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The Use Of Platelet Transfusions In The Intensive Care Unit and Impact On Platelet Count: A 30,000 Patient Registry Study

2013· article· en· W2205850292 on OpenAlexaffabout
Shuoyan Ning, Rebecca Barty, Yang Liu, Nancy M. Heddle, Donald M. Arnold

Bibliographic record

VenueBlood · 2013
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicinePlatelet transfusionIntensive care unitPlateletCohortMedical recordEmergency medicineBlood transfusionInternal medicineComplicationCohort studyIntensive care medicine

Abstract

fetched live from OpenAlex

Abstract Background Thrombocytopenia is a common complication of critical illness and an independent risk factor for bleeding and death in the intensive care unit (ICU). Platelet transfusions are commonly used to improve platelet counts; however, the expected platelet increment from a transfusion in this setting has not been established. The objective of this study was to describe the frequency of platelet transfusion administration and their effect on platelet count increments in a large cohort of non-oncology critically ill adults. Methods We performed an analysis of a registry database, which was developed to capture clinical and laboratory data on all blood transfusions administered in 3 academic hospitals in Hamilton, Ontario, Canada. We included all patients ≥18 years who received one or more platelet transfusion during an ICU admission. Data validation was done by integrity checks with medical records and laboratory information system performed by a biostatistician. Non-transfused ICU patients were used as controls. The absolute increment in platelet count was calculated for each single platelet transfusion using the closest platelet count taken within 24 hours before the transfusion and 4-24 hours after the transfusion. Results Between April 2006 and October 2012, 33,222 patients were admitted to ICU, including 29,511 (88.8%) who did not have a diagnosis of cancer. Of those, 4,502 (15.3%) received one or more platelet transfusion during any ICU admission (n=4,690); 31.9% were female and median age at the time of first admission was 69 years (IQR 59-77). Among the 25,009 non-transfused patients admitted to ICU during the same period, 38.1% were female and the median age was 65 years (IQR 52–76). Median pre-transfusion platelet count was 87 x109/L (IQR 59-131) and a single platelet transfusion resulted in a median platelet count increment of 21 x109/L (IQR 6-40) as measured 6.7 hours (IQR 5.1-9.8) after the transfusion. There were 277 (25.4%) transfusions that yielded a platelet count increment of 5 x109/L or less. ICU mortality was 562/4,690 (12.4%) for patients who received a platelet transfusion, compared with 2,251/33,033(6.8%) for patients who were not transfused during their ICU stay. Summary/Conclusion Among this large cohort of non-oncology ICU patients, platelet transfusions were commonly administered for thrombocytopenia that was generally mild. In this setting one platelet transfusion resulted in a median platelet count rise of 21 x109/L. Many transfusion episodes yielded no appreciable increase in platelet count. Further studies are needed to determine the clinical effects of platelet transfusion in this setting controlling for confounding. Disclosures: Heddle: CIHR: Research Funding; Canadian Blood Services: Membership on an entity’s Board of Directors or advisory committees; Health Canada: Research Funding; Macopharma: Consultancy; ASH: Honoraria.

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)0.001
metaresearch head score (Gemma)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.005
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.269
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 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
Published2013
Admission routes2
Has abstractyes

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