The effectiveness of postoperative delirium prevention, diagnosis, and intervention protocol in patients monitored in the intensive care unit after cardiac surgery: a quasi-experimental study
The incidence of delirium is high in the intensive care unit (ICU) after cardiac surgery. The development of evidence-based care protocols for delirium management and training of nurses in this regard can ensure effective management of delirium. This quasi-experimental study aimed to assess the effectiveness of a postoperative delirium prevention, diagnosis, and intervention protocol in patients undergoing monitoring in the ICU after cardiac surgery.
Methods
This study included 64 patients who underwent cardiac surgery and met the inclusion criteria, along with 14 nurses working in the ICU. Patients were divided into control (n = 32) and intervention (n = 32) groups. The study comprised three phases: determining the incidence of delirium in the control group and the delirium diagnosis status of the nurses; providing training to nurses on postoperative delirium prevention, diagnosis and intervention protocol; implementing a preliminary study of the protocol; and finally, implementing the protocol in the intervention group. Statistical significance was set at p < 0.05.
Results
While there was no significant agreement in delirium diagnosis between researcher and nurses in the control group (kappa: 0.207) (p > 0.05), significant agreement was observed in the intervention group (kappa: 1.00) (p < 0.001). The delirium diagnosis rate of the nurses was 14.3% in the control group and 100% in the intervention group, which was a significant difference. The incidence of delirium was 21.9% in the control group and 9.4% in the intervention group, although the difference was not significant.
Conclusion
Postoperative delirium prevention, diagnosis, and intervention protocol effectively enhance delirium diagnosis compliance among researchers and nurses and improve the accuracy of delirium diagnosis among postcardiac surgery ICU patients. The implementation of this protocol is recommended for delirium management in such patients.
Trial registration
This study was retrospectively registered at Clinicaltrials.gov on 19.02.2024 (Clinical Trials ID: NCT06268119).
Hinweise
Institution where the study was conducted: Antalya Training and Research Hospital, Türkiye.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Abkürzungen
APACHE II
Acute Physiology and Chronic Health Evaluation
CAM-ICU
Confusion Assessment method for the ICU
GCS
Glasgow Coma Scale
ICU
Intensive Care Unit
RASS
Richmond Agitation and Sedation Scale
Background
Delirium is a condition characterized by impaired attention, impaired awareness, and cognitive impairment [1]. Postoperative delirium is a sudden and fluctuating change in mental state that occurs in patients after anesthesia and surgery [2], typically begins in the recovery room, and can appear up to five days postsurgery. There are three subtypes of delirium: hyperactive with agitated behaviour, hypoactive with decreased alertness and motor activity and mixed with features of both types [3]. The incidence of delirium is notably high among patients in the intensive care unit (ICU) following cardiac surgery. Chen et al. (2021) reported in a meta-analysis study that the incidence of delirium ranged from 4.1 to 54.9% [4]. Simeone et al. (2018) also reported in a different study that this rate was 73% [5]. In addition, different studies have reported that hypoactive delirium after cardiac surgery is more common than other subtypes [6, 7]. Although the mechanism leading to delirium after cardiac surgery is not known exactly, it is thought to be multifactorial [8]. Risk factors for delirium after cardiac surgery include aging, diabetes, preoperative depression, mild cognitive impairment, carotid artery stenosis, New York Heart Association (NYHA) functional class III or IV, duration of mechanical ventilation, and length of stay in the intensive care unit [4]. Delirium in these patients extends the length of intensive care unit (ICU) and hospital stays, necessitates prolonged use of invasive mechanical ventilation, and increases hospital costs [8, 9]. Additionally, it increases the risk of falls, morbidity, and mortality [10, 11]. The negative impact of delirium on patient outcomes extends beyond these immediate effects. Studies have shown that patients with delirium, when followed up after discharge, experience a significant decline in long-term quality of life [12, 13]. These patients tend to become more dependent on daily activities such as bathing, dressing, cleaning, and cooking [12, 14], face memory problems, difficulty concentrating, confusion, disorientation [11‐13], persistent sleep disturbances, nightmares, emotional issues, mobility problems, and an increased rate of hospital readmission [12]. Moreover, the prognosis may be worse in hypoactive delirium because it is relatively under-detected by healthcare professionals compared to other subtypes and therefore delayed treatment [3].
