Evidence map›Paper›PMID 39406697›Full record

ReviewTransfusion medicine (Oxford, England)2024

Pitfalls of reasoning in hospital-based transfusion medicine.

Sheharyar Raza, Jeremy W Jacobs, Garrett S Booth, Jeannie Callum

Abstract readReviewCase Reports
In one paragraph

Review in Transfusion medicine (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Pitfalls of reasoning in hospital-based transfusion medicine.Transfusion medicine (Oxford, England) · 2024
    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

4 authors.

Sheharyar RazaDepartment of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.ORCID https://orcid.org/0000-0002-8247-1484
Jeremy W JacobsDepartment of Pathology Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee, USA.ORCID https://orcid.org/0000-0002-5719-9685
Garrett S BoothDepartment of Pathology Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Jeannie CallumDepartment of Pathology and Molecular Medicine, Queen's University, Kingston, Ontario, Canada.

Funding

Canadian Blood Services
6 · The paper itself

Abstract

introductionHospital-based transfusion involves hundreds of daily medical decisions. Medical decision-making under uncertainty is susceptible to cognitive biases which can lead to systematic errors of reasoning and suboptimal patient care. Here we review common cognitive biases that may be relevant for transfusion practice. MATERIALS AND

methodsBiases were selected based on categorical diversity, evidence from healthcare contexts, and relevance for transfusion medicine. For each bias, we provide background psychology literature, representative clinical examples, considerations for transfusion medicine, and strategies for mitigation.

resultsWe report seven cognitive biases relating to memory (availability heuristic, limited memory), interpretation (framing effects, anchoring bias), and incentives (search satisficing, sunk cost fallacy, feedback sanction).

conclusionPitfalls of reasoning due to cognitive biases are prominent in medical decision making and relevant for hospital transfusion medicine. An awareness of these phenomena might stimulate further research, encourage corrective measures, and motivate nudge-based interventions to improve transfusion practice.

Indexed as

Transfusion MedicineBiasBlood TransfusionClinical Decision-MakingHospitalsHumanscognitive biasesheuristicsmedical decision‐makingnudgestransfusion medicine

Identifiers

PMID39406697
PMCPMC11653058

What OpenQuestion holds

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LicenceCC BY-NC
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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.