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    APACHE II Score

    Estimates ICU mortality.
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    When to Use
    Pearls/Pitfalls
    Why Use

    This score can be calculated on all patients newly admitted to the intensive care unit. While it is not mandatory and will not help with patient management, it is a useful tool for risk stratification and to compare the care received by patients with similar risk characteristics in different units.

    • APACHE II is the most widely used ICU mortality prediction score.
    • It differs from the original APACHE score in some ways; the number of variables is decreased and the weight of some of the variables is adjusted.
    • APACHE III and APACHE IV scores were also developed but are not commonly used because their statistical method is under copyright control.
    • The score was derived in a general ICU population and may be less precise when applied to specific populations such as liver failure or HIV patients.
    • Since APACHE II was studied on patients newly admitted to the ICU, it is not accurate when dealing with patients transferred from another unit or another hospital. This is known as lead time bias and is addressed in APACHE III.
    • The APACHE II score must be recalibrated before it can be used in a population other than the one it was derived in.
    • ICU prediction scores in general need to be periodically recalibrated to reflect changes in practice and patient demographics.
    • Mortality prediction scores such as APACHE II are often used to assess the baseline risk groups being compared in clinical trials.
    • They can also be used to determine prognosis and help family members make informed decisions about the aggressiveness of care.
    years
    F
    mm Hg
    beats/min
    breaths/min
    mEq/L
    mEq/L
    mg/dL
    %
    ×10³/µL
    Use either A-a Gradient OR PaO2
    mm Hg
    mm Hg

    Result:

    Please fill out required fields.

    Next Steps
    Evidence
    Creator Insights

    Management

    The APACHE II score was designed as a mortality prediction tool but was not intended to influence the medical management of patients during their ICU stay.

    Critical Actions

    • A number of variables are used to calculate the APACHE II score. The worst values recorded during the initial 24 hours in the ICU should be used. Alternatively, the variables initially recorded during the patient’s admission can be used for practical reasons.
    • The APACHE II score is calculated at the beginning of the ICU admission to help determine the patient’s mortality risk for the admission. It is not calculated sequentially and is not meant to show improvement or effect of interventions. As such it should not be used to direct medical management.

    Formula

    Addition of the selected points; points assigned below:

    Facts & Figures

    The APACHE-II Score provides an estimate of ICU mortality based on a number of laboratory values and patient signs taking both acute and chronic disease into account. Note: The data used should be from the initial 24 hours in the ICU, and the worst value (further from baseline/normal) should be used.

    The following defines “chronic organ insufficiency” and immunocompromise:

    • Liver insufficiency
      • Biopsy proven cirrhosis
      • Documented portal hypertension
      • Episodes of past upper GI bleeding attributed to portal hypertension
      • Prior episodes of hepatic failure / encephalopathy / coma
    • Cardiovascular
      • New York Heart Association Class IV Heart Failure
    • Respiratory
      • Chronic restrictive, obstructive or vascular disease resulting in severe exercice restriction, i.e. unable to climb stairs or perform household duties
      • Documented chronic hypoxia, hypercapnia, secondary polycythemia , severe pulmonary hypertension (> 40 mmHg), or respirator dependency
    • Renal
      • Receiving chronic dialysis
    • Immunosuppression
      • The patient has received therapy that suppresses resistance to infection e.g. immuno-suppression, chemotherapy, radiation, long term or recent hight dose steroids, or has a disease that is sufficiently advanced to suppress resistance to infection, e.g. leukemia, lymphoma, AIDS

     

