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November 2007

Automating shunt calculation improves analytical quality

Tartu University Hospital has improved the quality of blood gas testing in its clinical laboratory and critical care units by introducing an automatic system for blood gas analysis.

Not only did the quality of processes in the preanalytical phase improve, but also the automatic calculation of pO2(A-a), for APACHE scoring as a measure of the quality of the analytical phase, was more accurate than manual calculation.

MEASURING THE QUALITY OF THE ANALYTICAL PHASE

There are several scoring systems for the estimation of the effectiveness and quality of critical care units; one of them is APACHE II ("Acute Physiology and Chronic Health Evaluation")[1,2].

After admission of a patient to an intensive care unit, an integer score from 0 to 71 is computed, based on several measurements: higher scores imply a more severe disease and a higher risk of death. The point score is calculated from 12 routine physiological measurements (such as blood pressure, body temperature, heart rate, etc.) during the first 24 hours of admission, information about previous health status and some information obtained at admission.

Of the 12 measurements, seven are performed by the laboratory: serum sodium, serum potassium, serum creatinine, packed cell volume, white blood cell count, arterial pH, oxygenation (pO2 if FO2(I) <50% and pO2(A-a) if FO2(I) >50 %).

The Anesthesiology and Intensive Care Clinic of Tartu University Hospital, Estonia (see End-note), has been using the "Quality Reporting and Benchmarking Service for Healthcare" program, provided by Intensium iQR, since 2006 [3].

The APACHE II form in Intensium contains a special equation for calculation of pO2(A-a) (the difference in the partial pressure of oxygen of the alveolar air and arterial blood, an indicator of the efficacy of the oxygenation process in the lung).

There are several problems with this equation, since the result may vary depending on the analyzer configuration, manufacturer of the analyzer and quality control service used.

MANUAL CALCULATION

The difference in the partial pressure of oxygen in the alveolar air and arterial blood is calculated [4] as follows:

pO2(A-a) = pO2(A) – pO2(a)   (equation 1)

where pO2(A) is the partial pressure (or tension) of oxygen in alveolar air, and pO2(a) is the partial pressure (or tension) of oxygen in blood.

The pO2(a) is measured by an analyzer and pO2(A) calculated by the "alveolar air equation":

pO2(A)= FO2(I)(p(amb) – pH2O) – pCO2/RQ  (equation 2)

where FO2(I) is the fraction of oxygen in inspired air, p(amb) is the ambient barometric pressure, pH2O is the saturated vapor pressure of water (47mmHg), pCO2 is the partial pressure (or tension) of carbon dioxide in blood and RQ is the respiratory quotient.
 
RQ is a ratio indicating the relation of the volume of CO2 production to the oxygen consumption in the body. The range of RQ for organisms in metabolic balance usually is from 1.0 to 0.7 [5]. RQ is an input parameter, such as patient temperature or FO2(I), and in case the value is not given by the nurse, the analyzer uses a "standard" value of RQ.

The p(amb) equation using Dalton's law may be written for room air as:

p(amb) = pO2 + pCO2 + pN2 + pH2O + pX   (equation 3)

where pN2 is the partial pressure of nitrogen and pX is the partial pressure (or tension) of any other gas in the air sample.

However, in blood gas work, the standard is for measurement of partial pressure always at body temperature (usually 37 °C), and in the presence of saturated water vapor (pH2O = 47 mmHg). [6]
With a p(amb) of 760 mmHg, pH2O as 47 mmHg and RQ as 1, the equation will be (1):

pO2(A-a) = FO2(I)(713) – pCO2pO2   (equation 4)

The same equation is used by Intensium.

AUTOMATIC CALCULATION

The equation used by the automatic blood gas system is:

pO2(A-a) = FO2(I)(p(Amb)- pH2O)- pCO2(RQ-1- FO2(I)-1(RQ-1-1))  (equation 5)

Default value for RQ is 0.86.

With an RQ of 0.86 the equation will be: 

pO2(A-a) = FO2(I)(p(Amb)- pH2O)- pCO2(1.16-(0.16) FO2(I)) (equation 6) 

COMPARISON OF AUTOMATIC AND MANUAL RESULT CALCULATIONS

In our critical care units, using the manual system, nurses calculated manually 

  • the pO2(A-a) difference value using the values of pCO2, pO2 and FO2(I)
  • the pO2/FO2(I) values, using the values of pO2 and FO2(I)

In the automatic system, the pO2(A-a) difference and the pO2/FO2(I) values are calculated automatically.

We have compared the results of 101 patients for pO2(A-a) difference with an FO2(I) above 50 %, using automatic and manual calculations. The results were compared with mean differences paired t-test and linear regression.

The regression line was: automatic = (– 4.4) + 0.99 × manual with a confidence interval of 95 %. Mean difference was 8.3 mmHg.

