How Much Does Intravenous Fluid Cause Hematocrit to Drop? Improving Interpretation of Hematocrit Toward Better Post-Hemorrhage Care

Author:

Qureshi Nabeel12ORCID,Bloom Matthew3,Pevnick Joshua1

Affiliation:

1. General Internal Medicine, Cedars-Sinai Medical Center , Los Angeles, CA 90048, USA

2. RAND Health, RAND Corporation , Santa Monica, CA 90401, USA

3. Surgery, Cedars-Sinai Medical Center , Los Angeles, CA 90048, USA

Abstract

ABSTRACT Introduction Hemorrhage is assessed, at least in part, via hematocrit testing. To differentiate unexpected drops in hematocrit because of ongoing hemorrhage versus expected drops as a result of known hemorrhage and intravenous fluid administration, we model expected post-operative hematocrit values accounting for fluid balance and intraoperative estimated blood loss (EBL) among patients without substantial post-operative bleeding. Materials and Methods We reviewed patient-level data from the electronic health record of an academic medical center for all non-pregnant adults admitted for elective knee or hip arthroplasty from November 2013 to September 2022 who did not require blood products. We used linear regression to evaluate the association between post-operative hematocrit and predictor variables including pre-operative hematocrit, intraoperative net fluid intake, blood volume, time from surgery to lab testing, EBL, patient height, and patient weight. Results We included 6,648 cases. Mean (SD) estimated blood volume was 4,804 mL (1023), mean net fluid intake was 1,121 mL (792), and mean EBL was 144 mL (194). Each 100 mL of EBL and 1,000 mL net positive fluid intake was associated with a decrease of 0.52 units (95% CI, 0.51-0.53) and 2.4 units (2.2-2.7) in post-operative hematocrit. Pre-operative hematocrit was the strongest predictor of post-operative hematocrit. Each 1-unit increase in pre-operative hematocrit was associated with a 0.70-unit increase (95% CI, 0.67-0.73) in post-operative hematocrit. Our estimates were robust to sensitivity analyses, and all variables included in the model were statistically significant with P <.005. Conclusion Patient-specific data, including fluid received since the time of initial hemorrhage, can aid in estimating expected post-hemorrhage hematocrit values, and thus in assessing for the ongoing hemorrhage.

Publisher

Oxford University Press (OUP)

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