Abstract
Background
Delirium is a form of acute brain dysfunction and geriatric patients are particularly vulnerable to this health problem. The aim of the study was to assess the incidence of delirium and determine the risk factors for delirium in patients ≥ 60 years of age hospitalized due to acute myocardial infarction (AMI).
Methods
The study included 405 consecutive patients (mean age: 73.1 ± 8.5, males: 61%) hospitalized due to AMI divided and characterized according to the in-hospital delirium presence.
Results
Of 405 patients, 57 (14%, mean age: 80.9 ± 7.3, males: 58%) experienced delirium. Patients with delirium were older (80.9 ± 7.3 vs. 71.82 ± 8.1 years), all of them presented multimorbidity, they more frequently used polypharmacy (96.5 vs. 30.2%) and their hospitalization was longer (8.0 ± 1.4 vs. 4.6 ± 1.0 days) as compared to the patients without delirium. Patients with delirium more frequently experience periprocedural complications as well as the in-hospital reversible problems: fever (40.4 vs. 0.9%), infections (78.9 vs. 3.7%), pulmonary oedema (73.7 vs. 0.6%), hypoxemia (91.1 vs. 98.3%), urinary catheter (96.5 vs. 17.2%), dehydration (89.5 vs. 6.6%), and insomnia (71.9 vs. 0.3%) compared to patients without delirium (P < 0.001 for all). Valvular heart disease (OR = 4.78; 95%CI: 1.10-2.70; P < 0.001, pulmonary oedema (OR = 66.79; 95%CI: 12.04-370.34, P < 0.001), and dehydration (OR = 37.26; 95%CI: 10.50-132.27, P < 0.001) were risk factors for delirium occurrence.
Conclusions
The in-hospital course of AMI is complicated by delirium occurrence in 14% of patients ≥ 60 years old. Recognizing and modification of potential, reversible risk factors associated with AMI can reduce the risk of delirium.
Population ageing is a progressing phenomenon entailing negative health, as well as social and economic consequences. As a result of the process of ageing and senility “geriatric symptoms” occur, to which modern medicine includes, among others, the delirium syndrome.[1]
Delirium syndrome is a form of acute brain dysfunction characterized by sudden onset, dynamic course and fluctuating symptoms. It is a state dominated by psychomotor agitation, disturbance of consciousness, attention and psychomotor activity, perception, memory and mood, as well as reversal of the sleep-wake cycle.[2-5] In the clinical picture, it may take a hyperactive, hypoactive or mixed form. Hyperkinetic delirium mostly manifests itself in anxiety and aggression, accompanied by visual and auditory hallucinations. The hypokinetic form, on the other hand, includes the symptoms of apathy and social withdrawal. Most frequently, the patient is somnolent and their response to stimuli is reduced. It occurs mainly in elderly patients.[5] In the mixed form of delirium, the patient experiences the hyperactive and hypoactive traits alternately.[6]
The precise cause of delirium remains unknown. However, multifactorial aetiology is generally accepted.[7] It occurs in 8%-17% of elderly people during hospitalization and in 11%-46% of cardiological patients.[8]
Despite the proven correlation with increased mortality, long-term dementia and increased medical costs connected with hospitalization, the diagnosis of delirium remains overlooked in medical practice.[6] In elderly patients, the admission procedure should involve delirium prevention from the very onset. The prevention should especially include screening and mental state assessment, with the use of the Confusion Assessment Method (CAM),[7] for example, which accounts for the hypomotoric subtype of the disorder. Furthermore, early identification of delirium risk factors may prevent the condition and the related morbidity and mortality.[5] The identification of both predisposing and precipitating factors, particularly those modifiable, plays a key role in effective prevention. Education of medical staff concerning the identification and elimination of modifiable delirium risk factors seems crucial, therefore.
These research results should contribute to greater knowledge about the risk of delirium in patients above 60 years of age admitted to a hospital urgently due to life-threatening conditions, thus reducing the threat to life resulting from the disease entity and increasing the patient’s quality of life.
The aim of the study was to assess the incidence of delirium and determine the risk factors for delirium in patients ≥ 60 years of age hospitalized with acute myocardial infarction (AMI).
METHODS
Study Design and Data Collection
The research program lasted for 12 months from the assigned date. The risk factors assessment was conducted on day 0 of hospitalization (initial phase), then between day 1 and the day preceding discharge (hospitalization period) and within the last 24 h before discharge (final phase). In the initial phase, the patients were qualified for the study according to the criteria of inclusion and exclusion – the main inclusion criterion assessed in the initial phase was unconfirmed delirium syndrome. Each patient was evaluated for delirium at least once daily during routine ward rounds, with additional assessments in case of clinical suspicion. In the final phase, impaired consciousness due to delirium was present in none of the study subjects and their health was sufficiently good to allow for their discharge from hospital. A flow chart describing patient selection and inclusion in the study is provided in Figure 1.
Figure 1.
Flow diagram of patient selection.