    Point Values

    Criteria Point Value
    Age in years
    ≤44 0
    45-54 +2
    55-64 +3
    65-74 +5
    >74 +6
    History of severe organ insufficiency or immunocompromised?
    Yes, and non-operative or emergency post-operative patient +5
    Yes, and elective post-operative patient +2
    No 0
    Rectal Temperature (°C)
    >40.9 +5
    39-40.9 +3
    38.5-38.9 +1
    36-38.4 0
    34-35.9 +1
    32-33.9 +2
    30-31.9 +3
    <30 +4
    Mean arterial pressure (mmHg)
    >159 +4
    130-159 +3
    110-129 +2
    70-109 0
    50-69 +2
    <50 +4
    Heart rate (beats per minute)
    >179 +4
    140-179 +3
    110-139 +2
    70-109 0
    55-69 +2
    40-54 +3
    <40 +4
    Respiratory Rate (breaths per minute)
    >49 +4
    35-49 +3
    25-34 +1
    12-24 0
    10-11 +1
    6-9 +2
    <6 +4
    Oxygenation (use PaO2 if FiO2 < 50%, otherwise use A-a gradient)
    A-a gradient >499 +4
    A-a gradient 350-499 +3
    A-a gradient 200-349 +2
    A-a gradient <200 (if FiO2 over 49%) or pO2 >70 (if FiO2 less than 50%) 0
    PaO2 = 61-70 +1
    PaO2 = 55-60 +3
    PaO2 <55 +4
    Arterial pH
    >7.69 +4
    7.60-7.69 +3
    7.50-7.59 +1
    7.33-7.49 0
    7.25-7.32 +2
    7.15-7.24 +3
    <7.15 +4
    Serum sodium (mMol/L)
    >179 +4
    160-179 +3
    155-159 +2
    150-154 +1
    130-149 0
    120-129 +2
    111-119 +3
    <111 +4
    Serum potassium (mMol/L)
    >6.9 +4
    6-6.9 +3
    5.5-5.9 +1
    3.5-5.4 0
    3-3.4 +1
    2.5-2.9 +2
    <2.5 +4
    Serum Creatinine (mg/100mL)
    >3.4 and ACUTE renal failure +8
    2.0-3.4 and ACUTE renal failure +6
    >3.4 and CHRONIC renal failure +4
    1.5-1.9 and ACUTE renal failure +4
    2.0-3.4 and CHRONIC renal failure +3
    1.5-1.9 and CHRONIC renal failure +2
    0.6-1.4 0
    <0.6 +2
    Hematocrit (%)
    >59.9 +4
    50-59.9 +2
    46-49.9 +1
    30-45.9 0
    20-29.9 +2
    <20 +4
    White blood count (total/cubic mm in 1000's)
    >39.9 +4
    20-39.9 +2
    15-19.9 +1
    3.0-14.9 0
    1.0-2.9 +2
    <1.0 +4
    Glasgow Coma Scale (GCS)
    1 - 15 15 - [GCS Score]

    Mortality Rates

    APACHE II Score Approximated Mortality Rate
    0-4 4%
    5-9 8%
    10-14 15%
    15-19 25%
    20-24 40%
    25-29 55%
    30-34 75%
    >34 85%

    Evidence Appraisal

    • The APACHE II score was initially presented and validated in this study by Knaus, et. al. that prospectively enrolled 5815 patients from 13 hospitals. Complete data on all 12 physiologic measurements was only available for 5030 patients. The APACHE II score was shown to have good prognostic value in acutely ill patients.
    • This study prospectively validated the APACHE II score in 1721 consecutively admitted patients in a single center. The area under the ROC curve was higher than 0.8. The patient population was mostly comprised of surgical patients however.
    Dr. William Knaus

    From the Creator

    Why did you develop the APACHE system?
    When we started [developing APACHE] in the 1970s, DRGs [diagnosis-related groups] were just coming on the scene, and obviously they were oriented towards the business and financing aspects of healthcare. There’s little correlation to the clinical. But people were relying on DRGs as a way to classify and identify patients, especially in the ICU. So it was important at that time to not so much reinvent the diagnostic system, but to talk about how patients come in at different levels of severity. And at that time, there was really nothing out there. People would use one single blood test, like a blood lactate level, and then they would pick a threshold, above this or below that. But drawing thresholds is a losing method when you have a continuous measure, like blood lactate.

    Then Bryan Jennett created the Glasgow Coma Scale score, and was very successful with that. But that only applied to head trauma patients and emergencies.

