Background: The typical sign or main symptom in acute coronary syndrome (ACS) patients is chest pain, which is an initial benchmark or early sign for diagnosis. Certain factors, such as gender differences, the presence of diabetes mellitus or other clinical conditions, may make the patient not realize they have ACS. Therefore, this study aims to identify the characteristics of chest pain symptoms in male and female patients with ACS.Design and Methods: This is a non-experimental quantitative study, namely analytical observation using a cross-sectional approach within 4 months (January-April 2019). Furthermore, the samples were 53 ACS patients (28 male and 25 female).Results: The chest pain characteristics that have a significant relationship with gender differences in ACS patients are shown based on the aspects of location, pain duration and quality. Male patients are more likely to feel pain at the left or middle chest, the duration is between <20 to >20 min with moderate pain quality, which tends to become severe, while females are more likely to feel pain at the chest which radiates to the neck and chin, the duration is usually >20 min, with mild to moderate pain quality.Conclusions: The result showed a significant difference in chest pain characteristics in male and female patients with ACS. Regarding location, duration and quality of chest pain, male ACS patients mostly have more typical symptoms, while females’ symptoms are atypical.

Background: Chest pain is considered one of the crucial indicators in detecting acute coronary syndrome (ACS), and one of the most common complaints frequently found in hospitals. Atypical characteristics of chest pain have prevented patients from being aware of ACS. Chest pain symptoms have become ambiguous, particularly for specific parameters, such as gender, diabetes mellitus (DM), or other clinical conditions. Therefore, it is critical for high-risk patients to have adequate knowledge of specific symptoms of ACS, which is frequently associated with late treatment or prehospital delay. Therefore, this study aims to identify the particular characteristics of chest pain symptoms in DM and non-DM patients with ACS.Design and Methods: This is a quantitative and non-experimental research, with the cross-sectional approach used to carry out the analytical observation at a general hospital from January-April 2019. Data were obtained from a total sample of 61 patients, comprising 33 ACS with DM and 28 ACS non-DM patients.Results: The result showed that the characteristic of patients with chest pain symptoms has a significant relation to DM and ACS. Therefore, non-DM patients with ACS are more likely to feel chest pain at moderate to a severe level, while ACS-DM patients are more likely to have low to moderate chest pain levels.Conclusion: The significant differences in the characteristics of chest pain in DM and non-DM patients suffering from acute coronary syndrome are the points of location of chest pain radiating to the neck and quality of pain.

Background: Chest pain misinterpretation is the leading cause of pre-hospital delay in acute coronary syndrome (ACS). This study aims to identify and differentiate the chest pain characteristics associated with ACS. Methods: A total of 164 patients with a primary complaint of chest pain in the ER were included in the study. ACS diagnosis was made by a cardiologist based on the WHO criteria, and the patients were interviewed 48 hours after their admission. Furthermore, every question was analysed using the crosstabs method to obtain the odds ratio, and logistic regression analysis was applied to identify the model of focused questions on chest pain assessment. Results: Among the samples, 50% of them had an ACS. Four questions fitted the final model of ACS chest pain focused questions: 1) Did the chest pain occur at the left/middle chest? 2) Did the chest pain radiate to the back? 3) Was the chest pain provoked by activity and relieved by rest? 4) Was the chest pain provoked by food ingestion, positional changes, or breathing? This model has 92.7% sensitivity, 84.1% specificity, 85% positive predictive value (PPV), 86% negative predictive value (NPV), and 86% accuracy. After adjusting for gender and diabetes mellitus (DM), the final model has a significant increase in Nagelkerke R-square to 0.737 and Hosmer and Lemeshow test statistic of 0.639. Conclusion: Focused questions on 1) left/middle chest pain, 2) retrosternal chest pain, 3) exertional chest pain that is relieved by rest, and 4) chest pain from food ingestion, positional changes, or breathing triggering can be used to rule out ACS with high predictive value. The findings from this study can be used in health promotion materials and campaigns to improve public awareness regarding ACS symptoms. Additionally, digital health interventions to triage patients’ suffering with chest pain can also be developed.