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Abstract

Introduction

Several extrinsic factors contribute to the development of cardiac dysrhythmias. In intensive care unit (ICU) settings and among critically ill patients who are exposed to a large number of risk factors, cardiac disturbances are more common.

Objectives

This study aimed to examine the epidemiology, risk factors, and outcome of cardiac dysrhythmias in a non-cardiac ICU.

Methods

This is a retrospective, single-center, observational study conducted in a tertiary noncardiac ICU at Imam Khomeini Hospital in Ahvaz, Iran. Out of the 360 adult patients aged 18 years and older who were admitted to ICU for longer than 24 h, 340 cases who met the study inclusion criteria were recruited between March 2018 until October 2018.

Results

The most common nonsinus dysrhythmias were new-onset atrial fibrillation (NOAF) (12.9%) and ventricular tachycardia (21 patients—6.2%). According to our results, previous percutaneous coronary instrumentation, acute kidney injury, sepsis, and hyperkalemia act as risk factors in the development of cardiac dysrhythmias. Additionally, we found out that thyroid dysfunction and pneumonia can predict the development of NOAF in critically ill patients. The estimated mortality rate among patients with NOAF in this study was 15.7% (p < .05).

Conclusion

Cardiac dysrhythmias are common in ICU patients and treating the risk factors can help to prevent their development and improve patient management and outcome.

Keywords

dysrhythmia atrial fibrillation intensive care units

Introduction

Background: In the intensive care unit (ICU) and during the course of critical illness, cardiac disturbances are more common (Bosch et al., 2018). In the development of cardiac dysrhythmias, several factors act as risk factors in the noncardiac ICU. These include advanced age, electrolyte disturbances, commonly used medications, sepsis, and septic shock (Steinberg, 2018). Critically ill patients are exposed to a large number of these risk factors, and this may result in the development of dysrhythmias in their course of ICU admission (Kozik & Wung, 2012). Additionally, cardiac dysrhythmia is associated with higher mortality in critically ill patients (Tongyoo et al., 2013).

Review of Literature: Atrial fibrillation (AF) is the most common dysrhythmia and cardiac complication in ICU setting and among critically ill patients (Reinelt et al., 2001). In previous studies, the lifetime risk of developing AF in the community was estimated to be 25% (Echeverría et al., 2020). AF is known to increase the risk for numerous cardiovascular diseases including stroke, heart failure, and other comorbidities (Lahdenoja et al., 2018). ICU clinicians are fully familiar with AF because they encounter either preexisting or new-onset AF (NOAF) among nearly one in every three critically ill patients (Artucio & Pereira, 1990). It has been reported that AF is also associated with poor outcomes (Tongyoo et al., 2013; Yoshida et al., 2018).

The aim of the present study was to determine the prevalence of cardiac dysrhythmias, their predictors, and their outcome in critically ill patients. Additionally, we also evaluated the incidence of NOAF and its risk factors and outcome in our ICU setting. To the best of our knowledge, no such comprehensive study has yet been conducted in Iran.

Methods

Design: This is a retrospective, single-center, observational study conducted in a tertiary university hospital in Ahvaz, Iran. This hospital has a noncardiac, medical-surgical intensive care unit (ICU) with 32 beds. The present study was carried out based on the patient record review.

Research objectives: Our primary objective was to determine the prevalence of cardiac dysrhythmias in the ICU setting and describe the characteristics of patient risk factors associated with the development of cardiac dysrhythmias. We also assessed the incidence of NOAF and its association with risk factors and patient outcomes.

Sample: All adult patients were admitted to the ICU.

Inclusion Criteria: All 360 adult patients aged 18 years and older admitted to ICU for longer than 24 h, between March 2018 until October 2018 were included in this study.

Exclusion Criteria: Patients with inadequate electrocardiogram (ECG) recording data and those having a permanent pacemaker or automated implantable cardioverter defibrillator, as well as postcardiac surgery patients were excluded from the study. We also excluded patients with a history of chronic persistent or paroxysmal AF or patients developing AF in the first 2 h of admission to ICU.