    So we started looking at the role of using physiology of a patient in the intensive care unit and to then develop a comprehensive measure of severity that could at least begin to discriminate one patient from another better than the DRG. We were unexpectedly well-received. At our first critical care congress in the late '70s, there was an extraordinary amount of interest, and so we began to pursue that. We evolved that—it had a large number of variables, and even something as simple as the equations we had developed for APACHE at that time, you would have to put them on the computer on Friday evening and wait until Monday morning. We were dealing with technology that was still not able to handle computations of large volume. So we decided to hone down APACHE II to put it down on one side of a piece of paper, and I think that was the single most important efficiency that we made. I remember we had a research associate who was hiking in the Himalayas, and she was hospitalized in Kuala Lumpur, she said there was nothing in the hospital, some oxygen, no mattresses. But there was APACHE II, taped to the wall. So we knew that there was something to the simplicity of the use of that.

    There was a big strategic discussion about whether we should just stop and then just continuously update with a new database, because as we know now, with the scoring systems of any kind of classification system, it’s not like wine, it doesn’t get better with age. You need a database that is very current. APACHE II published a couple years ago how much the outcomes in critical care had changed across the spectrum and we are doing better than we had before, so databases from years and years ago don’t really represent contemporary outcomes.

    But at that time, technology was getting a lot better, computers were beginning to run faster, we had a lot more computer speed, and we envisioned the future even in the late '80s and early '90s that we could have an algorithmic-based system that would retrieve data automatically for people, and be able to help them make critical decisions based on how sick the patient was, whether the therapy was working, how long the patient was anticipated to stay, etc. It was the last time that the country before most recently was trying to make some headway with interoperability in healthcare technology.

    But at that time we didn’t know. We were looking forward towards the future where people would be collecting data and using scoring systems, like they still do on MDCalc, and would be able to consult a computer, much like Google’s algorithms do now. It’s continuously learning from the database who you are, what you ask for, etc. And we really thought that you could have a system which was dynamic and algorithmic-based, that could start to provide some decision support that I and many others felt we needed.

    And of course what has happened, to make a long story short, that in the decades since APACHE II was published, it’s been extraordinarily disappointing to me personally, that we’ve made such little progress in pushing healthcare technology forward with interoperability and with modern computers. We ended up not being able to achieve those very ambitious goals. I think it continues, it’s being updated nicely, and over the years the full APACHE IV system, which is the latest version with the latest algorithm and database, is not really being used nearly as much as APACHE II.

    So in retrospect, if we had known the future was going to be as limited in the development of healthcare technology, I think we would’ve said, let’s stay with APACHE II and let’s just try and update the database so it would be compatible with contemporary outcomes. While we have developed systems like APACHE IV which are much more sensitive and much more capable than APACHE II, the ability to feed those algorithms automatically is still extremely limited. So if you’re using APACHE, make sure you use it with a database, either yours or someone else’s, that uses contemporary patients, so the relationship between the score and what happens to people does change over time. You can use the same score, but you want to have current patients and their outcomes in the system.

    The inability, for whatever reason, of healthcare to achieve the same degree of technology that the banking and retail and all other large industries have, is going to be seen as the major shortcoming of modern times. I don’t want to comment on who is responsible for that, but we have a series of products that historically began in business, in the financial offices, and never saw or never wanted to develop the capability to talk to each other. That’s what we’re unfortunately stuck with.

    People are taken care of by clinicians, but there is no system out there that was designed primarily with clinicians in mind. Whereas all these websites that are so popular—Google, Amazon, Apple you name it—why are they so popular? Because they take information about what the user wants and what the user needs. The user is a person, an individual. It’s not an institution. If only medicine had been able to see that, and somehow make that transition from developing an information system for an institution or a practice as opposed to developing it for the individuals using it. I haven’t seen that happen.

    About the Creator

    William Knaus, MD, is a Professor Emeritus of The University of Virginia School of Medicine and a member of The National Academy of Medicine. Dr. Knaus is an active researcher in many areas including cancer genomics, sepsis, and outcomes of seriously ill patients.

    To view Dr. William Knaus's publications, visit PubMed

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