Setting
This cohort study was conducted in the tertiary reference cardiology centre (1st Cardiology Department of the Upper-Silesian Medical Centre, Katowice, Polska) in the period between the 1st January 2019 and the 1st January 2020. The analysis was conducted based on the standardized questionnaire which included scales: Mini-Mental State Examination (MMSE), Visual Analogue Scale (VAS), CAM, and Geriatric Depression Scale. In the analysis, the data collected based on medical history, fever chart, medical order sheet and nurse reports were also used.
Participants
The following inclusion criteria were applied in the study: (1) age ≥ 60 years; (2) diagnosed AMI; (3) coronary angiography without coronary intervention or coronary angiography with simultaneous Percutaneous Coronary Interventions (PCI) performed within 24 h from admission to the 1st Cardiology Department; (4) placement of the patient in a room with Intense Cardiac Monitoring in the day 0 of their stay at the 1st Cardiology Department; (5) delirium diagnosed during hospitalization between day 1 and the day preceding discharge based on the CAM scale; and (6) conscious written consent. Delirium was diagnosed using the Confusion Assessment Method (CAM) and confirmed by a psychiatric consultation, ensuring a standardized and formal approach to diagnosis.
The following participants were excluded from the study: (1) with delirium diagnosed based on the CAM scale on day 0 of hospitalization; (2) transferred from the Anesthesiology and Intensive Care Unit to the 1st Cardiology Department; (3) with a result of ≤ 10 points in the MMSE scale; (4) after intubation; (5) with diagnosed neurological disease; (6) with sight or hearing impairment; and (7) addicted to psychoactive substances.
Data Collection
Comprehensive analysis of delirium risk factors conducted during hospitalization at the 1st Cardiology Department comprised three phases: the initial one (24 h from the admission), the hospitalization period phase and the final one (24 h before discharge). The following data were analysed: (1) general information: age, sex, length of hospitalization; (2) peri- and post-procedural period: type of infarction, type of coronary intervention, vascular access, length of applied compression after the hemodynamic procedure, pain following coronary angiography; (3) PCI: the occurrence of pain and its intensity were assessed based on the VAS scale, presence pseudoaneurysm; (4) clinical assessment: multimorbidity (was defined as the presence of two or more chronic diseases), presence of chronic diseases (diabetes, chronic kidney disease, valvular heart disease, atrial fibrillation, chronic obstructive pulmonary disease), left ventricle ejection fraction (LVEF) in echocardiography at admission; (5) accompanying symptoms: fever, infection, pulmonary oedema, hypoxemia, dehydration ( was defined as a clinical diagnosis confirmed by laboratory parameters such as elevated urea/creatinine ratio and signs of volume depletion - dry mucous membranes, hypotension, tachycardia), insomnia, inserted urinary catheter; (6) functional status assessment: psychiatric conditions; (7) assessment of the pharmacotherapy used: polypharmacy (was defined by taking 5 or more medications), number of medications taken before and during hospitalization including medications administered orally.
Bioethical Aspect
Before the study was conducted, the Bioethical Commission’s opinion was sought on the research project – the opinion number: PCN/0022/KB/281/19.
Statistical Methods
The data were collected in an Excel 2013 spreadsheet, operating in Windows 8.1. Initial verification was conducted in Excel. Then the data were transferred to Statistica 13.1 PL (StatSoft Polska, Kraków, Polska) and SAS 9.2 (Institute Inc. Cary, USA) databases. The values of continuous variables were presented as means. To assess the distribution of variables the Shapiro-Wilk test was applied. To assess the differences between the groups, Students t test and Wilcoxon non-parametric test was used. The frequency of features (qualitative variables) is presented in percentages. Additionally, the number of observations (N) is provided for each feature, corresponding to the total number of cases in the study. The impact of independent variables on a dependent variable was assessed by using a single-factor logistic regression analysis, the results of which were presented as raw odds ratio values with 95% CI. P ≤ 0.05 was accepted as the level of statistical significance.
RESULTS
General Information
405 patients (males: 248/61.2%) aged 60-93 were included in the study. Delirium was diagnosed in 57 (14%) subjects (males: 33/58%). The average age of subjects diagnosed with delirium (80.9 ± 7.3) was significantly higher than the mean age of patients who did not experience delirium (71.8 ± 8.1), P < 0.001). There were no statistically significant differences in the studied population concerning sex. The period of hospitalization amounted to 8.0 ± 1.4 days on average, which was about twice as long as in the case of patients without delirium (4.6 ± 1.0 days, P < 0.001; Table 1). Two patients died during the study.
