Literature DB >> 19419351

Validation of SAPS 3 Admission Score and comparison with SAPS II.

M Capuzzo1, A Scaramuzza, B Vaccarini, G Gilli, S Zannoli, L Farabegoli, G Felisatti, E Davanzo, R Alvisi.   

Abstract

BACKGROUND: The objective of this study was to validate the Simplified Acute Physiology Score SAPS 3 Admission Score (SAPS 3) and to compare its fit with that of SAPS II in an independent sample of patients admitted to a single-centre intensive care unit (ICU).
METHODS: The data for all adult patients consecutively admitted to an eight-bed ICU of a 700-bed university hospital between 1 January 2006 and 2 September 2007 were collected. SAPS II and SAPS 3 were computed, as well as the predicted hospital mortality. The calibration of SAPS II and SAPS 3, according to the general equation (GE), and equations for Southern Europe and Mediterranean countries (SE&MC), and Central and Western Europe (C&WE), were assessed by the goodness-of-fit Hosmer-Lemeshow H and C statistics. Standardized mortality ratios (SMR) with 95% confidence interval (95% CI) were computed for SAPS II and SAPS 3 equations.
RESULTS: Six hundred and eighty-four patients were studied (males 63%). The median age was 73 (quartiles 65-80) years. The fit of SAPS 3 using the C&WE equation (H 13.49, P=0.095; C 12.73, P=0.121) as well as that of SAPS II was acceptable (H 6.02, P=0.644; C12.08, P=0.147), while SAPS 3 GE (H 23.36, P=0.002; C 22.37, P=0.004) and S&MC (H 25.73, P=0.001; C 26.19, P=0.001) did not fit well. SAPS 3 GE, SAPS 3 SE&M Countries and the SAPS II significantly over estimated the mortality. Only 95% CI of SMR for SAPS 3 C&WE included 1 (SMR 0.97; 95% CI 0.89-1.05).
CONCLUSION: Each ICU should identify the SAPS 3 equation most suitable for its case mix. The SAPS II model tended to overestimate the mortality.

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Year:  2009        PMID: 19419351     DOI: 10.1111/j.1399-6576.2009.01929.x

Source DB:  PubMed          Journal:  Acta Anaesthesiol Scand        ISSN: 0001-5172            Impact factor:   2.105


  9 in total

1.  Comparison between SAPS II and SAPS 3 in predicting hospital mortality in a cohort of 103 Italian ICUs. Is new always better?

Authors:  Daniele Poole; Carlotta Rossi; Nicola Latronico; Giancarlo Rossi; Stefano Finazzi; Guido Bertolini
Journal:  Intensive Care Med       Date:  2012-05-15       Impact factor: 17.440

2.  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 3.  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

4.  Predictive Performance of the Simplified Acute Physiology Score (SAPS) II and the Initial Sequential Organ Failure Assessment (SOFA) Score in Acutely Ill Intensive Care Patients: Post-Hoc Analyses of the SUP-ICU Inception Cohort Study.

Authors:  Anders Granholm; Morten Hylander Møller; Mette Krag; Anders Perner; Peter Buhl Hjortrup
Journal:  PLoS One       Date:  2016-12-22       Impact factor: 3.240

5.  Determinants of the calibration of SAPS II and SAPS 3 mortality scores in intensive care: a European multicenter study.

Authors:  Antoine Poncet; Thomas V Perneger; Paolo Merlani; Maurizia Capuzzo; Christophe Combescure
Journal:  Crit Care       Date:  2017-04-04       Impact factor: 9.097

6.  Simplified Mortality Score for the Intensive Care Unit (SMS-ICU): protocol for the development and validation of a bedside clinical prediction rule.

Authors:  Anders Granholm; Anders Perner; Mette Krag; Peter Buhl Hjortrup; Nicolai Haase; Lars Broksø Holst; Søren Marker; Marie Oxenbøll Collet; Aksel Karl Georg Jensen; Morten Hylander Møller
Journal:  BMJ Open       Date:  2017-03-09       Impact factor: 2.692

7.  The predictive performance of SAPS 2 and SAPS 3 in an intermediate care unit for internal medicine at a German university transplant center; A retrospective analysis.

Authors:  Michael Jahn; Jan Rekowski; Guido Gerken; Andreas Kribben; Ali Canbay; Antonios Katsounas
Journal:  PLoS One       Date:  2019-09-25       Impact factor: 3.240

8.  Performance of Sequential Organ Failure Assessment and Simplified Acute Physiology Score II for Post-Cardiac Surgery Patients in Intensive Care Unit.

Authors:  Fei Xu; Weina Li; Cheng Zhang; Rong Cao
Journal:  Front Cardiovasc Med       Date:  2021-12-06

9.  Prediction of prognosis in elderly patients with sepsis based on machine learning (random survival forest).

Authors:  Luming Zhang; Tao Huang; Fengshuo Xu; Shaojin Li; Shuai Zheng; Jun Lyu; Haiyan Yin
Journal:  BMC Emerg Med       Date:  2022-02-11
  9 in total

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