Preoperative detection of serum phosphorylated neurofilament heavy chain subunit predicts postoperative delirium: a prospective observational study
by
Kazuhito Mietani
1,
Maiko Hasegawa-Moriyama
2,
Kouichi Yagi
3,
Reo Inoue
1,
Toru Ogata
4,
Makoto Kurano
5,
Nobutake Shimojo
6,
Yasuyuki Seto
3,
Masahiko Sumitani
7,* and 
Kanji Uchida
1 1
Department of Anesthesiology and Pain Relief Center, The University of Tokyo Hospital, Tokyo, Japan
2
Department of Pain and Palliative Medical Sciences, Faculty of Medicine, The University of Tokyo, Tokyo, Japan
3
Department of Gastrointestinal Surgery, The University of Tokyo Hospital, Tokyo, Japan
4
Department of Rehabilitation Medicine, The University of Tokyo Hospital, Tokyo, Japan
5
Department of Clinical Laboratory Medicine, The University of Tokyo Hospital, Tokyo, Japan
6
Department of Emergency and Critical Care Medicine, Tsukuba University Hospital, Ibaraki, Japan
7
Department of Pain and Palliative Medicine, The University of Tokyo Hospital, Tokyo, Japan
*
Author to whom correspondence should be addressed.
J. Gerontol. Geriatr. 2022, 70(3), 169-177; https://doi.org/10.36150/2499-6564-N488
Submission received: 28 December 2021
/
Accepted: 28 March 2022
/
Published: 31 May 2022
Abstract
Background & Aims: Elderly surgical patients are susceptible to development of postoperative
delirium. Interventions for postoperative delirium have little effect on its
progression, indicating the importance of early detection and prevention.
This study investigated preoperative biomarkers to predict postoperative
delirium. Methods: Delirium-related serum biomarkers were measured before the start of surgery
in patients who underwent esophageal cancer surgery and were compared
between patients who did and did not develop postoperative delirium. Results: Fifteen of 96 patients (15.6%) developed postoperative delirium.
Brain-derived phosphorylated neurofilament heavy subunit was preoperatively
detected in 80% of patients with postoperative delirium. The preoperative
interleukin-6 (IL-6) concentration was significantly higher whereas the
concentrations of plasminogen activator inhibitor-1 (PAI-1) was
significantly lower in patients with postoperative delirium. Detection of
phosphorylated neurofilament heavy subunit was associated with postoperative
delirium independent of age (adjusted odds ratio, 5.86; 95% confidence
interval, 1.60-29.03; p = 0.0064). The sensitivity and specificity of
postoperative delirium detection was increased when age was combined with
detection of phosphorylated neurofilament heavy subunit. Conclusions: Preoperative evaluation of phosphorylated neurofilament heavy subunit can
predict postoperative delirium independent of age. Early detection of serum
phosphorylated neurofilament heavy subunit before surgery may enable
clinicians to identify patients at risk for postoperative delirium and start
early intervention.
List of abbreviations
PD: postoperative delirium
CAM-ICU: the Confusion Assessment Method for the Intensive Care Unit
ICDSC: the Intensive Care Delirium Screening Checklist
ICU: intensive care unit
pNF-H: phosphorylated neurofilament heavy subunit
CNS: central nervous system
PECAM-1: platelet endothelial cell adhesion molecule-1
MMP-9: matrix metalloprotease-9
PAI-1: plasminogen activator inhibitor-1
IL-6: interleukin-6
BBB: blood brain barrier
CSF: cerebrospinal fluid
NRS: Numeric Rating Scale
NSE: Neuron-specific enolase
ApoE: apolipoprotein E
BACKGROUND and AIMS
Postoperative delirium (PD) is a complication that occurs in 30 to 50% of elderly
patients and is associated with a significant increase in length of hospital stay,
cost of care, and mortality 1,2. Older age, male sex, dementia,
mild cognitive impairment, laboratory abnormalities, drugs including opioids,
surgery, anaesthesia, high pain levels, anaemia, infections, acute illness, and
acute exacerbation of chronic illness are commonly identified as risk factors for
the development of delirium 3.
The Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) 4 and the Intensive Care Delirium
Screening Checklist (ICDSC) 5 are
commonly used to screen for delirium in critically ill patients in the intensive
care unit (ICU). A meta-analysis of the diagnostic accuracy of these screening tools
revealed that the ICDSC had a pooled sensitivity of 74% and a specificity of 82%
whereas the CAM-ICU had a pooled sensitivity of 80% and a pooled specificity of 96%
to detect delirium 6. However, it
can still be difficult to predict PD, and delayed diagnosis can lead to brain
atrophy, even in patients who recover from PD 7.
On the basis of a previous report that linked the incidence of PD to brain atrophy
8, we measured the serum
concentration of phosphorylated neurofilament heavy subunit (pNF-H), a major
cytoskeletal protein of central nervous system (CNS) axons, in patients with PD.
Although pNF-H is normally undetectable in blood samples of healthy patients, it was
detected in 56.1 to 65.2% of patients who experienced PD 9,10,
suggesting that neural damage is accompanied by PD development. In addition, we
previously reported that elevation of the serum pNF-H levels was correlated with the
progression of delirium-related CNS damage, which was associated with platelet
endothelial cell adhesion molecule (PECAM)-1 9. Therefore, pNF-H may serve as a biomarker of neural tissue
damage, which is exacerbated by the effects of perioperative mediators involved in
inflammation-induced coagulation/fibrinolysis. The increase in matrix
metalloprotease (MMP)-9 and plasminogen activator inhibitor (PAI)-1 disrupts the
integrity of the blood brain barrier (BBB), resulting in neurodegenerative
progression in the aged brain 11,12.