Table 1. Clinical characteristics of the study group (n = 405) including a comparison between ND and D patients.
| Variable | Feature of the variable | Total | ND | D | P-value |
| Data are presented as mean ± SD or n (%). D: delirium; ND: no delirium. | |||||
| Age | 60-74 yrs | 220 (54.3%) | 211 (60.6%) | 9 (15.5%) | < 0.001 |
| 75-89 yrs | 179 (44.2%) | 134 (38.5%) | 45 (78.9%) | ||
| 90-93 yrs | 6 (1.5%) | 3 (0.9%) | 3 (5.6%) | ||
| Sex | Male | 248 (61.2%) | 215 (61.7%) | 33 (57.9%) | < 0.6 |
| Female | 157 (38.2%) | 133 (38.3%) | 24 (42.1%) | ||
| Myocardial infarction | STEMI | 209 (51.6%) | 186 (53.4%) | 23 (40.3%) | < 0.07 |
| NSTEMI | 196 (48.4%) | 162 (46.6%) | 34 (59.6%) | ||
| Multimorbidity | Number of chronic diseases | 3.5 ± 1.4 | 3.3 ± 1.0 | 4.6 ± 1.4 | < 0.001 |
| LVEF | At admission | 47.2 ± 9.7 | 49.3 ± 8.0 | 33.6 ± 7.9 | < 0.001 |
| Polypharmacy before hospitalization | 160 (39.5%) | 105 (30.2%) | 55 (96.5%) | < 0.001 | |
| Number of medications | p.o. before hospitalization | 4.0 ± 2.4 | 3.6 ± 2.1 | 7.0 ± 1.6 | < 0.001 |
| p.o. during hospitalization | 7.3 ± 2.5 | 6.7 ± 1.9 | 11.0 ± 1.9 | < 0.001 | |
| Diabetes | 180 (44.4%) | 132 (37.9%) | 48 (84.2%) | < 0.0001 | |
| Chronic kidney disease | 130 (32.1%) | 99 (28.4%) | 31 (54.5%) | < 0.0001 | |
Delirium and Type of Infarction and Coronary Intervention
No differences were observed as far as the type of AMI: ST-segment Elevation Myocardial Infarction (STEMI) vs. non-ST-elevation Myocardial Infarction (NSTEMI) (51.6% vs. 48.4%, P < 0.07) and the type of coronary intervention: the frequency of solely coronary angiography or PCI (10.8% vs. 89.9%, P < 0.5) in the populations with delirium and without it. Delirium was more frequently observed among the subjected with femoral access (primary or conversion from radial access) (68.4% vs. 26.4%, P < 0.001) as compared to the procedure performed with solely radial access (57.9% vs. 81.9%) (P < 0.001) and in patients with compression applied on the procedure site for longer period (12.0 ± 3.0 vs. 8.5 ± 3.2 h; P < 0.001) as compared to patients not experiencing delirium.
Pain following coronary angiography/PCI occurred in 75.4% of patients with delirium and 34.8% of those without delirium. The severity of pain measured using VAS in patients with delirium was, respectively, as follows: mild pain (10.5% vs. 9.5%), moderate pain (56.2% vs. 13.8%) and acute pain (14.0% vs. 0.5%) as compared with patients without delirium. None of the patients experienced the so-called “total pain”. The average period during which the pain continued after the invasive procedure in patients with delirium amounted to 2.9 ± 1.8 h (despite the administered pharmacotherapy) which was significantly longer than in patients without delirium (0.5 ± 0.9 h after the procedure). Pseudoaneurysm occurred in 45.6% of patients with delirium and 2% of patients without delirium (Table 2; P < 0.001 for all).
Table 2. Clinical characteristics of the study group (n = 405) and population comparison without delirium and with delirium–potent modifiable variables.
| Variable | Total | ND | D | P-value |
| Data are presented as mean ± SD or n (%). D: delirium; ND: no delirium. | ||||
| Periprocedural conditions | ||||
| Procedure via femoral access | 131 (32.3%) | 92 (26.4%) | 39 (68.4%) | < 0.001 |
| Procedure via radial access | 318 (78.5%) | 285 (81.9%) | 33 (57.9%) | < 0.001 |
| Time of pressure applied at the site of artery access, h | 9.0 ± 3.4 | 8.5 ± 3.2 | 12.0 ± 3.0 | < 0.001 |
| Pain after coronary intervention, h | 0.8 ± 1.4 | 0.5 ± 0.9 | 2.9 ± 1.8 | < 0.001 |
| Pseudoaneurysm | 33 (8.1%) | 7 (2.0%) | 26 (45.6%) | < 0.001 |
| In-hospital course – complications: | ||||
| Insomnia during hospitalization | 42 (10.3%) | 1 (0.3%) | 41 (71.9%) | < 0.001 |
| Fever | 26 (6.4%) | 3 (0.9%) | 23 (40.4%) | < 0.001 |
| Inflammation/infection | 58 (14.3%) | 13 (3.7%) | 45 (78.9%) | < 0.001 |
| Pulmonary oedema | 44 (10.9%) | 2 (0.6%) | 42 (73.7%) | < 0.001 |
| Saturation measurement, SpO2, % | 97.3 ± 2.7 | 98.3 ± 0.7 | 91.1 ± 2.4 | < 0.001 |
| Urinary catheter | 115 (28.4%) | 60 (17.2%) | 55 (96.5%) | < 0.001 |
| Dehydration | 74 (18.3%) | 23 (6.6%) | 51 (89.5%) | < 0.001 |
Delirium and Clinical Assessment
The whole studied population was burdened with multimorbidity – it was diagnosed in every patient, as well as hypertension. The average number of diseases present in the studied population amounted to 3.5 ± 1.4 and was higher in patients with delirium (3.3 ± 1.0 vs. 4.6 ± 1.4). Apart from hypertension, the studied group was characterized by a high percentage of diabetes (84.2% vs. 37.9%), chronic kidney disease (40.4% vs. 18.1%), significant valvular heart defect (49.1% vs. 10.6%), atrial fibrillation (77.2% vs. 5.5%) and chronic obstructive pulmonary disease (28.0% vs. 13.2%) as compared to patients without the symptoms of delirium. Patients with delirium presented lower LVEF (33.6% ± 7.9% vs. 49.3% ± 8.0%; P < 0.001 for all; Table 1).
