Quality of life for patients after coronary artery bypass grafting surgery

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Mohamed, Menna Ibrahim, Belal Shehata, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5898468/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 21 You are reading this latest preprint version Abstract Background Understanding the quality of life of patients following coronary artery bypass grafting is crucial for improving g post-operative management and long-term patient outcomes. Our study aimed to assess the QoL of patients post-CABG and identify the factors that influence their ability to perform daily activities. Methods This retrospective cross-sectional study was conducted at our cardiac surgery unit. Patients aged 18 years or older who underwent coronary artery bypass grafting surgery and who had completed at least six months of recovery following their surgery were selected through convenience sampling from hospital records. The collected data were reviewed and followed up through phone interviews via the SF-36 questionnaire. Results The study evaluated 139 patients (median age: 61 years; 79.1% male), predominantly Egyptian (98.6%) and married (82.7%). The majority were nonsmokers (45.3%) or ex-smokers (40.3%), with common comorbidities including hypertension (68.3%), dyslipidemia (57.6%), and diabetes mellitus (47.5%). Self-assessed health status was rated as excellent or very good by 46% of the patients. Quality of life, assessed via the SF-36, revealed median scores for physical functioning (40), general health (50), social functioning (77.5), and overall QOL (60). QOL was positively correlated with multiple health domains, particularly physical and role limitations (p < 0.001). Gender analysis indicated that males scored higher in physical functioning (p = 0.007), but no significant differences were observed in overall QOL. Marital status, sleep duration, and hypertension were significant factors influencing QOL, with optimal outcomes linked to 6–8 hours of sleep. Smoking status and family cardiac history had no significant impact on QOL. Conclusion This study highlights quality of life post-CABG, and reveals that ideal sleep duration (6–8 hours), marital status and ex-smoking are key predictors of improved QoL. Hypertension negatively affected QoL, whereas factors, such as comorbidities, smoking, and dyslipidemia were not significantly correlated. The findings stress the need for interventions targeting sleep, hypertension control, and social support during recovery. Further comparative studies are needed to assess QoL in patients undergoing both CABG and PCI. Coronary artery bypass grafting quality of life cardiac surgery ischemic heart disease. Figures Figure 1 Figure 2 Introduction Coronary artery bypass grafting (CABG) remains the most common treatment for advanced coronary artery disease (CAD), the leading cause of morbidity and mortality globally. Demographic changes and lifestyle factors such as smoking, inactivity, and a poor diet all contribute to the spread of CAD. While CABG is the most commonly used revascularization treatment, some people may benefit from other treatments, including percutaneous coronary interventions (PCIs) or hybrid coronary revascularization. However, CABG is widely chosen because of its superior ability to decrease recurrent ischemic episodes, especially in people with multivessel disease or diabetes. [ 1 ] An Italian study conducted in 2009 utilizing the SF-36 questionnaire revealed significant increases in pain relief and physical activity after CABG, stressing the influence on quality of life. [ 2 ] Furthermore, a 2017 study by Puskas et al. showed that CABG, particularly in diabetic patients, produces better long-term outcomes than does PCI. [ 3 ] According to preoperative quality of life (QoL) assessments, patients who undergo coronary artery bypass grafting have considerably poorer health status, with symptoms including chronic chest pain, exhaustion, and heightened anxiety about the treatment and its potential results. A 2020 study conducted in Croatia reported significantly low preoperative QoL ratings, emphasizing the importance of thorough preoperative evaluations in identifying and resolving these difficulties. CABG has been proven to considerably enhance QoL at near term, with patients reporting increased physical performance and alleviation from severe symptoms such as chest discomfort. Long-term outcomes may differ on the basis of patient-specific factors such as age, comorbidities, and adherence to lifestyle adjustments following surgery. [ 1 , 4 , 5 ] Despite these improvements, long-term results reveal a more complicated perspective. While many patients maintain good quality of life in the years following surgery, a significant number may experience health decline due to factors such as aging, comorbidities, or inadequate adherence to lifestyle adjustments.