In addition, significant concentrations of pro- and anti-inflammatory markers are
detectable in the serum and cerebrospinal fluid (CSF) after surgery in elderly
adults 13,14, and different anaesthetic agents may modulate
immune signaling pathways 15,16. Zhang et al. 17 reported that dexmedetomidine
suppresses postoperative elevation of pro-inflammatory cytokines such as interleukin
(IL)-6 and reduces the incidence of PD in elderly patients over the first 3 days
after hip fracture surgery.
These findings suggest that management of anaesthesia in surgery and sedation in the
ICU can affect cognitive outcomes. Accordingly, perioperative intervention may be
able to reduce the risk of PD in high-risk elderly patients. However, preoperative
biomarkers that can be used for early prediction of PD have not yet been identified.
In this study, we hypothesised that (1) chronic neurodegeneration is present in the
elderly patients before surgery; (2) acute exacerbation of neural damage is
triggered by surgical stress, resulting in PD development, and (3) patients with CNS
markers that are detectable before surgery can be susceptible to PD. Therefore, this
study aimed to investigate whether serum biomarkers, CNS-derived biomarkers, and
pNF-H can predict PD in elderly patients to identify patients at risk and allow
prevention. Additionally, the link between the pNF-H level and factors involved in
inflammation and coagulation/fibrinolysis was explored.
PATIENTS AND METHODS
ETHICS
The study was approved by the Ethical Committee of the University of Tokyo
[Approval ID:10051] and conducted in hospitals of the University of Tokyo from
October 2016 to June 2019. The local ethics committee of each institution
approved the trial protocol and written informed consent was obtained from each
patient. The study was registered in the University Medical Information Network
(UMIN trial ID: UMIN000010329).
STUDY POPULATION
Patients scheduled to undergo oesophageal cancer surgery were eligible for
inclusion. The surgical procedure consisted of open, robot-assisted, or
mediastinoscope-assisted esophagectomy. All patients undergoing oesophageal
cancer surgeries were admitted to the ICU. The exclusion criteria were as
follows: (1) patients with a score of 4 on the American Society of
Anesthesiologists physical classification; (2) patients with a history of
clinically relevant cognitive dysfunction or a neurological disorder diagnosed
by a neurologist before surgery according to the patient’s records, and
(3) patients who were regularly prescribed tranquilizers that could influence PD
18.
PATIENT ASSESSMENT
In the first 3 days after surgery, delirium-associated symptoms were screened by
the attending nurses at least three times a day during regular ward rounds using
the CAM-ICU. Patients with suspected PD underwent further assessment using the
ICDSC to confirm the diagnosis. The postoperative pain intensity was evaluated
using the Numeric Rating Scale (NRS), with 0 indicating no pain and 10
indicating the worst possible pain 19. The total amount of fentanyl equivalents used during
surgery was the exposure variable as previously described 20,21. The fentanyl equivalent conversion factors for 1
μg of fentanyl were 1 μg of remifentanil and 100 μg of
morphine.
MEASUREMENT OF BIOMARKERS
Blood samples were collected from an arterial blood pressure monitoring line
immediately after induction of anaesthesia and before the start of surgery in
the operating room and stored at -20°C. Neuron-specific enolase (NSE),
platelet endothelial cell adhesion molecule-1 (PECAM-1), matrix
metalloprotease-9 (MMP-9), PAI-1, and IL-6 were measured using a multiplex
immunoassay (Luminex® Assay Human Premixed Multi-Analyte Kit;
R&D, Rockville, MD, USA) according to the manufacturer’s protocol.
Measurement of pNF-H was performed using an enzyme-linked immunosorbent assay
(Modrice, Czech Republic) according to the manufacturer’s protocol; the
threshold concentration for detection was 70.5 ng/mL. All samples were measured
in duplicate.
STATISTICAL ANALYSIS
Statistical analyses were performed using JMP Pro software version 16 (SAS
Institute, Cary, NC, USA). Patient characteristics and log-transformed biomarker
concentrations were compared using the Wilcoxon rank-sum test or
Pearson’s chi-square test. Logistic regression based on the
log-transformed concentration of the potential candidate variables was performed
to identify independent parameters and biomarkers for PD as previously reported
22. P < 0.05
was considered significant.
RESULTS
A total of 120 patients who underwent elective oesophageal cancer surgery and
provided written informed consent for participation were screened (Fig. 1). Two eligible patients were excluded
based on the criteria. Blood samples were not collected from 20 patients who were
reintubated in the ICU or operating room, or admitted to the ICU under intubation
because of unstable haemodynamics. In addition, two patients who underwent other
surgical procedures were excluded. Patients between 47 and 85 years old were
enrolled in this study. PD occurred in 15 of 96 patients (15.6%) in the first 3 days
after surgery. PD patients were significantly older than those who did not
experience PD (Tab. I). Preoperative
opioid use were significantly correlated with PD. Regarding intraoperative
parameters, the surgical procedure, combination of epidural anaesthesia with general
anaesthesia, and were also correlated with PD (Tab. II). Neither the total amount of opioids used during surgery nor
the postoperative pain intensity designated by the NRS (Supplementary Table I) differed between the two groups. A
significantly higher proportion of PD patients were positive for pNF-H before
surgery (Tab. III). In addition, the
preoperative IL-6 concentration was significantly higher in PD patients. However,
multivariate logistic regression analysis showed that factors involved in
inflammation and coagulation/fibrinolysis were not associated with the detection of
pNF-H (Supplementary Table II).
