Evidence map›Paper›PMID 40336680›Full record

ArticleCureus2025

Granulocyte Transfusion in Pediatric and Adult Neutropenic Patients: A 16-Year Retrospective Review.

Yigit Baykara, Yaseen Jamal, AnhThu Nguyen, Thinh Quach, Suchitra Pandey, Desireny Mateo, Muharrem Yunce

Abstract read
In one paragraph

Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Yigit BaykaraPathology, Stanford University, Stanford, USA.
Yaseen JamalPathology, Stanford University, Stanford, USA.
AnhThu NguyenTransfusion Medicine, Stanford Health Care, Stanford, USA.
Thinh QuachTransfusion Medicine, Stanford Health Care, Stanford, USA.
Suchitra PandeyPathology, Stanford University, Stanford, USA.
Desireny MateoTechnical Services, Stanford Blood Center, Stanford, USA.
Muharrem YuncePathology, Stanford University, Stanford, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Granulocyte transfusion therapy has been explored as a potential treatment for severe neutropenia, particularly in patients with life-threatening infections unresponsive to conventional therapies. However, its clinical utility remains uncertain due to inconsistent evidence, challenges in donor availability, and risks of alloimmunization. Here, we evaluated granulocyte transfusions administered to 35 pediatric and adult patients at our institution. Materials and methods A retrospective chart review was conducted for 35 patients who received granulocyte transfusions between 2009 and 2024. Patient data included demographics, primary diagnosis, infection type, infection site, average granulocyte count in the units, average granulocyte dose, human leukocyte antigen-calculated panel reactive antibody (HLA-cPRA) Class I and II IgG antibodies, 42- and 90-day survival, average post-transfusion absolute neutrophil count (ANC) increment, and number of transfusions. Binomial logistic regression analysis was performed to determine the clinical variables associated with increased survival. Results Overall survival at 42 and 90 days was 21/35 (60%) and 20/35 (57%), respectively. No significant survival differences were observed based on infection type, diagnosis, or sex. Higher body weight, increased number of transfusions, and greater granulocyte dose per kilogram were associated with improved survival. While high-dose transfusions (≥0.6×10

Indexed as

granulocytegranulocyte transfusionhuman leukocyte antigenneutropeniasepsis

Identifiers

PMID40336680
PMCPMC12056885

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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.