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Does prolonged mechanical ventilation influence the prevalence of post-operative delirium in patients undergoing cardiopulmonary bypass over the span of a year?
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Guo, Y., Li, C., Mu, Y., Wu, T., & Lin, X. (2024). Incidence and associated factors of postoperative delirium in adults undergoing cardiac surgery with cardiopulmonary bypass: A prospective cohort study.
Journal of clinical nursing. https://doi.org/10.1111/jocn.17596
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Journal of Clinical Nursing, 2024; 0:1–15
https://doi.org/10.1111/jocn.17596
1 of 15
Journal of Clinical Nursing
EMPIRICAL RESEARCH QUANTITATIVE
Incidence and Associated Factors of Postoperative
Delirium in Adults Undergoing Cardiac Surgery With
Cardiopulmonary Bypass: A Prospective Cohort Study
Yating Guo1,2 | Chengyang Li3 | Yan Mu4 | Tingting Wu5 | Xiuxia Lin4
1Department of Nursing, Zhangzhou Affiliated Hospital of Fujian Medical University and Zhangzhou Municipal Hospital of Fujian Province, Zhangzhou,
Fujian, China | 2College of Nursing, Fujian University of Traditional Chinese Medicine, Fujian, China | 3School of Nursing, Fujian Medical University,
Fuzhou, Fujian, China | 4Department of Nursing, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian,
China | 5Department of Nursing, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China
Correspondence: Yan Mu (muyan06@126.com)
Received: 9 October 2024 | Revised: 6 November 2024 | Accepted: 26 November 2024
Funding: The authors received no specific funding for this work
.
Keywords: associated factors | cardiac surgery | cardiopulmonary bypass | incidence | postoperative delirium
ABSTRACT
Background: Delirium is one of the most common and serious complications after cardiac surgery with cardiopulmonary by-
pass (CPB). A comprehensive assessment of independent risk factors for postoperative delirium (POD) is essential for early de-
tection and prevention.
Aims and Objectives: To investigate the incidence and independent associated factors of POD in adults undergoing cardiac
surgery with CPB.
Design: Prospective cohort design.
Methods: A total of 203 patients were enrolled in this study from October 2022 to December 2023 in China. Richmond agitation
and sedation scale (RASS) and confusion assessment method- intensive care unit (CAM- ICU) were used for assessing delirium
symptom. This study analysed various factors for POD, including demographic, physical, psychological, social, spiritual and
environmental aspects. Using logistic regression analysis to identify the independent associated factors.
Results: A totla of 60.1% (n = 122) of patients had POD. Of these cases, 86 (70.5%) were hypoactive delirium, 4 (3.3%) were hy-
peractive delirium and 32 (26.2%) were mixed delirium. Advanced age (OR = 1.069, 95% confidence interval [CI]: 1.031–1.107;
p < 0.001), preoperative depression (OR = 1.847, 95% CI: 1.246–2.736; p = 0.002), postoperative albumin level (OR = 0.921, 95% CI:
0.851–0.997; p = 0.042) and duration of mechanical ventilation (OR > 1.000, 95% CI: 1.000–1.001; p < 0.001) were independent
predictors of POD.
Conclusions: The incidence of POD in patients undergoing cardiac surgery with CPB was high. This study identified advanced
age, preoperative depression, postoperative albumin level and duration of mechanical ventilation as significant and independent
predictors of POD.
Relevance to Clinical Practice: The study's findings highlight the urgent necessity for improved clinical vigilance and proac-
tive management strategies.
Patient or Public Contribution: No patient or public contribution.
© 2024 John Wiley & Sons Ltd.
https://doi.org/10.1111/jocn.17596
https://orcid.org/0009-0005-2263-8296
https://orcid.org/0000-0001-9282-0345
mailto:
mailto:muyan06@126.com
http://crossmark.crossref.org/dialog/?doi=10.1111%2Fjocn.17596&domain=pdf&date_stamp=2024-12-09
2 of 15 Journal of Clinical Nursing, 2024
1 | Introduction and Background
As the incidence of cardiovascular disease increases annually
(Roth et al. 2020; Aldwikat, Manias, and Nicholson 2020), an
increasing number of patients in China are undergoing cardiac
surgery, with 63.5% of these procedures being performed using
cardiopulmonary bypass (CPB) (Circulatio 2022; Aldwikat,
Manias, and Nicholson 2020). Postoperative delirium (POD) is
a common neurological complication of cardiac surgery with
CPB and is one of the main factors leading to poor prognosis
in patients undergoing cardiac surgery (Andrási et al. 2022;
Aldwikat, Manias, and Nicholson 2020). POD is defined as
delirium occurring 1–7 days after surgery (Hughes et al. 2020;
Aldwikat, Manias, and Nicholson 2020). It is an acute, fluc-
tuating and degenerative syndrome of the central nervous
system characterised by significant consciousness disorders,
cognitive changes, lack of concentration and disrupted sleep
cycles (European Delirium Association; American Delirium
Society 2014; Aldwikat, Manias, and Nicholson 2020). POD is
not only a psychological transformation but also a clinical ill-
ness characterised by pathological and physiological alterations,
with a complicated occurrence process. It is thought to be
caused by a variety of pathophysiological factors, including neu-
roinflammation theory, neurotransmitter theory, neuronal met-
abolic disorder theory, etc. (Shioiri et al. 2016; Brown et al. 2015;
Taylor et al. 2022). However, it is difficult to explain the onset
and progression of POD using a single pathophysiological cause,
and the particular pathophysiological mechanisms underlying
delirium are unknown. In the past decade, numerous studies
have described the incidence, diagnosis, evaluation criteria
and methods, clinical symptoms, pathophysiological research
and treatment of POD after cardiac surgery. The incidence and
missed diagnosis rates of POD in cardiac surgery patients are
still high, which is still an unavoidable problem for cardiac sur-
gery physicians and nurses.
Due to differences in assessment methods, study popula-
tions and types of surgery, the reported incidence of delir-
ium after CPB in adults ranges from 11.2% to 45.5% (Ibala
et al. 2021; Theologou, Giakoumidakis, and Charitos 2018a;
Shi et al. 2019; Aldwikat, Manias, and Nicholson 2020).
