Int J Geriatr Psychiatry 2019 07 23;34(7):1018-1028. Epub 2019 Apr 23.
Department of Anesthesiology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States.
Objectives: Delirium is an important postoperative complication, yet predictive risk factors for postoperative delirium severity remain elusive. We hypothesized that the NSQIP risk calculation for serious complications (NSQIP-SC) or risk of death (NSQIP-D), and cognitive tests of executive function (Trail Making Tests A and B [TMTA and TMTB]), would be predictive of postoperative delirium severity. Further, we demonstrate how advanced statistical techniques can be used to identify candidate predictors.
Methods/design: Data from an ongoing perioperative prospective cohort study of 100 adults (65 y old or older) undergoing noncardiac surgery were analyzed. In addition to NSQIP-SC, NSQIP-D, TMTA, and TMTB, participant age, sex, American Society of Anesthesiologists (ASA) score, tobacco use, surgery type, depression, Framingham risk score, and preoperative blood pressure were collected. The Delirium Rating Scale-R-98 (DRS) measured delirium severity; the Confusion Assessment Method (CAM) identified delirium. LASSO and best subsets linear regression were employed to identify predictive risk factors.
Results: 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. LASSO and best subsets regression identified NSQIP-SC and TMTB to predict postoperative delirium severity (P < 00.001, adjusted R : 0.30). NSQIP-SC and TMTB were also selected as predictors for postoperative delirium incidence (AUROC 0.81, 95% CI, 0.72-0.90).
Conclusions: In this cohort, we identified NSQIP risk score for serious complications and a measure of executive function, TMT-B, to predict postoperative delirium severity using advanced modeling techniques. Future studies should investigate the utility of these variables in a formal delirium severity prediction model.