Introduction: Postoperative delirium (POD) that is associated with intracranial surgeries can have several adverse outcomes, including a high rate of morbidity and mortality. The use of intraoperative neurophysiological monitoring (IONM) via somatosensory evoked potentials (SSEP) and electroencephalography (EEG) provides continuous information regarding cerebral blood flow (CBF) during aneurysm clipping. In this study, we hypothesize that CBF changes during aneurysm clipping increase the risk of POD. We aimed to demonstrate that significant changes in IONM data during surgery increase the risk of POD after adjusting for clinical and intraoperative factors. Methods: 470 patients undergoing craniotomy for aneurysm clipping surgery with IONM were retrospectively reviewed for the development of POD. Significant IONM changes were evaluated based on a visual review of EEG and SSEP data and documentation of significant changes during surgery. Data changes during IONM were classified as SSEP changes, EEG changes, or IONM changes (SSEP and/or EEG changes). Results: Of the 470 patients who underwent aneurysm clipping, 115 (24.5%) had POD and 35 (30.4%) had IONM changes. IONM and SSEP changes were significantly associated with POD (p < 0.001). After adjusting for confounding variables, IONM and SSEP changes were significantly associated with POD (adjusted odds ratio (aOR) 2.4 [CI: 1.40–4.17]; p = 0.002) and (aOR 2.49 [CI: 1.39–4.45]; p = 0.002), respectively. We also found that the odds of POD were higher in patients with ruptured aneurysms and in patients who developed focal neurological deficits postoperatively (aOR 2.76, 1.72–4.42; p < 0.001) and (aOR 2.11, 1.02–4.36, p = 0.04), respectively. Conclusion: Patients who develop POD after craniotomy for aneurysm clipping surgery are twice as likely to have experienced significant IONM or SSEP changes during the surgery. Patients with ruptured aneurysms and who develop postoperative focal neurological deficits are also more than twice as likely to develop POD. These findings provide a strong platform for future research in testing therapeutic interventions based on IONM changes, which aim to decrease the risk of POD after aneurysm clipping surgeries.

1.
Tsui
A
,
Yeo
N
,
Searle
SD
,
Bowden
H
,
Hoffmann
K
,
Hornby
J
, et al
.
Extremes of baseline cognitive function determine the severity of delirium: a population study
.
Brain
.
2023
;
146
(
5
):
2132
41
.
2.
Zipser
CM
,
Deuel
J
,
Ernst
J
,
Schubert
M
,
von Känel
R
,
Böttger
S
.
The predisposing and precipitating risk factors for delirium in neurosurgery: a prospective cohort study of 949 patients
.
Acta Neurochir
.
2019
;
161
(
7
):
1307
15
.
3.
Schubert
M
,
Schürch
R
,
Boettger
S
,
Garcia Nuñez
D
,
Schwarz
U
,
Bettex
D
, et al
.
A hospital-wide evaluation of delirium prevalence and outcomes in acute care patients: a cohort study
.
BMC Health Serv Res
.
2018
;
18
(
1
):
550
.
4.
Leslie
DL
,
Marcantonio
ER
,
Zhang
Y
,
Leo-Summers
L
,
Inouye
SK
.
One-year health care costs associated with delirium in the elderly population
.
Arch Intern Med
.
2008
;
168
(
1
):
27
32
.
5.
Moskowitz
EE
,
Overbey
DM
,
Jones
TS
,
Jones
EL
,
Arcomano
TR
,
Moore
JT
, et al
.
Post-operative delirium is associated with increased 5-year mortality
.
Am J Surg
.
2017
;
214
(
6
):
1036
8
.
6.
Wang
J
,
Ji
Y
,
Wang
N
,
Chen
W
,
Bao
Y
,
Qin
Q
, et al
.
Risk factors for the incidence of delirium in cerebrovascular patients in a Neurosurgery Intensive Care Unit: a prospective study
.
J Clin Nurs
.
2018
;
27
(
1–2
):
407
15
.
7.
Mrkobrada
M
,
Chan
MTV
,
Cowan
D
,
Spence
J
,
Campbell
D
,
Wang
CY
, et al
.
Rationale and design for the detection and neurological impact of cerebrovascular events in non-cardiac surgery patient’s cohort evaluation (NeuroVISION) study: a prospective international cohort study
.
BMJ Open
.
2018
;
8
(
7
):
e021521
.
8.
Mette
D
,
Strunk
R
,
Zuccarello
M
.
Cerebral blood flow measurement in neurosurgery
.
Transl Stroke Res
.
2011
;
2
(
2
):
152
8
.
9.
Sundt
TM
,
Sharbrough
FW
,
Anderson
RE
,
Michenfelder
JD
.
Cerebral blood flow measurements and electroencephalograms during carotid endarterectomy
.
J Neurosurg
.
2007
;
107
(
4
):
887
97
.
10.
Kashkoush
AI
,
Nguyen
C
,
Balzer
J
,
Habeych
M
,
Crammond
DJ
,
Thirumala
PD
.
Diagnostic accuracy of somatosensory evoked potentials during intracranial aneurysm clipping for perioperative stroke
.
