Comparison of the performance of SAPS II, SAPS 3, APACHE II, and their customized prognostic models in a surgical intensive care unit

Sakr, Yasser; Krauss, C; Amaral, Andre Carlos Kajdacsy-Balla; Réa-Neto, Álvaro; Specht, M.; Reinhart, Konrad; Marx, Gernot

doi:10.1093/bja/aen291

Cited by 114 publications

(116 citation statements)

References 25 publications

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“…For a long time, surgical patients were evaluated by the ASA physical status, which gives information on the health status before surgery and, therefore, it is extremely limited to predict the worse evolution and hospital outcome. Sakr Y et al 16 evaluated 1,851 surgical patients in the ICU, in which the majority were Cardiac Surgery patients. In this study, the discriminatory assessment of the SAPS 3 was better than that of the APACHE II and SAPS II, but with poor calibration (probability to estimate mortality correlating with the observed mortality).…”

Section: Discussionmentioning

confidence: 99%

“…Recently, Soares and Salluh 13 validated the SAPS 3 in a Brazilian cohort of cancer patients, obtaining good results. Although this prognostic index has been incorporated in several clinical assay protocols in the intensive care environment 14,15 , only one study 16 was developed in surgical ICU patients in Europe, proving to be better than other indexes used before in this population. Therefore, the objective of the present study was to evaluate the discriminatory power of the SAPS 3 system in a Brazilian population of surgical patients of two tertiary hospitals regarding hospital mortality.…”

Section: Introductionmentioning

confidence: 99%

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Aplicabilidade do escore fisiológico agudo simplificado (SAPS 3) em hospitais brasileiros

Silva¹,

Malbouisson²,

Nuevo³

et al. 2010

Rev. Bras. Anestesiol.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Aplicabilidade do escore fisiológico agudo simplificado (SAPS 3) em hospitais brasileiros

Silva¹,

Malbouisson²,

Nuevo³

et al. 2010

Rev. Bras. Anestesiol.

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“…Nonetheless, such scores (e.g., SAPS 3 and APACHE III) have been reported to face the same drawbacks as SAPS II [9,12,38]. Moreover, those scores remain the most widely used scores in practice [39].…”

Section: What Are the Next Steps?mentioning

confidence: 99%

Mortality Prediction in the ICU Based on MIMIC-II Results from the Super ICU Learner Algorithm (SICULA) Project

Pirracchio

2016

Secondary Analysis of Electronic Health Records

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Learning ObjectivesIn this chapter, we illustrate the use of MIMIC II clinical data, non-parametric prediction algorithm, ensemble machine learning, and the Super Learner algorithm. IntroductionPredicting mortality in patients hospitalized in intensive care units (ICU) is crucial for assessing severity of illness and adjudicating the value of novel treatments, interventions and health care policies. Several severity scores have been developed with the objective of predicting hospital mortality from baseline patient characteristics, defined as measurements obtained within the first 24 h after ICU admission. The first scores proposed, APACHE [1] (Acute Physiology and Chronic Health Evaluation), APACHE II [2], and SAPS [3] (Simplified Acute Physiology Score), relied upon subjective methods for variable importance measure, namely by prompting a panel of experts to select and assign weights to variables according to perceived relevance for mortality prediction. Further scores, such as the SAPS II [4] were subsequently developed using statistical modeling techniques [4][5][6][7]. To this day, the SAPS II [4] and APACHE II [2] scores remain the most widely used in clinical practice. However, since first being published, they have been modified several times in order to improve their predictive performance [6][7][8][9][10][11]. Despite these extensions of SAPS, predicted hospital mortality remains generally overestimated [8,9,[12][13][14]. As an illustration, Poole et al. [9] compared the SAPS II and the SAPS3 performance in a cohort of more than 28,000 admissions to 10 different Italian ICUs. They concluded that both scores provided unreliable predictions, but unexpectedly the newer SAPS 3 turned out to overpredict mortality more than the

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“…While not specifically designed for individual patient care, scoring systems may guide (but will not replace) clinical decision making regarding withdrawal of treatment and/or futility of continued aggressive care. 1,2 However, reliability of a severity score reportedly deteriorates when applied to different populations, probably due to case mix, the level and quality of care, and the development of new treatment options changing overall patient outcomes. 2 Application of a severity scoring system in the intensive care unit with different case mixes raises issues of the system's reliability and validity.…”

Section: Introductionmentioning

confidence: 99%

Performance of simplified acute physiology score 3 admission score as a predictor of ICU mortality in a tertiary care hospital of rural Telangana, India

et al. 2016

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Comparison of the performance of SAPS II, SAPS 3, APACHE II, and their customized prognostic models in a surgical intensive care unit

Abstract: In this group of surgical ICU patients, the performance of SAPS 3 was similar to that of APACHE II and SAPS II. Customization improved the calibration of all prognostic models.

Cited by 114 publications

References 25 publications

Aplicabilidade do escore fisiológico agudo simplificado (SAPS 3) em hospitais brasileiros

Aplicabilidade do escore fisiológico agudo simplificado (SAPS 3) em hospitais brasileiros

Mortality Prediction in the ICU Based on MIMIC-II Results from the Super ICU Learner Algorithm (SICULA) Project

Performance of simplified acute physiology score 3 admission score as a predictor of ICU mortality in a tertiary care hospital of rural Telangana, India

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