Sage Journals: Discover world-class research

Abstract

Background:

Rapid interpretation of electrocardiography (ECGs) is essential for reducing patient mortality and morbidity associated with heart conditions. Despite its significance, many healthcare providers struggle to achieve proficiency in ECG interpretation.

Objective:

This study assessed nurses’ knowledge, practices, and associated factors regarding ECG interpretation in the emergency and intensive care units of selected public hospitals in Addis Ababa, Ethiopia.

Methods:

A cross-sectional study was conducted to evaluate nurses’ knowledge, practices, and factors related to ECG interpretation in selected public hospitals of emergency and intensive care units in Addis Ababa, Ethiopia. Data were collected using structured, self-administered questionnaires and analyzed using SPSS version 26. Binary logistic regression models were employed to identify associations between the dependent and independent variables.

Results:

Among 255 of the study participants, only 60 (23.5%) and 69 (27.1%) of them demonstrated good knowledge and practice in ECG strip interpretation, respectively. The most frequently recognized ECG strip was asystole. Factors associated with good knowledge and practice encompassed holding a master’s degree, receiving ECG training, and working in intensive care units.

Conclusion:

This study identified the lack of knowledge and practice among nurses in ECG interpretation. The findings highlight the need for training programs and experience-sharing initiatives to enhance nurses’ proficiency in ECG interpretation which might ultimately improve patient outcomes.

Keywords

electrocardiography knowledge nurse practice

Introduction

Electrocardiography (ECG) is an essential, noninvasive modern tool to assess the electrical activities of the heart.¹ It has a high capacity to detect any abnormalities in people with cardiovascular diseases.^2,3 Cardiovascular diseases have increased worldwide, causing morbidity in half a billion people, and their mortality reached 20.5 million people.⁴ Early ECG and its interpretation enhance patient survival.⁵

Health professionals who work in emergency departments and intensive care units (ICUs), particularly nurses who are the first responders for patients, must be proficient in skills such as ECG interpretation.⁶ The increasing shortage of physicians has shifted the responsibility of ECG interpretation to nurses, making their proficiency essential.^1,6,7 Competency in ECG interpretation requires understanding of the features and concepts of ECG strips, as well as critical thinking skills.⁸ Despite its importance, many healthcare providers struggle with ECG interpretation.⁹ Poor knowledge and practice in ECG interpretation is a global issue that affects both low- and high-income countries. For instance, a study in China found that 70.9% of ICU nurses had low knowledge regarding ECG, which is consistent with findings from a study in Saudi Arabia.^1,10,11 Similarly, studies conducted in Egypt and Addis Ababa indicated that 80% and 90.9% of the nurses studied had unsatisfactory levels of knowledge, respectively.¹¹ This lack of understanding among nurses can lead to inadequate management of potentially life-threatening cardiac arrhythmias.⁶

A nurse who lacks proficiency in ECG interpretation can have significant consequences for patient care, including delays in diagnosis and treatment, medication errors, poor patient outcomes, and complications. In addition, it raises legal and ethical concerns while compromising patient safety, quality of care, and overall healthcare costs.^3,12 Bridging these gaps requires a comprehensive approach that includes specialized training, clinical experience, certification, ongoing education, simulation and skill laboratories, and collaboration among various healthcare disciplines.¹³ However, there is a lack of data regarding the knowledge and practice of nurses in ECG interpretation, specifically in Ethiopia. This study aimed to assess nurses’ knowledge, practices, and associated factors related to electrocardiogram (ECG) interpretation in the emergency and ICUs of selected public hospitals in Addis Ababa, Ethiopia.

The insights gained from this study in Addis Ababa could serve as a model for other regions facing similar healthcare challenges related to the lack of knowledge and practice among nurses on ECG interpretation. Sharing best practices through publications or conferences could help disseminate knowledge about ECG interpretation.¹ Collaborating with international health organizations could facilitate research opportunities that further explore the effectiveness of this approach across diverse settings.¹¹ However, further research is necessary to address existing knowledge gaps and refine methodologies for effectively assessing its impact. The outcomes could enhance ECG interpretation knowledge and practice among healthcare professionals, particularly nurses, ultimately improving patient care in emergency rooms and ICUs. By focusing on policy implications and operational practices tailored to local contexts such as Addis Ababa, healthcare systems can better prepare for future challenges while improving patient outcomes. Many studies focus on specific contexts or populations, making it challenging to generalize findings across different healthcare settings. There is a need for more comprehensive studies that explore various factors influencing the knowledge and practice gap among nurses in ICUs and emergency rooms on ECG interpretation.

