Literature DB >> 20169260

Applicability of the simplified acute physiology score (SAPS 3) in Brazilian hospitals.

João Manoel Silva Junior1, Luiz M Sá Malbouisson, Hector L Nuevo, Luiz Gustavo T Barbosa, Lauro Yoiti Marubayashi, Isabel Cristina Teixeira, Antonio Paulo Nassar Junior, Maria Jose Carvalho Carmona, Israel Ferreira da Silva, José Otávio Costa Auler Júnior, Ederlon Rezende.   

Abstract

BACKGROUND AND OBJECTIVES: The SAPS 3 (Simplified Acute Physiology Score 3) prognostic system is composed of 20 parameters, represented by an acute physiology score and assessment of the previous status, aimed at establishing a predictive mortality index for patients admitted to intensive care units (ICU). The objective of this study was to validate this system and determine its discriminatory power in surgical patients in Brazil.
METHODS: This is a prospective study undertaken in two surgical ICUs of two different hospitals over a one-year period; patients younger than 16 years, who stay at the ICU for less than 24 hours, readmitted to the unit, and those admitted for dialysis were excluded from the study. The predictive ability of the SAPS 3 index to differentiate survivors and non-survivors was determined by the ROC curve and calibration by the Hosmer-Lemeshow goodness-of-fit test.
RESULTS: One thousand three-hundred and ten patients were included in the study. Gastrointestinal surgeries predominated (34.9%). Eighteen was the lower SAPS 3 index and the highest was 154, with a mean of 48.5 +/- 18.1. The predicted and real hospital mortality was 10.3% and 10.8%, respectively; the standardized mortality ratio (SMR) was 1.04 (95%CI = 1.03-1.07). Calibration by the Hosmer and Lemeshow method showed X(2) = 10.47 p = 0.234. The SAPS 3 score that better discriminated survivors and non-survivors was 57, with sensitivity of 75.8% and specificity 86%. Among the patients with SAPS 3 index higher than 57, 73.5% did not survive versus 26.5% who survived (OR= 1.32, 95%CI 1.23-1.42, p < 0.0001).
CONCLUSIONS: The SAPS 3 system is valid for the Brazilian population of surgical patients, being a useful indicator of critical patients and to determine greater care in this group.

Entities:  

Mesh:

Year:  2010        PMID: 20169260

Source DB:  PubMed          Journal:  Rev Bras Anestesiol        ISSN: 0034-7094            Impact factor:   0.964


  22 in total

1.  Calibration strategies to validate predictive models: is new always better?

Authors:  Nicolás Serrano
Journal:  Intensive Care Med       Date:  2012-05-15       Impact factor: 17.440

Review 2.  Evaluation of Simplified Acute Physiology Score 3 performance: a systematic review of external validation studies.

Authors:  Antonio Paulo Nassar; Luiz Marcelo Sa Malbouisson; Rui Moreno
Journal:  Crit Care       Date:  2014-06-06       Impact factor: 9.097

3.  Mobility decline in patients hospitalized in an intensive care unit.

Authors:  Fábio Santos de Jesus; Daniel de Macedo Paim; Juliana de Oliveira Brito; Idiel de Araujo Barros; Thiago Barbosa Nogueira; Bruno Prata Martinez; Thiago Queiroz Pires
Journal:  Rev Bras Ter Intensiva       Date:  2016-06

4.  Validation of a prognostic score for mortality in elderly patients admitted to Intensive Care Unit.

Authors:  Luis Alejandro Sánchez-Hurtado; Adrian Ángeles-Veléz; Brigette Carmen Tejeda-Huezo; Juan Carlos García-Cruz; Teresa Juárez-Cedillo
Journal:  Indian J Crit Care Med       Date:  2016-12

5.  Percutaneous Coronary Intervention in Unprotected Left Main Coronary Artery Lesions.

Authors:  Douglas Dos Santos Grion; Debora Carvalho Grion; Igor Veiga Silverio; Leonardo Shingu de Oliveira; Isabela Faria Larini; Anna Victória Martins; Juliana Moreira; Marianne Machado; Lissa Shizue Tateiwa Niekawa; Adriana Dos Santos Grion; Cintia Magalhães Carvalho Grion
Journal:  Arq Bras Cardiol       Date:  2021-06       Impact factor: 2.000

6.  Is SAPS 3 better than APACHE II at predicting mortality in critically ill transplant patients?

Authors:  Vanessa M de Oliveira; Janete S Brauner; Edison Rodrigues Filho; Ruth G A Susin; Viviane Draghetti; Simone T Bolzan; Silvia R R Vieira
Journal:  Clinics (Sao Paulo)       Date:  2013       Impact factor: 2.365

Review 7.  The Simplified Acute Physiology Score III Is Superior to the Simplified Acute Physiology Score II and Acute Physiology and Chronic Health Evaluation II in Predicting Surgical and ICU Mortality in the "Oldest Old".

Authors:  Aftab Haq; Sachin Patil; Alexis Lanteri Parcells; Ronald S Chamberlain
Journal:  Curr Gerontol Geriatr Res       Date:  2014-02-17

8.  The effect of excess fluid balance on the mortality rate of surgical patients: a multicenter prospective study.

Authors:  João M Silva; Amanda Maria Ribas Rosa de Oliveira; Fernando Augusto Mendes Nogueira; Pedro Monferrari Monteiro Vianna; Marcos Cruz Pereira Filho; Leandro Ferreira Dias; Vivian Paz Leão Maia; Cesar de Souza Neucamp; Cristina Prata Amendola; Maria José Carvalho Carmona; Luiz M Sá Malbouisson
Journal:  Crit Care       Date:  2013-12-10       Impact factor: 9.097

9.  SAPS 3 score as a predictive factor for postoperative referral to intensive care unit.

Authors:  João M Silva; Helder Marcus Costa Rocha; Henrique Tadashi Katayama; Leandro Ferreira Dias; Mateus Barros de Paula; Leusi Magda Romano Andraus; Jose Maria Correa Silva; Luiz Marcelo Sá Malbouisson
Journal:  Ann Intensive Care       Date:  2016-04-30       Impact factor: 6.925

Review 10.  Performance of critical care prognostic scoring systems in low and middle-income countries: a systematic review.

Authors:  Rashan Haniffa; Ilhaam Isaam; A Pubudu De Silva; Arjen M Dondorp; Nicolette F De Keizer
Journal:  Crit Care       Date:  2018-01-26       Impact factor: 9.097

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.