Delirium and Accompanying Symptoms
Patients with delirium more frequently experienced in-hospital complications such as fever (40.4% vs. 0.9%), infection (78.9% vs. 3.7%), pulmonary oedema (73.7% vs. 0.6%), hypoxemia (91.1% ± 2.4% vs. 98.3% ± 0.7%), dehydration (89.5% vs. 6.6%), insomnia (71.9% vs. 0.3%), inserted urinary catheter (96.5% vs. 17.2%) as compared to patients without delirium. P < 0.001 for all (Table 2).
Delirium and Psychiatric Conditions
Delirium was much more frequently identified in patients with diagnosed mild (49.1 vs. 0.3%) and moderate (47.4 vs. 9.2%) dementia, measured according to the MMSE scale, as well as with traits of mild depression (59.6 vs. 2.3%) measured according to the Geriatric Depression Scale, as compared with the population without delirium. P < 0.001 for all (Table 3).
Table 3. Characteristics of the functional status of the study group (n = 405) and comparison population without delirium and with delirium.
| Variable name | Feature of the variable | Total | ND | D | P-value |
| Data are presented as n (%). D: delirium; GDS: Geriatric Depression Scale; MMSE: Mini Mental State Examination; ND: no delirium. | |||||
| MMSE scale | Cognitive disorders | 65 (16.2%) | 63 (18.1%) | 2 (3.5%) | < 0.001 |
| Mild dementia | 29 (7.2%) | 1 (0.3%) | 28 (49.1%) | ||
| Moderate dementia | 59 (14.6%) | 32 (9.2%) | 27 (47.4%) | ||
| GDS scale | Mild depression | 42 (10.4%) | 8 (2.3%) | 34 (59.6%) | < 0.001 |
Delirium and Pharmacotherapy
Polypharmacy was determined in 160 (39.5%) of the patients, in 96.5% of patients with delirium and 30.2% of those without it. Delirium syndrome was experienced more frequently by patients who took on average 7.0 ± 1.6 tablets (between 4 and 12) permanently before their admission, while during their hospitalization they took 11.0 ± 1.9 tablets (between 8 and 16). This was an amount much greater than taken by patients without delirium (before hospitalization 3.6 ± 2.1 tablets, during hospitalization 6.7 ± 1.9 tablets) P < 0.001 for all.
In addition to the analysis of polypharmacy, we examined the use of specific drug classes in patients with and without delirium. We found that the use of several medication groups was significantly more common among patients who developed delirium during hospitalization. In particular, patients with delirium were more likely to receive diuretics (93.0% vs. 86.5%), statins (94.7% vs. 75.3%), calcium channel blockers (84.2% vs. 51.1%), antiarrhythmics (93.0% vs. 44.3%), and hypoglycemic drugs (61.4% vs. 34.2%) (all P < 0.0001). The full list of analyzed drug classes is presented in Table 4.
Table 4. Characteristics of pharmacotherapy used in the study group (n = 405) and comparison of the population without delirium and with delirium.