POD significantly prolongs patient hospitalisation and
rehabilitation time (Cheng et al. 2021; Aldwikat, Manias, and
Nicholson 2020), increases healthcare costs (Potter et al. 2019;
Aldwikat, Manias, and Nicholson 2020), reduces postopera-
tive quality of life and functional status (Labaste et al. 2020;
Aldwikat, Manias, and Nicholson 2020) and is positively cor-
related with postoperative mortality and cognitive impairment
(Brown et al. 2018; Aldwikat, Manias, and Nicholson 2020),
placing an enormous burden on both patients and society.
Approximately 50% of hospitalised patients experience de-
lirium, which is preventable (Hshieh et al. 2018). Therefore,
identifying high- risk patients for delirium is critical for de-
signing clinical nursing strategies and allocating resources
efficiently.
Although all effective delirium prevention measures may po-
tentially be routinely delivered to hospitalised patients, their
implementation is constrained by the resource conditions of
most medical institutions. On the other hand, medical staff have
few options for efficiently preventing and treating delirium in
practical practice. A meta- analysis of 15 trials (2812 partici-
pants) found that the use of nonpharmacological interventions
to reduce the incidence and duration of delirium in critically ill
patients is not supported, and even the multicomponent non-
pharmacological intervention methods recommended in the
guidelines did not yield compelling results in the meta- analysis
(Bannon et al. 2019). A multicentre, wedge- shaped, cluster ran-
domised controlled trial discovered that multicomponent non-
pharmacological interventions (including preoperative delirium
education for patients, delirium education for nurses and ward
environment intervention) did not reduce the incidence of de-
lirium in high- risk populations (Rood et al. 2021). This shows
that present delirium prevention strategies remain ineffective
and that advancements in delirium research require a fresh
approach.
Gómez Tovar and Henao Castaño (2020) proposed a new per-
spective of understanding delirium as a symptom to promote
its prevention. Brant, Beck, and Miaskowski (2010) created a
dynamic symptoms model (DSM) by comparing and evaluat-
ing the symptom management theory, discomfort symptom
theory, symptom experience model and symptom time expe-
rience model. This theory emerged during the comparison of
theories and models for addressing symptom phenomena. In
Gómez Tovar and Henao Castaño (2020) provided a thorough
analytical technique for delirium symptoms based on the DSM
model. This approach offers a new research perspective for ap-
plying the DSM model to delirium. Gómez Tovar and Henao
Castaño (2020) conducted a literature analysis based on the
DSM and determined that the four primary elements impacting
delirium are demographic; physiological; psychological, social
spiritual; and environmental.
1.1 | Demographic
Age was associated with POD incidence in patients undergo-
ing CPB cardiac surgery. Several studies have reported that
the incidence of delirium after heart surgery increases with
age (Kotfis et al. 2018; Ordóñez- Velasco and Hernández-
Leiva 2021; Chen et al. 2021; Kapoor 2020). Two retrospective
investigations indicated no significant difference between the
Summary
• What Does This Paper Contribute to the Wider Global
Clinical Community?
○ The incidence of delirium after cardiac surgery with
cardiopulmonary bypass (CPB) was 60.1% and 70.5%
of patients had hypoactive delirium.
○ Early identification of high- risk reversible risk fac-
tors for postoperative delirium (POD), including ad-
vanced age, preoperative depression and duration of
mechanical ventilation, may benefit from targeted
prevention strategies.
○ Postoperative albumin levels independently corre-
lated with the incidence of POD. We need to pay at-
tention to and increase the albumin levels of patients
undergoing cardiac surgery with CPB and enhanced
nutrition to prevent delirium.
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probability of POD occurrence and age in patients after car-
diac surgery with CPB (Salem et al. 2021, 2020). In addition,
Mufti and Hirsch (2017) discovered that male sex was an in-
dependent risk factor for POD in patients undergoing cardiac
surgery. Another large retrospective study indicated that fe-
male patients were more likely to experience POD (Aldwikat,
Manias, and Nicholson 2020). Furthermore, the patients’ de-
gree of education influenced their comprehension and compli-
ance with therapy and nursing. Consequently, the association
between demographic characteristics such as age, sex and
POD remains controversial.
1.2 | Physiological
The duration of mechanical ventilation (Shirvani, Sedighi,
and Shahzamani 2022), type of cardiac surgery (Mailhot
et al. 2019), duration of surgery, duration of CPB (Ordóñez-
Velasco and Hernández- Leiva 2021), disease severity, previ-
ous history (diabetes, atrial fibrillation, etc.) (Ordóñez- Velasco
and Hernández- Leiva 2021; Chen et al. 2021), inflammatory
markers (Ordóñez- Velasco and Hernández- Leiva 2021), mal-
nutrition (Velayati et al. 2019) and impairment of daily func-
tion (Ordóñez- Velasco and Hernández- Leiva 2021) were all
associated with the occurrence of POD in CPB cardiac sur-
gery. Biomarkers included PO2 (Spiropoulou et al. 2022),
albumin (Shin, Choi, and Na 2021a, 2021b), creatinine
(Theologou, Giakoumidakis, and Charitos 2018b), lactate
(Wang et al. 2023) and haemoglobin (Bajracharya et al. 2023)
levels.
1.3 | Psychosocial, Social and Spiritual
Several studies have reported a link between anxiety, de-
pression and POD in patients undergoing cardiac surgery
(Eshmawey et al. 2019; Falk, Eriksson, and Stenman 2020).
However, two investigations found that preoperative anxiety
was not associated with the development of POD in patients
undergoing cardiovascular surgery (Fukunaga et al. 2022;
Milisen et al. 2020). In addition, a study indicated that per-
sonality factors, such as neuroticism and conscientiousness,
might predispose patients to POD (Shin et al. 2016), whereas
Fukunaga et al. (2022) discovered that agreeableness is an in-
dependent predictor of POD. Furthermore, few studies have
examined the relationship between individual personality
qualities and POD in the Chinese population. In addition, few
studies have examined the effects of preoperative social sup-
port on POD.
1.4 | Environmental
The study findings on the effects of environmental pressure
variables on POD are not yet evident. Surgery, anaesthesia
and the intensive care unit (ICU) environment may reduce
messenger RNA levels of synaptic nuclear protein alpha,
neurotrophic receptor tyrosine kinase 1 and synaptic protein
1a in the hippocampus, resulting in attention, memory and
thinking disorders (Illendula et al. 2020). Zaal et al. (2013)
discovered that the number of delirium days in a single ICU
fell by 0.4 days when compared to a typical ICU, suggesting
that the ICU environment may influence the course of delir-
ium in patients. Arenson et al. (2013) sought to reduce POD
by modifying the CSICU atmosphere but observed no signif-
icant decrease in the overall incidence of POD in the CSICU.