Out of the 360 patients, 340 met the criteria and entered the study. For each patient, the following data were obtained and included in relevant forms: demographic information (age and sex), history of heart disease (ischemic heart disease (IHD), hypertension, heart failure, recent myocardial infarction), history of coronary angiography, coronary artery bypass graft surgery, valve replacement surgery, comorbidities such as acute or chronic renal failure, thyroid diseases, sepsis, chronic obstructive pulmonary disease (COPD), pulmonary embolism (PE), acute respiratory distress syndrome, deep vein thrombosis, electrolyte disturbances (metabolic acidosis or alkalosis, hyperkalemia >4.5 meq/L, hypokalemia < 3.5 meq/L, hyponatremia <136 meq/L), history of opium addiction, and outcome of the disease (discharged or expired). In the course of data collection, we came across other comorbidities such as pneumonia, peritonitis, pancreatitis, urinary tract infection, pleural effusion, asthma, bronchiectasis, lung collapse, lung abscess, aspiration, and tracheal stenosis which were extracted and entered into our forms for further investigations.

Another form was prepared for organizing the data on cardiac dysrhythmias. All patients were under continuous ECG monitoring and daily 12-lead ECG. Patients were screened by ICU nursing and physicians for the development of cardiac dysrhythmias based on ECG monitoring and records. The presence or absence of cardiac dysrhythmias was assessed and confirmed based on cardiac counseling with a cardiologist. In this study, we recorded all kinds of cardiac dysrhythmias present in our ICU patients, which were then confirmed by the cardiologist.

Institutional and Ethical Approval: This study was approved by the Ethics Committee of Ahvaz Jundishapur University of Medical Sciences in June 2019 (Ref. ID: IR.AJUMS.REC.1398.189). Written informed consent was waived because of the observational and document-based nature of this study which involved no intervention.

Statistical Analysis: Continuous variables were summarized by mean ± standard deviation. Categorial variables were summarized as frequency and percentages. The normality of the data was assessed using the Kolmogorov-Smirnov test and the quantile-quantile plot. Chi-square test was used to assess the association between categorical variables. Significance level was set at .05, and all analyses were performed using SPSS version 24. (SPSS Inc., Chicago, IL, USA).

Results

Sample Characteristics: In this study, 340 patients were assessed. The mean age of patients was 57.56 ± 23.10 years, and 186 (54.7%) were male and 154 (45.3%) were female.

Research Question Results: According to our results, 132 (38.8%) patients had no dysrhythmia while 208 (61.2%) patients had one of the following dysrhythmias in their course of treatment: Sinus dysrhythmias, including sinus tachycardia (44 patients—12.9%) and sinus bradycardia (87 patients—25.6%) and nonsinus dysrhythmias including NOAF (44 patients—12.9%), ventricular tachycardia (21 patients—6.2%), atrioventricular block (1 patient—0.3%), and Bundle branch block (11 patients—3.2%).

We investigated the relationship between the presence of dysrhythmias and patients’ medical conditions, electrolyte disturbances and outcomes (Table 1). provides information about the prevalence and association between the mentioned variables and the presence of dysrhythmia. According to the obtained results, there was a significant relationship between the presence of dysrhythmias and the older age of patients. (p-value <.001). Among patients who developed dysrhythmia in their course of treatment, 103 (55.4%) and 105 (68.2%) were male and female, respectively. No significant relationship was observed between the presence of dysrhythmias and sex (p-value > .05). Also, 26 patients (7.6%) had a history of opium addiction, according to our results, there was no significant association between opium addiction and the presence of dysrhythmias (p-value > .05).

Table 1.

Prevalence of Medical Conditions in Participants and Their Correlation to Presence of Dysrhythmias.

