OBJECTIVE: To assess how the power of discrimination of a multipurpose severity score (Simplified Acute Physiology Score; SAPS) changes in relation to the length of stay (LOS) in the intensive care unit (ICU). DESIGN: In order to compute the SAPS probability, a model derived from logistic regression was developed in a cohort of 8059 patients. Measures of calibration (goodness-of-fit statistics) and discrimination [receiver operating characteristic (ROC) curve and relative area under the curve (AUC)] were adopted in a developmental set (5389 patients) and a validation set (2670 patients), both randomly selected. Once the logit was developed and the model validated, the whole database (8059 patients) was again assembled. To evaluate the accuracy of first-day SAPS probability over time, area under the ROC curve was computed for each of the initial 10 days of ICU care and for day 15. SETTING: 24 Italian ICUs. PATIENTS: A total of 8059 patients out of 10065 consecutive admissions over a period of 3 years (1990-1992) were included in this study. Patients whose SAPS was not correctly compiled (n = 687), patients younger than 18 years (n = 442), and patients whose LOS was less than 24 h (n = 877) were excluded from this analysis. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: The logistic model gave good results in terms of calibration and discrimination, both in the developmental set (goodness-of-fit: chi 2 = 9.24, p = 0.32; AUC = 0.79 +/- 0.01) and in the validation set (goodness-of-fit: chi 2 = 8.95, p = 0.537; AUC = 0.78 +/- 0.01). The AUC for the whole database showed a loss in discrimination closely related to LOS: 0.79 +/- 0.01 at a day 1 and 0.59 +/- 0.02 at day 15. CONCLUSION: The logistic model that we developed meets high standards for discrimination and calibration. However, SAPS loses its discriminative power over time; accuracy of prediction is maintained at an acceptable level only in patients who stay in the ICU no longer than 5 days. The stay in the ICU represents a complex variable, which is not predictable, that influences the performance of SAPS on the first day.
OBJECTIVE: To assess how the power of discrimination of a multipurpose severity score (Simplified Acute Physiology Score; SAPS) changes in relation to the length of stay (LOS) in the intensive care unit (ICU). DESIGN: In order to compute the SAPS probability, a model derived from logistic regression was developed in a cohort of 8059 patients. Measures of calibration (goodness-of-fit statistics) and discrimination [receiver operating characteristic (ROC) curve and relative area under the curve (AUC)] were adopted in a developmental set (5389 patients) and a validation set (2670 patients), both randomly selected. Once the logit was developed and the model validated, the whole database (8059 patients) was again assembled. To evaluate the accuracy of first-day SAPS probability over time, area under the ROC curve was computed for each of the initial 10 days of ICU care and for day 15. SETTING: 24 Italian ICUs. PATIENTS: A total of 8059 patients out of 10065 consecutive admissions over a period of 3 years (1990-1992) were included in this study. Patients whose SAPS was not correctly compiled (n = 687), patients younger than 18 years (n = 442), and patients whose LOS was less than 24 h (n = 877) were excluded from this analysis. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: The logistic model gave good results in terms of calibration and discrimination, both in the developmental set (goodness-of-fit: chi 2 = 9.24, p = 0.32; AUC = 0.79 +/- 0.01) and in the validation set (goodness-of-fit: chi 2 = 8.95, p = 0.537; AUC = 0.78 +/- 0.01). The AUC for the whole database showed a loss in discrimination closely related to LOS: 0.79 +/- 0.01 at a day 1 and 0.59 +/- 0.02 at day 15. CONCLUSION: The logistic model that we developed meets high standards for discrimination and calibration. However, SAPS loses its discriminative power over time; accuracy of prediction is maintained at an acceptable level only in patients who stay in the ICU no longer than 5 days. The stay in the ICU represents a complex variable, which is not predictable, that influences the performance of SAPS on the first day.
Authors: T A Brennan; A R Localio; L L Leape; N M Laird; L Peterson; H H Hiatt; B A Barnes Journal: Ann Intern Med Date: 1990-02-01 Impact factor: 25.391
Authors: J R Le Gall; P Loirat; A Alperovitch; P Glaser; C Granthil; D Mathieu; P Mercier; R Thomas; D Villers Journal: Crit Care Med Date: 1984-11 Impact factor: 7.598
Authors: D Carugo; M Dei Poli; A Guarino; P Navalesi; D Radrizzani; A Ravizza; F Roveda; A Sicignano; S Vesconi Journal: Minerva Anestesiol Date: 1994-05 Impact factor: 3.051
Authors: André Carlos Kajdacsy-Balla Amaral; Fábio Moreira Andrade; Rui Moreno; Antonio Artigas; Francis Cantraine; Jean-Louis Vincent Journal: Intensive Care Med Date: 2005-01-25 Impact factor: 17.440