Therefore, the link between environmental stressors and POD
in patients undergoing heart surgery with CPB requires addi-
tional investigation.
To address this issue, this study used the delirium DSM as a
theoretical guide to comprehensively analyse the independent
determinants of POD from multiple factors, assisting medical
staff in identifying delirium determinants, intervening early in
modifiable risk factors and providing a theoretical basis for the
precise management of delirium symptoms.
2 | Methods
This prospective cohort study investigated the prevalence of
POD and its associated factors in patients undergoing cardiac
surgery with CPB. Figure 1 illustrated the research framework.
This study was approved by the Ethics Committee of Fujian
Provincial Hospital (approval date: August 26, 2022, approval
number: K2022- 08- 032). All the patients provided written in-
formed consent. This study followed the Strengthening the
Reporting of Observational Studies in Epidemiology (STROBE)
checklist (Supporting Information S1).
2.1 | Study Design and Participants
The research subjects were patients who underwent cardiac sur-
gery with CPB at a tertiary hospital in Fujian Province between
August 2022 and October 2023.
• Inclusion criteria include (1) age ≥ 18 years; (2) heart dis-
ease (coronary atherosclerotic heart disease, valvular
heart disease, congenital heart disease, etc.) or major
vascular disease (aortic dissection, Marfan syndrome,
aortic aneurysm, etc.) who chose to undergo cardiac sur-
gery with CPB; (3) patients who needed to stay in the ICU
for ≥ 12 h after surgery; and (4) informed consent and vol-
untary participation.
• Exclusion criteria include (1) inability to undergo delir-
ium assessment due to severe neurological or psychiatric
abnormalities or a history of treatment for severe mental
disorders; (2) patients who already have severe cognitive
impairment before surgery (score < 9 on the Mini- Mental
State Examination); (3) patients who already have de-
lirium before surgery; (4) patients who already have se-
vere hearing impairment, visual abnormalities, slurred
speech, etc., and cannot communicate normally before
surgery; (5) patients who were pregnant or breastfeeding
before surgery; and (6) patients who died within 24 h after
surgery.
The patient’s preoperative, intraoperative and postoperative
nursing and pain treatment plans were carried out by the hospi-
tal’s procedure, with no modifications made to the participants.
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4 of 15 Journal of Clinical Nursing, 2024
The usual nursing plan calls for ICU nurses to do 20- to 30- min
preoperative visits to all patients the day before surgery. ICU
nurses advise patients and their families about ICU hospitalisa-
tion precautions and preparations, document patients’ particular
needs and patiently answer their inquiries. Patients undergoing
heart surgery should follow the hospital’s regular postoperative
care plan, which includes delirium assessment, pain assessment
and management, round- the- clock assistance, early activity and
exercise, psychosocial care and so on. Remifentanil, sufentanil
and dexmedetomidine are frequently used to provide pain relief
during and after surgery. Piperidine and morphine are used to
treat severe postoperative pain that cannot be alleviated by the
analgesics listed above.
2.2 | Delirium Assessment
Clinical nurses and researchers who have received standardised
training conducted face- to- face screening for delirium using the
Chinese version of the Richmond Agitation and Sedation Scale
(RASS) and the Chinese version of the Confusion Assessment
Method (CAM)- ICU scale 1 day before surgery. From postoper-
ative Days 1–7, clinical nurses and researchers used the RASS
and CAM- ICU scales to assess delirium face- to- face for all study
subjects, regardless of whether they were in the ICU or ward.
To capture the phenomenon of delirium ‘sunset’ (usually occur-
ring at sunset or dusk), avoid the assessment process affecting
patients’ rest and nighttime sleep, as well as facilitating nurses’
workflow, this study chose to conduct delirium assessment on
patients during two time periods: 08:00–10:00 and 18:00–20:00
every day.
This study used the CAM- ICU and RASS measures to assess de-
lirium subtypes. First, CAM- ICU was utilised to make a qualita-
tive diagnosis of delirium, followed by RASS for categorisation
and judgement. When the RASS score was −3 to 0, it indicated
hypoactive delirium. When the RASS score was 1–4, it was con-
sidered hyperactive delirium. Mixed delirium was defined as a
RASS score that varied between positive and negative values.
2.3 | Selections of Variables
The content of the collected data was established in accordance
with the research objectives and the comprehensiveness of
clinical data collection. General information and clinical data
for all patients were extracted from the hospital information
system. All data were collected prospectively. The assessment
FIGURE 1 | The framework for the study of POD in patients after cardiac surgery with CPB based on the delirium dynamic symptom model
(DSM).
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scales were administered in person by researchers 1 day prior
to surgery, allowing patients to complete questionnaires or
respond to inquiries individually. Based on the patients’ re-
sponses, researchers assisted them in completing each item on
the questionnaires.
2.3.1 | Demographic- Related Factors
The variables collected were as follows: age, gender (male/fe-
male), body mass index (BMI, kg/m2), education level (illiter-
acy/primary school/Junior middle school/high or polytechnic
school/university and above), marital status (married/single/di-
vorced/widowed), medical insurance (new rural medical insur-
ance/basic medical insurance for urban residents/basic medical
insurance for urban employees/commercial insurance/none),
smoking and drinking history (yes/no).
2.3.2 | Physiological- Related Factors
The variables collected were as follows: (1) general data: medical
history, including a history of hypertension, diabetes and cere-
brovascular disease. (2) Clinical data: preoperative data included
liver and kidney function tests and electrocardiogram rhythm.
Intraoperative data encompassed the type of surgery, duration
of surgery, duration of CPB and whether deep hypothermic cir-
culatory arrest was performed. Postoperative data included the
severity of the disease, duration of mechanical ventilation and
the first postoperative venous blood transfusion, which was as-
sessed through albumin level, glutamic- pyruvic transaminase,
glutamic oxaloacetic transaminase, creatinine, serum lactate
dehydrogenase (LDH) and haemoglobin level. Additionally,
the first arterial blood transfusion after surgery was evaluated
based on the lactate level and oxygenation index, along with the
Acute Physiology and Chronic Health Evaluation (APACHE) II
score. Furthermore, this study assessed patients’ preoperative
sleep quality using the Pittsburgh Sleep Quality Index (PSQI)
and evaluated preoperative physical functioning status through
the Activities of Daily Living (ADL) scale and the Medical
Outcomes Study Short Form- 12 (SF- 12) assessment tools.
