Evidence map›Paper›PMID 28470756›Full record

ArticleTransfusion2017

Differentiating pulmonary transfusion reactions using recipient and transfusion factors.

Nareg H Roubinian, Mark R Looney, Sheila Keating, Daryl J Kor, Clifford A Lowell, Ognjen Gajic, Rolf Hubmayr, Michael Gropper, Monique Koenigsberg, Gregory A Wilson and 4 more

Abstract read
In one paragraph

Article in Transfusion, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. TACO and TRALI: biology, risk factors, and prevention strategies.Hematology. American Society of Hematology. Education Program · 2018
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Nareg H RoubinianBlood Systems Research Institute.
Mark R LooneyUniversity of California at San Francisco, San Francisco, California.
Sheila KeatingBlood Systems Research Institute.
Daryl J KorMayo Clinic, Rochester, Minnesota.
Clifford A LowellBlood Systems Research Institute.
Ognjen GajicMayo Clinic, Rochester, Minnesota.
Rolf HubmayrMayo Clinic, Rochester, Minnesota.
Michael GropperUniversity of California at San Francisco, San Francisco, California.
Monique KoenigsbergUniversity of California at San Francisco, San Francisco, California.
Gregory A WilsonMayo Clinic, Rochester, Minnesota.
Michael A MatthayUniversity of California at San Francisco, San Francisco, California.
Pearl ToyUniversity of California at San Francisco, San Francisco, California.
Edward L MurphyBlood Systems Research Institute.
TRALI Study Group

Funding

Transfusion-Related Acute Lung Injury: Incidence and MechanismsP50HL081027 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI TOY, PEARL T · 2005 to 2009
$12.4M
Regulation of Innate Immune Signaling by Lyn KinaseR01AI113272 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LOWELL, CLIFFORD A · 2015 to 2019
$2.0M
NHLBI NIH HHS P50 HL081027NIAID NIH HHS R01 AI113272
6 · The paper itself

Abstract

backgroundIt is increasingly recognized that recipient risk factors play a prominent role in possible transfusion-related acute lung injury (pTRALI) and transfusion-associated circulatory overload (TACO). We hypothesized that both transfusion and recipient factors including natriuretic peptides could be used to distinguish TRALI from TACO and pTRALI. STUDY DESIGN AND

methodsWe performed a post hoc analysis of a case-control study of pulmonary transfusion reactions conducted at the University of California at San Francisco and Mayo Clinic, Rochester. We evaluated clinical data and brain natriuretic peptides (BNP) levels drawn after transfusion in patients with TRALI (n = 21), pTRALI (n = 26), TACO (n = 22), and controls (n = 24). Logistic regression and receiver operating characteristics curve analyses were used to determine the accuracy of clinical and biomarker predictors in differentiating TRALI from TACO and pTRALI.

resultsWe found that pTRALI and TACO were associated with older age, higher fluid balance, and elevated BNP levels relative to those of controls and TRALI. The following variables were useful in distinguishing cases of pTRALI and TACO from TRALI: age more than 70 years, BNP levels more than 1000 pg/mL, 24-hour fluid balance of more than 3 L, and a lower number of transfused blood components. Using the above variables, our logistic model had a 91% negative predictive value in the differential diagnosis of TRALI.

conclusionsModels incorporating readily available clinical and biomarker data can be used to differentiate transfusion-related respiratory complications. Additional studies examining recipient risk factors and the likelihood of TRALI may be useful in decision making regarding donor white blood cell antibody testing.

Indexed as

Acute Lung InjuryAdultAgedFemaleHumansLogistic ModelsMaleMiddle AgedNatriuretic Peptide, BrainTransfusion ReactionNatriuretic Peptide, Brain

Identifiers

PMID28470756
PMCPMC5758383

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.