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Comparison of acute physiology and chronic health evaluation II and Glasgow Coma Score in predicting the outcomes of Post Anesthesia Care Unit's patients.

Hosseini M, Ramazani J - Saudi J Anaesth (2015 Apr-Jun)

Bottom Line: The ROC-curve analysis suggested that the predictive ability of GCS is slightly better than APACHE II in this study.For GCS the area under the ROC curve was 86.1% (standard error [SE]: 3.8%), and for APACHE II it was 85.7% (SE: 3.5%), also the Hosmer-Lemeshow statistic revealed better calibration for GCS (χ(2) = 5.177, P = 0.521), than APACHE II (χ(2) = 10.203, P = 0.251).The survivors had significantly lower APACHE II and higher GCS compared with non-survivors, also GCS showed more predictive accuracy than APACHE II in prognosticating the outcomes in PACU.

View Article: PubMed Central - PubMed

Affiliation: Department of Nursing, North Khorasan University of Medical Sciences, Bojnourd, Iran.

ABSTRACT

Context: Acute physiology and chronic health evaluation II (APACHE II) is one of the most general classification systems of disease severity in Intensive Care Units and Glasgow Coma Score (GCS) is one of the most specific ones.

Aims: The aim of the current study was to assess APACHE II and GCS ability in predicting the outcomes (survivors, non-survivors) in the Post Anesthesia Care Unit's (PACU).

Settings and design: This was an observational and prospective study of 150 consecutive patients admitted in the PACU during 6-month period.

Materials and methods: Demographic information recorded on a checklist, also information about severity of disease calculated based on APACHE II scoring system in the first admission 24 h and GCS scale.

Statistical analysis used: Logistic regression, Hosmer-Lemeshow test and receiver operator characteristic (ROC) curves were used in statistical analysis (95% confidence interval).

Results: Data analysis showed a significant statistical difference between outcomes and both APACHE II and Glasgow Coma Score (GCS) (P < 0.0001). The ROC-curve analysis suggested that the predictive ability of GCS is slightly better than APACHE II in this study. For GCS the area under the ROC curve was 86.1% (standard error [SE]: 3.8%), and for APACHE II it was 85.7% (SE: 3.5%), also the Hosmer-Lemeshow statistic revealed better calibration for GCS (χ(2) = 5.177, P = 0.521), than APACHE II (χ(2) = 10.203, P = 0.251).

Conclusions: The survivors had significantly lower APACHE II and higher GCS compared with non-survivors, also GCS showed more predictive accuracy than APACHE II in prognosticating the outcomes in PACU.

No MeSH data available.


Related in: MedlinePlus

Receiver operator characteristic curves for acute physiology and chronic health evaluation (APACHE) II and Glasgow Coma Score (GCS) score. The area under curve is 0.857 for APACHE II and 0.861 for GCS score
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Figure 1: Receiver operator characteristic curves for acute physiology and chronic health evaluation (APACHE) II and Glasgow Coma Score (GCS) score. The area under curve is 0.857 for APACHE II and 0.861 for GCS score

Mentions: Discrimination for both scoring system was good. The best Yuden index (sensitivity + specificity-1) was used to determine the best cut-off point for each scoring system. Using a cut-off score 13.5, The APACHE II score predicted hospital mortality with a sensitivity of 96.6%, a specificity of 62.8% and accuracy of 79.7%, with an area under the ROC curve of 0.857 ± 0.035 SE (95%; 0.788-0.925, P < 0.0001). For GCS a cut off score 8.5 showed a sensitivity of 82.8%, a specificity of 82.6% and accuracy of 82.7% [Table 3], also the area under the ROC curve was 0.861 ± 0.038 SE (95%; 0.786-0.937, P < 0.0001). ROC curves were drawn for the APACHE II scoring systems and GCS to assess predictive accuracy [Figure 1].


Comparison of acute physiology and chronic health evaluation II and Glasgow Coma Score in predicting the outcomes of Post Anesthesia Care Unit's patients.

Hosseini M, Ramazani J - Saudi J Anaesth (2015 Apr-Jun)

Receiver operator characteristic curves for acute physiology and chronic health evaluation (APACHE) II and Glasgow Coma Score (GCS) score. The area under curve is 0.857 for APACHE II and 0.861 for GCS score
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4374217&req=5

Figure 1: Receiver operator characteristic curves for acute physiology and chronic health evaluation (APACHE) II and Glasgow Coma Score (GCS) score. The area under curve is 0.857 for APACHE II and 0.861 for GCS score
Mentions: Discrimination for both scoring system was good. The best Yuden index (sensitivity + specificity-1) was used to determine the best cut-off point for each scoring system. Using a cut-off score 13.5, The APACHE II score predicted hospital mortality with a sensitivity of 96.6%, a specificity of 62.8% and accuracy of 79.7%, with an area under the ROC curve of 0.857 ± 0.035 SE (95%; 0.788-0.925, P < 0.0001). For GCS a cut off score 8.5 showed a sensitivity of 82.8%, a specificity of 82.6% and accuracy of 82.7% [Table 3], also the area under the ROC curve was 0.861 ± 0.038 SE (95%; 0.786-0.937, P < 0.0001). ROC curves were drawn for the APACHE II scoring systems and GCS to assess predictive accuracy [Figure 1].

Bottom Line: The ROC-curve analysis suggested that the predictive ability of GCS is slightly better than APACHE II in this study.For GCS the area under the ROC curve was 86.1% (standard error [SE]: 3.8%), and for APACHE II it was 85.7% (SE: 3.5%), also the Hosmer-Lemeshow statistic revealed better calibration for GCS (χ(2) = 5.177, P = 0.521), than APACHE II (χ(2) = 10.203, P = 0.251).The survivors had significantly lower APACHE II and higher GCS compared with non-survivors, also GCS showed more predictive accuracy than APACHE II in prognosticating the outcomes in PACU.

View Article: PubMed Central - PubMed

Affiliation: Department of Nursing, North Khorasan University of Medical Sciences, Bojnourd, Iran.

ABSTRACT

Context: Acute physiology and chronic health evaluation II (APACHE II) is one of the most general classification systems of disease severity in Intensive Care Units and Glasgow Coma Score (GCS) is one of the most specific ones.

Aims: The aim of the current study was to assess APACHE II and GCS ability in predicting the outcomes (survivors, non-survivors) in the Post Anesthesia Care Unit's (PACU).

Settings and design: This was an observational and prospective study of 150 consecutive patients admitted in the PACU during 6-month period.

Materials and methods: Demographic information recorded on a checklist, also information about severity of disease calculated based on APACHE II scoring system in the first admission 24 h and GCS scale.

Statistical analysis used: Logistic regression, Hosmer-Lemeshow test and receiver operator characteristic (ROC) curves were used in statistical analysis (95% confidence interval).

Results: Data analysis showed a significant statistical difference between outcomes and both APACHE II and Glasgow Coma Score (GCS) (P < 0.0001). The ROC-curve analysis suggested that the predictive ability of GCS is slightly better than APACHE II in this study. For GCS the area under the ROC curve was 86.1% (standard error [SE]: 3.8%), and for APACHE II it was 85.7% (SE: 3.5%), also the Hosmer-Lemeshow statistic revealed better calibration for GCS (χ(2) = 5.177, P = 0.521), than APACHE II (χ(2) = 10.203, P = 0.251).

Conclusions: The survivors had significantly lower APACHE II and higher GCS compared with non-survivors, also GCS showed more predictive accuracy than APACHE II in prognosticating the outcomes in PACU.

No MeSH data available.


Related in: MedlinePlus