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  Indian J Med Microbiol
 

Figure 1: ROC curve and corresponding AUC. ROC curves typically feature true-positive rate (sensitivity) on the Y-axis and false-positive rate (1-specificity) on the X-axis for different cut-off points of a parameter. The area under ROC curve was 0.800 (95% CI 0.752-0.847). The sensitivity of the ONEWS in predicting adverse maternal outcome was 74.8 per cent, specificity 76.2 per cent, positive predictive value 59.5 per cent and negative predictive value 86.7 per cent using a cut-off score of 3. Diagonal segments are produced by ties. ROC, receiver operating characteristic; AUC, area under the curve; CI, confidence interval; ONEWS, Obstetrics National Early Warning System.

Figure 1: ROC curve and corresponding AUC. ROC curves typically feature true-positive rate (sensitivity) on the Y-axis and false-positive rate (1-specificity) on the X-axis for different cut-off points of a parameter. The area under ROC curve was 0.800 (95% CI 0.752-0.847). The sensitivity of the ONEWS in predicting adverse maternal outcome was 74.8 per cent, specificity 76.2 per cent, positive predictive value 59.5 per cent and negative predictive value 86.7 per cent using a cut-off score of 3. Diagonal segments are produced by ties. ROC, receiver operating characteristic; AUC, area under the curve; CI, confidence interval; ONEWS, Obstetrics National Early Warning System.