Preoperative detection of pNF-H (adjusted odds ratio, 5.86; 95% confidence interval,
1.60-29.03; p = 0.0064) and age (adjusted odds ratio, 1.12; 95% confidence
interval,1.03-1.23; p = 0.0062) were independent factors associated with PD (Tab. IV), even in the analysis including
preoperative use of opioids as a covariate (Supplementary Table III). The specificity of PD diagnosis increased when
age was combined with pNF-H detection. (Supplementary Table IV).
DISCUSSION
Preoperative detection of pNF-H was significantly associated with PD (Tab. III). Because pNF-H detection was
associated with PD independent of age (Tab.
IV), the specificity of age for indicating PD development improved when
combined with preoperative pNF-H detection (Supplementary Table IV).
Postoperative pain, opioid analgesia, and systemic inflammation have been identified
as delirium risk factors 23-25. Recently, the use of combined epidural and general
analgesia was suggested as a way to reduce PD risk. The incidence of postoperative
delirium within 7 days was significantly lower in patients who received
epidural–general anaesthesia (1.8%) than that in the general anaesthesia
group (5.0%) 26. However, a
higher frequency of combined anesthesia in PD patients resulted in little difference
in the NRS score and postoperative opioid use between PD and non-PD patients (Table II and Supplementary Table I) in our study. Consistent with
previous studies 3, the surgical
procedure was significantly associated with development of PD (Tab. II). These surgical stresses can
cause increased production of the serum mediators involved in inflammation and
coagulation/fibrinolysis, which are associated with PD development 8, although we did not evaluate
serum mediators in the postoperative period. However, before surgery, the IL-6
concentration was higher in PD patients than that in patients who did not develop
PD, suggesting that patients in a proinflammatory state before surgery may have a
higher risk of PD regardless of postoperative conditions.
Blood brain barrier disruption induced by systemic inflammation can cause neuronal
damage 25. We previously
reported that P-selectin was the only independent variable associated with pNF-H
detection whereas PECAM-1 was associated with serum pNF-H levels in pNF-H-positive
patients on the postoperative day 3 9. In our present study, the preoperative PECAM-1 value was not
associated with preoperative pNF-H detection. According to our current and previous
findings, these markers of endothelial damage, including PECAM-1 and MMP-9, could be
induced after the induction of the systemic inflammatory condition, possibly
exacerbating axonal damage after surgery. The time course of these marker levels in
the perioperative periods should be further investigated.
The neuron-specific cytoskeletal protein pNF-H is responsible for protecting
neurofilaments from degeneration 27. Elevation of the serum pNF-H concentration has been reported
in mild traumatic brain injury patients on days 1 and 3 after injury. Moreover, the
pNF-H concentration has been correlated with brain injury severity. Similarly, NSE
is a prognostic marker following traumatic and anoxic brain injury 28,29. It has been previously reported that higher plasma NSE
concentrations are associated with mortality and delirium in critically ill septic
patients 30. However, the
concentration of NSE, which is enriched in neuronal cell bodies and a potential
marker of neuronal damage in PD patients, was not different between groups in our
study (Tab. III). Although the
discrepancy in the correlation of delirium with pNF-H and that of NSE has not been
demonstrated elsewhere, a correlation between pNF-H and apolipoprotein E (ApoE)
under stressful conditions has been previously proposed 31. In cultured neurons and the brains of
Alzheimer’s disease patients, p-NF-H interacts with ApoE to form
neurofibrillary tangles. It is likely that pNF-H rather than NSE is genetically
linked to PD because the ApoE epsilon 4 allele has been correlated with PD
32. The link between
pNF-H and ApoE should be further investigated further in PD patients.
Hyperphosphorylation of NF-H has been reported in the brains of elderly patients as
well as patients with Alzheimer’s disease 33. In addition, the serum pNF-H concentration is
elevated in the early pre-diagnostic stage of patients with amyotrophic lateral
sclerosis 34. Therefore, pNF-H,
rather than NSE, may be detectable in the early stages of neurodegenerative
progression in the elderly. Consistent with the common understanding that elderly
individuals with mild cognitive impairment and dementia are susceptible to PD
3, the baseline pNF-H
level was increased in PD patients before surgery (Tab. III). Future studies should examine the change in
pNF-H concentration in PD patients throughout the entire perioperative period.
In contrast to IL-6 elevation, the preoperative PAI-1 value tends to be lower in
non-PD patients than that in PD patients (Tab.
III). Plasma concentrations of PAI-1 have been consistently associated
with development of delirium in the ICU, with higher PAI-1 concentrations associated
with fewer delirium/coma-free days in the full cohort and a longer duration of
delirium among survivors 35.
However, Whether PAI-1 explains cognitive impairment in neurological disorders is
still controversial 36.
Alternatively, tumor cells produce PAI-1 37, and this might mask the serum level of non-tumor-derived
PAI-1. To investigate the involvement of the fibrinolytic system in the development
of PD, changes in PAI-1 levels throughout the perioperative periods should be
evaluated.
This study has several limitations. First, the presence of mild cognitive impairment
is a known risk factor for PD 38. However, the preoperative cognitive functional status was not
screened. Similarly, development of delirium preoperatively after admission was not
assessed either in this study. Second, a meta-analysis recently revealed that poor
functional status preoperatively, including frailty, is associated with PD in
elective surgery patients aged 65 years or older 39. In addition, polypharmacy is an independent
risk factor for PD in elderly patients 40. These reports suggest that preoperative assessment for
delirium risk is important, especially in elderly patients as previously suggested
41. Although the
association between preoperative status and PD was not be explored because of the
small number of patients with PD in this study, the utility of CNS-derived markers
such as pNF-H is useful in patients with frailty and cognitive decline should be
investigated.