Method

Study design, area, and period

An institution-based cross-sectional study was conducted in five randomly selected public hospitals in Addis Ababa, Ethiopia, from March to April 2024. These hospitals include Tikur Anbessa Specialized Hospital, St. Peter Specialized Hospital, AaBet Referral Hospital, Menelik Referral Hospital, and Zewditu Memorial Hospital, focusing on the emergency and ICUs.

Inclusion criteria: All nurses with at least 6 months of work experience during the data collection period in the randomly selected public hospitals were included in the study.

Exclusion criteria: All nurses who were unavailable during the study period due to maternity leave, annual leave, or sick leave were excluded.

Sample size determination: The sample size was calculated using a single population proportion formula. n, where n the is required sample size, Zα/2 is the critical value of the standard normal distribution at the desired confidence level (95% confidence, Zα/2 = 1.96), d is the margin of error (precision of the estimate), and P is the estimated population proportion (set at 0.5 due to the lack of prior studies in both emergency and ICU in Ethiopia, which gives the maximum sample). The study population was less than 10,000; therefore, a sample size correction formula was applied, nadj = . After adding a 10% non-response rate, the total final sample size was 277.

Sampling method and procedure

This study employed a stratified random sampling method to enhance the representativeness and generalizability of the findings. First, five public hospitals in Addis Ababa with ICU and emergency department setups were selected using the lottery method of simple random sampling from a pool of 12 eligible public hospitals. The sample size was proportionally allocated to each hospital and department based on their nurse population size to ensure balanced representation. Within each hospital stratum, simple random sampling was used to select individual nurses until the required sample size was achieved. The use of stratification and random selection reduces selection bias and enhances the likelihood that the sample reflects the broader nursing population within similar hospital contexts.

While the sample focuses on public hospitals, the diversity across multiple hospitals and departments allows cautious generalization of findings to nurses working in comparable clinical settings in other public hospitals. However, generalizability to nurses in private hospitals or non-hospital care settings may be limited due to possible differences in organizational structures, resources, and patient populations. Future research could extend sampling to include private and non-hospital nursing staff to further validate applicability across broader nurse populations.

Data collection tool

A structured, self-administered questionnaire was used for data collection. The questionnaire was adapted from various sources^1,9,10,13,14 and ECG interpretation guidelines,¹⁵ and it was modified to fit the participants’ characteristics. Therefore, it was validated by two experts, one from the English, and the other from the course expert. The reliability of the tool was determined from the pretest results, yielding Cronbach’s alpha of 0.825. The questionnaire comprised three sections: The first section focused on the demographic characteristics of the nurses and included 12 questions. The second section consisted of 12 true or false questions assessing the nurses’ knowledge of ECG interpretation. The third section evaluated nurses’ practices in ECG interpretation and management for selected ECG strips, containing 20 multiple-choice questions. This section included 10 12-lead II ECG strips for interpretation.

Operational definition

The scoring system used to categorize knowledge and practice levels was based on a cutoff point of 65%. Nurses who scored more than 65% on knowledge-related questions were classified as having good knowledge, whereas those who scored more than 65% on electrocardiographic interpretation and/or management questions were classified as having good practice.¹¹ This cutoff was selected in line with previous studies assessing healthcare professionals’ knowledge and practice levels, where a threshold was around 60–70.¹¹

Data quality control and management

Two data collectors with a background in research education received training. During the data collection process, the principal investigator checked the data at each point to ensure completeness and identify any missing information. A pretest of the self-administered questionnaire was conducted on 5% of the final sample size at Yekatit 12 Hospital.

Statistical analysis

After verifying completeness, the data were coded and entered into Epi Data version 4.6, then exported to Statistical Product and Social Service (SPSS) version 27 for analysis. Outliers and multicollinearity were checked using standard residuals and the variance inflation factor, respectively, and all variables were a factor over 10. Goodness of fitness was checked using Hosmer–Lemshow test, and all variables showed p value >0.05, indicating fit to logistic regression. Binary logistic regression was used to identify associations between the dependent and independent variables; those with a p value under 0.25 candidates for multivariable analysis. Variables significant at a p value less than 0.05 and with an adjusted odds ratio within the 95% confidence interval were considered factors associated with the knowledge and practice of nurses on ECG interpretation. Results were presented using figures, tables, graphs, and narration.

