion-Related Acute Lung Injury

2014· review· en· W2003150160 on OpenAlexaff
Christopher N. Schmickl, Stefano Mastrobuoni, Filippos T Filippidis, Suchita Shah, Julia Anne Elisabeth Radic, M. Hassan Murad, Pearl Toy, Ognjen Gajic

Bibliographic record

VenueCritical Care Medicine · 2014
Typereview
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineTransfusion-related acute lung injuryPopulationIncidence (geometry)Relative riskEmergency medicineBlood transfusionIntensive care medicineInternal medicineLungConfidence intervalEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVES: To assess 1) the effectiveness of male-predominant plasma transfusion strategy for preventing transfusion-related acute lung injury and related mortality; and 2) whether this effect varies across different patient subgroups. DESIGN: Systematic Review and meta-analysis: Data were identified by querying MEDLINE and EMBASE (including proceedings of major conferences on blood transfusions), searching the Internet for hemovigilance reports, reviewing reference lists of eligible articles and contacting experts in the field. Eligible were all studies reporting transfusion-related acute lung injury incidence, all-cause mortality (primary outcomes), hospital length of stay, time to extubation, PaO2/FIO2-ratio or blood pressure changes (secondary outcomes) in recipients of plasma transfusions containing relatively more plasma from individuals at low risk of carrying leukocyte-antibodies ("male plasma") than those receiving comparator plasma ("control plasma"). No limits were placed on study design, population or language. The only exclusion criteria were non-human subjects and lack of control group. Prespecified study quality indicators (including risk of bias assessment) and potential effect modifiers were tested using Cochran's Q Test. Final analyses using random-effects models and I2 to assess heterogeneity were performed in the subset of studies judged to provide the best evidence and separately for significantly different subgroups using STATA 12.1 (StataCorp, College Station, TX). SETTING: As per primary studies. PATIENTS/SUBJECTS: As per primary studies. INTERVENTIONS: As per primary studies (generally: exposure to plasma containing relatively more male plasma than comparator plasma). MEASUREMENTS AND MAIN RESULTS: From a total of 850 retrieved records, we identified 45 eligible studies. For transfusion-related acute lung injury incidence, final analysis was restricted to 13 cohort studies and one randomized controlled trial in which transfusion-related acute lung injury cases only involved plasma transfusions. Risk of transfusion-related acute lung injury and mortality in plasma recipients exposed to men when compared with control plasma were 0.27 (95% CI, 0.20-0.38; p < 0.001; I = 0%; n = 14; 286 events) and 0.89 (95% CI, 0.80-1.00; p = 0.04; I = 79%; n = 7; 5, 710 events), respectively. No other significant interactions were found. Secondary outcomes showed similar results but were less reported and the studies were more heterogeneous. Sensitivity analyses did not alter the results. There was no evidence of publication bias. DISCUSSION: More than 800 million people in 17 countries are subject to male-predominant plasma transfusion policy and at least three more countries are planning or considering adoption of this strategy. On the basis of most observational data, judged to be of high quality, male-predominant plasma transfusion strategy reduces plasma-related transfusion-related acute lung injury incidence and possibly mortality. There was no evidence that the effect differs across patient subgroups, but power to detect such differences was low.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.880
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.035
GPT teacher head0.378
Teacher spread0.343 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations50
Published2014
Admission routes1
Has abstractyes

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