| Name of variable | Characteristic of variable | Total |
ND |
D |
P-value |
| Data are presented as n (%). D: delirium; IACE: angiotensin I-converting enzyme inhibitor; ND: no delirium. | |||||
| IACE | p.o. | 389 (96.0%) | 337 (96.8%) | 52 (91.2%) | P < 0.0001 |
| Beta-blockers | p.o. | 377 (93.1%) | 327 (94.0%) | 50 (87.7%) | P < 0.0007 |
| Diuretics | p.o. | 354 (87.4%) | 301 (86.5%) | 53 (93.0%) | P < 0.0001 |
| Statins | p.o. | 316 (78.0%) | 262 (75.3%) | 54 (94.7%) | P < 0.0008 |
| Calcium channel blockers | p.o. | 255 (63.0%) | 207 (51.1%) | 48 (84.2%) | P < 0.0001 |
| Antiarrhythmics | p.o. | 207 (51.1%) | 154 (44.3%) | 53 (93.0%) | P < 0.0001 |
| Hypoglycemic drugs | p.o. | 154 (38.0%) | 119 (34.2%) | 35 (61.4%) | P < 0.0001 |
| Xanthine oxidase inhibitors | p.o. | 50 (12.3%) | 41 (11.8%) | 9 (16.4%) | P < 0.0001 |
| Rivaroxaban | p.o. | 52 (12.8%) | 38 (10.9%) | 14 (24.6%) | P < 0.0001 |
| Thyrostatics | p.o. | 13 (3.2%) | 11 (3.2%) | 2 (3.4%) | P < 0.9 |
| Insulin | s.c. | 26 (6.4%) | 12 (3.4%) | 14 (24.6%) | P < 0.0001 |
| Acetaminophen | i.v. | 238 (58.8%) | 194 (55.7%) | 44 (77.2%) | P < 0.001 |
| Catecholamines | i.v. | 87 (21.5%) | 47 (13.5%) | 40 (70.2%) | P < 0.003 |
| Loop diuretics | i.v. | 58 (14.3%) | 16 (4.6%) | 42 (73.7%) | P < 0.0001 |
| Antibiotics | i.v. | 57 (14.1%) | 12 (3.4%) | 45 (78.9%) | P < 0.0001 |
| Nitrates | i.v. | 57 (14.1%) | 18 (5.2%) | 39 (68.4%) | P < 0.0001 |
| Eptifibatide | i.v. | 23 (5.7%) | 15 (4.3%) | 8 (14.0%) | P < 0.003 |
Delirium as the Dependent Variable in Logistic Regression Analysis
The analysis of logistic regression, taking age into account as an independent risk factor, demonstrated that valvular heart disease, pulmonary oedema and dehydration are significant predictors for the occurrence of delirium during hospitalization in AMI patients aged ≥ 60 years old (Table 5).
Table 5. Delirium risk factors in the studied population.
| Dependent variable | Factor – predictor | OR (95% CI) |
| Occurrence of delirium | Valvular heart defect | 4.78 (1.10-2.70) |
| Pulmonary edema | 66.79 (12.04-370.34) | |
| Dehydration | 37.26 (10.50-132.27) |
Analysis of the frequency of coexistence of all the above significant factors associated with delirium is presented in Table 6.
Table 6. Number of delirium risk factors in the population with delirium symptoms.
| Number of delirium risk factors |
Number of patients with delirium symptoms (n) |
Percentage of all studied delirium risk factors (%) |
| ≤ 4 | 1 | 1.8 |
| 5-6 | 3 | 5.6 |
| 7-8 | 15 | 25.9 |
| 9-10 | 13 | 22.8 |
| ≥ 11 | 25 | 43.9 |
DISCUSSION
Delirium, which is a form of acute brain dysfunction, is a significant health problem, especially in elderly patients. This study presents data on the incidence and risk factors of delirium in a population of patients with myocardial infarction aged ≥ 60 years. The topic and the result are of clinical importance as delirium is a significant in-hospital problem affecting the course of the disease and prognosis. This is especially true since the risk factors for delirium can be divided into predisposing (non-modifiable) and triggering factors.[9] Particularly noteworthy are those of a modifiable nature, the elimination of which may prevent the occurrence of delirium.
The analysis of the results covering 405 patients showed that delirium was experienced by as many as 57 of them, which is 14% of the respondents. These people were older (80.9 ± 7.3 vs. 71.82 ± 8.1 years, P < 0.001). These observations are consistent with data available in the literature.[10,11,12] There may be many reasons for this dependence. Advanced age may determine changes occurring in the Central Nervous System, such as reduced adaptive abilities or neurocognitive deficits, which contribute to an increased risk of delirium.[13,14,15] No significant relationship was observed between the occurrence of delirium and gender.
In the study group, there was no correlation between delirium and the type of AMI: STEMI vs. NSTEMI. However, Mossello, et al.[16] determined that patients with STEMI myocardial infarction may be at risk of developing delirium syndrome. All patients with delirium presented with multi-morbidities. It is proven by other authors who showed that multimorbidity may have a significant impact on the functional capacity of older people, also contributing to mental disorders.[17,18]
Patients with delirium were more likely to have polypharmacy (96.5% vs. 30.2%) and required longer hospitalization (8.0 ± 1.4 vs. 4.6 ± 1.0 days, P < 0.001) compared to those who did not experience delirium.[19,20] The longer hospital stay was due to, among others, the more severe clinical course and the time needed to normalize the mental condition of a patient with delirium. The authors of other studies confirm such observations.[21,22,23]
People with delirium also had more frequent reversible problems during their hospital stay, such as periprocedural complications (radial access, long-term pressure and pain after the procedure), as well as the occurrence of various accompanying symptoms: fever (40.4% vs. 0.9%), infections (78.9% vs. 3.7%), pulmonary oedema (73.7% vs. 0.6%), hypoxemia (91.1% vs. 98.3%), urinary catheter (96.5% vs. 17.2%), dehydration (89.5% vs. 6.6%) and insomnia (71.9% vs. 0.3%), compared to patients in whom no symptoms of delirium were observed.[9,21,23,24,25-30] The exact mechanisms linking pulmonary oedema and dehydration to delirium were not the focus of this study but are worth mentioning. Pulmonary congestion may impair oxygenation, leading to cerebral hypoxia, while dehydration contributes to metabolic disturbances, hypoperfusion, and neuroinflammation– all associated with delirium pathophysiology.
