The Problem

The 1952 epidemic of poliomyelitis in Copenhagen resulted in critical interest in acid–base disturbances1  and the creation of intensive care.2  Technical advances3  in measurement were accompanied by improvements in the diagrammatic representation.4  The vigorous “Great Transatlantic Debate” faded with the introduction of “standard base excess” (SBE) to represent metabolic acidosis. Nevertheless, the potential for confusion remains. Partial pressure of carbon dioxide (PCO2) is measured in different units by geographical location (mm Hg or kPa), and metabolic acidosis may be represented by SBE, BEB (base excess of blood), BD (base deficit), BEECF (base excess of extracellular fluid), or BDECF (base excess of extracellular fluid), and less reliably by HCO3 (bicarbonate).

The Acid–Base Chart presented in 1971 by Siggaard-Andersen5  plotted pH against log(PCO2). It generated a value for standard base excess and offered curved outlined areas where clinical conditions (and normal) might be found. In 1976, a new diagram was created6  plotting partial pressure of carbon dioxide against standard base excess. This produced linear pH lines as well as linear zones for six typical clinical conditions (and normal); the partially compensated zones were placed midway between complete compensation and none.

In 1998, Schlichtig et al.7  refined the location of the partially compensated zones using Schlichtig’s comprehensive collection of data from 21 published reports (see fig. 1).

Fig.

Acid–base diagram showing characteristic zones on PCO2 /standard base excess (SBE) axes.

Fig.

Acid–base diagram showing characteristic zones on PCO2 /standard base excess (SBE) axes.

There is one published attempt to validate this diagram.8  The authors found that it presented the “higher diagnostic agreement” but also reported that their own “two expert physicians disagreed with each other in the diagnosis of 1/3 of the cases.” This last statement, in conjunction with abundant anecdotes of error and confusion in critical care, emergency care, and anesthesia, prompted the present article.

The Proposal

Artificial intelligence already generates various clinical text reports. For example, text may be added to an electrocardiogram report and a tentative diagnosis may be created from a mammogram. Accuracy has improved, but such reports cause concern9–11  and caution persists.12  In striking contrast, there appear to be no text reports associated with acid–base values despite the level of certainty that can be achieved. The proposal is that values for pH and partial pressure of carbon dioxide should generate accurate text descriptions. These are examples of reports generated by this system:

Ideally, a diagram showing the location of the values should accompany the text. For further examples of such text reports, use a laptop or desktop computer to visit the site http://www.acid-base.com/diagramlarge.php (accessed December 11, 2018).

The proposed text presents four separate items:

  1. The direction and magnitude of the overall change in blood acidity

  2. The primary, or major, component (respiratory or metabolic), magnitude, and value

  3. The secondary, or minor, component (metabolic or respiratory), magnitude, and value

  4. Description of a characteristic zone where one exists

The first three items are not controversial. They are accurate text descriptions that reduce the possibility of confusion. Although the fourth line is soundly derived from published data, the nature of acid–base disturbances means that outliers will exist. For this reason line four is preceded with the word “Consider….”

Conclusion

Environments in which acid–base values are interpreted are often far from ideal: in many hospitals in different parts of the world, fatigue, staff shortage, and inexperience are common. Blood gas reports should include a version of this text report: it may not have the vivid colors shown on the website, text may continue on a single line, and the units used will depend on location (e.g., rarely, if ever, will the acidity be shown both as pH and [H+]).

There is no longer any reason for providing acid–base results as just numbers with, in some cases, a string of confusing options for metabolic acidosis. Minimizing confusion in high-stress environments must be a priority. This proposal provides a solution.

The author is grateful to Peter Grogono, B.A., M.A., M.Comp.Sc., Ph.D. (Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec, Canada) for the introduction to animating diagrams using JavaScript.

The author is not supported by, nor maintains any financial interest in, any commercial activity that may be associated with the topic of this article.

1.
Lassen
HCA
:
A preliminary report on the 1952 epidemic of poliomyelitis in Copenhagen with special reference to the treatment of acute respiratory insufficiency.
Lancet
1953
;
1
(
6749
):
37
41
.
2.
Louise Reisner-Sénélar
L
:
The birth of intensive care medicine: Björn Ibsen’s records.
Intensive Care Med
2011
;
37
:
1084
6
.
3.
Severinghaus
JW
,
Astrup
PB
:
History of blood gas analysis. IV. Leland Clark’s oxygen electrode.
J Clin Monit
1986
;
2
:
125
39
.
4.
Andersen
OS
,
Engel
K
:
A new acid-base nomogram: An improved method for the calculation of the relevant blood acid-base data.
Scand J Clin Lab Invest
1960
;
12
:
177
86
.
5.
Siggaard-Andersen
O
:
An acid-base chart for arterial blood with normal and pathophysiological reference areas.
Scand J Clin Lab Invest
1971
;
27
:
239
45
.
6.
Grogono
AW
,
Byles
PH
,
Hawke
W
:
Acid-base diagrams.
Lancet
1976
;
308
(
7984
):
499
500
.
7.
Schlichtig
R
,
Grogono
AW
,
Severinghaus
JW
:
Human PaCO2 and standard base excess compensation for acid-base imbalance.
Crit Care Med
1998
;
26
:
1173
9
.
8.
Panagiotis
B
,
Miltos
V
,
Loukos
A.
,
Theakos
N
:
Latest developments in graphic diagnostic approach of arterial blood gases disturbances.
Pneumon
2004
;
17
(
2
):
150
8
.
9.
Goodacre
S
,
Webster
A
,
Morris
F
:
Do computer generated ECG reports improve interpretation by accident and emergency senior house officers?
Postgrad Med J
2001
;
77
:
455
7
.
10.
Guglin
ME
:
Deepak Thatai: Common errors in computer electrocardiogram interpretation.
Int J Cardiol
2006
;
106
(
2
):
232
7
.
11.
Schläpfer
J
,
Wellens
HJ
:
Computer-interpreted electrocardiograms: Benefits and limitations.
J Am Coll Cardiol
2017
;
70
:
1183
92
.
12.
He
W
,
Juette
A
,
Denton
ER
,
Oliver
A
,
Martí
R
,
Zwiggelaar
R
:
A review on automatic mammographic density and parenchymal segmentation.
Int J Breast Cancer
2015
;
2015
:
276217
.