The PSQI scale has a total score range of 0–21, with higher values
indicating poorer sleep quality. A score greater than 5 implies
clinically substantial discomfort or inadequate sleep. The ADL
scale has a total score range of 14–56 points, with higher scores
indicating worse daily living abilities. A total score of 14 shows
that ADL is normal; 15–21 indicates mild impairment of ADL;
and > 22 indicates significant impairment of ADL. The SF- 12
scale has a total score range of 0–100 points, with higher scores
indicating greater health- related quality of life for patients.
2.3.3 | Psychological- ,
Social- and Spiritual- Related Factors
The variables collected in this study included the patient’s preop-
erative cognitive function, assessed using the Mini- Mental State
Examination (MMSE); preoperative anxiety and depression lev-
els, measured with the Hospital Anxiety and Depression Scale
(HADS); preoperative social support levels, evaluated through
the Social Support Rating Scale (SSRS); and preoperative per-
sonality types, determined using the Ten- Item Personality
Inventory in China (TIPI- C).
The overall score on the MMSE scale is 30 points. A score of
27–30 suggests normal cognition, whereas a score below 27
shows cognitive impairment (> 21 indicates mild cognitive
impairment, 10–20 indicates moderate cognitive impairment
and < 9 indicates severe cognitive impairment). The HADS scale
consists of two subscales: anxiety and depression, each having
a total score range of 0–21 points. A score of 0–7 indicates as-
ymptomatic, 8–10 indicates probable anxiety or depression and
11–21 indicates confirmed anxiety or depression. The entire
score range on the SSRS scale is 12–66 points: 22 is designated
as low support, 23–44 as broad support and 45–66 as high sup-
port. The TIPI- C scale has five dimensions: agreeableness (A),
conscientiousness (C), emotional stability (ES), extraversion (E)
and openness (O). This measure has a Likert 7- point scale rang-
ing from 1 (strongly disagree) to 7 (strongly agree).
2.3.4 | Environmental- Related Factors
If the patient were moved from the ICU to the general ward
within 7 days following surgery, the researcher would conduct
an ICU Environmental Stressor Scale (ICUES) scale evaluation
with the study subjects on the day of transfer. If the patient did
not remove the endotracheal tube within 7 days following sur-
gery, the researchers would evaluate the study participants in
person after the tube had been removed. This scale’s total score
runs from 42 to 168, with higher scores indicating more strain
on patients in the ICU setting.
2.4 | Statistical Analysis
The Kruskal–Wallis H test and the Mann–Whitney U test were
employed for the analysis of quantitative data. Qualitative data
were assessed using either the Chi- square test or Fisher’s exact
probability method. Statistical analyses were performed utilis-
ing SPSS version 23.0 software. Descriptive statistics, including
frequency, rate and composition ratio, were applied to charac-
terise the qualitative data. Quantitative data are presented as
mean ± standard deviation (x ± s) or median (quartiles) (P50
(P25, P75)), contingent upon the adherence to a normal distri-
bution. Initially, a univariate analysis was conducted with de-
lirium and its various subtypes serving as dependent variables,
while each risk factor was treated as an independent variable.
The values of the independent variables are defined as follows:
continuous variables are input according to their original scale
and categorical variables are coded as no = 0 and yes = 1. In the
one- way analysis, if the quantitative variables satisfy the crite-
ria for normal distribution and homogeneity of variance, one-
way analysis of variance (ANOVA) or t- tests are employed. In
instances where the data do not conform to the assumptions of
normal distribution and homogeneity of variance, it is advisable
to conduct nonparametric diagnostic analyses on the statistically
significant risk factors individually. Through multicollinearity
analysis, a total of 20 variables may be incorporated into a bi-
nary logistic regression analysis, allowing for the calculation of
their odds ratios (ORs) and 95% confidence intervals (95% CIs).
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6 of 15 Journal of Clinical Nursing, 2024
This approach facilitates a more nuanced examination of the
adjusted effects of various risk factors on the incidence of delir-
ium following CPB during cardiac surgery. All statistical tests
are considered significant at a threshold of p < 0.05 (two- tailed).
3 | Results
3.1 | The Incidence of
POD
This study involved the screening of 273 patients scheduled for
cardiac surgery with CPB. Of these, 70 patients were excluded
for failing to meet the established inclusion and exclusion cri-
teria. Consequently, a total of 203 patients were included in the
analysis, and the process of inclusion and exclusion of study sub-
jects is illustrated in Figure 2. All 203 patients who participated
in this study were monitored for 1 week postsurgery. Within
this follow- up period, 122 patients exhibited signs of delirium,
resulting in an incidence rate of 60.1%. Among those affected,
86 patients (70.5%) experienced hypoactive delirium, 4 patients
(3.3%) exhibited hyperactive delirium and 32 patients (26.2%)
presented with mixed delirium.
3.2 | Differences Between Patients With
and Without POD
3.2.1 | Demographic- Related Factors
The average age of 203 patients receiving CPB cardiac surgery
was 59.0 (52.0, 66.0), with a range of 20–80 years. 87 (42.9%)
of them were older than 60. The influence of age, gender and
education on the development of POD in adults following car-
diac surgery with CPB was confirmed through our univariate
analysis (p < 0.05). Conversely, marital status, medical insur- ance, BMI and history of smoking and/or alcohol consumption were not identified as significant risk factors for delirium in our study (p > 0.05). For further details, please refer to Table 2.
3.2.2 | Physiological- Related Factors
Univariate analysis indicated that 14 physiological factors were
significantly associated with POD (p < 0.05). These factors in-
cluded a history of diabetes, preoperative electrocardiogram
(ECG) rhythm, preoperative ADL, preoperative quality of life,
type of surgery, duration of surgery, duration of CPB, postop-
erative albumin levels, postoperative serum glutamic oxaloace-
tic transaminase, postoperative blood lactate dehydrogenase,
postoperative haemoglobin levels, postoperative lactate lev-
els, APACHE score and duration of mechanical ventilation.
Conversely, no statistically significant differences (p > 0.05)
were observed in preoperative liver and kidney function, history
of hypertension or history of cerebrovascular events between
the two patient groups. See Table 2 for details.
3.2.3 | Psychological- ,
Social- and Spiritual- Related Factors
The findings from the univariate analysis indicated that there
were statistically significant differences in preoperative cogni-
tive function, preoperative anxiety and preoperative depression
levels between the POD group and the non- POD, as illustrated
in Table 2. Conversely, preoperative personality traits and pre-
operative social support did not demonstrate a statistically sig-
nificant association with the incidence or prevalence of POD in
the univariate analysis (p > 0.05).
