Junior ICU staff are expected to fill out these cumberome forms, and nobody ever explains to them the hidden meaning behind this seemingly purposeless activity. However, there is method to this madness. Pragmatically, filling out APACHE forms ensures that the unit you work in will remain accredited for training. The ability to calculate SMRs on the basis of APACHE data helps compare your unit to other similar units. And you can use the data in clinical trials, retrospective audits, in mortality prediction, funding allocation and many other things besides.
Traditionally, we suck at answering questions about this boring topic. Question 11 from the first paper of 2009 asked the candidates to compare APACHE with SOFA, and 87% of us failed. Question 4 from the second paper of 2005 was more fair, asking generally about principles behind illness scoring systems and their relationship to outcome - still only 29% were able to score passing marks. Writing in 2017, the younger version of this author theorised that, though these questions have not been seen for many years, a local recurrence would be inevitable, and would likely lead many candidates to their doom; and this speculation was vindicated when scoring systems appeared again as Question 18 from the cursed first paper of 2023.
The objective of this chapter is to arm the candidates with enough basic information to score a passing mark. There are of course various scoring systems which are disease specific (eg. the Glasgow Coma Scale, the MELD score for liver disease) and which have defined uses in predicting prognosis and allocating treatment. The ICU scoring systems are somewhat different. Life In The Fast Lane has an excellent summary of ICU scoring systems, which is directed at the CICM Fellowship Exam candidate.
Here are some links to the seminal articles which describe these systems:
So.
ICU scoring systems collect data about the whole patient, with all their multisystem problems, and render this complex picture down into a single numerical value - their "illness severity score". So, if somebody asks, "how sick was that man?" you may be able to answer: "22".
How are these scoring systems useful?
LITFL gives the following as a list of qualities for the "ideal" ICU scoring system. Their
According to them, the ideal scoring system should have the following characteristics :
Also:
In his 2010 review of scoring systems, Jean-Louis Vincent gives this list of "ideal" features:
Most of them measure physiological variables.
eg. how low the hemoglobin, how high the blood presure etc.
Some of them measure interventions, eg. how much noradrenaline did the patient require, and whether they ended up mechanically ventilated or on dialysis
Most of the abovementioned variables are given a score, weighing their "severity". The weighting is derived from logistic regression analysis of large demographic data sets, which reveal the association of these physiological variables with mortality.
APACHE stands for Acute Physiology, Age and Chronic Health Evaluation (I-IV).
The APACHE-III was intoduced in 1991, and APACHE-IV in 2006. Each is an improvement (in terms of prognostic accuracy) but for some reason these are not widely used in Australia.
The APACHE system assesses three factors which influence ICU survival: chronic disease, patient reserve, and severity of acute illness. It takes into account such afctors as whether the admission was elective or not, and whether the admission was post-operative or nonsurgical.
The physiological component of the system is based on the most abnormal scores within the first 24 hours. Though it is not possible to predict individual patient outcomes, standardised mortality ratios can be used on large patient populations.
SOFA stands for Sequential Organ Failure Assessment .
There is a defined score of 1-4 for each organ system, which is collected daily. This not a predictive model- there are no mortality algorithms here. A higher SOFA score can be said to relate to increased mortality, but there is no mathematical model to help us figure out exactly how the total score relates to survival.
LITFL has a good table which describes the differences between these two scoring systems.
It is derived from the CICM Fellowship exam question (Question 11 from the second paper of 2009). With minor modifications, it is reproduced below:
.
APACHE |
SOFA |
|
Basic premise |
ICU mortality depends on three domains:
Thus, if one can quantify these domains, one may be able to predict mortality on the basis of such measurements. |
Degree of organ dysfunction is related to acute illness. Originally designed with sepsis in mind, but subsequently validated in other disease states. |
Measured parameters |
Heuristic groupings of 12 physiologic variables, Glasgow Coma Score (GCS), age, and chronic health evaluation status. |
6 domains of organ system function |
Measurement collection |
Worst score within the first 24 hours |
Daily measurement of |
Unique features |
Incorporates chronic illness, emergency admission, age, surgical vs non-surgical admission, and cardiorespiratory arrest |
Incorporates the use of organ system support sug as vasopressors and dialysis |
Scoring |
0 to 71 |
0 to 24 |
Mortality prediction |
The risk of hospital death is computed by combining APACHE II score with Knaus' |
SOFA does not predict mortality, and the original authors intended it to be used as a means of reproduceably describing a sequence of complications in the critically ill. That said, higher SOFA scores are in fact associated with increased mortality. |
Prognostic value |
APACHE is a poor predictor of individual patient outcome. |
One can monitor response to therapy by the change of daily SOFA scores |
Some studies have tested these scales head-to-head. An Indonesian study found that SOFA scores predict mortality better than APACHE-II in surgical ICU patients. The Canadians found that APACHE had good ROC chacateristics and predicted mortality resembled observed mortality, but in a population with a mean APACHE score of 16. An audit of a large Scottish database however has revealed that all scoring systems generally fail, and generate mortality predictions which are completely different to the observed mortality.
Young, Paul, et al. "End points for phase II trials in intensive care: Recommendations from the Australian and New Zealand clinical trials group consensus panel meeting." Critical Care and Resuscitation 15.3 (2013): 211. - this one is not available for free, but the 2012 version still is:
Young, Paul, et al. "End points for phase II trials in intensive care: recommendations from the Australian and New Zealand Clinical Trials Group consensus panel meeting." Critical Care and Resuscitation 14.3 (2012): 211.
Suter, P., et al. "Predicting outcome in ICU patients." Intensive Care Medicine20.5 (1994): 390-397.
Martinez, Elizabeth A., et al. "Identifying Meaningful Outcome Measures for the Intensive Care Unit." American Journal of Medical Quality (2013): 1062860613491823.
Tipping, Claire J., et al. "A systematic review of measurements of physical function in critically ill adults." Critical Care and Resuscitation 14.4 (2012): 302.
Gunning, Kevin, and Kathy Rowan. "Outcome data and scoring systems." Bmj319.7204 (1999): 241-244.
Woodman, Richard, et al. Measuring and reporting mortality in hospital patients. Australian Institute of Health and Welfare, 2009.
Vincent, J-L. "Is Mortality the Only Outcome Measure in ICU Patients?."Anaesthesia, Pain, Intensive Care and Emergency Medicine—APICE. Springer Milan, 1999. 113-117.
Rosenberg, Andrew L., et al. "Accepting critically ill transfer patients: adverse effect on a referral center's outcome and benchmark measures." Annals of internal medicine 138.11 (2003): 882-890.
Burack, Joshua H., et al. "Public reporting of surgical mortality: a survey of New York State cardiothoracic surgeons." The Annals of thoracic surgery 68.4 (1999): 1195-1200.
Hayes, J. A., et al. "Outcome measures for adult critical care: a systematic review." Health technology assessment (Winchester, England) 4.24 (1999): 1-111.
RUBENFELD, GORDON D., et al. "Outcomes research in critical care: results of the American Thoracic Society critical care assembly workshop on outcomes research." American journal of respiratory and critical care medicine 160.1 (1999): 358-367.
Turnbull, Alison E., et al. "Outcome Measurement in ICU Survivorship Research From 1970 to 2013: A Scoping Review of 425 Publications." Critical care medicine (2016).