Results

Socio-demographic characteristics

Of the 277 individuals invited to participate, 255 agreed, resulting in a response rate of 92%. The mean age of the study participants was 30.02 ± 4.7 years, with the majority being male (n = 157, 61.6%). Most participants worked in the emergency department (n = 135, 52.9%), and the majority were college or university graduates holding a bachelor’s degree (n = 188, 73.7%; Table 1).

Table 1.

Socio-demographic characteristics of nurses working in emergency rooms and ICUs of public hospitals in Addis Ababa, Ethiopia, 2024 (n = 255).

Variables	Category	Frequency (N)	Percentage (%)
Sex of the nurses	Male	157	61.6
	Female	98	38.4
Work place	AaBet Hospital	69	27.1
	Menelik Referral Hospital	31	12.2
	St. Peter Specialized Hospital	43	16.9
	Tikur Anbessa Specialized Hospital	66	25.9
	Zewditu Memorial Hospital	46	18.0
Level of education	BSc in ECCN	26	10.2
	BSc in Nursing	188	73.7
	MSc	41	16.1
Area of practice	ICU	135	52.9
	ED	120	47.1
Year of experience	1−5 years	165	64.7
	6−10 years	88	34.5
	11−15 years	2	0.8
BLS training	Yes	94	36.9
	No	161	63.1
ACLS training	Yes	52	20.4
	No	203	79.6
Presence of an ECG machine in the hospital	Yes	248	97.3
	No	7	2.7

ACLS, advanced cardiac life support; BLS, basic life support; BSc, Bachelor of Science; ECCN, Emergency and Critical Care Nurse; ECG, electrocardiogram; ED, Emergency department; ICU, intensive care unit; MSc, Master of Science.

Description of knowledge of ECG interpretation

Good ECG knowledge was defined by a test score above the 65th percentile. Among the 255 participants, only 60 (approximately 23.5%, with a 95% confidence interval of 19.0–29.0) achieved a score that placed them in this upper quartile. Most nurses correctly answered that the “QRS complex represents right and left ventricular depolarization” (n = 207, 81.2%). However, only 125 participants (49%) could appropriately recognize the order of ECG waves and intervals (Table 2).

Table 2.

Description of the knowledge of ECG interpretation of participants working in public hospitals in Addis Ababa, Ethiopia (n = 255).

Knowledge assessment question	Correct, N (%)
The correct order of ECG waves and interval	125 (49)
P wave represents left and right ventricular depolarization	152 (59.6)
QRS complex represents right and left ventricular depolarization	207 (81.2)
T waves represent ventricular depolarization	193 (75.7)
Pathologic Q waves are a sign of previous myocardial infarction	169 (66.3)
Normal PR interval is between 0.12 and 0.20	199 (78)
The ST segment should be flat and isotonic	174 (68.2)
Atrial fibrillation could have a regular rhythm	124 (48.6)
If in an ECG the P wave does not appear, there is conduction problem between the atriums	180(70.6)
Atrial flutter is characterized by a regular ventricular rhythm with a consistent R-R	104 (40.8)
Ventricular fibrillation is characterized by no identifiable P waves and T waves, but the QRS complex is identifiable	68 (26.7)
ST depression in the ECG indicated ischemia myocardium	155 (60.8)

ECG, electrocardiogram.

Description of practice in ECG interpretation

Good ECG practice was defined by a test score above the 65th percentile. Among the 255 participants, only 69 (approximately 27.1%, with a 95% confidence interval of 21.7%–33.0%) achieved a score that placed them in this upper quartile. The practice-related question results indicated that the most frequently known items were interpretation and recognition of sinus bradycardia, 194 (76.1%); asystole, 195 (76.5%); and myocardial infarction (MI), 146 (57.3%). Poor recognition of atrial flutter (33.3%) and supraventricular tachycardia (SVT) (38%) likely reflects both gaps in detailed knowledge and limited clinical exposure. These complex rhythms require specific training and experience to identify accurately. In Ethiopia, ECG interpretation is neither incorporated into the nursing curriculum nor provided as in-service training, contributing to the poor recognition rates. This combination of insufficient formal education and limited hands-on exposure hinders nurses’ ability to confidently identify these arrhythmias. Moreover, more than half of the participants were correctly able to identify the correct management of asystole 165 (64.7%) and MI 152 (59.6%; Table 3).

Table 3.

Description of practice in ECG interpretation of participants working at the public hospital of Addis Ababa, Ethiopia (n = 255).