FIGURE 2 | The flowchart of the study.
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7 of 15
3.2.4 | Environmental- Related Factors
The scores on the ICUES scale for the POD and the non- POD
were 93 and 91, respectively. However, univariate analysis re-
vealed no statistically significant difference in ICU environmen-
tal stress levels between the two groups (p > 0.05).
3.3 | Independent Factors Influencing POD in
Cardiac Surgery Patients With CPB
We selected 20 variables with statistically significant find-
ings from the univariate analysis (as shown in Table 1) and
conducted a collinearity diagnostic analysis as a preliminary
step. The F- value of the model was 4.205, with a significance
level of p < 0.001 for the independent variable. The variance
inflation factor (VIF) for these 20 variables was less than 3,
and the tolerance (Tol) was greater than 0.1, indicating the
absence of significant multicollinearity among the indepen-
dent variables (refer to Table A1). Additionally, delirium was
designated as the dependent variable in a binary logistic re-
gression analysis involving the 20 statistically relevant factors
identified in the univariate study. A comprehensive list of
variable assignments is provided in Table A2. The results in-
dicated that the postoperative albumin level (OR = 0.921, 95%
CI: 0.851–0.997; p = 0.042) served as an independent protec-
tive factor for POD in adult patients undergoing cardiac sur-
gery with CPB. Conversely, advanced age (OR = 1.069, 95% CI:
1.031–1.107; p < 0.001), preoperative depression (OR = 1.847,
95% CI: 1.246–2.736; p = 0.002) and the duration of mechanical
ventilation (OR > 1.000, 95% CI: 1.000–1.001; p < 0.001) were
identified as independent risk factors for POD in this patient
population (as shown in Table 2). The Cox and Snell R2 and
Nagelkerke's R2 for this regression equation were 0.327 and
0.442, respectively. The Hosmer–Lemeshow test yielded a sig-
nificant p value > 0.05, suggesting that the model’s predicted
probability of POD in cardiac surgery patients closely approxi-
mated the actual values observed in this study. Consequently,
the model was deemed to fit the data well, demonstrating an
excellent fitting effect.
4 | Discussion
POD represents a significant and prevalent complication
among adult patients undergoing cardiac surgery with CPB,
primarily manifesting as neurological dysfunction. The find-
ings of this study indicated that 122 patients who underwent
CPB cardiac surgery experienced delirium within 7 days
postoperatively, resulting in an incidence rate of 60.1%. This
rate was comparable to, yet notably higher than, the reported
incidence rates of 11.2%–45.5% in the recent literature (Shi
et al. 2019; Theologou, Giakoumidakis, and Charitos 2018a;
Ibala et al. 2021). The observed discrepancies may be at-
tributed to variations in inclusion and exclusion criteria,
baseline characteristics of the patients, the type of surgery,
cardioplegia type, CPB time, assessment tools for delirium,
timing and frequency of assessments, as well as geographical
differences in the populations studied. This investigation spe-
cifically included patients who were admitted to the ICU for a
minimum of 12 h following surgery. The delirium observation
period for all participants extended to 7 days postsurgery, with
evaluations conducted bi- daily. Prior to the implementation
of the study, raters underwent systematic training focused
on delirium- related knowledge to ensure the reliability of the
assessment outcomes. Notably, among the patients diagnosed
with POD in this study, those exhibiting hypoactive delir-
ium constituted the largest subgroup, accounting for 70.5%.
Hypoactive delirium was characterised by reduced alertness
and a lack of verbal communication, and was frequently
observed in elderly populations, which aligned with the av-
erage age of delirious participants in this study, recorded at
63.0 years (range: 55.3–68.8 years). The duration of delirium
among patients within the 7- day postoperative period varied
from 0 to 168 h, with a median duration of 12 h. The prolonged
duration of delirium may be influenced by factors such as the
type of surgical procedure, length of surgery, surgical tech-
niques employed, duration of CPB as well as the specific types
of delirium and their triggering factors. The elevated inci-
dence of delirium and its potentially severe ramifications war-
rant significant attention from clinical medical personnel. It is
imperative that healthcare providers enhance their vigilance
in monitoring and managing delirium symptoms, employ
standardised assessment tools for delirium and improve their
competencies in recognising and addressing these symptoms
effectively.
The findings of this study indicated that age served as the most
significant and immutable predictor of POD in patients under-
going cardiac surgery with CPB. In contrast, factors such as
gender, educational background and histories of smoking and
alcohol consumption did not demonstrate a statistically sig-
nificant effect on the incidence and progression of delirium
following cardiac surgery. Specifically, the risk of developing
POD increased by a factor of 1.069 for each additional year of
patient age, a finding that was consistent with previous research
(Kupiec et al. 2020; Andrási et al. 2022; Lu et al. 2024). Prior
studies have consistently identified age as an independent risk
factor for predicting POD in this patient population (Kupiec
et al. 2020, Andrási et al. 2022, Lu et al. 2024). This correla-
tion may be attributed to the fact that, as individuals age, the
presence of chronic conditions such as atherosclerosis can lead
to diminished cardiac reserve and reduced cerebral blood flow
perfusion. Consequently, this decline in physiological capac-
ity might result in decreased tolerance to surgical trauma and
anaesthesia, thereby precipitating the onset and progression of
POD (Chan and Aneman 2019).
This study found that patients undergoing cardiac surgery with
prolonged mechanical ventilation had a higher risk of devel-
oping POD, which is similar to the results of a previous study
(Shirvani, Sedighi, and Shahzamani 2022). Mechanical ven-
tilation support is a routine supportive treatment for cardiac
surgery patients admitted to the ICU after surgery. However,
due to its invasive nature and significant limitations on pa-
tient activity, it can easily cause ventilator- associated lung in-
jury, leading to pulmonary and even systemic inflammatory
reactions. Inflammatory mediators can penetrate the blood–
brain barrier and cause inflammatory damage and neuronal
apoptosis (Breitbart et al. 1997), leading to nerve damage and
increasing the likelihood of POD occurrence. Therefore, to
minimise the risk of postoperative neurological complications
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TABLE 1 | Univariate analysis of factors for POD (n = 203)
(
N(%)∕P50
(
P25, P75
)
∕x ± s
)
.
