Quantification of Metabolic Acidosis at Bedside by S.A.L.T Approach

Introduction: Traditionally, metabolic acidosis is analyzed using an anion gap (AG). The aim of the study was to compare the utility of quantitative David Story’s simplified Stewart approach against traditional approach to analyze metabolic acidosis. ICU setting. Analytical, cross-sectional observat...

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Main Authors: Harshitha Seshadri, Anitha Nileshwar, Shwethapriya Rao, Nisha Sara M. Jacob
Format: Article
Language:English
Published: Wolters Kluwer Medknow Publications 2024-12-01
Series:Journal of Emergencies, Trauma and Shock
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Online Access:https://journals.lww.com/10.4103/jets.jets_1_24
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author Harshitha Seshadri
Anitha Nileshwar
Shwethapriya Rao
Nisha Sara M. Jacob
author_facet Harshitha Seshadri
Anitha Nileshwar
Shwethapriya Rao
Nisha Sara M. Jacob
author_sort Harshitha Seshadri
collection DOAJ
description Introduction: Traditionally, metabolic acidosis is analyzed using an anion gap (AG). The aim of the study was to compare the utility of quantitative David Story’s simplified Stewart approach against traditional approach to analyze metabolic acidosis. ICU setting. Analytical, cross-sectional observational study. Methods: Blood gas reports of 50 adult critically ill patients with primary metabolic acidosis at admission were analyzed using both approaches. With traditional approach, acidosis was classified simply as high or normal AG acidosis. With S.A.L.T approach, the components of base deficit were further quantified into sodium chloride, albumin, lactate, and other ions effects. A contribution of sodium chloride or albumin effect of > 30% to the base deficit was considered significant. The proportion of patients with such abnormalities was determined. Descriptive statistics was used. Results: The mean ± standard deviation (SD) age of patients was 54.52 ± 19.71 years, 52% were males, and 72% were medical admissions. The median (interquartile range [IQR]) Sequential Organ Failure Assessment score was 10 (5–13). The mean ± SD pH, bicarbonate, base excess, and albumin were 7.198 ± 0.13, 11.73 ± 4.2 mmol/L, −15.13 ± 5.6 mmol/L, and 2.9 ± 0.77 g%, respectively. The median (IQR) of serum lactate was 6.77 (1.53, 16.32) mmol/L. Hyponatremia and hypochloremia were seen in 68% and 46% of patients, respectively. Eighty-eight percent of patients had acidosis due to other ions, 52% due to lactates. Twenty-eight percent had a significant sodium chloride effect and 32% had significant hypoalbuminemia. Conclusion: Quantification of base deficit of metabolic acidosis using S.A.L.T approach showed changes in sodium chloride levels and hypoalbuminemia affecting base deficit in nearly 30% of the patients. Quantification of metabolic acidosis using S.A.L.T approach is likely to help treat metabolic acidosis more appropriately, with clinical implications.
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spelling doaj-art-a23e08e53be3478f8cf3c179949fea692025-01-07T06:57:17ZengWolters Kluwer Medknow PublicationsJournal of Emergencies, Trauma and Shock0974-27000974-519X2024-12-0117420120710.4103/jets.jets_1_24Quantification of Metabolic Acidosis at Bedside by S.A.L.T ApproachHarshitha SeshadriAnitha NileshwarShwethapriya RaoNisha Sara M. JacobIntroduction: Traditionally, metabolic acidosis is analyzed using an anion gap (AG). The aim of the study was to compare the utility of quantitative David Story’s simplified Stewart approach against traditional approach to analyze metabolic acidosis. ICU setting. Analytical, cross-sectional observational study. Methods: Blood gas reports of 50 adult critically ill patients with primary metabolic acidosis at admission were analyzed using both approaches. With traditional approach, acidosis was classified simply as high or normal AG acidosis. With S.A.L.T approach, the components of base deficit were further quantified into sodium chloride, albumin, lactate, and other ions effects. A contribution of sodium chloride or albumin effect of > 30% to the base deficit was considered significant. The proportion of patients with such abnormalities was determined. Descriptive statistics was used. Results: The mean ± standard deviation (SD) age of patients was 54.52 ± 19.71 years, 52% were males, and 72% were medical admissions. The median (interquartile range [IQR]) Sequential Organ Failure Assessment score was 10 (5–13). The mean ± SD pH, bicarbonate, base excess, and albumin were 7.198 ± 0.13, 11.73 ± 4.2 mmol/L, −15.13 ± 5.6 mmol/L, and 2.9 ± 0.77 g%, respectively. The median (IQR) of serum lactate was 6.77 (1.53, 16.32) mmol/L. Hyponatremia and hypochloremia were seen in 68% and 46% of patients, respectively. Eighty-eight percent of patients had acidosis due to other ions, 52% due to lactates. Twenty-eight percent had a significant sodium chloride effect and 32% had significant hypoalbuminemia. Conclusion: Quantification of base deficit of metabolic acidosis using S.A.L.T approach showed changes in sodium chloride levels and hypoalbuminemia affecting base deficit in nearly 30% of the patients. Quantification of metabolic acidosis using S.A.L.T approach is likely to help treat metabolic acidosis more appropriately, with clinical implications.https://journals.lww.com/10.4103/jets.jets_1_24anionbicarbonatehypoalbuminemiametabolic acidosissodium chloridestewart
spellingShingle Harshitha Seshadri
Anitha Nileshwar
Shwethapriya Rao
Nisha Sara M. Jacob
Quantification of Metabolic Acidosis at Bedside by S.A.L.T Approach
Journal of Emergencies, Trauma and Shock
anion
bicarbonate
hypoalbuminemia
metabolic acidosis
sodium chloride
stewart
title Quantification of Metabolic Acidosis at Bedside by S.A.L.T Approach
title_full Quantification of Metabolic Acidosis at Bedside by S.A.L.T Approach
title_fullStr Quantification of Metabolic Acidosis at Bedside by S.A.L.T Approach
title_full_unstemmed Quantification of Metabolic Acidosis at Bedside by S.A.L.T Approach
title_short Quantification of Metabolic Acidosis at Bedside by S.A.L.T Approach
title_sort quantification of metabolic acidosis at bedside by s a l t approach
topic anion
bicarbonate
hypoalbuminemia
metabolic acidosis
sodium chloride
stewart
url https://journals.lww.com/10.4103/jets.jets_1_24
work_keys_str_mv AT harshithaseshadri quantificationofmetabolicacidosisatbedsidebysaltapproach
AT anithanileshwar quantificationofmetabolicacidosisatbedsidebysaltapproach
AT shwethapriyarao quantificationofmetabolicacidosisatbedsidebysaltapproach
AT nishasaramjacob quantificationofmetabolicacidosisatbedsidebysaltapproach