Practice assessment question	Correct, N (%)
Sinus bradycardia	194 (76.1)
Sinus bradycardia management	174 (68.2)
Ventricular tachycardia	102 (40)
Ventricular tachycardia management	125 (49.0)
Atrial flutter	85 (33.3)
Atrial flutter management	133 (52.2)
Asystole	195 (76.5)
Asystole management	165 (64.7)
Myocardial infraction	146 (57.3)
MI management	152 (59.6)
Second-degree heart block	115 (45.1)
Second-degree heart block management	155 (60.8)
Atrial fibrillation	103 (40.4)
Atrial fibrillation management	127 (49.8)
SVT	97 (38)
SVT management	126 (49.4)
Ventricular fibrillation	97 (38)
Ventricular fibrillation management	96 (37.6)
Sinus tachycardia	106 (41.6)
Sinus tachycardia management	79 (31)

MI, myocardial infarction; SVT, supraventricular tachycardia.

Factors associated with knowledge and practice of ECG interpretation for nurses

The logistic regression model with multivariable analysis revealed that the level of education, workplace, and ECG training were significantly associated with the knowledge and practice of nurses in ECG interpretation. Nurses working in ICUs demonstrated three times more knowledge (adjusted odds ratio (AOR) = 2.79; 95% CI: 1.27–6.16) and practice (AOR = 2.72; 95% CI: 1.26–5.88) in ECG interpretation compared to their counterparts in other departments. In addition, nurses with a master’s degree were six times more likely to possess good knowledge (AOR = 6.74; 95% CI: 2.7–8.45) and five times more likely to practice effectively (AOR = 5.64; 95% CI: 3.41–12.47) than those with a bachelor’s degree. Furthermore, nurses who received ECG training had two times more knowledge (AOR = 2.89; 95% CI: 1.11–7.47) and four times more practice (AOR = 4.31; 95% CI: 1.7–10.94) than those who did not receive any training (Table 4).

Table 4.

Factors associated with knowledge and practice of ECG interpretation for nurses working in emergency rooms and intensive care units of public hospitals in Addis Ababa, Ethiopia.

Variable for knowledge	AOR (with 95% CI)	p Value
Work place
ICU	2.79 (1.27–6.16)	0.011*
Educational level
MSc	6.74 (2.7–8.45)	0. 006**
ECG interpretation training
Yes	2.89 (1.11–7.47)	0.030*
Variable for practice	AOR (with 95% CI)	p Value
Work place
ICU	2.72 (1.26–5.88)	0.011*
Educational level
MSc	5.64 (3.41–12.47)	0.014*
ECG interpretation training
Yes	4.31 (1.7–10.94)	0.002***

Significant at p < 0.05.

AOR, adjusted odds ratio; CI, circumference interval; ECG, electrocardiogram; ICU, intensive care unit; MSc, Master of Science.

Discussion

This study assessed nurses’ knowledge and practice on ECG interpretation, showed that only 23.5% demonstrated adequate knowledge and 27.1% demonstrated explicit good practice. While some ECG components, such as identifying the QRS complex and recognizing MI, were correctly interpreted by most of the participants. Other critical arrhythmia, such as ventricular tachycardia and atrial flutter, showed remarkably lower accuracy. Educational level, clinical area, and prior ECG training emerged as significant factors influencing nurses’ knowledge and practice in ECG interpretation. This highlights the need for ongoing educational support and training programs to enhance nurses’ competence in ECG interpretation.

Our findings align with those of many international studies, reporting suboptimal ECG knowledge among nurses. For instance, a study in China found that 70.9% of ICU nurses had low ECG knowledge,¹² while similar findings were reported in Saudi Arabia¹⁰ and Egypt,² where 61% of nurses could not accurately interpret the ECG 12-lead rhythm. Similarly, Indonesian nurses struggled with the ECG interpretation, with 70.9% showing inadequate skill.¹⁶ A prior study in Addis Ababa showed that 90.9% of nurses had inadequate ECG competence.¹¹ The slight variation in this figure might be explained by the difference in the study population; for instance, ICU nurses in our study demonstrated adequate knowledge levels than nurses working in the emergency room, likely due to ICU nurses having more frequent exposure to cardiac cases, thus might contribute to nurses having better knowledge and skill on ECG interpretation.¹