Current guidelines for managing delirium emphasize multicomponent nonpharmacological interventions over single-component approaches [15‐19]. Therefore, care protocols play a crucial role in the implementation of these multicomponent interventions, significantly improving patient outcomes [20‐22]. Nurses are essential in the comprehensive evaluation of ICU patients, identifying and managing delirium risk factors, diagnosing delirium, and providing necessary interventions [23, 24]. As a result of, care protocols based on scientific evidence and systematically structured recommendations offer numerous benefits, including disease prevention, health improvement, facilitating decision-making by standardizing care practices, and enhancing nurses’ autonomy [25‐28]. Research indicates that the incidence of delirium decreases with the implementation of multicomponent nonpharmacological nursing interventions and care protocols [20, 29, 30].
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In the literature, care protocols for delirium prevention are associated primarily with cardiac and other surgical procedures [20, 22, 30, 31]. Delirium management encompasses a broad range of activities, including prevention, diagnosis, and intervention. However, owing to a lack of knowledge about delirium and insufficient use of diagnostic tools, the rates of diagnosing hypoactive delirium and subsequent intervention are inadequate [32‐34].
Consequently, the postoperative delirium prevention, diagnosis, and intervention protocol, designed for ICU patients after cardiac surgery, is a crucial study for comprehensive patient assessment in intensive care, encompassing steps for delirium management, including prevention, diagnosis, and intervention.
This study assessed the impact of a thoroughly developed care protocol on the prevention, diagnosis, and intervention of postoperative delirium.
Methods
Study design and setting
This study was a quasi-experimental study with nonrandomized control and intervention groups. The study was conducted between March and May 2023 in the Cardiovascular Surgery ICU of a training and research hospital in Antalya, Türkiye, which is a tertiary care unit with six beds. The study was reported in accordance with the STROBE checklist [35].
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Participants
The population of the study included patients in the intensive care unit due to cardiac surgery and nurses working in the same place. The inclusion criteria for patients were voluntary participation, age 18 years or older, ability to speak and communicate in Turkish, having undergone cardiac surgery, being on postoperative day 1, having a Richmond Agitation and Sedation Scale (RASS) score of −3 or higher, a Glasgow Coma Scale (GCS) score of 8 or higher, and no serious psychiatric, neurological, visual, or auditory problems. Postoperative day 0 represents the day of surgery and the first hours after surgery. On postoperative day 0, patients were under the influence of anaesthetic drugs, unconscious/semi-conscious and intubated. However, one day after surgery (postoperative day 1), the patients were extubated, conscious and able to communicate. Therefore, delirium was started to be evaluated from postoperative day 1. The exclusion criteria were undergoing noncardiac surgeries, having a history of previous cardiac surgery, experiencing postponed or canceled surgeries, being preoperatively hospitalized in the cardiovascular surgery clinic, or requiring emergency surgery. The study flow diagram is presented in Fig. 1. Additionally, all nurses who were on leave and not on report at the time of the study were included in the study.
Fig. 1
CONSORT flow diagram of the study
×
Sample size and sampling procedure
The sample size was determined by a statistical expert via the G*Power Version 3.1.9.2 program, referencing Fallahpoor et al. (2016) [36]. With a type 1 error of 0.05, a type 2 error of 0.10 (90% power), and an effect size of 0.618, the required sample size was 28 per group, totaling 56. Considering dropout rates of 10.7% [36] and 20% [20] in similar studies, the sample size was increased by 14%, resulting in 64 patients: 32 in the control group and 32 in the intervention group.
The study was conducted in a single intensive care unit. Therefore, random assignment could not be made to prevent the interventions from affecting the control group.
Data collection tools
The data were collected via the Patient Identification Form, including sociodemographic characteristics such as age, sex, educational status and disease characteristics such as height, weight, BMI, history of hospitalization in the hospital and ICU, current diagnosis and type of surgery, Acute Physiology and Chronic Health Evaluation (APACHE II) [37], GCS, RASS [38, 39], the Confusion Assessment method for the ICU (CAM-ICU) [40, 41], the Nurse Identification Form including sociodemographic and professional information of the nurses, the Knowledge Assessment Form for Postoperative Delirium (Pretest and Posttest), and the Postoperative Delirium Prevention, Diagnosis, and Intervention Protocol Checklist.