J Clin Monit Comput
.
2020
;
34
(
4
):
811
9
.
11.
Kashkoush
AI
,
Jankowitz
BT
,
Gardner
P
,
Friedlander
RM
,
Chang
YF
,
Crammond
DJ
, et al
.
Somatosensory evoked potentials during temporary arterial occlusion for intracranial aneurysm surgery: predictive value for perioperative stroke
.
World Neurosurg
.
2017
;
104
:
442
51
.
12.
Kashkoush
AI
,
Jankowitz
BT
,
Nguyen
C
,
Gardner
PA
,
Wecht
DA
,
Friedlander
RM
, et al
.
Perioperative stroke after cerebral aneurysm clipping: risk factors and postoperative impact
.
J Clin Neurosci
.
2017
;
44
:
188
95
.
13.
Thirumala
PD
,
Udesh
R
,
Muralidharan
A
,
Thiagarajan
K
,
Crammond
DJ
,
Chang
YF
, et al
.
Diagnostic value of somatosensory-evoked potential monitoring during cerebral aneurysm clipping: a systematic review
.
World Neurosurg
.
2016
;
89
:
672
80
.
14.
Park
D
,
Kim
BH
,
Lee
SE
,
Jeong
E
,
Cho
K
,
Park
JK
, et al
.
Usefulness of intraoperative neurophysiological monitoring during the clipping of unruptured intracranial aneurysm: diagnostic efficacy and detailed protocol
.
Front Surg
.
2021
;
8
:
631053
.
15.
Moehl
K
,
Shandal
V
,
Anetakis
K
,
Paras
S
,
Mina
A
,
Crammond
D
, et al
.
Predicting transient ischemic attack after carotid endarterectomy: the role of intraoperative neurophysiological monitoring
.
Clin Neurophysiol
.
2022
;
141
:
1
8
.
16.
von Hofen-Hohloch
J
,
Awissus
C
,
Fischer
MM
,
Michalski
D
,
Rumpf
JJ
,
Classen
J
.
Delirium screening in neurocritical care and stroke unit patients: a pilot study on the influence of neurological deficits on CAM-ICU and ICDSC outcome
.
Neurocrit Care
.
2020
;
33
(
3
):
708
17
.
17.
Marcantonio
ER
.
Delirium in hospitalized older adults
.
N Engl J Med
.
2017
;
377
(
15
):
1456
66
.
18.
Wippold
FJ
;
Expert Panel on Neurologic Imaging
.
Focal neurologic deficit
.
AJNR Am J Neuroradiol
.
2008
;
29
(
10
):
1998
2000
.
19.
Staarmann
B
,
O’Neal
K
,
Magner
M
,
Zuccarello
M
.
Sensitivity and specificity of intraoperative neuromonitoring for identifying safety and duration of temporary aneurysm clipping based on vascular territory, a multimodal strategy
.
World Neurosurg
.
2017
;
100
:
522
30
.
20.
Neurophysiological monitoring in neuroanesthesia
.
Curr Opin Anaesthesiology
.
2018
;
1
:
15
8
.
21.
Eggspuehler
A
,
Sutter
MA
,
Grob
D
,
Jeszenszky
D
,
Dvorak
J
.
Multimodal intraoperative monitoring during surgery of spinal deformities in 217 patients
.
Eur Spine J
.
2007
;
16
(
Suppl 2
):
188
96
.
22.
Jin
Z
,
Hu
J
,
Ma
D
.
Postoperative delirium: perioperative assessment, risk reduction, and management
.
Br J Anaesth
.
2020
;
125
(
4
):
492
504
.
23.
Obert
DP
,
Schweizer
C
,
Zinn
S
,
Kratzer
S
,
Hight
D
,
Sleigh
J
, et al
.
The influence of age on EEG-based anaesthesia indices
.
J Clin Anesth
.
2021
;
73
:
110325
.
24.
Shanker
A
,
Abel
JH
,
Schamberg
G
,
Brown
EN
,
Donald
J
,
Shanker
A
, et al
.
Etiology of burst suppression EEG patterns
.
Front Psychol
.
2021
;
12
:
673529
.
25.
Fleseriu
CM
,
Sultan
I
,
Brown
JA
,
Mina
A
,
Frenchman
J
,
Crammond
DJ
, et al
.
Role of intraoperative neurophysiological monitoring in preventing stroke after cardiac surgery
.
Ann Thorac Surg
.
2023
;
116
(
3
):
623
9
.
26.
Al-Qudah
AM
,
Ta’ani
OA
,
Thirumala
PD
,
Sultan
I
,
Visweswaran
S
,
Nadkarni
N
, et al
.
Role of intraoperative neuromonitoring to predict postoperative delirium in cardiovascular surgery
.
J Cardiothorac Vasc Anesth
.
2024
;
38
(
2
):
526
33
.
27.
Janjua
MS
,
Spurling
BC
,
Arthur
ME
.
Postoperative delirium
. In:
StatPearls
.
StatPearls Publishing
;
2023
. http://www.ncbi.nlm.nih.gov/books/NBK534831/(Accessed August 30, 2023).
You do not currently have access to this content.