Variable
POD
Statistic pYes (n = 122) No (n = 81)
Age 63.0 (55.3, 68.8) 55 (49, 59.8) −5.157a < 0.001
Gender
Male 54 (44.3) 48 (67.6) 4.380b 0.036
Female 68 (55.7) 33 (32.4)
Marital status
Married 119 (97.5) 77 (96.6) 1.317b 0.579
Single 2 (1.6) 3 (2.5)
Divorced 1 (0.8) 1 (1.0)
Widowed 0 (0.0) 0 (0.0)
Education
Illiteracy 35 (28.7) 16 (19.8) −2.533a 0.011
Primary school 38 (31.1) 16 (19.8)
Junior middle school 32 (26.2) 32 (39.5)
High or polytechnic school 10 (8.2) 13 (16.0)
University and above 6 (4.9) 4 (4.9)
Medical insurance
New rural medical insurance 84 (68.9) 50 (61.7) 2.124b 0.730
Basic medical insurance for urban residents 12 (9.8) 10 (12.3)
Basic medical insurance for urban employees 23 (18.9) 17 (21.0)
Commercial insurance 1 (0.8) 1 (1.2)
None 2 (1.6) 3 (3.7)
BMI (kg/m2) 23.0 (20.8, 25.7) 23.5 ± 4.1 −1.148a 0.251
Smoking
Yes 37 (30.3) 33 (40.7) 2.336b 0.126
No 85 (69.7) 48 (59.3)
Alcohol
Yes 40 (32.8) 29 (35.8) 0.197b 0.657
No 82 (67.2) 52 (64.2)
History of diabetes
Yes 20 (16.4) 5 (6.2) 4.709b 0.030
No 102 (83.6) 76 (93.8)
History of hypertension
Yes 40 (32.8) 21 (25.9) 1.090b 0.296
No 82 (67.2) 60 (74.1)
History of cerebrovascular diseases
Yes 10 (8.2) 7 (8.6) 0.013b 0.911
No 112 (91.8) 74 (91.4)
(Continues)
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Variable
POD
Statistic pYes (n = 122) No (n = 81)
Preoperative electrocardiogram rhythm
SR 75 (61.5) 60 (74.1) 18.438b < 0.001
Af 46 (37.7) 14 (17.3)
AF 0 (0.0) 4 (4.9)
Af + AF 0 (0.0) 1 (1.2)
Accelerated atrial autonomous rhythm 0 (0.0) 2 (2.5)
Pacing rhythm 1 (0.8) 0 (0.0)
First preoperative venous blood transfusion
ALT (U/L) 20.0 (13.3, 31.0) 20.0 (12.0, 29.3) −0.630a 0.529
AST(U/L) 22.0 (17.0, 27.0) 20.0 (15.0, 26.0) −1.859a 0.063
Cr (umol/L) 71.5 (58.3, 85.0) 71.5 (58.3 86.3) −0.122a 0.903
Preoperative sleep quality
≤ 5: sleep well 13 (10.7) 11 (13.6) −0.630a 0.528
> 5: clinically significant distress or poor sleep 109 (89.3) 70 (86.4)
Preoperative activities of daily living
14: normal 74 (60.7) 64 (79.0) −2.754a 0.006
15–21: mild damage 20 (16.4) 8 (9.9)
> 21: severe damage 28 (23.0) 9 (11.1)
Preoperative cognitive function
27–30: normal 44 (36.1) 44 (54.3) −2.992a 0.003
21–26: mild cognitive impairment 44 (36.1) 27 (33.3)
10–20: moderate cognitive impairment 34 (27.9) 10 (12.3)
< 9: severe cognitive impairment 0 (0.0) 0 (0.0)
Preoperative anxiety
0~7: asymptomatic 60 (49.2) 55 (67.9) −2.767a 0.006
8~10: suspected anxiety 29 (23.8) 15 (18.5)
11~21: existence of anxiety 33 (27.0) 11 (13.6)
Preoperative depression
0~7: asymptomatic 39 (32.0) 51 (63.0) −4.350a < 0.001
8~10: suspected depression 23 (18.9) 11 (13.6)
11~21: existence of depression 60 (49.2) 19 (23.5)
Preoperative personality traits
Extraversion score 8 (8, 8) 8 (7, 9) −0.108a 0.914
Agreeableness score 8 (8, 9) 8 (8, 9) −0.239a 0.811
Responsibility score 8 (7, 8) 8 (7, 8) −1.034a 0.301
Emotional stability score 8 (8, 9) 8 (8, 9) −0.677a 0.498
Openness score 8 (7, 8) 8 (7, 9) −0.657a 0.511
(Continues)
TABLE 1 | (Continued)
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10 of 15 Journal of Clinical Nursing, 2024
in patients, it is recommended that medical staff improve the
efficiency of team communication, strengthen teamwork, ac-
curately evaluate the timing of endotracheal intubation and
extubation and shorten postoperative mechanical ventilation
time as much as possible, thereby reducing the incidence
of POD.
Variable
POD
Statistic pYes (n = 122) No (n = 81)
Preoperative social support
23~44: general support 115 (94.3) 74 (91.4) −0.798a 0.425
45~66: high support 7 (5.7) 7 (8.6)
Preoperative quality of life 80.9 ± 15.9 85.9 ± 14.1 2.305c 0.022
Surgical type
Valve replacement/shaping surgery 95 (77.9) 66 (81.5) 22.132b < 0.001
CABG 5 (4.1) 1 (1.2)
Valve replacement/shaping surgery + CABG 9 (7.4) 1 (1.2)
Large vessel surgery 2 (1.6) 2 (2.5)
Cardiac tumour resection surgery 0 (0.0) 9 (11.1)
Large vessel surgery + Valve replacement/shaping
surgery
9 (7.4) 2 (2.5)
Large vessel surgery + CABG 2 (1.6) 0 (0.0)
Surgical duration (min) 310 (266.3, 407.5) 295 (242.5, 350) −2.040a 0.041
Duration of CPB (min) 179.5 (137.3, 225.8) 156.5 (124.0, 203.0) −2.387a 0.017
Deep hypothermic circulatory arrest
Yes 3 (2.5) 2 (2.5) 0.000b 1.000
No 119 (97.5) 79 (97.5)
The first postoperative venous blood transfusion
ALB (g/L) 32.0 (28.0, 35.0) 33.5 (31.0, 36.0) −3.231a 0.001
ALT (U/L) 23.5 (18.0, 34.0) 24.5 (17, 30) −0.692a 0.489
AST(U/L) 89.5 (56.3, 133.3) 72.0 (51, 109) −2.241a 0.025
Cr (μmol/L) 84.0 (69.3, 105.8) 75.0 (68.0, 100.5) −1.641a 0.101
LDH (U/L) 532.5 (404.0, 636.8) 463.0 (344.5, 582.5) −2.555a 0.011
Hb (g/L) 105.04 ± 18.13 111.43 ± 16.14 −2.936c 0.004
The first arterial blood transfusion after surgery
Oxygenation index (mmHg) 298.8 (239.5, 423.8) 335.0 (252.5, 432.5) −0.717a 0.473
Lac (mmHg) 6.7 ± 3.5 5.7 ± 2.9 −2.178c 0.031
APACHE 28.5 (25.0, 32.0) 25.0 (22.0, 28.8) −3.674a < 0.001
During of mechanical ventilation (min) 2652.5 (1246.3,
6717.5)
1235.0 (1128.8,
2526.3)
−5.106a < 0.001
ICUESS score 93.0 (81.0, 107.0) 91.0 (79.5, 109.0) −0.388a 0.698
Abbreviations: Af, atrial fibrillation; AF, atrial flutter; ALB, Albumin; ALT, alanine aminotransferase; APACHE II, Association of Peoria Area Christian Home
Educators II; AST, aspartate transaminase; BMI, body mass index; CABG, coronary artery bypass surgery; CPB, cardiopulmonary bypass; Cr, creatinine; Hb,
haemoglobin; ICUESS, Intensive Care Unite Environmental Stressor Scale; Lac, lactic acid; LDH, lactic dehydrogenase; POD, postoperative delirium; SR, sinus
rhythm.
