Predicting postoperative delirium severity in older adults: The role of surgical risk and executive function.
aging
delirium
executive function
perioperative
risk
severity
Journal
International journal of geriatric psychiatry
ISSN: 1099-1166
Titre abrégé: Int J Geriatr Psychiatry
Pays: England
ID NLM: 8710629
Informations de publication
Date de publication:
07 2019
07 2019
Historique:
received:
05
12
2018
accepted:
20
03
2019
pubmed:
26
3
2019
medline:
1
2
2020
entrez:
26
3
2019
Statut:
ppublish
Résumé
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. 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. 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 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.
Identifiants
pubmed: 30907449
doi: 10.1002/gps.5104
pmc: PMC6579704
mid: NIHMS1019646
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1018-1028Subventions
Organisme : NIA NIH HHS
ID : K23 AG055700
Pays : United States
Organisme : NHLBI NIH HHS
ID : T32 HL091816
Pays : United States
Informations de copyright
© 2019 John Wiley & Sons, Ltd.
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