Literature review, protocol, and algorithm development
Development of a postoperative delirium prevention, diagnosis, and intervention protocol
The protocol, which includes recommendations for nursing interventions to prevent, diagnose, and manage postoperative delirium, was developed by researchers in accordance with current guidelines and the literature. The interventional studies and guidelines published between 2013 and 2022 were reviewed between December 1, 2022, and January 1, 2023, and the COCHRANE Library, PubMed, ScienceDirect, and Google Scholar databases were used for the development of the evidence-based protocol. The literature search utilized terms such as “delirium and cardiac surgery,” “delirium and nursing,” “delirium and care protocol,” and “delirium and guidelines.” An evidence-based protocol and training booklet were developed on the basis of English-language studies and guidelines accessed in full text. The content and construct validity of these materials were evaluated via feedback from seven nursing faculty experts with PhDs and research interests in delirium, and the final version was refined according to their suggestions (Fig. 2).
Fig. 2
Postoperative delirium prevention, diagnosis, and intervention protocol
×
Development of a postoperative delirium prevention, diagnosis, and intervention algorithm
The protocol for preventing, diagnosing, and intervening in postoperative delirium was transformed into an algorithm to facilitate use by nurses in the cardiovascular surgery ICU, enhance the continuity of care and provide clear guidance for nursing interventions (Fig. 3).
Fig. 3
Postoperative delirium prevention, diagnosis and intervention algorithm
×
Research implementation
I. Phase: Data collection from control group patients (06.03.2023–31.03.2023)
In the control group, patients hospitalized in the cardiovascular surgery service preoperatively were informed about the study, provided both written and verbal consent, and completed the Patient Identification Form. Additionally, the researcher instructed patients on the attention assessment test used in the CAM-ICU.
Upon admission to the ICU after cardiac surgery, the researcher completed the APACHE II form on postoperative day 1 for patients. From postoperative day 1 onward, delirium was diagnosed via the GCS, RASS, and CAM-ICU twice daily between 09.00–11.00 and 21.00–23.00 during hospitalization. The type of delirium was also determined in patients with delirium. Patients received routine nursing care for delirium, and nurses recorded any observed delirium for each patient in the control group.
Phase II: Training and preliminary study of postoperative delirium prevention, diagnosis, and intervention protocol
Training and preliminary study of postoperative delirium prevention, diagnosis, and intervention protocol
Providing training to nurses (03.04.2023–07.04.2023)
The training booklet was developed by the researchers in line with the literature in order to provide intensive care nurses with knowledge and skills about postoperative delirium. It includes the definition of delirium and postoperative delirium, epidemiology and importance of postoperative delirium, physiopathology, risk factors, types and symptoms of delirium, nursing care in the prevention, diagnosis and intervention of postoperative delirium. The researcher conducted approximately two hours of training on postoperative delirium prevention, diagnosis, and intervention protocol for nurses in the cardiovascular surgery ICU. Prior to training, the nurses completed the Nurse Diagnosis Form and the Knowledge Assessment Form for Postoperative Delirium (pretest–posttest). Following the training, the first posttest was administered via the knowledge assessment form. Upon completion of the training, the “Postoperative Delirium Prevention, Diagnosis, and Intervention Protocol Training Booklet” was provided to the nurses.
Preliminary study of the protocol (10.04.2023–30.04.2023)
During this stage, ICU nurses began implementing the “Postoperative Delirium Prevention, Diagnosis, and Intervention Protocol,” with the researcher addressing any missing or unclear aspects and answering questions.
Compliance with the protocol was assessed through daily monitoring of the “Postoperative Delirium Prevention, Diagnosis, and Intervention Protocol Checklist.” Following the preliminary phase, the second posttest was administered via the knowledge assessment form. Patients involved at this stage were not included in the study.
Phase III: Data collection process and evaluation from intervention group patients
Data collection process for the intervention group (01.04.2023–22.04.2024)
The preoperative follow-up and practices for patients in the intervention group at the cardiovascular surgery clinic were the same as those in the control group.