CONCLUSIONS
Detection of the presence of serum pNF-H before surgery is significantly associated
with PD in ICU patients after esophageal cancer surgery. Early detection of serum
pNF-H before surgery may enable clinicians to identify patients at risk for PD.
Thus, the optimal modes of anaesthesia and sedation could be selected for patients
with detectable pNF-H. Furthermore, early detection of high-risk patients would
allow close patient monitoring and preventative interventions in the ICU.
Acknowledgements
We would like to thank the patients and their families and caregivers as well as the
ICU staff of the University of Tokyo Hospital. We thank Edanz (https://www.edanz.com) for editing
a draft of this manuscript.
Conflict of interest statement
The department to which M. Hasegawa-Moriyama belongs is supported by Shionogi Co.,
Ltd. (Osaka, Japan), Nippon Zoki Pharmaceutical Co., Ltd. (Osaka, Japan), and
Heartfelt Co., Ltd. (Kumamoto, Japan). Kanji Uchida has collaborative research
agreement and accompanied from research funding with Nihon Kohden Corporation
(Tokyo, Japan) and Nipro Corporation (Osaka, Japan) concerning topics unrelated to
the present study. The funder had no role in the study design or collection,
analysis, or interpretation of data.
Funding
K. Mietani received a grant from JSPS KAKENHI (Grant Number: 19H03749). M. Sumitani
received a Health Labour and Science Research Grant for research on chronic pain
(Grant Number: H26-Cancer-060).
Author contributions
KM acquired patient data. MH-M performed the statistical analyses, interpreted the
data, and wrote the initial draft of the manuscript. RI, KY, and NS assisted KM with
data acquisition. MS, MK, YS and TO contributed to the study concept and design and
manuscript editing. KU wrote and reviewed the final version of the manuscript. All
contributors approved the final version.
Ethical consideration
The study was approved by the Ethical Committee of the University of Tokyo
[1261-(4)]. The local ethics committee of each institution approved the trial
protocol and written informed consent was obtained from each patient. The study was
registered in the University Medical Information Network (UMIN trial ID:
UMIN000037699). We confirmed that all methods were carried out in accordance with
relevant guidelines and regulations.
Figures and tables
Figure 1.
Flow-chart indicating the number of patients excluded and included in the
data analysis.
Table I.
Patient characteristics.
| Variable | Non-PD | PD | P-value |
|---|---|---|---|
| n = 81 | n = 15 | ||
| Age (y) | 67 ± 9 | 74 ± 7 | 0.0021 |
| Gender (M/F) | 69/12 | 13/2 | 0.8813 |
| BMI | 21.9 ± 3.0 | 21.4 ± 2.8 | 0.5624 |
| ASA-PS 1/2/3 (n) | 14/45/22 | 0/8/7 | 0.1226 |
| Smoker never/past/current (n) | 8/65/8 | 2/12/1 | 0.8675 |
| Preoperative adjuvant chemotherapy | 30/51 | 3/12 | 0.2019 |
| Preoperative adjuvant radiation therapy | 73/8 | 12/3 | 0.2582 |
| Preoperative complication | |||
| Ischemic heart disease | 71/10 | 11/4 | 0.3507 |
| Diabetes mellitus | 68/13 | 10/5 | 0.1152 |
| COPD | 68/13 | 13/2 | 0.7901 |
| Cerebrovascular disease | 73/8 | 13/2 | 0.6873 |
| History of cancer surgery | 65/16 | 13/2 | 0.5585 |
| Preoperative opioid use | 80/1 | 12/3 | 0.0008 |
Abbreviations: PD: postoperative delirium; BMI: body mass index; ASA-PS:
American Society of Anesthesiologists physical status; COPD: chronic
obstructive pulmonary disease
Table II.
Intraoperative data and postoperative analgesia.
| Variable | Non-PD | PD | P-value |
|---|---|---|---|
| n = 81 | n = 15 | ||
| Surgical procedure | 33/35/13 | 13/1/1 | 0.0044 |
| 1. open 2. robot-assisted 3. laparoscopy | |||
| Type of anesthetics | 9/30/42 | 1/5/9 | 0.8002 |
| Propofol/desflurane/sevoflurane (n) | |||
| Combination of epidural anesthesia (yes/no) | 81/0 | 13/2 | 0.0009 |
| Total use of fentanyl (i.v., mg/kg) | 10.3 ± 4.4 | 12.6 ± 7.4 | 0.2496 |
| Total use of remifentanil (i.v., mg/kg) | 46.3 ± 31.8 | 46.0 ± 31.5 | 0.9724 |
| The use of pethidine (i.v., n) | 77/4 | 14/1 | 0.7820 |
| Use of morphine (epi, n) | 40/41 | 9/6 | 0.4499 |
| Total amount of opioids; FE (mg/kg) | 56.8 ± 32.2 | 58.8 ± 36.6 | 0.8491 |
| Anesthesia time (min) | 495 ± 95 | 466 ± 109 | 0.3409 |
| Operation time (min) | 426 ± 97 | 400 ± 88 | 0.3212 |
| Bleeding volume (cc) | 355 ± 283 | 488 ± 310 | 0.1389 |
| Infusion volume (cc) | 3865 ± 1035 | 3663 ± 1066 | 0.5076 |
| Transfusion volume (cc) | 387 ± 445 | 574 ± 367 | 0.0947 |
Abbreviations: PD: postoperative delirium; FE: fentanyl equivalent
Table III.
