Detecting Exogenous Contamination of Clinical Blood Samples with Crystalloid Solutions: A Data Driven Approach to Derive and Validate Delta Checks

Abstract

Abstract Pre-analytical error may occur when collecting blood samples from intravenous (IV) lines. Blood samples can be inadvertently diluted by exogenous solutions if an insufficient amount of blood is discarded prior to collection. Rules built in the laboratory information system or middleware can be used to alert laboratory staff to specimens that require co-investigation with the clinical team to determine if sample dilution is possible or likely. Currently, however, there is a lack of literature to guide laboratorians on how to define quality rules of this nature, particularly for detecting subtle, rather than gross contamination by commonly administered IV-fluids. Accordingly, the primary objective of this study is to derive sensitive and specific, multivariate delta checks to detect more subtle blood sample contamination by commonly used crystalloid solutions. To derive the rules, we began with in vitro experiments by spiking increasing volumes of major IV-fluids (normal saline (NS), lactated ringers (LR), and 5% dextrose (D5W)) into clinical blood samples that were collected from healthy donors (n=3). Crystalloid solutions were serially spiked into blood samples at 10% (solution:sample) increments for NS and LR from 10% up to 90%, and in 5% increments for D5W, up to 50%. Basic metabolic panel (BMP) analytes were measured and compared between neat and contrived samples. All testing was performed on Roche Cobas 8000 chemistry auto-analyzers. Based on in vitro data, we derived multivariate delta checks using analytes in a BMP that would reflect 10-40% contamination by a given fluid. We then performed a retrospective data analysis on more than 28 thousand, serially collected BMP results to identify samples that were flagged by these rules. Chart review was then performed to identify EHR-based evidence of temporally associated administration of crystalloid solutions through a peripheral IV access line. Increasing sample dilution from the in vitro study showed significant changes in several BMP analytes across all fluid types. With respect to NS, the most significant changes relative to baseline were observed with potassium, calcium, and chloride, while for LR, the most significant changes relative to baseline were observed with glucose, bicarbonate, and calcium. For D5W, significant changes were observed with glucose, calcium, chloride and sodium. Accordingly, delta check rules were implemented using relative changes of the aforementioned analytes. On chart review, we found 80-100% of flagged samples came from patients with administration of that given fluid in the last 12-24 hours. The results from this study support delta checks that consider multiple analytes, and fluid-specific bias profiles, as this may provide a more sensitive and specific approach to detecting contamination of clinical blood samples by crystalloid solutions. Further evaluation using retrospective data analysis will be used to validate these rules sensitivity and specificity followed by prospective testing before implementation.