Abstract
Now a day’s price of health protection for a care unit patient has been three times more as compared to general word patient. Monitoring the care unit improvement is a major criteria with respect to control the major hospital expenses. To predict the outcome in an ICU the common illness severity scores are generally used which characterize the severity of diseases, depend on the rate of organ disorder and assessment of resources used for this purpose. Primarily, the separate types of scoring systems are used necessarily for the treatment purpose. Their compound uses provide a more correct symptom of disease intensity and prophecy to the doctor regarding duration of rest and mortality for the ICU patient. This paper gives brief overview of the generally used scoring system, examines the details regarding their development, qualified information concerning their execution. It is important and also necessary for all these marking approach will be modernize accordingly with times as care unit community increases, change in heterogeneity of diseases and new symptomatic, remedial and anticipating strategy become available day by day.
Keywords: Simplified Acute Physiology Score (SAPS), Mortality Probability Model (MPM), Acute Physiology and Chronic Health Evaluation (APACHE), Organ System Failure (OSF), Sequential Organ Failure Assessment (SOFA), Intensive Care Unit (ICU), length of stay (LOS).
References
- Fan Y ,Gao C , Jiang S , Leng Y , Huang Y, Li W, Establishment and Effectiveness Evaluation of a Scoring System-RAAS (RDW, AGE, APACHE II, SOFA) for Sepsis by a Retrospective Analysis, Pages 465—474 , 20 January 2022 Volume 2022:15 DOI https://doi.org/10.2147/JIR.S348490
- Rui Zhanga, Jianrui Wei, Youfeng Zhua, Xiaoling Ye, Houqiang Liu, SAPS III is superior to SOFA for predicting 28-day mortality in sepsis patients based on Sepsis 3.0 criteria, International Journal of Infectious Diseases Pages 135-141, Volume 114, January 2022,. https://doi.org/10.1016/j.ijid.2021.11.015.
- MPH, McCarty , HEC-C , Catherine A. PhD; Renier, Colleen M. BS; Conway, Pat G. PhD, MSW; Vogel, Linda APRN; Woehrle, Theo A. MPA; Anderson, Leslie A. PT; Hanson, Eric J. PT; Lisa M. PhD Benrud; Gerchman-Smith, Mary APRN Development, Implementation, and Evaluation of an Early Mobility Protocol in a Regional Level II Trauma Center, Critical Care Nursing Quarterly: Volume 45 , January/March 2022 , Issue 1 - p 83-87 doi: 10.1097/CNQ.0000000000000391.
- Ahmad Abujabera, Adam Fadlallab, Abdulqadir, Nashwana Ayman El-Menyarcd Hassan Al-Thanic Predicting prolonged length of stay in patients with traumatic brain injury: A machine learning approach Intelligence-Based Medicine,2022, Volume 6, , 100052 https://doi.org/10.1016/j.ibmed.2022.100052.
- Ezgi Özyılmaz, Özlem Özkan Kuşçu, Emre Karakoç, Aslı Boz, Gülşah Orhan Tıraşçı, Gülşah Seydaoğlu, Rengin Güzel, Worse pre-admission quality of life is a strong predictor of mortality in critically ill patients Turk J Phys Med Rehab 2022;68(x):i-xi DOI: 5606/tftrd.2022.5287.
- RP Moreno: Outcome prediction in intensive care: why we need to reinvent the wheel. CurrOpinCrit Care 2008, 14:483-484.
- Hiillman. Critical care without walls. Curr Opin Criti Care 2002 :8: 594-99
- Metnitz P ,Moreno R, Jordan B: The changing prognostic determinants inthe critically ill patient. In 2007 Yearbook of Intensive care and EmergencyMedicine. Edited by Vincent JL. Heidelberg: Springer; 2007:899-907.
- Wagner DP, Knaus WA, Zimmerman JE, Draper EA, Lawrence DE: APACHEacutephysiology and chronic health evaluation: a physiologically based classification system. CritCare Med 1981, 9:591-597.
- Knaus WA, Draper EA, Wagner DP, Zimmerman JE: APACHE II: A severity ofdisease classifi cation system. Crit Care Med 1985, 13:818-829.
- Knaus WA, Wagner DP, Draper EA, Zimmerman JE, Bergner M, Bastos PG, SirioCA, Murphy DJ, Lotring T, Damiano A, Harrell FE: The APACHE III prognostic system: Risk prediction of hospital mortality for critically ill hospitalizedadults. Chest 1991, 100:1619-1636.
- Wagner DP , Zimmerman JE, , Draper EA, Wright L, Alzola C, Knaus WA: Evaluation of acute physiology and chronic health evaluation IIIpredictions of hospital mortality in an independent database. Crit CareMed 1998, 26:1317-1326.
- Zimmerman JE ,Knaus WA, Wagner DP, Draper EA: Variations in mortalityand length of stay in intensive care units. Ann Intern Med 1993, 118:753-761.
- Zimmerman JE, Kramer AA, McNair DS, Malila FM: Acute Physiology and Chronic Health Evaluation (APACHE) IV: hospital mortality assessment fortoday’s critically ill patients. Crit Care Med 2006, 34:1297-1310.