Upon admission to the ICU after cardiac surgery, the researcher completed the APACHE II form on postoperative day 1 for patients in the intervention group. Additionally, the GCS, RASS, and CAM-ICU assessments were conducted twice daily by nurses between 09.00–11.00 and 21.00–23.00, starting from postoperative day 1. The type of delirium was also determined in patients with delirium. Patients in this group received nursing care following the postoperative delirium prevention, diagnosis, and intervention protocol. Furthermore, the researcher evaluated patients in the intervention group for delirium development twice daily between 11.00–12.00 and 23.00–00.00. Daily checks of the Postoperative Delirium Prevention, Diagnosis, and Intervention Protocol Checklist were performed by the researcher. Upon completion of the data collection process from the intervention group, the third posttest was administered via the information evaluation form.
Evaluation
The effectiveness of the postoperative delirium prevention, diagnosis, and intervention protocol was assessed by comparing the researcher’s and nurses’ compliance with the delirium diagnosis, the nurses’ delirium diagnosis status, the incidence of postoperative delirium in both the control and intervention groups, the duration of delirium, and the length of ICU hospitalization. Nurses’ compliance with the delirium diagnosis, the nurses’ delirium diagnosis status were determined by using “Postoperative Delirium Prevention, Diagnosis, and Intervention Protocol Checklist”. Additionally, the pretest and posttest knowledge scores of the nurses were compared.
Data analysis
The research data were statistically evaluated by a statistical expert via the IBM SPSS Statistics 23 program. Statistician blinding was performed in the study. Descriptive statistics were employed, including numbers, percentages, means, standard deviations, medians (25th-75th percentiles), minimum values, and maximum values. The normality of the distribution of the data was assessed via the Shapiro‒Wilk test. Parametric tests were applied to normally distributed data, whereas nonparametric tests were utilized for nonnormally distributed data. The means and standard deviations are reported for numerical data, whereas categorical data are expressed as numbers and percentages. Friedman analysis (post hoc: Bonferroni test) was employed to assess changes in knowledge scores over time in nurses' responses to the knowledge assessment form. Nurses who correctly answered at least 24 out of 30 questions (80%) in the knowledge test were considered successful, and their success status was determined via the Cochran Q test. This rate (80%) was determined in line with expert opinions. Differences between groups concerning categorical variables were analyzed via the chi-square test. The independent sample t test was utilized for comparing groups in terms of numerical variables, given that the parametric test assumptions were met. Kappa agreement analysis was employed to determine the agreement between researchers and nurses in diagnosing delirium within the control and intervention groups.
Results
The findings are presented under two headings: findings related to nurses and findings related to patients.
Findings related to nurses
Among the 14 nurses, 64.3% were female and 64.3% held bachelor's degrees. A total of 71.4% of the nurses had not received training on delirium management, nor had they participated in any scientific programs related to delirium management. Additionally, none of the nurses had a dedicated source to stay updated on developments in delirium management and nursing interventions. Furthermore, 35.7% of the nurses reported caring for 1–2 or 3–4 patients with delirium per month. The mean age of the nurses was 35.71 ± 8.46. Also, the mean total service period (months) of the nurses in nursing and ICU were 164.93 ± 104.57 and 73.50 ± 53.15, respectively.
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Knowledge of postoperative delirium
A significant increase in the knowledge and achievement scores of the nurses following the training compared with before the training was observed (Table 1) (p < 0.001). According to the post hoc Bonferroni test, there are significant differences between the Pre-Training and Post-Training, Post-Training 3rd week, and Post-Training 2nd month tests. The increase after the pre-test was found to be statistically significant (p < 0.001).
Table 1
Mean total knowledge scores and achievement status
Pretraining
Posttraining
Posttraining
3. Week
Posttraining
2. Month
Statistical analysis
Test statistics
P
Median
(25–75)
A20.5
(20–24)
B27.5
(26–29)
B28.5
(26–29)
B28.0
(26–29)
F = 27.496
< 0.001*
Achievement Score
10 (%71.4)
13 (%92.9)
14 (%100.0)
14 (%100.0)
C = 27.387
< 0.001*
Means followed by distinct small letters (A,B) in the same line are significantly different (p <0.001)
\(\overline X\) arithmetic mean, SD standard deviation, F Friedman test, C Cochran Q test
*p <0.001
The descriptive characteristics of the patients in the control and intervention groups were similar, and there was no significant difference between the groups (Table 2) (p>0.05).
