Evaluation of the Acid-Base Status in Patients Admitted to the ICU Due to Severe COVID-19: Physicochemical versus Traditional Approaches.

Abstract

Stewart's approach is known to have better diagnostic accuracy for the identification of metabolic acid-base disturbances compared to traditional methods based either on plasma bicarbonate concentration ([HCO3-]) and anion gap (AG) or on base excess/deficit (BE). This study aimed to identify metabolic acid-base disorders using either Stewart's or traditional approaches in critically ill COVID-19 patients admitted to the ICU, to recognize potential hidden acid-base metabolic abnormalities and to assess the prognostic value of these abnormalities for patient outcome. This was a single-center retrospective study, in which we collected data from patients with severe COVID-19 admitted to the ICU. Electronical files were used to retrieve data for arterial blood gases, serum electrolytes, and proteins and to derive [HCO3-], BE, anion gap (AG), AG adjusted for albumin (AGadj), strong ion difference, strong ion gap (SIG), and SIG corrected for water excess/deficit (SIGcorr). The acid-base status was evaluated in each patient using the BE, [HCO3-], and physicochemical approaches. We included 185 patients. The physicochemical approach detected more individuals with metabolic acid-base abnormalities than the BE and [HCO3-] approaches (p < 0.001), and at least one acid-base disorder was recognized in most patients. According to the physicochemical method, 170/185 patients (91.4%) had at least one disorder, as opposed to the number of patients identified using the BE 90/186 (48%) and HCO3 62/186 (33%) methods. Regarding the derived acid-base status variables, non-survivors had greater AGadj, (p = 0.013) and SIGcorr (p = 0.035) compared to survivors. The identification of hidden acid-base disturbances may provide a detailed understanding of the underlying conditions in patients and of the possible pathophysiological mechanisms implicated. The association of these acid-base abnormalities with mortality provides the opportunity to recognize patients at increased risk of death and support them accordingly.