This simplified acute physiology score (SAPS II) calculator determines the severity of health at ICU admission and predicts mortality rates. There is in depth information below the form about all the parameters involved and the mortality correlation equations.
How does this simplified acute physiology score (SAPS II) calculator work?
This health tool is a disease severity classification system published in 1993 and used in intensive care units worldwide.
SAPS II is addressed to patients over 15, usually within 24 hours of admission to ICU. Data are collected during the first 24 hours after ICU admission. The score is only administered once to check the patient’s health condition.
Once the calculations are done, the simplified acute physiology score (SAPS II) calculator provides an integer point score between 0 and 163 which correlates to mortality rates given in percentage, between 0 and 100%.
SAPS II is also used in studies to compare morbidity and outcomes between individual and groups of patients as it tends to be more accurate than similar intensive care classification tools such as APACHE II.
The system comprises of 15 items, resulting from clinical data, application of ER scores and physiological measurements as follows:
■ Age – in years, the higher the age, the higher the number of points awarded;
■ Heart rate – the worst value in beats per minute (highest or lowest);
■ Systolic blood pressure – same as with heart rate, highest or lowest value, whichever is the worst;
■ Glasgow coma score – lowest value in the first assessment after admission and before any sedation procedure occurs;
■ Body temperature – in degrees Celsius or Fahrenheit, with a cut of at 39C/102.2F;
■ PaO2/FiO2 ratio – in case of mechanical ventilation or CPAP (Continuous positive airway pressure ventilation);
■ Urinary output – as per 24 hours, if patient is admitted for less than 24h, urine output will be adapted for the average daily figure;
■ Serum urea or BUN – whichever is measured or higher, for serum urea in g/L and for BUN (serum urea nitrogen) in mg/dL;
■ WBC count – white blood cell number, cells per mm3, the lowest or highest measurement, whichever is more severe;
■ Serum potassium level, Serum sodium level and serum bicarbonate – all measured in mEq/L;
■ Bilirubin – measured in mg/dL to evidence liver function;
■ Chronic diseases – present with provision for metastatic cancer (proven by surgery or CT scan), hematologic malignancy (if lymphoma, acute leukemia, or multiple myeloma) and HIV positive patient (with clinical complications, diagnosing acquired immunodeficiency syndrome, in the range of: pneumocystis carinii pneumonia, Lymphoma, tuberculosis, Kaposi's sarcoma, or toxoplasma).
The above parameters are each awarded a particular number of points depending on severity and the evaluator is advised to use the worst determination results for each parameter.
The original study was developed on a cohort of 13,152 patients divided in developmental and validation groups, 65 – 35. Patients under 18 years, patients in cardiac care or having had cardiac surgery were excluded. Both groups performed similarly and the under the receiver operating characteristic curve was 0.88 for development group and 0.86 in the validation group.
Mortality rates correlated with SAPS II
Mortality prediction is based on the following formula that employs certain study based variables and the integer result from SAPS II. There is a sigmoidal relationship between score and mortality rates.
The formulas used are:
logit =−7.7631 + 0.0737 x Score + 0.9971 x ln(Score + 1)
Mortality = elogit/(1+elogit) * 100
However, the resulting percentage should be viewed as statistical only, as individual cases can evolve differently. Similar mortality predictions for ICU use are obtained through the SOFA score (Sequential Organ Failure Assessment). The following table evidences some examples of SAPS II scores and their mortality percentages.
|SAPS II score||Mortality rate|
1) Le Gall J-R, Lemeshow S, Saulnier F. (1993). . JAMA; 270:2957-2963
2)Deša K, Perić M, Husedžinović I et al. (2012) . Croat Med J; 53(5): 442–449.
3) Gilani MT, Razavi M, Azad AM. (2014) . Niger Med J; 55(2): 144–147.
4) Le Gall J-R, Neumann A, Hemery F et al. (2005) . Crit Care; 9(6): R645–R652.04 Apr, 2016