Candidate plasma parameters to predict postoperative delirium.
| Variable | Non-PD | PD | P-value |
|---|---|---|---|
| n = 81 | n = 15 | ||
| pNF-H positivity +/- | 33/48 | 12/3 | 0.0051 |
| WBC | 11348 ± 4816 | 1500 ± 8084 | 0.1096 |
| CRP | 0.45 ± 0.60 | 0.71 ± 0.74 | 0.2295 |
| Log NSE | 9.61 ± 0.63 | 9.41 ± 0.67 | 0.2847 |
| Log Apo E | 10.16 ± 0.50 | 9.80 ± 0.20 | < 0.0001 |
| Log P selectin | 10.85 ± 0.58 | 10.54 ± 0.58 | 0.0723 |
| Log PECAM-1 | 9.42 ± 0.62 | 9.13 ± 0.63 | 0.1210 |
| Log MMP-9 | 8.96 ± 0.93 | 9.09 ± 0.93 | 0.6147 |
| Log PAI-1 | 10.92 ± 0.47 | 10.47 ± 0.88 | 0.0700 |
| Log IL-6 | 0.06 ± 1.01 | 0.82 ± 1,.00 | 0.0141 |
Abbreviations: PD: postoperative delirium; pNF-H: phosphorylated
neurofilament heavy subunit; WBC: white blood cell; CRP: C-reactive
protein; NSE: neuron-specific enolase; ApoE: apolipoprotein E; PECAM-1:
platelet endothelial cell adhesion molecule-1; MMP-9: matrix
metalloproteinase-9; PAI-1: plasminogen activator inhibitor-1; IL-6:
interleukin-6
Table IV.
Logistic regression analysis for prediction of postoperative delirium.
| Variable | Univariable OR | 95% CI | P-value | Adjusted OR | 95% CI | P-value |
|---|---|---|---|---|---|---|
| Age | 1.11 | 1.03-1.21 | 0.0041 | 1.12 | 1.03-1.24 | 0.0062 |
| pNF-H | 5.82 | 1.69-27.00 | 0.0042 | 5.86 | 1.60-29.03 | 0.0064 |
Abbreviations: OR: odds ratio; CI: confidence interval; pNF-H:
phosphorylated neurofilament heavy subunit
Additional Table I.
Postoperative type and onset of delirium, analgesic use, and pain
intensity.
| Variable | Non-PD | PD | P-value |
|---|---|---|---|
| n = 82 | n = 14 | ||
| Type of PD (hyperactive, hypoactive, mixed) | NA | 9/3/3 | NA |
| Onset of PD postoperative day 0/1/2/3 | NA | 7/2/3/3 | NA |
| Total postoperative use of fentanyl (mg/kg) POD3 | 51.8 ± 25.7 | 75.8 ± 47.4 | 0.0749 |
| NRS on postoperative day 1 | 2.0 ± 1.5 | 1.9 ± 1.5 | 0.8146 |
| NRS on postoperative day 2 | 2.0 ± 1.4 | 1.8 ± 1.3 | 0.5074 |
| NRS on postoperative day 3 | 1.7 ± 1.5 | 1.3 ± 1.1 | 0.1769 |
PD: postoperative delirium; NRS: numerical rating scale; POD:
postoperative day
Additional Table II.
Correlation of phosphorylated neurofilament heavy subunit positivity with
other laboratory measurements.
Additional Table II.
Correlation of phosphorylated neurofilament heavy subunit positivity with
other laboratory measurements.
| Variable | Univariable OR | 95% CI | P-value |
|---|---|---|---|
| WBC | 1.00 | 1.00 | 0.0598 |
| CRP | 0.90 | 0.45-1.74 | 0.7633 |
| Log ApoE | 0.60 | 0.34-1.38 | 0.2289 |
| Log P-selectin | 1.12 | 0.56-2.23 | 0.7518 |
| Log PECAM-1 | 0.91 | 0.48-1.74 | 0.7797 |
| Log PAI-1 | 0.73 | 0.35-1.49 | 0.3902 |
| Log IL-6 | 1.48 | 0.98-2.42 | 0.0637 |
OR: odds ratio; CI: confidential interval; WBC: white blood cell; CRP:
C-reactive protein; ApoE: apolipoprotein E; PECAM-1: platelet
endothelial cell adhesion molecule-1; PAI-1: plasminogen activator
inhibitor-1; IL-6: interleukin-6
Additional Table III.
Logistic regression analysis for prediction of postoperative delirium with
preoperative use of opioids as a covariate.
Additional Table III.
Logistic regression analysis for prediction of postoperative delirium with
preoperative use of opioids as a covariate.
| Variable | Univariable OR | 95% CI | P-value | Adjusted OR | 95% CI | P-value |
|---|---|---|---|---|---|---|
| Age | 1.11 | 1.03-1.21 | 0.004 | 1.09 | 1.00-1.19 | 0.032 |
| Preoperative use of opioids | 20.0 | 2.35-423.06 | 0.006 | 41.67 | 1.20-1441.16 | 0.018 |
| pNF-H | 5.82 | 1.69-27.00 | 0.004 | 7.42 | 1.49-37.02 | 0.005 |
Abbreviations: OR: odds ratio; CI: confidence interval; pNF-H:
phosphorylated neurofilament heavy subunit
Additional Table IV.
