Physicochemical Approach to Determine the Mechanism for Acid-Base Disorders in 793 Hospitalized Foals

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Abstract

Background: The quantitative effect of strong electrolytes, unmeasured strong anions (UAs), pCO2, and plasma protein concentrations in determining plasma pH can be demonstrated using the physicochemical approach. Plasma anion gap (AG) and strong ion gap (SIG) are used to assess UAs in different species. Hypotheses: Strong ions are a major factor influencing changes in plasma pH of hospitalized foals. AG and SIG accurately predict severe hyper-l-lactatemia ([l-lac-] > 7 mmol/L). Animals: Seven hundred and ninety three hospitalized foals < 7 days old. Methods: Retrospective study. The relationship between measured pH and physicochemical variables, and the relationship between plasma [l-lac-] and AG and SIG, were determined using regression analyses. Optimal AG and SIG cut points to predict hyper-l-lactatemia were identified using an ROC curve analysis. Results: Combined, the measured strong ion difference and SIG accounted for 54-69% of the changes in the measured arterial pH of hospitalized foals. AG and SIG were significantly associated with plasma [l-lac-] (P < .0001). The receiver operator characteristics (ROC) AUC of AG and SIG for prediction of severe hyper-l-lactatemia were 0.89 (95%CI, 0.8-0.95; P < .0001) and 0.90 (95%CI, 0.81-0.96; P < .0001), respectively. Severe hyper-l-lactatemia was best predicted by AG > 27 mmol/L (sensitivity 80%, 95%CI, 56-94, specificity 85%, 95%CI, 73-93; P < .0001) and SIG < .0001). Conclusion and clinical relevance: Altered concentrations of strong ions (Na+, K+, Cl-) and UAs were the primary cause of acidemia of hospitalized foals. AG and SIG were good predictors of hyper-l-lactatemia and could be used as surrogate tests.

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Gomez, D. E., Biermann, N. M., & Sanchez, L. C. (2015). Physicochemical Approach to Determine the Mechanism for Acid-Base Disorders in 793 Hospitalized Foals. Journal of Veterinary Internal Medicine, 29(5), 1395–1402. https://doi.org/10.1111/jvim.13590

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