PT  - JOURNAL ARTICLE
AU  - Lindroth H.
AU  - Bratzke L.
AU  - Twadell S.
AU  - Rowley P.
AU  - Kildow J.
AU  - Danner M.
AU  - Turner L.
AU  - Hernandez B.
AU  - Chang W.
AU  - Brown R.
AU  - Sanders R.D.
TI  - Derivation of a simple postoperative delirium incidence and severity prediction model
AID  - 10.1101/426148
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 426148
4099  - http://biorxiv.org/content/early/2018/09/28/426148.short
4100  - http://biorxiv.org/content/early/2018/09/28/426148.full
AB  - Background Delirium is an important postoperative complication, yet a simple and effective delirium prediction model remains elusive. We hypothesized that the combination of the National Surgical Quality Improvement Program (NSQIP) risk calculator for serious complications (NSQIP-SC) or risk of death (NSQIP-D), and cognitive tests of executive function (Trail Making Test A and B [TMTA, TMTB]), could provide a parsimonious model to predict postoperative delirium incidence or severity.Methods Data were collected from 100 adults (≥65yo) undergoing major non-cardiac surgery. In addition to NSQIP-SC, NSQIP-D, TMTA and TMTB, we collected participant age, sex, ASA score, tobacco use, type of surgery, depression, Framingham risk score, and preoperative blood pressure. Delirium was diagnosed with the Confusion Assessment Method (CAM), and the Delirium Rating Scale-R-98 (DRS) was used to assess symptom severity. LASSO and Best Subsets logistic and linear regression were employed in line with TRIPOD guidelines.Results Three participants were excluded due to intraoperative deaths (2) and alcohol withdrawal (1). Ninety-seven participants with a mean age of 71.68±4.55, 55% male (31/97 CAM+, 32%) and a mean Peak DRS of 21.5±6.40 were analyzed. Of the variables included, only NSQIP-SC and TMTB were identified to be predictors of postoperative delirium incidence (p<0.001, AUROC 0.81, 95% CI: 0.72, 0.90) and severity (p<0.001, Adj. R2: 0.30).Conclusions In this cohort, preoperative NSQIP-SC and TMTB were identified as predictors of postoperative delirium incidence and severity. Future studies should verify whether this two-factor model could be used for accurate delirium prediction.