By contrast, a Spanish study reported that 93% of emergency nurses correctly interpreted ECGs.¹⁷ This stark difference might be attributed to variations in healthcare infrastructure, nurses’ training curricula, and continuing education availability. In addition, many nurses in our study had received cardiac-related training 2–5 years prior, suggesting that knowledge decay over time without refresher courses could contribute to lower ECG competence levels.^5,6 This highlights the critical importance of regular, updated ECG training to maintain proficiency.⁹

More than half of the study participants (50%) were unfamiliar with the correct order of the ECG wave and intervals; this finding contrasts with a Pakistan study, where over 50% answered correctly.¹⁴ Similarly, 51.4% of participants incorrectly believed that atrial fibrillation could have a regular rhythm, whereas 61.5% of Turkish nurses answered this correctly.¹ However, questions related to fundamental ECG components such as the P wave representing atrial depolarization (59.9%), the QRS complex representing ventricular depolarization (81.2%), and ST depression indicating myocardial ischemia (60.8%) were answered correctly by most of the nurses, mirroring results from Turkey and China.^1,12

Regarding ECG practice, the most commonly recognized arrhythmias were asystole (76.5%), sinus bradycardia (76.1%), and myocardial infarction (MI; 57.3%). These rates are somewhat lower than those reported in Turkey, where asystole recognition reached 94.1%,¹ and Pakistan, where 61.7% correctly identified acute MI.¹⁴ Conversely, ventricular tachycardia and atrial flutter were poorly identified, with correct response rates of 40% and 33.3%, respectively. This contrasts sharply with Turkish nurses, who recognized ventricular tachycardia and atrial flutter at rates above 80%.¹ Such discrepancies may reflect differences in training emphasis, clinical exposure, or availability of ECG interpretation resources.^1,14 In Ethiopia, a significant proportion of nurses have limited ECG-related training and poor practice in ECG interpretation, which likely contributes to these lower recognition rates.

A significant difference in ECG knowledge was observed based on the nurses’ work area. ICU nurses demonstrated superior knowledge compared to nurses working in the emergency department, probably due to frequent exposure of ICU nurses to ECG. This increased exposure to cardiac patients and ECG interpretation likely enhances ICU nurses’ skills in ECG. Remarkably, a Pakistani study found the opposite trend, with coronary care and emergency nurses scoring higher than ICU nurses,¹⁴ suggesting that institutional roles and patient distribution critically influence ECG competency.¹⁴

Educational level, such as nurses’ masters’ degree level, also played a role; nurses with a master’s degree performed better than those with bachelor’s or diploma qualifications. This aligns with findings from Malaysia and Saudi Arabia, where higher academic attainment correlated with improved ECG knowledge and practice.¹⁷ These results reinforce the value of advanced education and specialized training in developing clinical competencies.

Our study demonstrated a significant association between prior cardiac-related training and both knowledge (p = 0.006) and practice (p = 0.014) of ECG interpretation. This is consistent with studies from Spain,¹⁷ Turkey,¹ and Malaysia,²⁵ which showed that recent and ongoing training substantially improves nurses’ ECG interpretation skills. However, the effectiveness of training depends on its frequency and recency; outdated training may not sufficiently equip nurses to interpret complex arrhythmias accurately.

The overall low levels of ECG knowledge and practice among nurses in this study highlight a critical gap in emergency and intensive care settings that could impact patient outcomes. Given the demonstrated benefits of training and education, healthcare institutions should prioritize regular, updated ECG interpretation training tailored to nurses’ clinical roles. In addition, integrating ECG competency assessments into professional development and certification processes may help maintain high standards. The differences observed across countries emphasize the influence of healthcare infrastructure, nurse education systems, and resource availability. Future research should explore these contextual factors in greater depth to design targeted interventions that address local challenges. This study briefly highlights potential curriculum gaps in nursing education that may contribute to the poor recognition of certain cardiac rhythms, such as atrial flutter and SVT. This addition underscores the need for strengthened ECG interpretation training within nursing curricula.

Limitation

The study is limited by its cross-sectional design, which restricts the ability to establish cause-and-effect relationships. In addition, private hospitals were excluded due to budget constraints, limiting the generalizability of findings to public hospital settings only, where patient flow, resource availability, and management systems may differ from public hospitals in Addis Ababa. The use of self-reported questionnaires may also introduce response bias, as participants might overestimate or underestimate their knowledge and practices, potentially affecting the accuracy of the results. These factors should be considered when interpreting the findings and applying them to broader nurse populations.

