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| VIEW POINT |
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| Year : 2015 | Volume
: 3
| Issue : 2 | Page : 3-7 |
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SOFA vs APACHE II as ICU scoring system for sepsis: A dilemma
JD Lakhani
Professor & HOD; Department of Medicine, SBKS MI & RC, Sumandeep Vidyapeeth, Piparia, Waghodia, Vadodara, Gujarat, India
| Date of Web Publication | 24-Aug-2018 |
Correspondence Address:
J D Lakhani
Professor & HOD; Department of Medicine, SBKS MI & RC, Sumandeep Vidyapeeth, Piparia, Waghodia, Vadodara, Gujarat
India
 Source of Support: None, Conflict of Interest: None
DOI: 10.4103/2347-6486.239792
How to cite this article:
Lakhani J D. SOFA vs APACHE II as ICU scoring system for sepsis: A dilemma. J Integr Health Sci 2015;3:3-7 |
APACHE II (Acute Physiology and Chronic Health Evaluation II) introduced in 1985 is a modification of the original APACHE developed in 1981.[1],[2],[3] It is a scoring system aimed to determine the severity of disease and also to predict mortality of adult patients admitted to intensive care units. This system was developed as a result of data available from 5815 intensive care admissions from 13 hospitals of USA between 1979 and 1982. An increasing score was correlated with severity and subsequent risk of hospital death[2]. APACHE III, which is based on a larger database is an updated version of APACHE II. It has 18 physiological variables including chronic ill health parameters. Mortality prediction is done on basis of daily clinical updates.[4] This score has a wide lengthy range of 0 to 299, which makes it use difficult and time consuming. [4],[5] APACHE IV, having 142 variables is a statistical model of logistic regression.[6] Because of its complexity it is not widely used. APACHE II therefore is widely accepted and is one of the most validated score with readymade calculators available on the internet.[7] The Simplified Acute Physiology Score (SAPS) is simplified version of APACHE and is comparable to APACHE II.[8],[9]
Acute Physiology and Chronic Health Evaluation-II (APACHE-II) scoring system has three domains: “Acute Physiology”, “Chronic Health Evaluation” and “Age”; of which first two are reflected by the acronym-APACHE. First domain relates with “acute” changes (within first 24 hours of ICU admission) in physiological parameters like oxygenation (PaO2 in relation to FiO2), Rectal temperature, Mean arterial pressure, Arterial pH, Heart rate, Respiratory rate, Serum Sodium, Serum Potassium, Serum Creatinine, Hematocrit, White blood cell count and Glasgow Coma Scale (GCS). Thus, it relates with 12 physiological, objective and numerical parameters which are routinely observed and measured in intensive care unit. Physiological parameter above and below the set range is given an assigned score which categorizes severity of physiological dysfunction in numbers, which eventually can predict the outcome. It encompasses most organ functions and thus logically and by validation has been found to be a useful predictive score. Second domain, i.e. “Chronic Health Evaluation” which is evaluated based on past health status also is incorporated in the score and has bearing on the outcome. Domain of “preexisting co-morbidities” has a maximum score of 5 of total score points of 71 which means 7% contribution to mortality. Similarly third domain, i.e. “Age” will be having a contribution of 8.5% (6 of 71) and contribution of “co morbidities” and “age” combined will be in the tune of 15.5% (11 of 71). Though maximum total score is 71, in real case scenario, the upper limit of APACHE will not exceed fifty five.[7] Thus contributions of these two variables combined will be in the tune of 0% to 20% or more. Age, as one of the parameters in APACHE score makes it more comprehensive. Elderly patients may have chronic health problems thus in combination (age + chronic health problems) also, it will have significant contribution to the prognosis. The PREDICT model (Predicted Risk, Existing Diseases, and Intensive Care Therapy: the PREDICT model) has concluded that age and co-morbidity are the most important determinants of long-term prognosis of critically ill patients”. This prognostic model was developed from the clinical database of all the ICU admissions at Royal Perth Hospital (RPH) in Western Australia between 1989 and 2002 and can be used to estimate long-term survival of critically ill patients.[10] APACHE predicted mortality model is for severity of acute illness which was taken as a separate factor in the PREDICT model. In this, apart from age, co-morbidities (Charlson co-morbidity index) and APACHE-II, other important prognostic factors for estimation of long-term survival probabilities of critically ill patients were gender, duration of intensive care therapy or organ support within the first five days of ICU admission.[10] Consequently, it reflects that age and chronic health problem has a bearing on short term as well as long term mortality prediction. “Age” as a prognostic and stratifying variable in pneumonia patients is also included in CURB-65 score. The later score was derived from a study of 1068 patients in whom 9% mortality was observed in 30 days. Age 65 years (OR 3.5, 95% CI 1.6 to 8.0) was reported to be a factor independently associated with mortality.[11] Thus, though all prognostic scores do not include age as a parameter; it seems to be an important variable which is included in APACHE.