Table 2
Descriptive characteristics of patients in the control and intervention groups (n = 64)
Characteristics
Control group (n = 32)
Intervention Groups (n = 32)
Statistical analysis
n
%
n
%
Test statistics
P
Age (years)\(\overline{\boldsymbol X}\) ± SD (Min–Max)
63.09 ± 6.69
(44–74)
59.63 ± 9.10
(42–77)
t = −1.711
0.092
Age group
< 65 age
15
46.9
22
68.7
χ2 = 3.139
0.076
65 +
17
53.1
10
31.3
Gender
Female
7
21.9
5
15.6
χ2 = 0.410
0.522
Male
25
78.1
27
84.4
Education level
Illierate
4
12.5
2
6.3
χ2 = 9.149
0.057
Literate
3
9.4
2
6.3
Primary school
19
59.4
12
37.5
High school
4
12.5
15
46.9
Undergraduate and
2
6.2
1
3.0
Marital status
Married
27
84.4
27
84.4
χ2 = 0.000
1.000
Single
5
15.6
5
15.6
Employment status
Yes
13
40.6
16
50.0
χ2 = 0.567
0.451
No
19
59.4
16
50.0
Smoking
Yes
25
78.1
26
81.2
χ2 = 0.097
0.756
No
7
21.9
6
18.8
Duration of smoking \(\overline X\) ± SD
(Min–Max)
31.60 ± 10.83
(15–50)
24.92 ± 14.32
(1–55)
t = −1.873
0.067
Alcohol
Yes
5
15.6
10
31.2
χ2 = 2.177
0.140
No
27
84.4
22
68.8
Body Mass Index (kg/m2)
18.5–24.99
8
25.0
6
18.8
χ2 = 2.494
0.287
25–29
16
50.0
12
37.4
≥ 30
8
25.0
14
43.8
Body Mass Index (kg/m2) X̄ ± SD
(Min–Max)
27.55 ± 3.56
(20.06–35.15)
29.06 ± 4.54
(19.63–39.79)
t = −1.479
0.144
\(\overline X\) arithmetic mean, SD standard deviation, t independent sample t test, χ2chi-square test, Min minimum value, Max maximum value
The medical characteristics of the patients in the control and intervention groups were similar, and there was no significant difference between the groups (Table 3) (p > 0.05).
Table 3
Medical characteristics of patients in the control and intervention groups (n = 64)
Medical characteristics
Control group
(n = 32)
Intervention groups (n = 32)
Statistical analysis
n
%
n
%
Test statistics
P
History of hospitalization
Yes
24
75.0
26
81.2
1χ2 = 0.366
0.545
No
8
25.0
6
18.8
History of intensive care unit admission
Yes
4
12.5
6
18,8
1χ2 = 0.474
0.491
No
28
87.5
26
81.2
Reason for hospitalization/intensive care unit
Surgery
12
50.0
17
65.4
1χ2 = 1.213
0.271
Other diagnosis/treatment
12
50.0
9
34.6
Type of surgery
CABG surgery
24
75.0
23
71.9
1χ2 = 0.098
0.952
Valve surgery
6
18.8
7
21.9
CABG surgery + Valve surgery
2
6.2
2
6.2
Admission to service
Emergency
5
15.6
8
25.0
1χ2 = 1.121
0.571
Policlinic
12
37.5
9
28.1
Othera
15
46.9
15
46.9
Hearing/vision problem
Yes
16
50.0
20
62.5
1χ2 = 1.016
0.313
No
16
50.0
12
37.5
Vision problems
Yes
14
73.7
20
95.2
2χ2 = 3.635
0.085
No
5
26.3
1
4.8
Hearing problem
Yes
3
18.8
4
20.0
2χ2 = 0.009
1.000
No
13
81.2
16
80.0
Prosthetic device use
Yes
16
50.0
17
53.1
1χ2 = 0.141
0.707
No
16
50.0
15
46.9
Comorbid chronic disease
Yes
26
81.2
22
68.8
1χ2 = 1.333
0.248
No
6
18.8
10
31.2
Continuous medication
Yes
27
84.4
23
71.9
1χ2 = 1.463
0.226
No
5
15.6
9
28.1
Number of continues medication \(\overline X\) ± SD
(Min–Max)
2.96 ± 2.44
(0–9)
3.04 ± 1.64
(1–7)
t = 0.133
0.895
APACHE II \(\overline X\) ± SD
(Min–Max)
22.09 ± 2.32
(18–27)
20.78 ± 3.00
(17–31)
t = −1.957
0.055
\(\overline X\) arithmetic mean, SD standard deviation, t independent sampling t test, 1χ2 Pearson chi-square test, 2χ2 Fisher’s exact test, Min minimum value, Max maximum value
areferral from other hospitals
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Although there was no statistically significant agreement between the researcher and the nurses in the control group regarding the rates of diagnosing delirium (kappa: 0.207) (p > 0.05), statistically significant agreement was observed between the researcher and the nurses in the intervention group (kappa: 1.00) (p < 0.001). These data are presented in Table 4.
