Evaluation of neuro-intensive care unit performance in China: predicting outcomes of Simplified Acute Physiology Score II or Glasgow Coma Scale
- PMID: 23506592
Evaluation of neuro-intensive care unit performance in China: predicting outcomes of Simplified Acute Physiology Score II or Glasgow Coma Scale
Abstract
Background: Severity scoring systems are useful tools for measuring the severity of the disease and its outcome. This pilot study was to verify and compare the prognostic performance of the Simplified Acute Physiology Score II (SAPS II) and Glasgow Coma Scale (GCS) in neuro-intensive care unit (N-ICU) patients.
Methods: A total of 1684 patients consecutively admitted to the N-ICU at Xuanwu Hospital between January 1, 2005 and December 31, 2011 were enrolled in this study. The data-base included admission data, at 24-, 48-, and 72-hour SAPS II and GCS. Repeated measure data analysis of variance, Logistic regression analysis, the Hosmer-Lemeshow goodness-of-fit statistic, and the area under the receiver operating characteristic were used to evaluate the performance.
Results: There was a significant difference between the SAPS II or GCS score at four time points (F = 16.110, P = 0.000 or F = 8.108, P = 0.000). The SAPS II scores or GCS score at four time points interacted with the outcomes with significant difference (F = 116.771, P = 0.000 or F = 65.316, P = 0.000). Calibration of the SAPS II or GCS score at each time point on all patients was good. The percentage of a risk estimate prediction corresponding to observed mortality was also good. The 72-hour score have the greatest consistency. Discriminations of the SAPS II or GCS score at each time were all satisfactory. The 72-hour score had the greatest discriminative power. The cut-off value was 33 (sensitivity of 85.2% and specificity of 74.3%) and 6 (sensitivity of 70.6% and specificity of 65.0%). The SAPS II at each time point on all patients showed better calibration, consistency and discrimination than GCS. The binary Logistic regression analysis identified physiological variables, GCS, age, and disease category as significant independent risk factors of death. After the two variables including underlying disease and type of admission were excluded, we built the simplified SAPS II model. A correlation was suggested between the simplified SAPS II score at each time point and outcome, regardless of the diagnosis.
Conclusions: The GCS scoring system tends to be a little weaker in the predictive power than the SAPS II scoring system in this Chinese cohort of N-ICU patients. The advantage of SAPS II scoring system still exists that it dose not need to take into account the diagnosis or diseases categories, even in the special N-ICU. The simplified SAPS II scoring system is considered a new idea for the estimation of effectiveness.
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