As discussed earlier, the concept of APACHE score is generic and is not disease or organ specific. As a result, it can be applied to all types of patients of ICU, medical as well as surgical barring some conditions like admission following coronary artery bypass graft (CABG) surgery or for primary burns. Sepsis patients are also admitted in ICU and APACHE-II can assess the severity and predict the outcome of this group of patients also. Results of observational study by Pandya et al. (2015) published in the current issue of JIHS confirms that APACHE-II can predict mortality in sepsis patients.[12] However, the question of concern is, to what extent APACHE-II is useful for the Sepsis patients admitted to ICU?
Sepsis patients have multi organ dysfunction syndrome also, hence a score specific for organ dysfunction like SOFA (Sequential Organ Failure Assessment score) which can assess the presence and severity of organ dysfunction may be a preferred choice.[13] This score was developed in 1994 and is the most commonly used organ dysfunction score. In SOFA score respiratory, renal, cardiovascular, neurological, hepatic and coagulation; are the six organ systems taken into account and the function and dysfunction are graded in score from 0 to 4.
In Knaus et al study from which APACHE II scoring system is derived confirmed that increased mortality is associated with an increased number of failed organs and also increased duration of organ failure. In this study, 46.76% (2,719) patients of total 5,677 ICU admissions had organ failure.[2] This makes APACHE application generalisable to all ICU patients including sepsis patients. SOFA score has been used and validated in sepsis and it is also used as a generic score in ICU, i.e; in all types of ICU patients (including sepsis). Although APACHE system was found to be slightly superior to SOFA and SAPS II in predicting mortality when it was applied in all ICU patients[14], large prospective studies comparing APACHE and SOFA in all ICU patients and in sepsis patients are lacking.
One of the differences between APACHE-II and SOFA score is that the latter does not include ‘age’ and “chronic health variables'. APACHE is an admission score and worst parameter in 24 hours is included for calculation of the score. Better predictability is obtained when 48 hours parameters are included instead of 24 hours.[14],[15] Like APACHE II, Simplified Acute Physiology (SAPS) II, and Mortality Prediction Model (MPM) are “first-day ICU severity scores” as first 24 hours parameters are considered which may result in ignoring factors that may influence patient outcome beyond the first 24 hours of admission.[15],[16],[17] SOFA does not include ‘age’ and ‘chronic health variables’.
APACHE-II, a physiology-based scoring system has advantages over diagnosis based prediction scores, like in patients where diagnosis cannot be made and/or patients are admitted in ICU with single or multiple organ failure.[18] Nevertheless, the questions remain - When diagnosis of “sepsis” is made and patient is admitted in ICU, should we use physiology based score or should we apply some other model? Is SOFA score a specific model for prediction in patients of sepsis? As no scoring system is ideal[18], which scoring system should be applied for sepsis?
Scoring systems as discussed earlier could be generic or specific (diagnosis/disease specific). In APACHE II, SAPS II, and Mortality Prediction Model (MPM), “one time” data is needed. On the contarary, in SOFA and Multiple Organ Dysfunction Score (MODS) collection of data is “Sequential-repetitive”, throughout the duration of ICU stay.[18] APACHE-II works as “static” model where worst variable in first 24 hours is considered, while SOFA is a “dynamic” model were sequential assessment of organ dysfunction change is recorded and both mean and highest SOFA scores are considered for prediction.[19]
ICU patients of sepsis in India are different from west. As a result, may not be giving same results by models developed on the basis of Western ICU patients.[16],[20],[21] Sepsis patients in India may include patients of “tropical sepsis” like patients of malaria, typhoid and others.[12],[20],[22] Desai and Lakhani (2013) compared SOFA and APACHE-II, in rural based ICU in patients having sepsis. They concluded that SOFA score was better than APACHE for predicting the outcome in sepsis patients. In above cited study they found third day SOFA score predicted mortality better in sepsis patients. The concept of dynamicity i.e. changes in SOFA score is also considered in the new definition of sepsis. Sepsis now is defined as “substantiation of infection along with life threatening organ dysfunction which is clinically evident by acute change of two point score or more, in the SOFA score”.[23],[24],[25],[26] This highlights the importance of organ dysfunction assessment, its change in score and its impact on survival or death.[24],[25],[26]. In fact Seymour and colleagues through
their validity study on SOFA, SIRS criteria and LODS score derived a new score named quick SOFA (q SOFA). Although this quick SOFA score is meant for identification of patients of suspected infection outside ICU, the novel purpose of this score is to prevent complications and eventually to reduce mortality due to sepsis. [23],[24],[25],[26] This itself suggests that sepsis is a dynamic process and rapid sequential change is occurring which may change prognosis.