Sensitivity and specificity for postoperative delirium by age with and
without phosphorylated neurofilament heavy subumit positivity.
Additional Table IV.
Sensitivity and specificity for postoperative delirium by age with and
without phosphorylated neurofilament heavy subumit positivity.
| With pNF-H positivity | 66 | 67 | 68 | 69 | 70 | 71 | 72 | 73 | 74 | 75 | 76 | 77 | 78 | 79 | 80 | 81 | 82 |
| Sensitivity | 0.8 | 0.8 | 0.60 | 0.47 | 0.47 | 0.47 | 0.47 | 0.40 | 0.40 | 0.33 | 0.33 | 0.33 | 0.27 | 0.20 | 0.20 | 0.20 | 0.20 |
| Specificity | 0.69 | 0.74 | 0.72 | 0.80 | 0.85 | 0.85 | 0.89 | 0.90 | 0.93 | 0.93 | 0.94 | 0.96 | 0.96 | 0.98 | 0.98 | 0.98 | 0.99 |
| Without pNF-H positivity | 66 | 67 | 68 | 69 | 70 | 71 | 72 | 73 | 74 | 75 | 76 | 77 | 78 | 79 | 80 | 81 | 82 |
| Sensitivity | 1.00 | 0.93 | 0.73 | 0.60 | 0.60 | 0.60 | 0.60 | 0.53 | 0.53 | 0.47 | 0.47 | 0.40 | 0.33 | 0.27 | 0.27 | 0.27 | 0.27 |
| Specificity | 0.36 | 0.41 | 0.46 | 0.54 | 0.67 | 0.68 | 0.72 | 0.74 | 0.79 | 0.80 | 0.81 | 0.84 | 0.86 | 0.89 | 0.89 | 0.91 | 0.95 |
Consent for publication Not applicable. | |
Data availability Anonymised data from this study are available from the corresponding author for
academic purposes upon reasonable request. |
References
- Jin Z, Hu J, Ma D. Postoperative delirium: perioperative assessment, risk reduction, and management. Br J Anaesth 2020;25:492-504. https://doi.org/10.1016/j.bja.2020.06.06310.1016/j.bja.2020.06.063
- Zywiel MG, Hurley RT, Perruccio AV, et al. Health economic implications of perioperative delirium in older patients after surgery for a fragility hip fracture. J Bone Joint Surg Am 2015;97:829-836. https://doi.org/10.2106/JBJS.N.0072410.2106/JBJS.N.00724
- Marcantonio ER. Delirium in hospitalized older adults. N Engl J Med 2017;377:1456-1466. https://doi.org/10.1056/NEJMcp160550110.1056/NEJMcp1605501
- Ely EW, Margolin R, Francis J, et al. Evaluation of delirium in critically ill patients: validation of the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). Crit Care Med 2001;29:1370-1379. https://doi.org/10.1097/00003246-200107000-0001210.1097/00003246-200107000-00012
- Devlin JW, Fong JJ, Schumaker G, et al. Use of a validated delirium assessment tool improves the ability of physicians to identify delirium in medical intensive care unit patients. Crit Care Med 2007;35:2721-2724. https://doi.org/10.1097/01.ccm.0000292011.93074.8210.1097/01.ccm.0000292011.93074.82
- Gusmao-Flores D, Salluh JI, Chalhub RA, et al. The confusion assessment method for the intensive care unit (CAM-ICU) and intensive care delirium screening checklist (ICDSC) for the diagnosis of delirium: a systematic review and meta-analysis of clinical studies. Crit Car 2012;16:R115. https://doi.org/10.1186/cc1140710.1186/cc11407
- Gunther ML, Morandi A, Krauskopf E, et al. The association between brain volumes, delirium duration, and cognitive outcomes in intensive care unit survivors: the VISIONS cohort magnetic resonance imaging study. Crit Care Med 2012;40:2022-2232. https://doi.org/10.1097/CCM.0b013e318250acc010.1097/CCM.0b013e318250acc0
- Kline RP, Pirraglia E, Cheng H, et al. Surgery and brain atrophy in cognitively normal elderly subjects and subjects diagnosed with mild cognitive impairment. Anesthesiology 2012;116:603-612. https://doi.org/10.1097/ALN.0b013e318246ec0b10.1097/ALN.0b013e318246ec0b
- Mietani K, Sumitani M, Ogata T, et al. Dysfunction of the blood-brain barrier in postoperative delirium patients, referring to the axonal damage biomarker phosphorylated neurofilament heavy subunit. PLoS One 2019;14:e0222721. https://doi.org/10.1371/journal.pone.022272110.1371/journal.pone.0222721
- Inoue R, Sumitani M, Ogata T, et al. Direct evidence of central nervous system axonal damage in patients with postoperative delirium: a preliminary study of pNF-H as a promising serum biomarker. Neurosci Lett 2017;653:39-44. https://doi.org/10.1016/j.neulet.2017.05.02310.1016/j.neulet.2017.05.023
- Hussain B, Fang C, Chang J. Blood-brain barrier breakdown: an emerging biomarker of cognitive impairment in normal aging and dementia. Front Neurosci 2021;15:688090. https://doi.org/10.3389/fnins.2021.68809010.3389/fnins.2021.688090
- McNeil JB, Hughes CG, Girard T, et al. Plasma biomarkers of inflammation, coagulation, and brain injury as predictors of delirium duration in older hospitalized patients. PLoS One 2019;14:e0226412. https://doi.org/10.1371/journal.pone.022641210.1371/journal.pone.0226412
- Hirsch J, Vacas S, Terrando N, et al. Perioperative cerebrospinal fluid and plasma inflammatory markers after orthopedic surgery. J Neuroinflammation 2016;13:211. https://doi.org/10.1186/s12974-016-0681-910.1186/s12974-016-0681-9
