Among many severity scoring systems mentioned in this Section, APACHE scores
are the most commonly used and deserve some understanding. The basic premise in
these scores is that worst physiological derangement noted during first 24
hours after admission in an intensive care unit (ICU) more or less determines
the chance of hospital survival as these define organ insufficiency. This
implies, though, that treatment and care are not of much consequence as they
are nearly same in hospitals across the United States where this system was
evolved. APACHE-I was proposed in the year 1981 and was surprisingly accurate
in predicting mortality in patients in a variety of ICUs. An exception noted
later was the patients requiring coronary by-pass graft where the physiological
derangement was high but mortality was low. APACHE-I considered 34 routinely
collected physiological measurements and required no extra efforts. Each of
these measurements was assigned weight according to the severity of
derangement. For example, if serum pH value is either <7.15 or ≥7.70, the
weight is +4 as both are considered equally grave, whereas normal value between
7.33 and 7.49 has weight zero as this is no derangement (Knaus WA, Draper EA,
Wagnwer DP, Zimmerman JE. APACHE II: A severity of disease classification
system. Crit Care Med 1985; 13:818-829.). Slightly higher pH value between 7.50
and 7.59 was assigned weight +1 but on the lower side the value between 7.25
and 7.32 was assigned weight +2 as this is considered relatively more harmful.
Sum of these weights for 34 measurements was APACHE. Higher the score, more is
the chance of death. However, this was found too complex for adoption.
APACHE-II is the simplified version of APACHE-I and included only 12
physiological measurements. But it added points for age ranging from 0 for
<45 years to 6 for ≥75 years, and previous history (5 points for
nonoperative or postoperative emergency patients and 2 points for elective
postoperative patients). Maximum possible score is 71 although in practice none
exceeds 55. A score of 40 or more has been seen to be strongly associated with
hospital death. These scores were woven into a logistic regression (discussed
later in the book) with mortality as the outcome using data from a large number
of ICUs across the United Sates. The equation derived was
Ln( ) = - 3.517 + (0.146*APACHE-II score) + (0.603, only if postoperative
surgery) + (diagnostic category weight) ,
whereRis the predicted risk of death, and diagnostic
category weight was separately derived for 50 disease groups. For example, this
weight for asthma/allergies is –2.108 and for cardiogenic shock is +0.393.
Negative weight implies that the risk of mortality is less and positive weight
implies that the risk is more. These weights are available in Knaus et al.
Subsequently, APACHE-III appeared between 1991 and 2002 in several different
versions. This included 17 physiological variables, adjustment of location and
length of stay before ICU admission, and used splines for statistical modeling.
The last version of APACHE-III covered 96 disease groups. APACHE-IV appeared in
2006 and included 116 disease groups. This revised the prediction equation,
used five new predictors, extended splines, and made prior length of stay
continuous in terms of minutes and not just in integer days. The details of
APACHE-IV have been described by JE Zimmerman and AA Kramer (Outcome prediction
in critical care: the Acute Physiology and Chronic Health Evaluation models.
Curr Opin Crit Care 2008; 14:491-497).
In short, APACHE-III and IV are more complex and only marginally increase the
predictive accuracy over APACHE-II. Thus many still prefer APACHE-II. The
percentage of ICU patients correctly classified into survive/death by APACHE II
was observed as 85.5% in U.S. hospitals and the area under ROC curve was 0.863
(Knaus et al. 1985). Note that correct prediction is not as high as the hype
around this scoring system. Moreover, not many studies are available that can
guide us regarding use of APACHE in developing countries where ICU care and
mortality could be very different.
This scoring system is applicable to critical cases wherein survival is known
not to exceed 80%. If I am naïve and use this as predictivity for survival
without using any scoring system, I would be right in at least 80% cases. Thus
a scoring system such as APACHE-II adds just about 5% to the accuracy of
prediction. You may like to examine if it is worth taking and using more than
12 physiological measurements for a gain of paltry 5%.
Notwithstanding the problems just enumerated, APACHE scoring is still useful in
many setups. You can legitimately compare severity of cases admitted in
intensive care unit (ICU) of one hospital with that in another hospital, or in
two or more groups such as severity in people in different occupations.
Similarly, if a regimen is effective in 72% cases with APACHE-II score between
20 and 24, and another is effective in 78% with the same score, you are
confident of 6% difference in efficacy. Also, if average APACHE-II score in
critical cases admitted in a hospital during 2005-2009 is 17 and the average
rises to 21 in cases admitted during 2010-2014, it would be legitimate to say
that the cases admitted later are more severe. Actual utility of APACHE scores
lie in this kind of comparison rather than in predicting survival.
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