Conclusion

The results showed a lack of knowledge and practice among nurses in Ethiopia, especially in the study setting of Addis Ababa. The precision of responses to specific ECG interpretation questions varied; some questions received high response rates, while most demonstrated lower accuracy. This finding underlined the importance of providing ongoing learning opportunities and experience-sharing programs for nurses. Factors such as educational level, practice area, and previous training significantly affect knowledge and practice on ECG interpretation. Therefore, it is crucial to implement educational programs and continuous training to support nurses in staying updated with the latest advancements in ECG technology.

Implications of the study

This study identified areas where nursing professionals may require supplementary provision. Moreover, it serves as a foundation for initiating training programs, new clinical guidelines, and protocols that emphasize the importance of accurately interpreting ECGs. Moreover, these findings are valuable for policymakers and hospital administrators as they seek to address gaps in staff knowledge, allocate resources effectively, and enhance the quality of care within emergency departments and ICUs.

Footnotes

Acknowledgements

The authors are grateful to the data collectors, the Addis Ababa University College of Health Sciences Department of Emergency and Critical Care, the health professionals in the pediatric emergency unit, and all study participants for their contributions to the study’s success.

Declarations

ORCID iD

Ousman Adal

References

Tahboub

Dal Yilmaz

. Nurses’ knowledge and practices of electrocardiogram interpretation. Int Cardiovasc Res J 2019; 13: 80–84.

Sabaan

. Effect of application of training program about electrocardiogram on nurses competency level and expected clinical outcome of cardiac patients. Egypt J Health Care 2016; 7: 112–124.

Yau

Wong

, et al. Capability of emergency nurses for electrocardiogram interpretation. Int Emerg Nurs 2021; 54: 100953.

Di Cesare

Bixby

Gaziano

, et al. World Heart Report 2023. Confronting the world’s number one killer. Geneva, Switzerland: World Heart Federation, 2023.

Neha

Bist

Dixit

, et al. Knowledge of student nurses regarding interpretation of electrocardiogram: a pre-experimental study. Nurs Healthcare Int J 2019; 3.

Wen

Hong

Chen

, et al. CRISP method with flipped classroom approach in ECG teaching of arrhythmia for trainee nurses: a randomized controlled study. BMC Med Educ 2022; 22: 850.

Supriadi

Kurniawan

Esa

, et al. Record results analysis electrocardiogram (ECG) at Pangandaran Health Center. J Phys Conf Ser 2019; 1179: 012149.

Ibraheem

. Nurses’ knowledge toward electrocardiogram interpretation at Al-Basrah Teaching Hospitals. University of Basrah College of Nursing, 2022.

Amini

Mirzaei

Hosseini

, et al. Assessment of electrocardiogram interpretation competency among healthcare professionals and students of Ardabil University of Medical Sciences: a multidisciplinary study. BMC Med Educ 2022; 22: 448.

10.

Aljohani

. Competency in ECG interpretation and arrhythmias management among critical care nurses in Saudi Arabia: a cross sectional study. Healthcare 2022; 10: 2576.

11.

Belay

Gezahegn

Melaku

, et al. Nurses’ competency on electrocardiography interpretation in adult emergency room: Addis Ababa, Ethiopia, 2021. Multicenter cross-sectional study. Int Emerg Nurs 2024; 74: 101453.

12.

Buluba

. ICU nurses’ knowledge and attitude towards electrocardiogram interpretation in Fujian province, China: a cross-sectional study. Front Med (Lausanne) 2023; 10: 1260312.

13.

Kashou

May

DeSimone

, et al. The essential skill of ECG interpretation: how do we define and improve competency? Postgrad Med J 2020; 96(1133): 125–127.

14.

Yaqoob

Ali

Siddiqui

, et al. 12-Leads electrocardiogram interpretation competency among nurses working in critical care areas at Dow University Hospital, Karachi. J Liaquat Univ Med Health Sci 2023; 22: 174–178.

15.

Rawshani

. Pocket guide to ECG interpretation. 2017. http://www.ecgwaves.com/

16.

Ros

Isa

Fauzi

. Critical care nurses’ competency in electrocardiogram interpretation: a cross-sectional study. Malays J Med Health Sci 2022; 18: 124–131.

17.

Malk

Hassan

. Evaluation of nurses practice regarding electrocardiogram procedure. Sumerianz J Med Healthcare 2018; 1: 24–30.

Knowledge and practice on electrocardiography interpretation among nurses in emergency and intensive care units of selected public hospitals in Addis Ababa,Ethiopia