- McNair DS, Zimmerman JE, Kramer AA, Malila FM, Shaffer VL: Intensive careunit length of stay: Benchmarking based on Acute Physiology andChronic Health Evaluation (APACHE) IV. Crit Care Med 2006, 34:2517-2529.
- Loirat P , Alperovitch A , Le Gall J-R, Granthil C, Glaser P, Mathieu D, Mercier P,Thomas R: A simplified acute physiology score for ICU patients. Crit CareMed 1984, 12:975-977.
- Lemeshow S , Le Gall J-R, Saulnier F: A new simplified acute physiology score (SAPS II) based on a European/North American multicenter study.JAMA1993, 270:2957-2963.
- Almeida E, Moreno RP, Metnitz PG, Jordan B, Bauer P, Campos RA, Iapichino G,Edbrooke D, Capuzzo M, Le Gall JR: SAPS 3 - from evaluation of the patient to evaluation of the intensive care unit. Part 2: Development of aprognostic model for hospital mortality at ICU admission. Intensive CareMed 2005, 31:1345-1355.
- Einfalt J, Rothen HU, Stricker K, Bauer P, Metnitz PG, Moreno RP, Takala J:Variability in outcome and resource use in intensive care units. Intensive Care Med 2007, 33:1329-1336.
- Avrunin JS, Pastides H, Lemeshow S, Teres D, Steingrub JS: A method for predicting survival and mortality of ICU patients using objectively derived weights. Crit Care Med 1985, 13:519-525.
- Lemeshow S, Teres D, Klar J, Avrunin JS, Gehlbach SH, Rapoport J: Mortality Probability Models (MPM II) based on an international cohort of intensive care unit patients. JAMA 1993, 270:2478-2486.
- Lemeshow S,Rapoport J, Teres D, Gehlbach S: A method for assessing theclinical performance and cost-eff ectiveness of intensive care units: amulticenter inception cohort study. Crit Care Med 1994, 22:1385-1391.
- Teres D,Higgins TL, Copes WS, Nathanson BH, Stark M, Kramer AA: Assessingcontemporary intensive care unit outcome: an updated Mortality Probability Admission Model (MPM0-III). Crit Care Med 2007, 35:827-835.
- Teres D, Nathanson BH, Higgins TL, Copes WS, Kramer A, Stark M: A revised method to assess intensive care unit clinical performance and resourceutilization. Crit Care Med 2007, 35:1853-1862.
- MacKirdy FN, Livingston BM, Howie JC, Jones R, Norrie JD: Assessment of the performance of fi ve intensive care scoring models within a large Scottishdatabase. Crit Care Med 2000, 28:1820-1827.
- Vasilevskis EE, Lane R, Dean ML, Kuzniewicz MW, Trivedi NG, Rennie DJ, Clay T,Kotler PL, Dudley RA: Variation in ICU risk-adjusted mortality: impact of methods of assessment and potential confounders. Chest 2008,133:1319-1327.
- Shepardson LB, Sirio CA, Rotondi AJ, Cooper GS, Angus DC, Harper DL, Rosenthal GE: Community-wide assessment of intensive care outcomes using a physiologically based prognostic measure: implications for criticalcare delivery from Cleveland Health Quality Choice. Chest 1999,115:793-801.
- Moreno R, Metnitz B, Schaden E, Le Gall JR, Bauer P, Metnitz PG: Austrian validation and customization of the SAPS 3 Admission Score. Intensive CareMed 2009, 35:616-622.
- Rea-Neto A, Sakr Y, Krauss C, Amaral AC, Specht M, Reinhart K, Marx G:Comparison of the performance of SAPS II, SAPS 3, APACHE II, and their customized prognostic models in a surgical intensive care unit. Br JAnaesth2008, 101:798-803.
- Carpenter JR, Harrison DA, Parry GJ, Short A, Rowan K: A new risk predictionmodel for critical care: the Intensive Care National Audit & Research Centre (ICNARC) model. Crit Care Med 2007, 35:1091-1098.
- Zimmerman JE., Kramer AA : Assessing the calibration of mortality benchmarks in critical care: The Hosmer-Lemeshow test revisited. Crit CareMed 2007, 35:2052-2056.
- Miller ME, Hui SL, Tierney WM: Validation techniques for logistic regression models. Stat Med 1991, 10:1213-1226.
- Poole D, Rossi C, Anghileri A, Giardino M, Latronico N, Radrizzani D, Langer M,B ertolini G: External validation of the Simplified Acute Physiology Score (SAPS) 3 in a cohort of 28,357 patients from 147 Italian intensive careunits. Intensive Care Med 2009, 35:1916-1924.
- Antonelli M , Willatts S ,de Mendonça A , Moreno R, Vincent JL, Matos A, , Cantraine F, Thijs J, Takala J, Sprung C, Bruining H,: The use of maximum SOFA score to quantify organ dysfunction/ failure in intensive care. Results of a prospective, multicentre study. Intensive Care Med 1999, 25:686-696.
Corresponding Author
Prabhudutta Ray
Institute of Advanced Research, Gandhinagar, Gujarat, India
DOI: https://dx.doi.org/10.18535/jmscr/v11i3.25