Medical condition	Prevalence (%)	Dysrhythmia prevalence (%)	OR (CI 95%)	P value
Previous PCI	22 (6.5%)	19 (86.4%)	3.94 (1.14–13.60)	.20*
Previous CABG	16 (4.7%)	9 (56.3%)	2.35 (0.26–21.27)	.435
Previous valvular surgery	7 (2.1%)	6 (85.7%)	3.83 (0.144–2.89)	.449
IHD	49 (17.4%)	46 (46%)	0.199(0.144–5.81)	.199
HF	52 (15.3%)	42 (80.8%)	2.32 (0.81–6.66)	.111
Recent MI	15 (4.4%)	14 (93.3%)	0.614 (0.54–0.69)	.267
Hypertension	125 (36.8%)	82 (65.6%)	1.389 (0.87–2.21)	.166
Acute kidney injury	72 (21.2%)	54 (75%)	2.92 (1.58–5.51)	.001*
Chronic kidney injury	47 (13.8%)	32 (68.1%)	0.771 (0.17–3.50)	.736
Pneumonia	27 (8.0%)	16 (59.3%)	1.174 (0.46–2.99)	.737
Peritonitis	16 (4.7%)	13 (81.3%)	1.049 (0.34–3.20)	.934
Sepsis	63 (18.5%)	55 (87.3%)	5.37 (2.44–11.8)	<.001*
COPD	19 (5.6%)	12 (63.2%)	2.107 (0.68–6.54)	.190
Pleural effusion	21 (6.2%)	16 (76.2%)	1.800 (0.64–5.08)	.262
Asthma	10 (2.9%)	9 (90.0%)	4.792 (0.59–38.77)	.106
Pulmonary embolism	13 (3.8%)	10 (76.9%)	1.771 (0.47–6.69)	.391
DVT	4 (1.2%)	2 (40.0%)	1.75 (0.18–17.05)	.625
ARDS	5 (1.5%)	4 (80.0%)	0.577 (0.08–4.15)	.582
Lung abscess	5 (1.5%)	4 (80.0%)	0.190 (0.20–1.85)	.111
Aspiration	13 (3.8%)	8 (61.5%)	1.169 (0.34–3.96)	.803
Thyroid disease	15 (4.4%)	10 (66.7%)	1.63 (0.51–5.24)	.408
Metabolic acidosis	117 (34.4%)	90 (76.9%)	1.117 (0.60–2.07)	.728
Metabolic alkalosis	23 (6.8%)	16 (69.6%)	1.34 (0.53–3.35)	.839
Hyperkalemia	37 (10.9%)	32 (86.5%)	2.286 (1.15–4.53)	.016*
Hypokalemia	21 (6.2%)	13 (61.9%)	0.629 (0.58–0.68)	.186

Significance level <.05. OR = odds ratio, CI = confidence interval; PCI = percutaneous coronary instrumentation; CABG = coronary artery bypass graft; IHD = ischemic heart disease; HF = heart failure; MI = myocardial infarction; COPD = chronic obstructive pulmonary disease; DVT = deep vein thrombosis; ARDS = acute respiratory distress syndrome.

In this study, we assessed the incidence of NOAF and the relationship between the presence of NOAF and participants’ medical conditions and electrolyte disturbances (Table 2). We found that 25 (16.2%) and 18 (9.7%) patients who presented with NOAF were female and male, respectively. No significant association was found between NOAF and sex (p value >.05). In addition, 4 (15.4%) cases with NOAF had a history of opium addiction, and we found no significant association between these two variables (p value > .05).

Table 2.

Prevalence of Medical Conditions in Participants and Their Correlation to Presence of NOAF.