[ 6 ] Quality-adjusted life years (QALYs) are commonly used to assess long-term success, with some studies reporting values of approximately 0.41. Although this value indicates an increase in life expectancy and quality of life, it is considered moderate when compared with other chronic disease operations, implying that post-CABG care and support should be enhanced.‎ Crucially, mental health has a significant effect on these results. According to a Saudi Arabian study, patients who received supportive therapy or had strong family support following surgery reported improved quality of life scores.[ 7 ] These findings emphasize the necessity of comprehensive postoperative care that takes into account both psychological and physical factors to optimize long-term success. Evidence has demonstrated the critical importance of assessing QOL in patients who ‎have undergone CABG. However, there is a considerable lack of evidence on the specific impacts of CABG on the Egyptian population, especially in terms of the level of QOL improvement and the impact of numerous influencing factors.[ 8 ] Smoking, obesity, hypertension, and diabetes are all risk factors for CAD, which is becoming a rising public health issue in Egypt. Cardiovascular disorders (CADs) are the major cause of death in Egypt, accounting for approxiamtely 46% of all deaths. Limited access to advanced healthcare facilities, financial constraints, diagnostic delays, and inadequate preventive strategies make it difficult to address this burden. [ 9 ] These aspects highlight the critical necessity for extensive research to assess CABG outcomes and the role of influencing factors in enhancing the quality of life of Egyptian patients. Patients and methods This was a retrospective cross-sectional study conducted to assess quality of life in patients who underwent coronary artery bypass grafting surgery at the cardiac surgery unit of the cardiothoracic surgery department of Alexandria University, Egypt. This study explored the factors most significantly affecting post-CABG QOL outcomes. By evaluating changes in symptom burden, psychological well-being, and social functioning, this research aimed to assess QoL scores across different domains (physical, psychological, social, and environmental) in post-CABG patients. A total of 139 patients, selected through convenience sampling from hospital records, were included in the study. Participants were included if they were aged 18 years or older and had completed six months or more since their surgery at the time of the survey. Patients were excluded if they had missing or incomplete hospital records, or were unable or unwilling to provide informed consent for participation in the study. Data collection involved telephone interviews lasting 10–20 minutes, and verbal informed consent was obtained. The SF-36 Health Survey was utilized to evaluate patients' QoL, with modifications made to enhance clarity and relevance. [ 10 ] The data sources included demographic information, medical history, and surgical outcomes extracted from hospital records. The variables assessed included independent variables such as age, sex, marital status, severity of pain, mental and physical health, and dependent variables including the ability to perform daily tasks (at home and outside), participation in sports, and social engagement. Responses were scored on a 1–5 scale, where 1 indicated the worst outcome and 5 the best outcome. For participants who agreed, the questionnaire was completed during the call. Statistical analysis Due to our modification and removal of questions from the SF-36 questionnaire, we performed a reliability test, revealing that Cronbach’s alpha indicates that the questionnaire has good internal consistency. The data were analyzed using descriptive and inferential statistics. Descriptive statistics, including frequencies and percentages, were utilized to delineate the sample characteristics based on socio-demographic and clinical variables. Shapiro-Wilk test was used to assess the normality of the data. The quantitative data were presented as the median and interquartile range (IQR). Fisher's exact, chi-square, Mann-Whitney, and Kruskal-Wallis tests were employed to compare groups across many factors. Fisher's exact and chi-square tests were utilized for categorical variables, whereas Mann-Whitney and Kruskal-Wallis H tests were employed for continuous and ordinal variables. Spearman’s correlation coefficient was employed to ascertain independent variables that could affect alterations in the different components of the SF-36 questionnaire following modification. A multivariate regression model was employed to identify independent factors capable of predicting alterations in overall quality of life. The correlation coefficient was computed to assess linear correlations among continuous variables. A p-value less than 0.05 was considered statistically significant. Data analysis was performed via SPSS version 26. Results Baseline Summary The study population included 139 patients, with a median age of 61 years (IQR: 58–67). The majority of patients were male (79.1%), married (82.7%), and Egyptian (98.6%). The majority consisted of nonsmokers (45.3%) and ex-smokers (40.3%). The predominant comorbidities were hypertension (68.3%), diabetes mellitus (47.5%), and dyslipidemia (57.6%). A considerable proportion of individuals presented with two or more comorbidities. Concerning self-assessed health state, the majority of participants classified their health as either excellent (18.7%) or very good (27.3%). The demographic data are presented in Table 1 . Health-Related Quality of Life (SF-36 QOL) Scores The median scores for the six SF-36 domains were as follows: physical functioning (PF) 40 (IQR: 35–75), general health (GH) 50 (IQR: 45–60), social functioning (SF) 77.5 (IQR: 50–100), role limitations due to physical health (RP) 25 (IQR: 0–75), role limitations due to emotional problems (RE) 100 (IQR: 0–100), and bodily pain (BP) 67.5 (IQR: 36.25–100). The median physical component summary (PCS) score was 51.25 (IQR: 35–70), and the overall quality of life (QOL) score was 60 (IQR: 38.75–77.08) Table 1 Baseline characteristics of the included participants. Variable n (%) Age Age (Median (IQR)) 61 (58–67) ≤ 60 61 (43.9%) > 61 78 (56.1%) Gender Male 110 (79.1%) Female 29 (20.9%) Weight (Median (IQR)) 81 (72.5–93) Marital status Married 115 (82.7%) Widow/widower 15 (10.8%) Single 5 (3.6%) Divorced 4 (2.9%) Nationality Egyptian 137 (98.6%) Other 2 (1.4%) Smoking status Nonsmoker 63 (45.3%) Current-Smoker 20 (14.4%) Ex-smoker 56 (40.3%) Smoking-index (Median (IQR)) 1 (0.50-2) Hours of sleep per day More than 10 hours 15 (10.8%) 6–8 hours 77 (55.4%) 4–6 hours 33 (23.7%) 4 hours or less 14 (10.1%) Comorbidities Hypertension 95 (68.3%) Diabetes mellitus 66 (47.5%) Dyslipidemia 80 (57.6%) Two comorbidities Hypertension and diabetes 52 (37.4%) Hypertension and dyslipidemia 66 (47.5%) Diabetes and dyslipidemia 50 (35.97%) Three comorbidities Hypertension, diabetes mellitus and dyslipidemia 44 (31.7%) Others 48 (34.5%) Family history of cardiac diseases 63 (45.3%) Health-status Excellent 26 (18.7%) Very good 38 (27.3%) Good 49 (35.3%) Not bad 15 (10.8%) Bad 11 (7.9%) SF-36 questionnaire domains (Median (IQR)) Physical functioning 40 (35–75) General Health 50 (45–60) Social functioning 77.5 (50–100) Role limitations due to physical health 25 (0–75) Role limitations due to emotional problems 100 (0-100) Pain 67.5 (36.25–100) Physical Component Summary (PCS) 51.25 (35–70) Overall Quality of Life (QOL) 60 (38.75–77.08) Relationship between SF-36 domains and overall quality of life Spearman’s correlation analysis revealed a positive correlations between QOL and various health domains, including the PCS (r = 0.921, p < 0.001), PF (r = 0.679, p < 0.001), RP (r = 0.834, p < 0.001), BP (r = 0.724, p < 0.001), and SF (r = 0.735, p < 0.001). A moderate positive correlation was observed between emotional role limitations (r = 0.775, p < 0.001). The general health domain showed a weaker positive correlation with overall QOL (r = 0.184, p = 0.03). (Table 2 in Supplements) Sex-Based Differences in Quality of Life Comparisons between male and female patients were made. While both genders reported similar general health and social functioning levels, significant differences were observed in median physical functioning scores (60 vs. 45, p = 0.007), where males had higher scores. No significant differences were observed between the sexes for RE, PCS, or overall QOL. (Table 3 ) Males and females who had no hypertension had better QOL scores, as shown in Fig. 1 . While