Table 4
Distribution of the researchers’ and nurses’ agreement in diagnosing delirium in the control and intervention groups
Researcher
Statistical analysis
Delirium
No Delirium
Kappa
P
Nurse
Control group (n = 32)
Delirium
1 (%14.3)
0 (%0.0)
0.207
0.055
No Delirium
6 (%85.7)
25 (%100.0)
Intervention group (n = 32)
Delirium
3 (%100.0)
0 (%0.0)
1.000
< 0.001*
No Delirium
0 (%0.0)
29 (%100.0)
*p <0.001
The study revealed that the incidence of delirium was 21.9% in the control group and 9.4% in the intervention group; however, this difference was not statistically significant (p > 0.05). In the control group, 85.7% (n = 6) of the nurses were unable to diagnose patients with delirium. In contrast, 100% (n = 3) of the nurses in the intervention group were successfully diagnosed. This finding indicates a significantly greater rate of delirium diagnosis by nurses in the intervention group than in the control group (p = 0.033) (p <0.05). Additionally, there were no significant differences between the control and intervention groups in terms of delirium type, the time of onset of delirium, the duration of delirium, or the length of stay in the ICU (p > 0.05) (Table 5).
Table 5
Comparison of delirium diagnosis status and delirium characteristics between the control and intervention groups
Delirium features
Control group
(n = 32)
Intervention Groups
(n = 32)
Statistical analysis
n
%
n
%
Test statistics
P
Incidence of delirium**
7
21.9
3
9.4
1χ2 = 1.896
0.168
Nurses’ diagnosis status of delirium
Yes
1
14.3
3
100
2χ2 = 6.429
0.033*
No
6
85.7
-
-
Delirium types
Hypoactive
6
85.7
2
66.7
2χ2 = 0.476
0.490
Hyperactive
-
-
-
-
Mixed
1
14.3
1
33.3
Time of onset of delirium
Postoperative 1.day morning
5
71.4
2
66.7
1χ2 = 3.197
0.202
Postoperative 1.day evening
-
-
1
33.3
Postoperative 2.day morning
2
28.6
-
-
Duration of delirium (day) X̄ ± SD
(Min–Max)
2.33 ± 1.03
(1–4)
3.33 ± 1.53
(2–5)
t = 1.183
0.275
The length of stay in the ICU (day) X̄ ± SD (Min–Max)
1.94 ± 0.67
(1–4)
1.78 ± 0.91
(1–5)
t = −0.785
0.436
\(\overline X\) arithmetic mean, SD standard deviation, 1χ2 Pearson chi-square test, 2χ2 Fisher’s exact test, t independent sample t test, Min minimum value, Max maximum value
*p < 0.05
**set by the researcher with CAM-ICU
Discussion
In this study, no significant agreement was found between the researcher and the nurses in the control group regarding the rates of delirium diagnosis (p > 0.05). However, in the intervention group, there was significant agreement between the researcher and the nurses (kappa: 1.00). These findings align with previous research. In a study examining the effect of training given to ICU nurses on diagnosing delirium, the agreement between the researcher and the nurses was reported to be low before the training but increased significantly after the training [42]. Similarly, a study by Rice et al. (2011) on nurses’ delirium diagnosis reported that nurses failed to diagnose nine out of twelve delirium cases identified by the researcher, with eight of these cases being hypoactive delirium. This resulted in poor agreement between the nurses and the researcher (kappa: 0.34) [43]. Also, Mistarz et al. (2011) compared the delirium diagnosis status of ICU nurses with that of a nurse via the CAM-ICU diagnostic tool. They reported that ICU nurses accurately diagnosed only three out of eleven delirium cases and incorrectly diagnosed delirium in two patients who were not delirious according to the CAM-ICU. This also resulted in poor agreement (kappa: 0.22) [44].
