ArticleTransfusion2026
Novel method for trend change detection and hypothesis generation in hemovigilance: A transfusion-related immunomodulation and blood production changes study.
Article in Transfusion, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
Abstract
backgroundImmunomodulatory consequences of transfusion, known as transfusion-related immune modulation (TRIM), impact patients but are not captured by hemovigilance systems. This study's objective is to explore TRIM impacts of production changes made by the blood supplier.
methodsWe included all transfused and non-transfused adult inpatients from 2002 to 2022 in Hamilton, Canada. Non-transfused patients served as controls to identify confounding temporal trends. We captured data from the Transfusion Research Utilization Surveillance and Tracking (TRUST) database and recorded TRIM outcomes including: sepsis, respiratory failure, venous thrombosis, organ dysfunction and in-hospital mortality using International Classification of Diseases codes, Canadian Classification of Health Interventions codes, and laboratory parameters, where applicable. The blood supplier provided data on production changes and quality control assessments. We used time series trend graphs to summarize aggregate data and the rolling window E-Divisive with Medians to detect change. A transparent and replicable point system approach identified changes in blood production most likely to have TRIM impacts.
resultsA cohort of 568,991 non-transfused and 102,446 transfused hospital admissions were included. We generated 40 time series TRIM trend graphs for transfused (n = 35) and non-transfused patients (n = 5). The blood supplier independently identified 12 key product policy, collection, or production changes. Consolidation of production in Ontario and introduction of buffy coat manufacturing were identified as having high TRIM impacts for patients transfused with any blood components.
conclusionUsing a novel hypothesis generating data mining design, consolidation of blood production and buffy coat manufacturing are identified as changes with possible TRIM impacts among transfused hospitalized patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.