In 1941, Saklad proposed a classification system that attempted to assess and measure a
patient’s physiologic reserve before a surgical procedure.( After undergoing a few modifications, it became widely
known as the American Society of Anesthesiologists (ASA) physical status classification
system.( It became widely used
and became part of the routine pre-operative assessment in many countries (it is also used
for billing reasons in the United States).( It is an apparently simple classification system that has been
frequently shown to be associated with morbidity and mortality.The ASA classification system was revolutionary in its field.( Contrary to modern prognostic scores,(
the ASA relies on an apparently simple principle: outcome depends on the patient’s previous
comorbidities and how those comorbidities affected the patient. If comorbidities affect the
patient’s physiologic reserve, then less remains for withstanding surgical stress. As
statistics interweaved into medicine, prognostication began to rely on more objective,
“palpable” features. As a result, none of the most commonly used severity indexes applied
in the modern intensive care units setting incorporate any measure of previous performance
status,( despite the fact that performance status has been repeatedly shown
to be have prognostic significance.( Even scoring systems aimed at predicting
morbidity after surgery, such as POSSUM, P-POSSUM and SORT,( fail to account
for performance status. There are some reasons for this. First, objective measurements are
less prone to personal and local bias. For example, heart rate assessment is performed in
the same manner everywhere, as is the case for blood pressure, pH, etc. In contrast, the
ASA score varies widely from person to person, as it is subjective. Therefore, it is not
surprising that the agreement between ASA scores obtained by different physicians and
between ASA scores obtained at different time points is only moderate.(Second, objective scores are easier to compare. All frequentist statistical analyses are
based on the appropriate measurement of a relevant variable a certain number of times
(and/or in a certain number of subjects) that is sufficient to obtain a certain level of
significance. Measuring and pooling opinions is cumbersome, even for experienced social
sciences experts, let alone for bedside physicians. Therefore, it is easy to understand
that due to benchmarking and external validity reasons (among many other reasons),
objective scores are frequently applied in anesthesiology and in critical care
medicine.(Nevertheless, there are advantages to including subjective measures in preoperative risk
evaluations. Any score that incorporates any degree of subjectiveness may aid in
communication and provide, in a certain sense, a measurable opinion of the attending
physician. This cannot be determined by simple statistical analysis. When the
anesthesiologist transfers a patient to the intensivist after major surgery, informing
him/her of the patient’s ASA score may help him/her to predict the course of the
postoperative period, regardless of the number of comorbidities or any other variables
measured in the intraoperative period. It may also help the intensivist understand how the
anesthesiologist felt about the patient’s condition. One may say that simply recording the
ASA score in the pre-operatory evaluation chart may be a form of emotional reporting, a
measurement of “how well the anesthesiologist thinks things will go”.(This brings us to ask what we should currently expect from the ASA score. Moreno et
al.,( in this edition, used data
from the EuSOS study to further evaluate the role of the ASA score in modern practice. It
was a very timely analysis for which the authors should be commended. Reexamining the role
of old practices and tools is an essential part of the necessary reinvention of clinical
practice. The authors concluded that the discriminatory capability of the ASA score was
low, which was interpreted as a lack of clinical relevance to the modern anesthesiology
practice. It is not surprising that ASA 1 and 2 were grouped together in the same risk
category after recursive partitioning. In the main EuSOS study, mortality was not
significantly different for ASA 1 and 2.( Additionally, some misclassification issues existed with the ASA score
(as pointed by the authors in the discussion). However, as shown in figure 2 and in the
Kaplan Meier’s plots, survival decreased when the ASA increased from 2 to 5. The
association between ASA score and higher mortality was maintained in a multivariate
analysis. This may suggest that the ASA score measures something that we cannot yet clearly
define. Consequently, a relevant point that could not be assessed by the authors in the
present analysis was whether the ASA score still provides any information that is not
captured by other scores or other clinical prediction rules. It is also unclear if ASA
performance would be better (or worse) in a specific subset of patients. Recursive
partitioning was performed by the authors, but it only evaluated ASA score and did not
account for other relevant variables or possible interactions. For example, ASA score might
be less relevant for smaller procedures than for major abdominal or thoracic surgeries.
Other interactions between outcome-associated variables may be expected, such as that
between the anesthesiologist’s experience and the ASA score.Therefore, before we can conclusively state that the ASA score is outdated, we should
address every possible scenario where the score could provide useful information. For
example, many clinical symptoms and diagnostic procedures have low discriminative
capability and are still applied regularly. The presence of rales has low reliability for
the diagnosis of pneumonia, but auscultation for the identification of rales is still
taught to medical students worldwide.(
Moreno’s work highlights the importance of keeping a high level of suspicion regarding the
validity of old practices.( It may not
be sufficient to deconstruct the role of a very old tool, but this is a move forward in the
interpretation of the ASA score.
Authors: Rupert M Pearse; Rui P Moreno; Peter Bauer; Paolo Pelosi; Philipp Metnitz; Claudia Spies; Benoit Vallet; Jean-Louis Vincent; Andreas Hoeft; Andrew Rhodes Journal: Lancet Date: 2012-09-22 Impact factor: 79.321
Authors: Sarah Scott; Jonathan N Lund; Stuart Gold; Richard Elliott; Mair Vater; Mallicka P Chakrabarty; Thomas P Heinink; John P Williams Journal: BMC Anesthesiol Date: 2014-11-18 Impact factor: 2.217