The results indicate that the automatically calculated pO2(A-a) difference values were significantly lower than the values derived from manual calculation. For example, a sample with an automatic calculation (equation 5) of pO2(A-a) of 480 mmHg gives a score (according Table I) of +3 points; the manual calculation (equation 4) of pO2(A-a) of the same sample was 501 mmHg, giving a score of +4 points.

The automatic equation (equation 5) is not only faster to calculate than the manual one (equation 4), but the pO2(A-a) values from the automatic system are more accurate because they are based on measured parameters rather than default values.

  +4 +3 +2 +1 0 +1 +2 +3 +4
pO2  <55 55-
60
  61-
70
>70        
pO2(A-a)         <200   200-
349
350-
499
>500

The total number of APACHE II points gives a score ranging from 0
to 71, with an increasing score representing a rising severity of
illness.

Logit = –3.517 + 0.146 (Apache II)
+ diagnostic category weight [7]   (equation 7)

Probability of death = elogit/1 + elogit   (equation 8)

A ratio (equation 8) greater than 1.0 may reflect poor care and a
ratio below 1.0 may reflect good care [1].
 

TABLE 1: APACHE II scores for pO2 and pO2(A-a)

Definitely, the one-point difference is not clinically important, since according to equation 7, the APACHE II points are multiplied by 0.146 and a difference of one point is not significant. However, the accurate estimation of APACHE II score points should be very important for research studies and quality control reports [1]. 

CONCLUSION

In our experience the automatic system improved the quality of the analytical phase. The automatic calculation of pO2(A-a), for APACHE scoring as a measure of quality control, has both improved the precision of the reports and has reduced the time for documentation.

End-note

Estonia’s largest hospital is Tartu University Hospital (TUH), comprising a consortium of 16 clinics. The largest clinic, the Anesthesiology and Intensive Care Clinic, is composed of eight departments including 30 operating rooms.

TUH receives around 418,000 outpatient visits per year of which 13 % are made to the emergency medicine units. Of 43,700 inpatients, 78 % of them are admitted due to emergency reasons [8].

The number of blood gas analyses is constantly increasing. In 2006 more than 40,000 blood gas analyses were performed in the United Laboratories (UL), the clinical laboratory of the TUH.

References
  1. Gunning K, Rowan K. ABC of intensive care, outcome data and scoring systems. BMJ 1999; 319: 241-44.
  2. Glance LG, Osler TM, Dick A. Rating the quality of intensive care units: is it a function of the intensive care unit scoring system? Crit Care Med 2002 Sep; 30(9): 1976-82.
  3. Intensium iQR Quality Reporting and Benchmarking Service for Healthcare. http://www.intensium.com.
  4. Rashad Net University. Arterial hypoxemia. http://www.rashaduniversity.com.
  5. Beals M, Gross L, Harrell S. Metabolism for energy and the respiratory quotient. http://www.tiem.utk.edu.
  6. Burtis CA, Ashwood ER, Bruns DE. TIETZ textbook of clinical chemistry and molecular diagnostics, 4th edition. Philadelphia: Elsevier Saunders, 2006.
  7. Knaus WA et al. APACHE II. A severity of disease classification system. Crit Care Med 1985; 13: 818-29.
  8. Clinicum, SA Tartu Ülikooli Kliinikumi maineraamat, 2007.
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References
  1. Gunning K, Rowan K. ABC of intensive care, outcome data and scoring systems. BMJ 1999; 319: 241-44.
  2. Glance LG, Osler TM, Dick A. Rating the quality of intensive care units: is it a function of the intensive care unit scoring system? Crit Care Med 2002 Sep; 30(9): 1976-82.
  3. Intensium iQR Quality Reporting and Benchmarking Service for Healthcare. http://www.intensium.com.
  4. Rashad Net University. Arterial hypoxemia. http://www.rashaduniversity.com.
  5. Beals M, Gross L, Harrell S. Metabolism for energy and the respiratory quotient. http://www.tiem.utk.edu.
  6. Burtis CA, Ashwood ER, Bruns DE. TIETZ textbook of clinical chemistry and molecular diagnostics, 4th edition. Philadelphia: Elsevier Saunders, 2006.
  7. Knaus WA et al. APACHE II. A severity of disease classification system. Crit Care Med 1985; 13: 818-29.
  8. Clinicum, SA Tartu Ülikooli Kliinikumi maineraamat, 2007.
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Agnes Ivanov

is quality manager at the United Laboratories of Tartu University Hospital 

United Laboratories of Tartu University Hospital 
L. Puusepa 1a 
50406 Tartu 
Estonia 

Articles by this author
Anu Tamm

  

is director at the United Laboratories of Tartu University Hospital
United Laboratories of Tartu University Hospital  L.
Puusepa 1a  50406 Tartu Estonia.

Articles by this author
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