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1000
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Abstract/Summary
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Estimating intraoperative blood loss is one of the daily challenges for clinicians. Despite the knowledge of the inaccuracy of visual estimation by anaesthetists and surgeons, this is still the mainstay to estimate surgical blood loss. This review aims at highlighting the strengths and weaknesses of currently used measurement methods. A systematic review of studies on estimation of blood loss was carried out. Studies were included investigating the accuracy of techniques for quantifying blood loss in vivo and in vitro. We excluded nonhuman trials and studies using only monitoring parameters to estimate blood loss. A meta-analysis was performed to evaluate systematic measurement errors of the different methods. Only studies that were compared with a validated reference e.g. Haemoglobin extraction assay were included. 90 studies met the inclusion criteria for systematic review and were analyzed. Six studies were included in the meta-analysis, as only these were conducted with a validated reference. The mixed effect meta-analysis showed the highest correlation to the reference for colorimetric methods (0.93 95% CI 0.91-0.96), followed by gravimetric (0.77 95% CI 0.61-0.93) and finally visual methods (0.61 95% CI 0.40-0.82). The bias for estimated blood loss (ml) was lowest for colorimetric methods (57.59 95% CI 23.88-91.3) compared to the reference, followed by gravimetric (326.36 95% CI 201.65-450.86) and visual methods (456.51 95% CI 395.19-517.83). Of the many studies included, only a few were compared with a validated reference. The majority of the studies chose known imprecise procedures as the method of comparison. Colorimetric methods offer the highest degree of accuracy in blood loss estimation. Systems that use colorimetric techniques have a significant advantage in the real-time assessment of blood loss.
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1000
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Hinweis
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DeepGreen-ID: 622b152545914ea98a72d6730da4d771 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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