aThe result calculated using Mann–Whitney U test is the Z- value.
bThe results calculated using Chi square test show a statistical value of χ2.
cThe result calculated using a two sample t- test is the t- value.
TABLE 1 | (Continued)
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In addition, the results of this study showed that albumin is
a protective factor against POD in patients undergoing CPB
cardiac surgery, which is similar to previous studies (Shin,
Choi, and Na 2021a, 2021b; Cereghetti et al. 2017). Thus, al-
bumin may be a helpful and straightforward biomarker for
predicting POD in patients following cardiac surgery with
CPB. However, previous studies (Shin, Choi, and Na 2021a,
2021b; Cereghetti et al. 2017) only clarified when the preop-
erative albumin level can predict delirium after cardiac sur-
gery. In this study, it was found that the patient’s first venous
albumin level after surgery is a protective factor for delirium
in patients undergoing CPB cardiac surgery. The higher the
patient’s first venous albumin level after surgery, the lower
the risk of POD occurrence. This may provide some basis for
precise intervention timing of delirium. However, the study’s
findings did not establish that early postoperative nutritional
assistance or other nutritional support strategies might en-
hance blood albumin levels in heart surgery patients, lower-
ing the risk of delirium. Low serum albumin levels were often
related to malnutrition. However, according to one research
[48], calorie and protein nutritional supplementation did not
affect blood albumin levels. This was because nonnutritional
variables controlled hepatic protein production, and in acute
illnesses, the drop in serum albumin levels might be due to
inflammatory responses rather than nutritional conditions.
There was no convincing indication that increasing food in-
take after managing inflammation would increase blood al-
bumin levels. As a result, the pathophysiological mechanism
linking albumin and delirium occurrence requires further in-
vestigation, as well as additional studies to better understand
whether nutritional support and when to use it, can increase
albumin levels and reduce delirium incidence in patients who
underwent cardiac surgery.
In our study, we used the HADS- D to screen for preoperative
depression in patients undergoing cardiac surgery with CPB.
Multivariate regression analysis revealed that patients with pre-
existing depression had a 1.847 times higher risk of developing
POD compared to those no or suspected depressive symptoms.
This is consistent with the findings of Segernas et al. (2022) and
Falk et al. (2022). This indicates the need for preoperative de-
pression screening for patients undergoing cardiac surgery with
CPB. It suggests that clinical medical staff can use standardised
depression assessment tools to identify high- risk populations
for POD at an early stage and provide patients with comprehen-
sive and regular preoperative education and postrehabilitation-
related information as early as possible. This can help them
reduce negative emotions and enhance their confidence in
disease recovery in unfamiliar environments and/or delirium
states. Specific interventions include guiding patients to watch
delirium education videos before surgery (Wheeler et al. 2023).
However, a systematic review (Nan, Yanqiu, and Lan 2022) have
found no statistically significant association between preopera-
tive depression and POD in adult cardiac surgery. This may be
because different studies used different research tools, and the
definition and classification of depression varies among different
research tools. At present, the pathophysiological mechanism
between depression and POD is not clear. Possible mecha-
nisms include decreased serotonin activity, increased cortisol
concentration and disturbed glucocorticoid levels in the brain,
but the causal relationship is still unclear (Fatehi Hassanabad
et al. 2021). Therefore, further basic and multicentre clinical
studies are recommended to confirm the association between
preoperative depression and POD in patients undergoing car-
diac surgery with CPB.
5 | Limitations
The limitations of this study include constraints related to
time, manpower, material resources and finances. The survey
was conducted at only one hospital, which limited the repre-
sentativeness of the sample size. The research team plans to
conduct multicentre studies in the future. Additionally, our
study followed up on patients’ delirium symptoms for only
7 days postsurgery, despite the volatile nature of these symp-
toms. Consequently, the incidence rate of POD measured
in this study may not accurately reflect the true incidence.
However, each patient was evaluated twice daily to minimise
the rates of missed diagnoses of POD. Furthermore, this study
solely employed the PSQI scale to evaluate patients’ sleep be-
fore surgery. This study did not assess patients’ sleep quality
following surgery since tracheal intubation, confusion and
other factors may make it difficult for them to communicate
their genuine sleep quality verbally. Future studies can use
more advanced tools, like as polysomnography, to investi-
gate the association between postoperative sleep quality and
POD in patients. Furthermore, while the occurrence and pro-
gression of delirium are influenced by multiple factors, this
study identified only one biomarker associated with delirium
symptoms. Future research could employ omics methods to
explore multiple biomarkers of delirium, aiming to identify
additional potential targets for the precise treatment of delir-
ium symptoms.
TABLE 2 | Binary logistic regression analysis of factors for POD (N = 203).