Medical condition	NOAF prevalence (%)	OR (CI 95%)	P value
Previous PCI	3 (13.6%)	1.097 (0.31–3.88)	.855
Previous CABG	2 (12.5%)	0.836 (0.776–90.33)	.064
Previous valvular surgery	3 (42.9%)	0.871 (0.84–0.91)	.348
IHD	12 (20.3%)	2.123 (0.691–6.53)	.183
HF	12 (23.1%)	1.842 (0.61–5.58)	.277
Recent MI	4 (26.7%)	5.87 (0.35–97.19)	.165
Hypertension	17 (13.6%)	1.14 (0.59–2.21)	.687
Acute kidney injury	10 (13.9%)	1.149 (0.54–2.46)	.721
Chronic kidney injury	8 (17%)	0.87 (0.84–0.91)	.331
Pneumonia	4 (14.8%)	3.049 (1.11–8.34)	.023*
Peritonitis	4 (25%)	1.159 (0.25–5.36)	.851
Sepsis	4 (22.2.%)	1.95 (0.52–7.29)	.314
COPD	2 (10.5%)	0.392 (0.51–3.02)	.354
Pleural effusion	3 (14.3%)	0.756 (0.17–3.38)	.715
Asthma	2 (20.0%)	0.86 (0.11–7.05)	.889
Pulmonary embolism	2 (15.4%)	0.619 (0.078–4.92)	.648
DVT	1 (20.0%)	0.872 (0.84–0.91)	.445
ARDS	1 (20.0%)	0.872 (0.84–0.91)	.445
Lung abscess	2 (40.0%)	0.872 (0.84–0.91)	.445
Aspiration	3 (23.1%)	1.4 (0.29–6.62)	.761
Thyroid disease	6 (40.0%)	5.19 (1.75–15.41)	.001*
Metabolic acidosis	19 (16.2%)	1.84 (0.84–4.01)	.121
Metabolic alkalosis	4 (17.4%)	1.04 (0.29–3.65)	.478
Hyperkalemia	7 (18.9%)	1.247 (0.54–2.86)	.603
Hypokalemia	3 (14.3%)	0.872 (0.84–0.91)	.510

Significance level <0.05. OR = odds ratio; CI = confidence interval; PCI = percutaneous coronary instrumentation; CABG = coronary artery bypass graft; IHD = ischemic heart disease; HF = heart failure; MI = myocardial infarction; COPD = chronic obstructive pulmonary disease; DVT = deep vein thrombosis; ARDS = acute respiratory distress syndrome; NOAF = new-onset atrial fibrillation.

In this study, the survival and mortality of the patients studied were 63.5% (216 out of 340) and 36.5% (124 out of 340). The mortality rate of patients with dysrhythmia was 12.58%, and there was a significant relationship between the presence of dysrhythmia and mortality (p value <.001; OR: 24.122; CI: 13.470–43.198). Estimated prevalence of NOAF was 12.6% (43 out of 340 cases). The mortality rate of patients with NOAF was 21%, and a significant association was observed between the presence of NOAF and mortality (p value < .05; OR: 2.378; CI: 1.104–5.16).

Discussion

In this comprehensive observational study, we determined the prevalence of cardiac dysrhythmias and their association with the existing risk factors in patients admitted to noncardiac, medical-surgical ICUs in our tertiary center. We evaluated the prevalence of cardiac dysrhythmia as 61.2% in our setting, this surprising prevalence may be due to underlying cardiac problems, surgical procedures, pain, indwelling catheters, or electrolyte imbalances. Dysrhythmias in our study were more common among patients with older age, and this could be due to the fact that elderly patients are more likely to suffer from comorbidities and severe illnesses, and to develop dysrhythmias in their course of treatment (Duarte et al., 2017).

In this study, the most common dysrhythmia among the studied patients was sinus bradycardia (87 patients—25.6%), which could be explained by underlying heart diseases, prescription of sedatives and opioid analgesics, and the use of beta-blockers and calcium channel blocking agents. Sinus tachycardia in 12.9% of the patients could be attributed to nonspecific etiologies such as dehydration, pain, systemic inflammatory response syndrome, sepsis, and the use of vasopressors (Dopamine, Dobutamine), beta-agonists (Salbutamol) and anticholinergic agents (Atrovent). The incidence of new-onset AF (NOAF) in our study was 12.6%. According to previous studies, the incidence of NOAF varies, ranging from 4.5% to 29.5% in a mixed ICU, 13.8% in a medical ICU, and 5.5% in surgical ICU (Yoshida et al., 2015), which is in line with our results. The most common reasons for the high prevalence of NOAF are the same as those of sinus tachycardia in addition to the history of heart failure and hypertension.