In new definition of sepsis, SIRS criteria like hypothermia, hyperthermia, tachycardia, tachypnea and WBC count are not considered important. These parameters are included in APACHE-II model. Thus, as in sepsis patients, SIRS criteria is not significant, theoretically, their gravity and severity in numbers as used in APACHE-II system can give less précised prediction.
SOFA score validated for sepsis gives equal emphasis (four score) to six organ systems. Studies have evaluated pattern of organ failure in sepsis which has different spectrum.[21],[27] In qSOFA also, three important organ dysfunction parameters mentioned are respiratory rate (22 or more), systolic blood pressure( 100 mm Hg or less) and altered mental status.[23]As cellular level mechanisms are considered important like serum lactate level and the septic shock,[26] characterised by hypotension unresponsive to intravenous fluids and need of vasopressors to maintain mean arterial BP at 65 mm of Hg,[23],[24],[25],[26] these criteria may in future be more important than physiology based parameters. Thus, predictive model which will incorporate this newer understanding and findings may serve as a better prediction score for sepsis. Albeit, use of SOFA score, APACHE score and other model as a single system or in combination, with or without modification may continue to be useful tool of prediction, till better specific scoring system for sepsis is generated and validated.
| References | |  |
| 1. | Knaus WA, Zimmerman JE, Wagner DP, Draper EA, Lawrence DE. APACHE-acute physiology and chronic health evaluation: a physiologically based classification system. Critical care medicine. 1981 Aug 1;9(8):591-7.  |
| 2. | Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: a severity of disease classification system. Critical care medicine. 1985 Oct 1;13(10):818-29. |
| 3. | Wong DT, Knaus WA. Predicting outcome in critical care: the current status of the APACHE prognostic scoring system. Canadian journal of anaesthesia. 1991 Apr 1;38(3):374-83. |
| 4. | Knaus WA, Wagner DP, Draper EA, Zimmerman JE, Bergner M, Bastos PG, Sirio CA, Murphy DJ, Lotring T, Damiano A. The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults. Chest Journal. 1991 Dec 1;100(6):1619-36. |
| 5. | Wilairatana PO, Noan NS, Chinprasatsak SO, Prodeengam KU, Kityaporn DW, Looareesuwan SO. Scoring systems for predicting outcomes of critically ill patients in northeastern Thailand. The Southeast Asian journal of tropical medicine and public health. 1995 Mar;26(1):66-72. |
| 6. | Zimmerman JE, Kramer AA, McNair DS, Malila FM. Acute Physiology and Chronic Health Evaluation (APACHE) IV: hospital mortality assessment for today's critically ill patients. Critical care medicine. 2006 May 1;34(5):1297-310.. |
| 7. | Kane SP. Acute Physiology and Chronic Health Evaluation (APACHE II) Calculator. ClinCalc: http ://clincalc.com/IcuMortality/APACHEII.aspx. Updated October 24, 2015. Accessed March 17, 2016. |
| 8. | Le Gall JR, Loirat P, Alperovitch A, Glaser P, Granthil C, Mathieu D, Mercier P, Thomas R, Villers D. A simplified acute physiology score for ICU patients. Critical care medicine. 1984 Nov 1;12(11):975-7. |
| 9. | Le Gall JR, Lemeshow S, Saulnier F. A new simplified acute physiology score (SAPS II) based on a European/North American multicenter study. Jama. 1993 Dec 22;270(24):2957-63. |
| 10. | Ho KM, Knuiman M, Finn J, Webb SA. Estimating long-term survival of critically ill patients: the PREDICT model. PLoS one. 2008 Sep 17;3(9):e3226. |
| 11. | Lim WS, Van der Eerden MM, Laing R, Boersma WG, Karalus N, Town GI, Lewis SA, Macfarlane JT. Defining community acquired pneumonia severity on presentation to hospital: an international derivation and validation study. Thorax. 2003 May 1;58(5):377-82. |