comparing the overall QOL scores in the case of smoking status, we found that in females, there were better results in nonsmokers, whereas in males, ex-smokers had higher scores, as shown in Fig. 2 . Table 3 Association between questionnaire domains based on sex. Variable Male (n = 110) Female (n = 29) Mann-Whitney U P values Median (IQR) Physical functioning 60 (43.75-80) 45 (17.5–67.5) 2113.500 0.007 General Health 52.5 (45–60) 50 (42.5–60) 1750.500 0.511 Social functioning 77.5 (50–100) 80 (50–95) 1645.500 0.790 Role limitations due to physical health 25 (0–75) 0 (0–75) 1762 0.352 Role limitations due to emotional problems 100 (0-100) 100 (50–100) 1399.500 0.257 Pain 70 (37.5–100) 45 (30–100) 1805 0.271 Overall-QOL 61.25 (37.4-79.17) 57.50 (42.083–68.33) 1723 0.507 Significant results refer to p < 0.05 There were significant differences in health dimensions, including physical functioning, social functioning, general health, physical role, emotional, bodily pain, and sleep duration. The group with 6–8 hours exhibited the highest median score for RP. Furthermore, no substantial changes in overall health were observed across the various sleep duration groups. These results suggest that enough sleep (especially 6–8 hours) is linked to better physical and emotional health, whereas shorter sleep durations are associated with poorer outcomes. (Table 4 in Supplement) The Kruskal-Wallis Test was done according to smoking status. There were no significant differences between the different questionnaire domains and smoking statuses (nonsmoker, current-smoker, and ex-smoker) for PF, SF, BP, RP, RE, and GH, with p-values of 0.098, 0.54, 0.794, 0.857, 0.067, and 0.373, respectively. Moreover, marital status strongly influences various health categories. The findings indicated notable PF, SF, BP, RP, and RE variations among marital status groups, with p-values of 0.003, 0.027, 0.011, 0.035, and 0.003, respectively. No significant variation in GH was observed among the marital status categories, with a p-value of 0.165. Demographic and Health-Related Factors Associated with Quality of Life Based on socio-demographic factors, the association of QOL categories revealed that marital status, sleep duration, and comorbidities were significantly associated with QOL. The sex distribution was similar across groups, with no statistically significant difference (χ²=0.085, p = 0.834). Additionally, smoking status did not significantly correlate with QOL (χ²=0.668, p = 0.716). Nevertheless, nonsmokers composed the largest subgroup in both QOL categories. Marital status was significantly associated with QOL (χ²=9.45, p = 0.024); married individuals were more common in the low-QOL group, whereas single participants were found exclusively in the high-QOL group. Sleep duration was also significantly correlated with QOL (χ²=12.077, p = 0.017). Most individuals in the high-QOL group reported 6–8 hours of sleep per night, whereas shorter or longer sleep patterns were more common in the low-QOL group. Hypertension was significantly associated with lower QOL (F = 4.386, p = 0.043). While diabetes mellitus did not considerably affect QOL (F = 0.479, p = 0.498), dyslipidemia had a marginal effect (F = 3.066, p = 0.086). Notably, other health conditions (e.g., respiratory or gastrointestinal issues) were more prevalent among those with lower QOL (F = 9.692, p = 0.002), indicating that additional comorbidities may have a negative impact on life quality. A family history of cardiac disease showed no significant association with QOL (F = 0.188, p = 0.731). (Table 5 ) Table 5 Relation between patients' socio-demographic characteristics and quality of life. Variable High-QOL (n = 80) Low-QOL (n = 59) P values n (%) Age-Median (IQR) 63 (58.50–66.50) 61.50 (53.50–66) Mann-Whitney U 0.773 Weight-Median (IQR) 86 (74.50–95.50) 85.50 (75–101) Mann-Whitney U 0.783 Smoking index- Median (IQR) 1 (0.5-2) 1 (0.5-3) Mann-Whitney U 0.883 Sex F = 0.085 0.834 Male 64 (80%) 46 (78%) Female 16 (20%) 13 (22%) Smoking status X 2 = 0.668 0.716 Nonsmoker 38 (47.5%) 25 (42.4%) Current-Smoker 10 (12.5%) 10 (16.9%) Ex-smoker 32 (40%) 24 (40.7%) Marital status X 2 = 9.45 0.024 Married 71 (88.8%) 44 (74.6%) Widow/widower 8 (10%) 7 (11.9%) Single 0 5 (8.5%) Divorced 3 (5.1%) 1 (1.3%) Hours of sleep per day X 2 = 12.077 0.017 More than 10 hours 7 (8.8%) 8 (13.6%) 6–8 hours 52 (65%) 25 (42.4%) 4–6 hours 18 (22.5%) 15 (25.4%) 4 hours or less 2 (2.5%) 4 (6.8%) Comorbidities Hypertension 49 (61.3%) 46 (78%) F = 4.386 0.043 Diabetes