Although hyperactive delirium is easily diagnosed because of the patient’s agitation and aggressive behavior [45], patients with hypoactive delirium can often be overlooked because of their extremely calm behaviors [46]. In a study conducted with ICU nurses, Speed (2015) reported that nurses struggled to consistently diagnose delirium if it fluctuated and if they lacked knowledge about the various clinical types of delirium [47]. In the present study, it was determined that nurses in the control group could not diagnose six patients with hypoactive delirium because their average knowledge score was low before the training, and they did not use a delirium diagnosis tool. After the training, the average knowledge score of the nurses increased, and they successfully diagnosed three cases of delirium, two of which were hypoactive, using the diagnostic tool in the intervention group. Similar to these studies, the literature reports that nurses often do not receive formal training on delirium [33], have low levels of knowledge [47], and do not use diagnostic tools or use them infrequently [32‐34]. Notably, the use of delirium screening tools among trained nurses increases the rate of delirium diagnosis [42, 48].
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The incidence of delirium in the ICU after cardiac surgery has been reported to be high in various studies [4, 5]. While some research suggests that nonpharmacological nursing interventions lead to a significant decrease in the incidence of delirium [20, 29, 30, 36, 49‐52], other studies have reported a decrease in incidence without a significant difference [42, 53]. In this study, the incidence of delirium was 21.9% in the control group and 9.4% in the intervention group. Although there was a noticeable 12.5% decrease in the incidence of delirium in the intervention group, this difference did not reach statistical significance. With the implementation of the protocol, awareness has been raised among nurses about delirium management. It is thought that repeated use of the protocol will be effective.
Nonpharmacological nursing interventions in the ICU have been reported to effectively reduce both the incidence and duration of delirium [54, 55]. Various systematic reviews, meta-analyses, and intervention studies have revealed that multicomponent nonpharmacological nursing interventions are particularly effective in shortening the duration of delirium [56‐58]. However, some other studies [20, 49, 59, 60] and our study have shown different results. This inconsistency in findings can be attributed to the low number of patients who developed delirium in the intervention group (three) and the long duration of delirium in one patient (five days).
In addition, reports in the literature have indicated that nonpharmacological nursing interventions in cardiac surgery patients lead to a significant decrease in ICU length of stay [20, 60]. However, other studies have reported no significant difference in ICU length of stay between control and intervention groups receiving nonpharmacological nursing interventions [21, 55, 56, 61]. Consistent with these findings, our study revealed similar average lengths of stay (days) in the ICU between the control and intervention groups, with no significant difference detected. This discrepancy in results may be influenced by various medical and individual patient characteristics.
The study has three limitations
The first one is that only one ICU was included in the study. Therefore, randomisation could not be performed to prevent both groups from being affected by the interventions. Secondly, medical doctors were not involved in the process of diagnosing delirium. Thirdly, the findings regarding the effect of the protocol on the duration of delirium are inconsistent with the literature. This inconsistency is thought to be due to the low number of patients who developed delirium in the intervention group (three) and the long duration of delirium in one of these patients (five days).
Conclusion and recommendations
These findings indicate that the postoperative delirium prevention, diagnosis, and intervention protocol is effective in diagnosing delirium. The protocol has raised awareness among nurses about the prevention and intervention of delirium. It is recommended that it be used repeatedly in order to fully determine the effect of the protocol in the prevention and intervention of delirium.
Acknowledgements
We would like to thank all the patients and nurses for their contributions to nursing science by participating in the research.
Declarations
Ethics approval and consent to participate
For the research, approval was obtained from both the Gazi University Ethics Commission, with a decision dated 17.06.2022, decision number E-77082166–302.08.01–385523, and the Antalya Provincial Health Directorate, with a decision dated 06.03.2023, decision number E-98360293–604.01.02–210671333. Additionally, the research procedures were thoroughly explained to both the participating patients and the nurses, and their verbal and written consent was obtained.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
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