Left ventricular ejection fraction determined in patients with delirium was significantly lower (33.6% ± 7.9%) compared to patients without delirium (49.3% ± 8.0%). Reduced LVEF may lead to chronically reduced blood flow in the cerebral circulation, which results in the risk of delirium syndrome. The study authors emphasize the importance of LVEF < 40% as a predisposing factor to the occurrence of delirium.[31,32,33]
Additionally, delirium was associated with the presence of mild (49.1% vs. 0.3%, P < 0.001) and moderate (47.4% vs. 9.2%) dementia.[21,34,35] Moreover, the study results showed that depression is also one of the factors determining the occurrence of delirium. The diagnosis of depression may mask the hypoactive subtype of the disorder, which is often overlooked in clinical practice.[36] The subtype of hypoactive disorder is usually interpreted as a result of patients' age or analgesic therapy.[37]
The analysis of risk factors also showed that valvular heart disease, pulmonary oedema and dehydration were independent predictors of the occurrence of delirium.[38] Moreover, the analysis of all relevant factors associated with delirium showed that 44% of patients with delirium had at least 11 comorbid health problems.
In some studies in the literature, the incidence of delirium is higher than in our study. The differences may result from diagnostic difficulties, differences in the characteristics of the study population and methodological conditions. Delirium is a difficult condition to diagnose, which can lead to variable results between tests. Differences in data collection methods and sample size may also be important.[39]
The conclusions of this study indicate that episodes of delirium are a complication occurring in 14% of patients aged ≥ 60 years hospitalized for acute myocardial infarction. Education of medical staff in the identification and elimination of potential exposure factors can protect up to 30% to 80% of older patients from the unfavourable situation of delirium. Also in the case of a diagnosis of delirium, it provides the patient with an appropriate, thoughtful approach and care that increases mental and physical comfort.[40] Moreover, the procedure for admitting elderly patients to the cardiology department should include delirium prevention from the very beginning. This prevention should particularly include screening tests and assessment of mental state using the CAM scale, which takes into account the often overlooked hypo-motor subtype.[7]
Limitations
The presented work is a prospective, single-centre survey and has some limitations related to its nature. The inclusion and exclusion criteria limited the ability to analyse cases of patients who developed delirium on the first day of hospitalization. The study was focused on the patients hospitalized in cardiology department. This is why patients transferred from ICU were excluded from the study that allowed to limit the impact on ICU-specific delirium risk factors. The analysis did not take into account data on direct coercion used in some cases. Moreover, the vast majority of the studied group constituted the general population living in the city (88.6%), therefore the results of the analysis should be related especially to this community. The study reveals several relationships, but they should be interpreted with caution - some parameters characterizing patients experiencing delirium may be its causes, while others may be its consequences.
Additionally, univariate regression was used to analyze the risk factors of the study, which has some limitations. It may lead to the simplification of complex relationships between variables and not take into account all confounding factors. Therefore, the interpretation of the obtained results should be made with caution. Despite such limitations, eliminating potentially reversible risk factors may certainly be crucial. Additionally, the retrospective nature of data analysis may introduce a risk of selection and information bias.
Conclusions
The in-hospital course of AMI is complicated by delirium occurrence in 14% of patients ≥ 60 years old. The population of AMI patients with delirium shows a high degree of multimorbidity and polypharmacy, which may suggest that there is a complex interaction between the state of delirium, existing diseases and the number of drugs used. Moreover, our study indicates an important role of reversible factors, such as dehydration or infections, in the occurrence of delirium in patients hospitalized due to myocardial infarction. The results of logistic regression analysis suggest a significant role of valvular heart disease, pulmonary edema and dehydration as significant predictors of delirium in patients aged ≥ 60 years. Early identification of reversible risk factors for delirium and their effective prevention are an extremely important step in improving the quality of care and reducing the risk of complications in patients affected by myocardial infarction. Education of nursing staff concerning the use of simple screening tools may effectively reduce the prevalence of delirium in this group.
Funding Statement
The study is supported by the First Department of Cardiology, School of Medicine in Katowice, Medical University of Silesia, Katowice, Poland.
References
- 1.Akbarzadeh MA, Hosseini MS. Is COVID-19 really a geriatric syndrome? Ageing Res Rev 2022; 79: 101657.
