TY - JOUR
T1 - The added value that increasing levels of diagnostic information provide in prognostic models to estimate hospital mortality for adult intensive care patients
AU - de Keizer, N. F.
AU - Bonsel, G. J.
AU - Goldfad, C.
AU - Rowan, K. M.
PY - 2000
Y1 - 2000
N2 - To investigate in a systematic, reproducible way the potential of adding increasing levels of diagnostic information to prognostic models for estimating hospital mortality. Prospective cohort study. Thirty UK intensive care units (ICUs) participating in the ICNARC Case Mix Programme. Eight thousand fifty-seven admissions to UK ICUs. Logistic regression analysis incorporating APACHE II score, admission type and increasing levels of diagnostic information was used to develop models to estimate hospital mortality for intensive care patients. The 53 UK APACHE II diagnostic categories were substituted with data from a hierarchical, five-tiered (type of condition required surgery or not, body system, anatomical site, physiological/pathological process, condition) coding method, the ICNARC Coding Method. The inter-rater reliability using the ICNARC Coding Method to code reasons for admission was good (kappa = 0.70). All new models had good discrimination (AUC = 0.79-0.81) and similar or better calibration compared with the UK APACHE II model (Hosmer-Lemeshow goodness-of-fit H = 18.03 to H = 26.77 for new models versus H = 63.51 for UK APACHE II model). The UK APACHE II model can be simplified by extending the admission type and substituting the 53 UK APACHE II diagnostic categories with nine body systems, without losing discriminative power or calibration
AB - To investigate in a systematic, reproducible way the potential of adding increasing levels of diagnostic information to prognostic models for estimating hospital mortality. Prospective cohort study. Thirty UK intensive care units (ICUs) participating in the ICNARC Case Mix Programme. Eight thousand fifty-seven admissions to UK ICUs. Logistic regression analysis incorporating APACHE II score, admission type and increasing levels of diagnostic information was used to develop models to estimate hospital mortality for intensive care patients. The 53 UK APACHE II diagnostic categories were substituted with data from a hierarchical, five-tiered (type of condition required surgery or not, body system, anatomical site, physiological/pathological process, condition) coding method, the ICNARC Coding Method. The inter-rater reliability using the ICNARC Coding Method to code reasons for admission was good (kappa = 0.70). All new models had good discrimination (AUC = 0.79-0.81) and similar or better calibration compared with the UK APACHE II model (Hosmer-Lemeshow goodness-of-fit H = 18.03 to H = 26.77 for new models versus H = 63.51 for UK APACHE II model). The UK APACHE II model can be simplified by extending the admission type and substituting the 53 UK APACHE II diagnostic categories with nine body systems, without losing discriminative power or calibration
U2 - https://doi.org/10.1007/s001340051207
DO - https://doi.org/10.1007/s001340051207
M3 - Article
C2 - 10923733
SN - 0342-4642
VL - 26
SP - 577
EP - 584
JO - Intensive care medicine
JF - Intensive care medicine
IS - 5
ER -