- Buvanendran A, Kroin JS, Berger RA, et al. Upregulation of prostaglandin E2 and interleukins in the central nervous system and peripheral tissue during and after surgery in humans. Anesthesiology 2006;104:403-410. https://doi.org/10.1097/00000542-200603000-0000510.1097/00000542-200603000-00005
- Yeager MP, Lunt P, Arruda J, et al. Cerebrospinal fluid cytokine levels after surgery with spinal or general anesthesia. Reg Anesth Pain Med 1999;24:557-562. https://doi.org/10.1016/s1098-7339(99)90049-410.1016/s1098-7339(99)90049-4
- Yuki K, Eckenhoff RG. Mechanisms of the immunological effects of volatile anesthetics: a review. Anesth Analg 2016;123:326-335. https://doi.org/10.1213/ANE.000000000000140310.1213/ANE.0000000000001403
- Zhang W, Wang T, Wang G, et al. Effects of dexmedetomidine on postoperative delirium and expression of IL-1β, IL-6, and TNF-α in elderly patients after hip fracture operation. Front Pharmacol 2020;11:678. https://doi.org/10.3389/fphar.2020.0067810.3389/fphar.2020.00678
- Schrijver EJ, de Vries OJ, Verburg A, et al. Efficacy and safety of haloperidol prophylaxis for delirium prevention in older medical and surgical at-risk patients acutely admitted to hospital through the emergency department: study protocol of a multicenter, randomised, double-blind, placebo-controlled clinical trial. BMC Geriatrics 2014;14:96. https://doi.org/10.1186/1471-2318-14-9610.1186/1471-2318-14-96
- Gerbershagen HJ, Rothaug J, Kalkman CJ, et al. Determination of moderate-to-severe postoperative pain on the numeric rating scale: a cut-off point analysis applying four different methods. Br J Anaesth 2011;107:619-626. https://doi.org/10.1093/bja/aer19510.1093/bja/aer195
- Du KN, Feng L, Newhouse A, et al. Effects of intraoperative opioid use on recurrence-free and overall survival in patients with esophageal adenocarcinoma and squamous cell carcinoma. Anesth Analg 2018;127:210-216. https://doi.org/10.1213/ANE.000000000000342810.1213/ANE.0000000000003428
- Ayad S, Babazade R, Elsharkawy H, et al. Comparison of transversus abdominis plane infiltration with liposomal bupivacaine versus continuous epidural analgesia versus intravenous opioid analgesia. PLoS One 2016;11:e0153675. https://doi.org/10.1371/journal.pone.015367510.1371/journal.pone.0153675
- Rudolph JL, Ramlawi B, Kuchel GA, et al. Chemokines are associated with delirium after cardiac surgery. J Gerontol A Biol Sci Med Sci 2008;63:184-189. https://doi.org/10.1093/gerona/63.2.18410.1093/gerona/63.2.184
- Weinstein SM, Poultsides L, Baaklini LR, et al. Postoperative delirium in total knee and hip arthroplasty patients: a study of perioperative modifiable risk factors. Br J Anaesth 2018;120:999-1008. https://doi.org/10.1016/j.bja.2017.12.04610.1016/j.bja.2017.12.046
- Xue P, Wu Z, Wang K, et al. Incidence and risk factors of postoperative delirium in elderly patients undergoing transurethral resection of prostate: a prospective cohort study. Neuropsychiatr Dis Treat 2016;12:137-142. https://doi.org/10.2147/NDT.S9724910.2147/NDT.S97249
- Hirsch J, Vacas S, Terrando N, et al. Perioperative cerebrospinal fluid and plasma inflammatory markers after orthopedic surgery. J Neuroinflammation 2016;13:211. https://doi.org/10.1186/s12974-016-0681-910.1186/s12974-016-0681-9
- Li YW, Li HJ, Li HJ, et al. Delirium in older patients after combined epidural-general anesthesia or general anesthesia for major surgery: a randomized trial. Anesthesiology 2021;135:218-232. https://doi.org/10.1097/ALN.000000000000383410.1097/ALN.0000000000003834
- Gatson JW, Barillas J, Hynan LS, et al. Detection of neurofilament-H in serum as a diagnostic tool to predict injury severity in patients who have suffered mild traumatic brain injury. J Neurosurg 2014;121:1232-1238. https://doi.org/10.3171/2014.7.JNS13247410.3171/2014.7.JNS132474
- Meric E, Gunduz A, Turedi S, et al. The prognostic value of neuron-specific enolase in head trauma patients. J Emerg Med 2010;38:297-301. https://doi.org/10.1016/j.jemermed.2007.11.03210.1016/j.jemermed.2007.11.032
- Vos PE, Lamers KJ, Hendriks JC, et al. Glial and neuronal proteins in serum predict outcome after severe traumatic brain injury. Neurology 2004;62:1303-1310. https://doi.org/10.1212/01.wnl.0000120550.00643.dc10.1212/01.wnl.0000120550.00643.dc
- Anderson BJ, Reilly JP, Shashaty MGS, et al. Admission plasma levels of the neuronal injury marker neuron-specific enolase are associated with mortality and delirium in sepsis. J Crit Care 2016;36:18-23. https://doi.org/10.1016/j.jcrc.2016.06.01210.1016/j.jcrc.2016.06.012