- 2.Lauretani F, Bellelli G, Pelà G, et al. Treatment of Delirium in Older Persons: What We Should Not Do! Int J Mol Sci 2020; 21: 2397.
- 3.Dubiel C, Hiebert BM, Stammers AN, et al Delirium definition influences prediction of functional survival in patients one-year postcardiac surgery. J Thorac Cardiovasc Surg. 2022;163:725–734. doi: 10.1016/j.jtcvs.2020.07.028. [DOI] [PubMed] [Google Scholar]
- 4.Chen YR, Chen YL, et al Evidence-based nursing care of older adult patients with postoperative delirium and hip fracture. Hu Li Za Zhi. 2021;68:90–96. doi: 10.6224/JN.202102_68(1).12. [DOI] [PubMed] [Google Scholar]
- 5.Spiropoulou E, Samanidis G, Kanakis M, et al Risk factors for acute postoperative delirium in cardiac surgery patients > 65 years old. J Pers Med. 2022;12:1529. doi: 10.3390/jpm12091529. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Rieck KM, Pagali S, Miller DM Delirium in hospitalized older adults. Hosp Pract (1995). 2020;48:3–16. doi: 10.1080/21548331.2019.1709359. [DOI] [PubMed] [Google Scholar]
- 7.Lange S, Mȩdrzycka-Da̧browska W, Tomaszek L, et al Nurses' knowledge, barriers and practice in the care of patients with delirium in the intensive care unit in Poland—A cross-sectional study. Front Public Health. 2023;11:1119526. doi: 10.3389/fpubh.2023.1119526. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Hshieh TT, Inouye SK, Oh ES Delirium in the Elderly. Clin Geriatr Med. 2020;36:183–199. doi: 10.1016/j.cger.2019.11.001. [DOI] [PubMed] [Google Scholar]
- 9.Carvalho LAC, Correia MDL, et al Accuracy of delirium risk factors in adult intensive care unit patients. Rev Esc Enferm USP. 2022;5:e20210222. doi: 10.1590/1980-220X-REEUSP-2021-0222. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Tasbihgou RS, Absalom RA Postoperative neurocognitive disorders. Korean J Anesthesiol. 2021;74:15. doi: 10.4097/kja.20294. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Greaves D, Psaltis JP, Davis JHD, et al Risk factors for delirium and cognitive decline following coronary artery bypass grafting surgery: a systematic review and meta-analysis. J Am Heart Assoc. 2020;9:e017275. doi: 10.1161/JAHA.120.017275. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Habeeb-Allah A, Alshraideh AJ Delirium post-cardiac surgery: Incidence and associated factors. Nurs Crit Care. 2021;26:150–155. doi: 10.1111/nicc.12492. [DOI] [PubMed] [Google Scholar]
- 13.Iglseder B, Frühwald T, Jagsch C Delirium in geriatric patients. Wien Med Wochenschr. 2022;172:114–121. doi: 10.1007/s10354-021-00904-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Swarbrick CJ, Partridge JSL Evidence-based strategies to reduce the incidence of postoperative delirium: a narrative review. Anaesthesia. 2022;77:92–101. doi: 10.1111/anae.15607. [DOI] [PubMed] [Google Scholar]
- 15.Dzubur A, Gacic E, Mekic M Comparison of Patients with Acute Myocardial Infarction According to Age. Med Arch. 2019;73:23–27. doi: 10.5455/medarh.2019.73.23-27. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Mossello E, Baroncini C, Pecorella L, et al Predictors and prognosis of delirium among older subjects in cardiac intensive care unit: focus on potentially preventable. Eur Heart J Acute Cardiovasc Care. 2020;9:771–778. doi: 10.1177/2048872619882359. [DOI] [PubMed] [Google Scholar]
- 17.Marengoni A, Akugizibwe R, Vetrano DL, et al Patterns of multimorbidity and risk of disability in community-dwelling older persons. Aging Clin Exp Res. 2021;33:457–462. doi: 10.1007/s40520-020-01773-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Oliveira FR, Oliveira VH, Oliveira IM, et al Hypertension, mitral valve disease, atrial fibrillation and low education level predict delirium and the worst outcome after cardiac surgery in BMC. Anesthesiol. 2018;18:15. doi: 10.1186/s12871-018-0481-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Pazan F, Wehling M Polypharmacy in older adults: a narrative review of definitions, epidemiology and consequences. Eur Geriatr Med. 2021;12:443–452. doi: 10.1007/s41999-021-00479-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Hoel RW, Connolly RMG, Takahashi PY Polypharmacy Management in Older Patients. Mayo Clin Proc. 2021;96:242–256. doi: 10.1016/j.mayocp.2020.06.012. [DOI] [PubMed] [Google Scholar]