We evaluated the association between any medical condition that the admitted patients had and the presence of dysrhythmias. According to our result, patients with a history of recent MI were nine times more likely to develop dysrhythmia. We also found that the following act as risk factors for developing dysrhythmias in critically ill patients: IHD cases undergoing percutaneous coronary instrumentation, acute kidney injury (AKI), sepsis, thyroid dysfunction, and hyperkalemia. Consistent with our findings, it has been reported in previous studies that in critically ill patients, high rates of dysrhythmia, and cardiac arrest were seen in patients with a history of recent MI, metabolic acidosis, and hyperkalemia (Francis Stuart et al., 2016; Yan et al., 2012); Yokata et al. found a significant association between hyperkalemia and developing NOAF (Yokota et al., 2018). Ross et al. also reported a significant association between developing AF and hyperthyroidism (Ross et al., 2016). According to Tongyoo et al. and Yoshida et al., older patients with prior cardiovascular and respiratory diseases, sepsis, and septic shock are more likely to develop cardiac dysrhythmia and NOAF in noncardiac ICUs (Tongyoo et al., 2013; Yoshida et al., 2015). Consistent with our findings, Klouwenberg et al. reported that inflammation, regardless of the presence of infection, may play a role as a risk factor for developing AF (Klein Klouwenberg et al., 2017). In some studies, it is stated that anti-inflammatory agents such as glucocorticoid and statins might decrease the incidence of AF (Jacob et al., 2014).

Duby et al. reported that a history of heart disease, heart failure, and hypertension was significantly more common in patients who developed NOAF (Duby et al., 2017). Other studies also reported hypertension as a predictor of dysrhythmia, especially NOAF (Lip et al., 2017). However, we found no significant association between hypertension and dysrhythmia. Pathophysiology of developing dysrhythmias in hypertensive patients depends on different factors such as hemodynamic changes, atrial and ventricular structural remodeling, left ventricular diastolic dysfunction, neuroendocrine factors, and circadian rhythm of blood pressure (Eguchi et al., 2012). A possible explanation for the discrepancies between our results and those of the mentioned studies can be the degree and severity of these factors in our studied patients.

In line with our findings, Ronco et al. reported cardiovascular complications such as HF, MI, dysrhythmias, and cardiac arrest in patients with AKI (Ronco et al., 2008). In contrast with our findings, however, previous studies found CKD as a risk factor for the presence of dysrhythmia and AF especially in patients on dialysis (Turakhia et al., 2018), which may be due to the limited cases of CKD in our study.

Our patients with a history of CABG or cardiac valve replacement surgery were less likely to develop NOAF, which is consistent with some previous studies (Kannel et al., 1982) but in contrast with others (Kalra et al., 2019; Thorén et al., 2020). These differences could be attributed to the fact that we did not evaluate postcardiac surgical patients or to the small number of our patients who had a history of heart surgery.

We found no significant association between ARDS and COPD with the presence of dysrhythmia; In contrast, Yokata et al. reported that patients with ARDS who require mechanical ventilation are susceptible to develop NOAF (Yokota et al., 2018). Also, based on a study conducted by Ambrus et al., NOAF during ARDS was associated with an increased risk of mortality (Ambrus et al., 2015). Previous studies also reported higher rates of different types of dysrhythmias such as supraventricular dysrhythmia in patients with COPD (Kong et al., 2020). Possible explanations for these differences can be different severity of diseases, the need for mechanical ventilation, and/or different characteristics of the evaluated patients.