| 12. | Pandya H, Pabani N, Shah K, Yadav R, Patel P, Raninga J. Study of various prognostic factors for sepsis patients requiring intensive medical care with special emphasis on APACHE II score in prognostication. JIHS. 2015;3(2) |
| 13. | Vincent JL, De Mendonça A, Cantraine F, Moreno R, Takala J, Suter PM, Sprung CL, Colardyn F, Blecher S. Use of the SOFA score to assess the incidence of organ dysfunction/failure in intensive care units: results of a multicenter, prospective study. Critical care medicine. 1998 Nov 1;26(11):1793-800. |
| 14. | Minne L, Abu-Hanna A, de Jonge E. Evaluation of SOFA-based models for predicting mortality in the ICU: A systematic review. Crit Care. 2008 Dec 17;12(6):R161. |
| 15. | Khan AA, Parekh D, Cho Y, Ruiz R, Selby RR, Jabbour N, Genyk YS, Mateo R. Improved prediction of outcome in patients with severe acute pancreatitis by the APACHE II score at 48 hours after hospital admission compared with the APACHE II score at admission. Archives of Surgery. 2002 Oct 1;137(10):1136-40. |
| 16. | Khan MS, Maitree P, Radhika A. Evaluation and comparison of the three scoring systems at 24 and 48 h of admission for prediction of mortality in an Indian ICU: a prospective cohort study. Ain-Shams Journal of Anaesthesiology. 2015 Jul 1;8(3):294. |
| 17. | Prakash P, Krishna K, Bhatia D. Usefulness of SAPS II Scoring System as an Early Predictor of Outcome in ICU Patients. JIACM. 2006;7(3):202-5. |
| 18. | Bouch DC, Thompson JP. Severity scoring systems in the critically ill. Continuing Education in Anaesthesia, Critical Care & Pain. 2008 Oct 1;8(5):181-5. |
| 19. | Ferreira FL, Bota DP, Bross A, Mélot C, Vincent JL. Serial evaluation of the SOFA score to predict outcome in critically ill patients. Jama. 2001 Oct 10;286(14):1754-8. |
| 20. | Desai S, Lakhani JD. Utility of SOFA and APACHE II score in sepsis in rural set up MICU. J Assoc Physicians India. 2013 Sep;61:608-11. |
| 21. | Desai SR, Lakhani JD. Clinical Profile of Patients with Multi-Organ Dysfunction Syndrome in Patients of Sepsis in Rural set up MICU People's .Journal of Scientific Research. 2014;7:28-32. |
| 22. | Udwadia FE. Multiple organ dysfunction syndrome due to tropical infections. Indian Journal of Critical Care Medicine. 2003 Oct 1;7(4):233. |
| 23. | Abraham E. New Definitions for Sepsis and Septic Shock: Continuing Evolution but With Much Still to Be Done. JAMA. 2016 Feb 23;315(8):757-9. |
| 24. | Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, Bellomo R, Bernard GR, Chiche JD, Coopersmith CM, Hotchkiss RS. The third international consensus definitions for sepsis and septic shock (Sepsis-3). Jama. 2016 Feb 23;315(8):801-10. |
| 25. | Seymour CW, Liu VX, Iwashyna TJ, Brunkhorst FM, Rea TD, Scherag A, Rubenfeld G, Kahn JM, Shankar-Hari M, Singer M, Deutschman CS. Assessment of clinical criteria for sepsis: for the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). Jama. 2016 Feb 23;315(8):762-74 |
| 26. | Shankar-Hari M, Phillips GS, Levy ML, Seymour CW, Liu VX, Deutschman CS, Angus DC, Rubenfeld GD, Singer M. Developing a new definition and assessing new clinical criteria for septic shock: for the third international consensus definitions for sepsis and septic shock (sepsis-3). Jama. 2016 Feb 23;315(8):775-87. |
| 27. | Silva E, Pedro MA, Sogayar AC, Mohovic T, Silva CL, Janiszewski M, Cal RG, de Sousa ÉF, Abe TP, de Andrade J, de Matos JD. Brazilian sepsis epidemiological study (BASES study). Critical Care. 2004 Jun 15;8(4):R251. |
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