1.
Systematic review highlights high risk of bias of clinical prediction models for blood transfusion in patients undergoing elective surgery
Dhiman P, Ma J, Gibbs VN, Rampotas A, Kamal H, Arshad SS, Kirtley S, Doree C, Murphy MF, Collins GS, et al
Journal of clinical epidemiology. 2023
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Abstract
BACKGROUND Blood transfusion can be a lifesaving intervention after perioperative blood loss. Many prediction models have been developed to identify patients most likely to require blood transfusion during elective surgery, but it is unclear whether any are suitable for clinical practice. STUDY DESIGN AND SETTING We conducted a systematic review, searching MEDLINE, Embase, PubMed, The Cochrane Library, Transfusion Evidence Library, Scopus, and Web of Science databases for studies reporting the development or validation of a blood transfusion prediction model in elective surgery patients between 01/01/2000 to 30/06/2021. We extracted study characteristics, discrimination performance (c-statistics) of final models and data which we used to perform risk of bias assessment using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). RESULTS We reviewed 66 studies (72 developed and 48 externally validated models). Pooled c-statistics of externally validated models ranged from 0.67 to 0.78. Most developed and validated models were at high risk of bias due to handling of predictors, validation methods, and too small sample sizes. CONCLUSION Most blood transfusion prediction models are at high risk of bias and suffer from poor reporting and methodological quality, which must be addressed before they can be safely used in clinical practice.
PICO Summary
Population
Patients undergoing elective surgery (66 studies).
Intervention
Blood transfusion prediction models used perioperatively.
Comparison
Outcome
This systematic review appraised 120 prediction models developed or validated for predicting blood transfusion in elective surgery (72 developed and 48 externally validated models). Pooled c-statistics of externally validated models ranged from 0.67 to 0.78. Most developed and validated models were at high risk of bias due to handling of predictors, validation methods, and too small sample sizes.
2.
The impact of electronic decision support on transfusion practice: a systematic review
Hibbs SP, Nielsen ND, Brunskill S, Doree C, Yazer MH, Kaufman RM, Murphy MF
Transfusion Medicine Reviews. 2015;29((1):):14-23.
Abstract
Decision support systems (DSSs) provide clinicians with tailored treatment recommendations by combining individual patient information and local guidelines. The objective of this systematic review was to assess the effects of electronic DSS on blood product ordering practices. Eligible studies were identified from searches of MEDLINE, Embase, CINAHL, The Cochrane Library, PubMed, and the Transfusion Evidence Library from January 2000 to April 2014. Of these, 23 articles were eligible, resulting in the inclusion of 20 independent studies in this systematic review. There was a significant variation in study population, the type of DSS used, and outcome reporting. All but one study used a before-after design without any element of randomization. Overall, there is good evidence that implementation of a DSS improves red blood cell usage. The effect of a DSS on plasma, platelets, and cryoprecipitate usage is less clear probably because fewer studies have been conducted focusing on these products. In addition, the introduction of a DSS resulted in cost savings in the 7 studies that reported financial outcomes. Patient outcomes were generally not studied in detail, and there were few data on the sustainability of the effect of DSS. Further data are needed to assess the effect of a DSS on blood products other than red blood cell, and future studies should standardize reporting of outcomes. Copyright 2015 Elsevier Inc. All rights reserved.
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Blood transfusion administration - one- or two-person checks: which is the safest method?
Watson D, Murdock J, Doree C, Murphy M, Roberts M, Blest A, Brunskill S
Transfusion. 2008;48((4):):783-9.