Table 5.
Specificity and sensitivity of the cut scores from the LEADS algorithm full cohort
CUT-OFF SCORES | SENSITIVITY | SPECIFICITY | LR | PPV | NPV |
236 | 0.64 | 0.88 | 5.33 | 0.364 | 0.958 |
244 | 0.88 | 0.85 | 6.03 | 0.393 | 0.985 |
253 | 0.88 | 0.83 | 5.26 | 0.361 | 0.985 |
Co-ordinates of the ROC curve identify cut-off values as an average of two consecutive ordered test values
Sensitivity is the proportion of patients that are correctly identified as needing nursing home.
Specificity is the proportion of people that are correctly identified as not needing nursing home.
LR+ = Likelihood ratio, how many more times likely patients will need nursing home with this cut-off score than those who do not.
Positive predictive value is the proportion of people who had a positive test for nursing home who did need a nursing home admission.
Negative predictive value is the proportion of people who had a negative test result and didn't need a nursing home admission