Bedside Rules for Managing Acid-Base Derangement in Respiratory Failure: Applications to COVID-19. Issue 2 (4th March 2020)

• Record Type: Journal Article
• Authors: Marano, Marco; Senigalliesi, Luigi
• Is Part Of: Clinical pulmonary medicine. Volume 27:Issue 2(2020)
• Page Start: 51
• Page End: 53
• Publication Date: 2020-03-04
• Subjects: acid-base -- respiratory acidosis -- respiratory alkalosis -- secondary response; Lungs -- Diseases -- Periodicals; 616.24005
• DOI: 10.1097/CPM.0000000000000354
• Languages: English
• ISSNs: 1068-0640

Abstract

Abstract : Respiratory failure is typically associated with changes in pCO2 leading to respiratory alkalosis (type 1 failure) and respiratory acidosis (type 2). As a compensatory response, plasma HCO3 concentration decreases if pCO2 decreases and increases conversely. These secondary responses prevent large pH fluctuations. However, metabolic acid-base disorders may still occur as a consequence of dysfunction of other organs and/or medical treatments. To recognize superimposed acid-base disorders, the availability of an accurate prediction of the expected HCO3 that corresponds to a given pCO2 is crucial. In chronic hypocapnia, the compensatory metabolic response is regulated by the equation ΔHCO3 /ΔpCO2 =0.4 mEq/L per mm Hg. An easy rule to compute the expected value of HCO3 may be 0.4×pCO2 +9. In chronic hypercapnia, the equation is ΔHCO3 /ΔpCO2 =0.48 mEq/L per mm Hg, and the expected value of HCO3 becomes 0.48×pCO2 +4.74. While this expression is accurate, it seems to be of limited use for simple "bedside" predictions. In this contribution, we propose the simpler expression: the expected value of HCO3 in chronic hypercapnia=½ pCO2 +3.5. For values of pCO2 not exceeding 70 mm Hg, with the proposed expression, the difference in HCO3 prediction in respect to the previous one is <0.5 mEq/L, which is clinically negligible. The root mean square value of the error introduced by the proposed expression is as small as 0.19 mEq/L. Because of its accuracy, we believe that the proposed formula may be useful to identify mixed disorders at the bedside in a simpler way.