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Update 1989 pp 322-328 | Cite as

Treatment of Metabolic Acidosis in Low Flow States: Should We Administer Bicarbonate?

  • A. I. Arieff
Conference paper
Part of the Update in Intensive Care and Emergency Medicine book series (UICM, volume 8)

Abstract

Metabolic acidosis can be divided into those with either normal or increased anion gap. Those with normal anion gap are usually of renal origin (renal tubular acidosis) and will not be discussed here. Those with increased anion gap that are of clinical significance include diabetic ketoacidosis, uremia and lactic acidosis. Lactic acidosis is the most common form of metabolic acidosis, is of diverse pathophysiology and is very difficult to manage. Lactic acidosis is generally defined as a metabolic acidosis due the accumulation of lactic acid in the blood in excess of 5 mM/L with an accompanying blood pH of less than 7.25. However, the mechanisms by which lactic acid accumulation occurs vary and include both the stimulation of lactate production and reductions of lactate metabolism. Clinically, the disorders of lactate metabolism are conveniently divided as being either anaerobic (Type A) or aerobic (Type B) [1]. The hallmark of Type A lactic acidosis is tissue hypoxia resulting in anaerobic lactic acid production. The most common causes of Type A lactic acidosis are cardiopulmonary arrest and other states characterized by impaired cardiac performance, reduced tissue perfusion and arterial hypoxemia. In these states, the hypoxia and circulatory insufficiency combine to reduce tissue oxygen availability, necessitating anaerobic metabolism and stimulating lactic acid production. In Type B lactic acidosis, on the other hand, tissue hypoxia appears to not be present, and instead lactic acid production is enhanced metabolically for other reasons in an otherwise aerobic state.

Keywords

Sodium Bicarbonate Metabolic Acidosis Lactic Acidosis Diabetic Ketoacidosis Renal Tubular Acidosis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© Springer-Verlag Berlin Heidelberg 1989

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  • A. I. Arieff

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