Variables β BE Wald χ2 p OR
95%CI
Lower Upper
Age 0.066 0.018 13.503 < 0.001 1.069 1.031 1.107
Preoperative existence of depression 0.613 0.201 9.349 0.002 1.847 1.246 2.736
Postoperative albumin level (g/L) −0.082 0.04 4.136 0.042 0.921 0.851 0.997
During of mechanical ventilation
(min)
0.000 0.000 16.707 < 0.001 > 1.000 1.000 1.001
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12 of 15 Journal of Clinical Nursing, 2024
6 | Conclusions
The incidence of delirium following cardiac surgery with CPB
was notably high, necessitating increased attention from clin-
ical medical staff. Factors such as advanced age, preoperative
depression, postoperative albumin levels and duration of me-
chanical ventilation could serve as predictors for the occurrence
of delirium in these patients. We recommend implementing pre-
ventive and personalised interventions that focus on assessing
delirium and identifying risk factors, facilitating early extuba-
tion, providing psychological assistance and preventing delir-
ium. Future study is needed to investigate the mechanism of
postoperative albumin levels and delirium in patients following
cardiac surgery with CPB, to develop more precise intervention
options.
7 | Relevance to Clinical Practice
This study has significant implications for understanding the
specific manifestation of delirium symptoms in patients after
cardiac surgery involving CPB. For the first time, our research
demonstrates a notable incidence of POD in Chinese patients
following cardiac surgery with CPB, along with a correlation to
postoperative albumin levels. Our findings emphasise the ne-
cessity for medical staff to actively assess and identify delirium
symptoms after cardiac surgery with CPB, as well as to recog-
nise high- risk patients, to improve clinical outcomes.
Author Contributions
Yating Guo was involved in conceptualisation, data curation, for-
mal analysis, methodology, investigation, project administra-
tion, resources, software, visualisation and writing- original draft.
Chengyang Li was involved in writing- review and editing. Yan Mu
was involved in resources and supervision. Tingting Wu was involved
in writing- review and editing. Xiuxia Lin was involved in resources.
The authors have disclosed that they do not have any potential con-
flicts of interest.
Acknowledgements
The authors thank the study participants as well as Fujian Provincial
Hospital for providing the source of the study participants.
Conflicts of Interest
The authors declare no conflicts of interest.
Data Availability Statement
The data that support the findings of this study are available from the
corresponding author upon reasonable request.
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Supporting Information
Additional supporting information can be found online in the
Supporting Information section.
Appendix A
TABLE A1 | Collinearity diagnosis.
Variable Tolerance (Tol) Variance inflation factor (VIF)
Age 0.672 1.487
Gender 0.763 1.311
Education 0.579 1.726
Previous diabetes 0.875 1.142
Preoperative electrocardiogram rhythm 0.827 1.209
Preoperative activities of daily living 0.710 1.409
Preoperative cognitive function 0.458 2.182
Preoperative anxiety 0.539 1.857
Preoperative depression 0.409 2.443
Preoperative quality of life 0.503 1.986
Surgical type 0.879 1.138
Surgical duration (min) 0.386 2.589
Duration of CPB (min) 0.565 1.771
The first postoperative venous blood transfusion
ALB (g/L) 0.647 1.545
AST (U/L) 0.635 1.575
LDH (U/L) 0.529 1.891
Hb (g/L) 0.636 1.572
The first arterial blood transfusion after surgery
Lac (mmHg) 0.729 1.371
APACHE 0.728 1.374
During of mechanical ventilation (min) 0.565 1.771
Abbreviations: ALB, albumin; AST, aspartate transaminase; CPB, cardiopulmonary bypass; Hb, hemoglobin; Lac, lactic acid; LDH, lactic dehydrogenase.
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TABLE A2 | Variable assignment and meaning.
Variable meaning Assignment
Age Continuous variable
Gender 0 = Female; 1 = Male
Education 0 = Illiteracy; 1 = Primary school; 2 = Middle school; 3 = High school/
Vocational school; 4 = University or above
Previous diabetes 0 = No; 1 = Yes
Preoperative AF 0 = No; 1 = Yes
Preoperative activities of daily living 0 = Normal; 1 = Mild damage; 2 = Severe damage
Preoperative cognitive function 0 = Normal; 1 = mild cognitive impairment; 2 = Moderate cognitive
impairment; 3 = Severe cognitive impairment
Preoperative anxiety 0 = Asymptomatic; 1 = Suspected anxiety; 2 = Existence of anxiety
Preoperative depression 0 = Asymptomatic; 1 = Suspected depression; 2 = Existence of depression
Preoperative quality of life Continuous variable
Surgical type 0 = Simple surgery; 1 = Mixed surgery or aortic surgery
Surgical duration (min) Continuous variable
Duration of CPB (min) Continuous variable
The first postoperative venous blood transfusion
ALB (g/L) Continuous variable
AST (U/L) Continuous variable
LDH (U/L) Continuous variable
Hb (g/L) Continuous variable
The first arterial blood transfusion after surgery
Lac (mmHg) Continuous variable
APACHE Continuous variable
During of mechanical ventilation (min) Continuous variable
Abbreviations: AF, atrial fibrillation; ALB, albumin; AST, aspartate transaminase; CPB, cardiopulmonary bypass; Hb, hemoglobin; Lac, lactic acid; LDH, lactic
dehydrogenase.
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- Incidence and Associated Factors of Postoperative Delirium in Adults Undergoing Cardiac Surgery With Cardiopulmonary Bypass: A Prospective Cohort Study
ABSTRACT
1 | Introduction and Background
1.1 | Demographic
1.2 | Physiological
1.3 | Psychosocial, Social and Spiritual
1.4 | Environmental
2 | Methods
2.1 | Study Design and Participants
2.2 | Delirium Assessment
2.3 | Selections of Variables
2.3.1 | Demographic-Related Factors
2.3.2 | Physiological-Related Factors
2.3.3 | Psychological-, Social- and Spiritual-Related Factors
2.3.4 | Environmental-Related Factors
2.4 | Statistical Analysis
3 | Results
3.1 | The Incidence of POD
3.2 | Differences Between Patients With and Without POD
3.2.1 | Demographic-Related Factors
3.2.2 | Physiological-Related Factors
3.2.3 | Psychological-, Social- and Spiritual-Related Factors
3.2.4 | Environmental-Related Factors
3.3 | Independent Factors Influencing POD in Cardiac Surgery Patients With CPB
4 | Discussion
5 | Limitations
6 | Conclusions
7 | Relevance to Clinical Practice
Author Contributions
Acknowledgements
Conflicts of Interest
Data Availability Statement
References
Appendix A
