Evidence map›Paper›PMID 40852363›Full record

ArticleFrontiers in medicine2025

Analysis of influencing factors and predictive model construction for platelet transfusion efficacy in hematological patients.

Yu Zou, Tianhua Jiang, Yue Fan, Simin Liang, Long Lin, Mao Zheng

Abstract read
In one paragraph

Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Observational
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Yu ZouDepartment of Blood Transfusion, Deyang People's Hospital, Deyang, China.
Tianhua JiangDepartment of Blood Transfusion, Deyang People's Hospital, Deyang, China.
Yue FanDepartment of Blood Transfusion, Deyang People's Hospital, Deyang, China.
Simin LiangDepartment of Blood Transfusion, Deyang People's Hospital, Deyang, China.
Long LinDepartment of Blood Transfusion, Deyang People's Hospital, Deyang, China.
Mao ZhengDepartment of Clinical Laboratory, Deyang People's Hospital, Deyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study aimed to systematically analyze the independent risk factors for platelet transfusion refractoriness (PTR) in hematological patients, and to develop and validate a nomogram prediction model, thereby providing scientific evidence for personalized platelet transfusion strategies in clinical practice. Methods: A retrospective cohort study was conducted involving 363 platelet transfusion episodes in hematological patients who received platelet transfusions at Deyang People's Hospital between January 2023 and August 2023. Comprehensive clinical data and laboratory parameters were collected. Potential PTR-related factors were initially identified through univariate analysis, followed by multivariate logistic regression to determine independent risk factors. Using Rstudio software, a nomogram prediction model was constructed based on the identified factors. The model's performance was rigorously evaluated through receiver operating characteristic (ROC) curve analysis, calibration curves, and internal validation using bootstrap resampling (1,000 repetitions) to assess discrimination, calibration, and clinical applicability. Results: This study retrospectively analyzed 363 platelet transfusion episodes involving 131 hematological patients, the incidence of PTR was 30.85% (112/363). Multivariate logistic regression analysis revealed four independent risk factors for PTR: female gender (OR = 1.876, 95% CI: 1.147-3.067), transfusion frequency ≥ 10 times (OR = 2.552, 95% CI: 1.089-5.981), splenomegaly (OR = 3.170, 95% CI: 1.334-7.534), and antibiotic usage (OR = 2.177, 95% CI: 1.078-4.396) (all Conclusion: We successfully developed and validated a PTR prediction model incorporating gender, transfusion frequency, splenomegaly, and antibiotic usage as key risk factors. This model exhibits promising clinical utility and can serve as an objective tool for optimizing individualized platelet transfusion protocols in hematological patients.

Indexed as

hematologic patientsnomogramplatelet transfusion refractorinesspredictive modelingrisk factors

Identifiers

PMID40852363
PMCPMC12367750

What Socratic holds

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LicenceCC BY
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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 Socratic graph.