Transfusion probability as an alternative measure of lab-guided medical decision-making.

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Tác giả: Jeannie Callum, Kevin Murray, Sheharyar Raza, Fahad Razak, Malcolm Risk, Xu Shi, Kevin Trentino, Amol Verma, Lili Zhao

Ngôn ngữ: eng

Ký hiệu phân loại: 296.1163 Sources

Thông tin xuất bản: United States : Transfusion , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 742953

BACKGROUND: The clinical decision to transfuse is strongly influenced by laboratory results. Analysis of transfusion decision-making through pre-transfusion laboratory results (e.g. pre-transfusion hemoglobin) is a common yet misleading approach to studying transfusion practice. STUDY DESIGN AND METHODS: We introduce "Transfusion Probability", an alternative method overcoming many limitations of pre-transfusion lab result analyses. Under this approach, we estimate the probability of transfusion after results at a specific value (e.g. hemoglobin 7.4 g/dL) or in a range of values (e.g. 7.0-7.9 g/dL) using the proportion of tests followed by transfusion. We provide a comprehensive methodology for causal inference on the effect of patient characteristics and other variables of interest. RESULTS: Analyses using pre-transfusion and transfusion probability were compared through a retrospective cohort study of hospitalized patients (N = 525,032). We found red blood cell transfusion probabilities of 76.2% in the 6.0-6.9 g/dL, 18.9% in the 7.0-7.9 g/dL, and 4.5% in the 8.0-8.9 g/dL hemoglobin ranges. After confounder adjustment, gastrointestinal bleeding patients were more likely to be transfused, with risk differences ranging from 6.6% in the 8.0-8.9 g/dL range to 13.8% in the 6.0-6.9 g/dL range. Pre-transfusion hemoglobin results showed minimal differences between gastrointestinal bleeding patients and other patients in unadjusted (0.00 g/dL) and adjusted analyses (-0.03 g/dL). DISCUSSION: In contrast to pre-transfusion result analysis, transfusion probability offers a nuanced account of transfusion practice and natural comparisons between patient groups. Wider use of our approach can provide actionable insights for clinical decision-making.
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