Previous studies have discussed that there is a bidirectional association between PE, and AF, in that AF in these patients can be both the cause and the consequence of PE (Lutsey et al., 2018). PE results in abrupt increase in pulmonary vascular resistance due to the occlusion which results in right ventricular failure and enlargement, which could further result in tricuspid valve regurgitation and AF development (Matthews et al., 2008). These differences could be explained by the small number of evaluated patients with this medical condition or the different severity of diseases in our population. Our findings suggest that there is no association between the presence of dysrhythmia and opium addiction, which is consistent with other studies (Butler et al., 2011).

Our findings also revealed high mortality rates among patients with dysrhythmia (12.58%) especially those with NOAF (21%). This mortality rate is less than the overall mortality rate of critically ill patients (36.5%). This relatively high-mortality rate is similar to the findings of some other studies on mixed critical care units (Abuhasira et al., 2022; Rimachi et al., 2007). Consistent with our results, it has been reported that new-onset AF is associated with a greater need for organ support and ventilation, resource utilization, longer ICU and hospital stay, and higher mortality among patients admitted in noncardiac ICUs (Duby et al., 2017). In Brown et al., the mortality rate of patients with NOAF in surgical ICU was reported to be 21% (Brown et al., 2018). Previous studies have shown that AF is also associated with mechanical ventilator weaning failure. A meta-analysis has also shown a higher mortality rate among patients with sepsis who developed AF (Gandhi et al., 2015). This increased risk of mortality can be due to an increased risk of embolic stroke or simply be a marker of multiorgan failure. However, further studies are required to find the reasons for high mortality rates among patients with NOAF and explore whether NOAF is an independent predictor of mortality or it is only a marker of severe illness. Findings of such studies suggest that the consequences of cardiac dysrhythmias and NOAF may be prolonged and affect general health or be a marker of poor outcome with worse morbidity and mortality over time. Therefore, identifying the risk factors of cardiac dysrhythmias in ICU setting helps preventing it. Preventive measures may include optimizing IHD, HTN, and HF condition by a cardiologist, proper anticoagulation for DVT and PTE prophylaxis, optimizing kidney function by a nephrologist, optimizing thyroid function by an endocrinologist, proper treatment of infections, correction of electrolyte disturbances, adequate analgesia, treatment of anxiety, and optimization of lung function before elective surgery and during hospitalization. These measures can potentially improve patient outcomes and reduce the difficult short- and long-term management of critically ill patients.

Study Strengths and Limitations

This study has several strengths: To the best of our knowledge, it is the first comprehensive scholarly attempt to determine the incidence of new-onset AF and the prevalence of other cardiac dysrhythmias and their predictors in ICU setting in Iran. It also included a careful evaluation of the medical-surgical ICU patients, focusing on specific medical conditions.

Our study, however, has several limitations: It is a single-center, retrospective study, so results might need validation using separate datasets in future studies. Second, the reasons for high mortality in patients with dysrhythmias are unclear and will require further investigation. In addition, genetic conditions, the treatments used, lifestyle, psychological status, environmental factors, or other reasons may be associated with cardiac dysrhythmias.

Implications for Practice

Results of this study have important implications for critical care givers (nurses and doctors) in terms of the prevalence and predisposing factors of cardiac dysrhythmias in critically ill patients and how to prevent them.

Conclusion

Cardiac dysrhythmias are common in ICU patients and identifying its risk factors can help prevent its development and improve patient management and outcomes.

Footnotes

Acknowledgments

Thanks to Yasaman Sheikhi MD, for implementation of this research as her thesis for the degree of MD (Research number: PAIN-9809).

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Ahvaz Jundishapur University of Medical Sciences, pain research center (grant number PAIN-9809)

ORCID iD

Mohsen Savaie

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Epidemiology,Risk Factors,and Outcome of Cardiac Dysrhythmias in a Noncardiac Intensive Care Unit

Abstract

Introduction

Objectives

Methods

Results

Conclusion

Keywords

Introduction

Methods

Results

Discussion

Study Strengths and Limitations

Implications for Practice

Conclusion

Footnotes

Acknowledgments

Declaration of Conflicting Interests

Funding

ORCID iD

References