- Huang Y, Liu XQ, Wyss-Coray T, et al. Apolipoprotein E fragments present in Alzheimer’s disease brains induce neurofibrillary tangle-like intracellular inclusions in neurons. Proc Natl Acad Sci USA 2001;98:8838-8843. https://doi.org/10.1073/pnas.15125469810.1073/pnas.151254698
- van Munster BC, Korevaar JC, Zwinderman AH, et al. The association between delirium and the apolipoprotein E epsilon 4 allele: new study results and a meta-analysis. Am J Geriatr Psychiatry 2009;17:856-862. https://doi.org/10.1097/JGP.0b013e3181ab8c8410.1097/JGP.0b013e3181ab8c84
- Hu YY, He SS, Wang XC, et al. Elevated levels of phosphorylated neurofilament proteins in cerebrospinal fluid of Alzheimer disease patients. Neurosci Lett 2002;320:156-160. https://doi.org/10.1016/s0304-3940(02)00047-210.1016/s0304-3940(02)00047-2
- De Schaepdryver M, Goossens J, De Meyer S, et al. Serum neurofilament heavy chains as early marker of motor neuron degeneration. Ann Clin Transl Neurol 2019;6:1971-1979. https://doi.org/10.1002/acn3.5089010.1002/acn3.50890
- Hughes CG, Pandharipande PP, Thompson JL, et al. Endothelial activation and blood-brain barrier injury as risk factors for delirium in critically ill patients. Crit Care Med 2016;44:e809-e817. https://doi.org/10.1097/CCM.000000000000173910.1097/CCM.0000000000001739
- Perez-Martin YM, Gonzalez-Platas M, Jimenez-Sosa A, et al. Can fibrinolytic system components explain cognitive impairment in multiple sclerosis?J Neurol Sci 2017;382:66-72. https://doi.org/10.1016/j.jns.2017.09.03410.1016/j.jns.2017.09.034
- De Cicco M. The prothrombotic state in cancer: pathogenic mechanisms. Crit Rev Oncol Hematol 2004;50:187-196. https://doi.org/10.1016/j.critrevonc.2003.10.00310.1016/j.critrevonc.2003.10.003
- Chen H, Mo L, Hu H, et al. Risk factors of postoperative delirium after cardiac surgery: a meta-analysis. J Cardiothorac Surg 2021;16:13. https://doi.org/10.1186/s13019-021-01496-w10.1186/s13019-021-01496-w
- Gracie TJ, Caufield-Noll C, Wang NY, et al. The association of preoperative frailty and postoperative delirium: a meta-analysis. Anesth Analg 2021;133:314-323. https://doi.org/10.1213/ANE.000000000000560910.1213/ANE.0000000000005609
- Nazemi AK, Gowd AK, Carmouche JJ, et al. Prevention and management of postoperative delirium in elderly patients following elective spinal surgery. Clin Spine Surg 2017;30:112-119. https://doi.org/10.1097/BSD.000000000000046710.1097/BSD.0000000000000467
- Rudolph JL, Marcantonio ER. Review articles: postoperative delirium: acute change with long-term implications. Anesth Analg 2011;112:1202-1211. https://doi.org/10.1213/ANE.0b013e3182147f6d10.1213/ANE.0b013e3182147f6d
Società Italiana di Gerontologia e Geriatria (SIGG) This is an open access article distributed in accordance with the CC-BY-NC-ND (Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International) license. The article can be used by giving appropriate credit and mentioning the license, but only for non-commercial purposes and only in the original version. For further information: https://creativecommons.org/licenses/by-nc-nd/4.0/deed.en
Share and Cite
MDPI and ACS Style
Mietani, K.; Hasegawa-Moriyama, M.; Yagi, K.; Inoue, R.; Ogata, T.; Kurano, M.; Shimojo, N.; Seto, Y.; Sumitani, M.; Uchida, K. Preoperative detection of serum phosphorylated neurofilament heavy chain subunit predicts postoperative delirium: a prospective observational study. J. Gerontol. Geriatr. 2022, 70, 169-177. https://doi.org/10.36150/2499-6564-N488
AMA Style
Mietani K, Hasegawa-Moriyama M, Yagi K, Inoue R, Ogata T, Kurano M, Shimojo N, Seto Y, Sumitani M, Uchida K. Preoperative detection of serum phosphorylated neurofilament heavy chain subunit predicts postoperative delirium: a prospective observational study. Journal of Gerontology and Geriatrics. 2022; 70(3):169-177. https://doi.org/10.36150/2499-6564-N488
Chicago/Turabian StyleMietani, Kazuhito, Maiko Hasegawa-Moriyama, Kouichi Yagi, Reo Inoue, Toru Ogata, Makoto Kurano, Nobutake Shimojo, Yasuyuki Seto, Masahiko Sumitani, and Kanji Uchida. 2022. "Preoperative detection of serum phosphorylated neurofilament heavy chain subunit predicts postoperative delirium: a prospective observational study" Journal of Gerontology and Geriatrics 70, no. 3: 169-177. https://doi.org/10.36150/2499-6564-N488
APA StyleMietani, K., Hasegawa-Moriyama, M., Yagi, K., Inoue, R., Ogata, T., Kurano, M., Shimojo, N., Seto, Y., Sumitani, M., & Uchida, K. (2022). Preoperative detection of serum phosphorylated neurofilament heavy chain subunit predicts postoperative delirium: a prospective observational study. Journal of Gerontology and Geriatrics, 70(3), 169-177. https://doi.org/10.36150/2499-6564-N488
