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A head to head evaluation of 8 biochemical scanning tools for unmeasured ions

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Abstract

We aimed to evaluate the sensitivity and specificity of 8 biochemical scanning tools in signalling the presence of unmeasured anions. We used blood gas and biochemical data from 15 patients during and after cardio-pulmonary bypass. Sampling time-points were pre-bypass (T1), 2 min post equilibration with priming fluid containing acetate and gluconate anions (T2), late bypass (T3) and 4 h after surgery (T4). We calculated the anion gap (AG), albumin—corrected anion gap (AGc), whole blood base excess (BE) gap, plasma BE gap, standard BE gap and the strong ion gap (SIG), plus 2 new indices—the unmeasured ion index (UIX) and unmeasured plasma anions according to the interstitial, plasma and erythrocyte acid–base model (IPEua). Total measured plasma concentrations of acetate and gluconate [XA] were proxies for unmeasured plasma anions. [XA] values (mmol/L) were 1.41 (0.87) at T1, 11.73 (3.28) at T2, 4.80 (1.49) at T3 and 1.36 (0.73) at T4. Corresponding [albumin] values (g/L) were 32.3 (2.0), 19.8 (2.6), 21.3 (2.5) and 29.1 (2.3) respectively. Only the AG failed to increase significantly at T2 in response to a mean [XA] surge of >10 mEq/L. At an [XA] threshold of 6 mEq/L, areas under receiver –operator characteristic curves in rank order were IPEua and UIX (0.88 and 0.87 respectively), SIG (0.81), AGc (0.79), standard BE gap (0.77), plasma BE gap (0.71), BE gap (0.70) and AG (0.59). Similar ranking hierarchies applied to positive and negative predictive values. We conclude that during acute hemodilution UIX and IPEua are superior to the anion gap (with and without albumin correction) and 4 other indices as scanning tools for unmeasured anions.

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Funding

Project supported by Departmental Funds.

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Authors and Affiliations

  1. Intensive Care Unit, Mater Research, Mater Health Services, University of Queensland, Salmon Building, Raymond Terrace, South Brisbane, QLD, 4101, Australia

    Thomas J. Morgan

  2. Department of Intensive Care, Sunshine Coast Hospital, Nambour, QLD, 4560, Australia

    Chris M. Anstey

  3. University of Queensland, Brisbane, QLD, 4101, Australia

    Chris M. Anstey

  4. Department of Pharmacology, Physiology and Neuroscience, University of South Carolina School of Medicine, Columbia, SC, 29209, USA

    Matthew B. Wolf

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  1. Thomas J. Morgan
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  2. Chris M. Anstey
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Correspondence to Thomas J. Morgan.

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Appendix: preliminary analysis

Appendix: preliminary analysis

Prior to ROC curve analysis, the data were examined to identify a suitable threshold point indicating the presence of XA. Kernel density plots for [XA] for each time sample were constructed and combined into a single summary plot (Fig. 4). On inspection, a threshold point was identified at 6.0 mEq/L. This point was adopted as that which maximised correct classification in each group.

Fig. 4
figure 4

Kernel density plot of the data from times T1, T2, T3 and T4. On the x-axis, XA represents the combined measured plasma concentrations of acetate and gluconate in mEq/L, while the y-axis represents the probability density function for XA. There is a clear inflection point at approximately 6.0 mEq/L which distinguishes results in times T1 and T4 (XA ≤ 6.0 mEq/L) from time T2 (XA > 6.0 mEq/L). Results from time T3 fell into both distributions

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Morgan, T.J., Anstey, C.M. & Wolf, M.B. A head to head evaluation of 8 biochemical scanning tools for unmeasured ions. J Clin Monit Comput 31, 449–457 (2017). https://doi.org/10.1007/s10877-016-9861-5

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  • DOI: https://doi.org/10.1007/s10877-016-9861-5

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