- 21.Mart FM, Roberson WS, Salas B, et al Prevention and management of delirium in the intensive care unit. Semin Respir Crit Care Med. 2021;42:112–126. doi: 10.1055/s-0040-1710572. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Herling FS, Greve EI, Vasilevs kis EE, el at. Interventions for preventing intensive care unit delirium in adults. Cochrane Database Syst Rev. 2018;11:CD009783. doi: 10.1002/14651858.CD009783.pub2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Dworsky JQ, Childers CP, Copeland T, et al Geriatric Events Among Older Adults Undergoing Nonelective Surgery Are Associated with Poor Outcomes. Am Surg. 2019;85:1089–1093. doi: 10.1177/000313481908501003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.O'Mahony R, Murthy L, Akunne A, et al Synopsis of the National Institute for Health and Clinical Excellence. Ann Intern Med. 2011;154:746–51. doi: 10.7326/0003-4819-154-11-201106070-00006. [DOI] [PubMed] [Google Scholar]
- 25.Jin Z, Hu J, Ma D Postoperative delirium: perioperative assessment, risk reduction, and management. Br J Anaesth. 2020;125:492–504. doi: 10.1016/j.bja.2020.06.063. [DOI] [PubMed] [Google Scholar]
- 26.Wang J, Ji Y, Wang N, el at Establishment and validation of a delirium prediction model for neurosurgery patients in intensive care. Int J Nurs Pract. 2020;26:12818. doi: 10.1111/ijn.12818. [DOI] [PubMed] [Google Scholar]
- 27.Corli O, Santucci C, Uggeri S, et al Factors for Timely Identification of Possible Occurrence of Delirium. Adv Ther. 2021;38:4289–4303. doi: 10.1007/s12325-021-01814-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Lim Z, Ling N, Ho VWT, et al Delirium is significantly associated with hospital frailty risk scores derived from administrative data. Int J Geriatr Psychiatry. 2023;38:5872. doi: 10.1002/gps.5872. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Braune S, Gurlit S Prevention of delirium in the intensive care unit. Dtsch Med Wochenschr. 2019;144:1611–1618. doi: 10.1055/a-0666-3947. [DOI] [PubMed] [Google Scholar]
- 30.Hwang SR, Hwang Sw, Chu YC, et al Association of sleep terror, walking or talking and tinnitus. J Formos Med Assoc. 2021;120:145–149. doi: 10.1016/j.jfma.2020.03.014. [DOI] [PubMed] [Google Scholar]
- 31.Chen X, Lu D, Guo N, Kang Z, et al Left ventricular ejection fraction and right atrial diameter are associated with deep regional CBF in arteriosclerotic cerebral small vessel disease. BMC Neurol. 2021;21:67. doi: 10.1186/s12883-021-02096-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Correale M, Altamura M, Carnevale R, et al Delirium in heart failure. Heart Fail Rev. 2020;25:713–723. doi: 10.1007/s10741-019-09842-w. [DOI] [PubMed] [Google Scholar]
- 33.Tian Y, Ji B, Diao X, Wang C, et al Dynamic predictive scores for cardiac surgery-associated agitated delirium: a single-centre retrospective observational study. J Cardiothorac Surg. 2023;18:219. doi: 10.1186/s13019-023-02339-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Stollings Jl, Kotfis K, Chanques G, et al Delirium in critical illness: clinical manifestations, outcomes, and management. Intensive Care Med. 2021;47:1089–1103. doi: 10.1007/s00134-021-06503-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Fong TG, Inouye SK The inter-relationship between delirium and dementia: the importance of delirium prevention. Nat Rev Neurol. 2022;18:579–596. doi: 10.1038/s41582-022-00698-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Diouf F, Hoang B, Bammatter L, et al Hypoactive delirium. Rev Med Suisse. 2023;19:1282–1285. doi: 10.53738/REVMED.2023.19.833.1282. [DOI] [PubMed] [Google Scholar]
- 37.Cortés-Beringola A, Vicent L, Martín-Asenjo R, et al Diagnosis, prevention, and management of delirium in the intensive. Am Heart J. 2021;232:164–176. doi: 10.1016/j.ahj.2020.11.011. [DOI] [PubMed] [Google Scholar]
- 38.Wei B, Feng Y, Chen Q, et al Risk factors for emergence agitation in adults after general anaesthesia: A systematic review and meta-analysis. Acta Anaesthesiol Scand. 2021;65:719–729. doi: 10.1111/aas.13774. [DOI] [PubMed] [Google Scholar]
- 39.Juan Pablo Ospina, Franklin King IV, Elizabeth Madva, et al Epidemiology, mechanisms, diagnosis, and treatment of delirium: a narrative review. Clinical Medicine and Therapeutics. 2021;1:3. [Google Scholar]
- 40.Lee Y, Lee J, Kim J, et al Non-Pharmacological Nursing Interventions for Prevention and Treatment of Delirium in Hospitalized Adult Patients: Systematic Review of Randomized Controlled Trials. Int J Environ Res Public Health. 2021;18:8853. doi: 10.3390/ijerph18168853. [DOI] [PMC free article] [PubMed] [Google Scholar]