mellitus 40 (50%) 26 (44.1%) F = 0.479 0.498 Dyslipidemia 41 (51.3%) 39 (66.1%) F = 3.066 0.086 Others 19 (23.8%) 29 (49.2%) F = 9.692 0.002 Family history of cardiac diseases 35 (43.8%) 28 (47.5%) F = 0.188 0.731 F refers to Fisher’s test. X 2 = Chi-square test. Significant results refer to p < 0.05 Multivariate analysis A multilinear regression model evaluating the influence of demographic and health variables on overall quality of life indicated that the predictors accounted for 64.3% of the variance in quality of life (adjusted R² = 0.643). Sleep duration (6–8 hours) emerged as the most significant predictor of quality of life, with a strong positive correlation (B = 39.526, Beta = 0.750, p = 0.005). Additionally, high cholesterol was negatively correlated with quality of life (B = -18.096, Beta = -0.346, p = 0.041), indicating that effective management of high cholesterol could enhance quality of life. (Table 6 in Supplements) Discussion Our study assessed the improvement in quality of life after 6 months or more in patients who underwent coronary artery bypass grafting surgery. This is essential because various clinical and sociodemographic factors influence postsurgical QOL. Our research revealed that while patients often experience an initial decline in health-related QOL shortly after surgery, significant improvements can occur within six months or more. According to gender influence, coronary heart disease is more common in males than in females. While considering gender differences in outcomes, we found no statistically significant difference in overall quality of life scores in most domains except for physical function. Yildiz et al. reported that females had lower mean scores than males did in the subdimensions of energy and vitality, social functioning, and pain, with the difference between the groups being statistically significant. [ 11 ]Peric et al. found that male patients also generated higher scores than female patients did. [ 12 ] However, the small number of female patients included in the present study may have affected the findings. While some studies suggest that elderly patients might experience poorer overall quality of life after CABG, our findings showed no relationship between overall QOL and age. Similarly, our findings are consistent with those of a multicenter study in the Netherlands that found no significant association between age and lower physical or mental component scores one year postsurgery. However, the study revealed a decline in mental quality of life in a substantial proportion of patients aged 80 years. [ 13 ] Adequate sleep duration, particularly 6–8 hours per night, is positively associated with better physical and emotional health outcomes post-CABG. Our results also supported that sleeping 6–8 hours was significantly associated with better QOL. In contrast, individuals with shorter or longer sleep durations reported a lower quality of life. Sleep disturbances are common in the postoperative period following CABG and often last several weeks. Factors such as pain, anxiety, and environmental conditions contribute to these disturbances, which can adversely affect recovery and QoL.[ 14 , 15 ] Smoking is consistently identified as a risk factor, which is associated with lower QOL after CABG. Surprisingly, our findings showed that there was no association between smoking status and overall QOL. Numerous studies have shown that smokers usually report lower scores in various quality of life domains, including emotional role, social functioning, and general health, than nonsmokers do. In addition, continued smoking after CABG is associated with a greater risk of death. Interestingly, our study found that ex-smoker males were of better QOL in comparison to other statuses (Fig. 2 ). Smoking cessation is associated with lower rates of postoperative complications and better overall survival rates. [ 16 , 17 ] Multiple comorbidities are linked to a lower quality of life. Our study revealed that HTN was a risk factor for QOL following CABG. Interestingly, we did not find statistically significant associations between QOL and dyslipidemia, DM, or family history of cardiac diseases. Several studies have the positive influence of marriage on various aspects of quality of life after CABG. Our study results revealed that being married, single, divorced, or widowed was significantly associated with QOL, supporting that married person had high quality (Table 5 ). One study found that single individuals had lower mean values across all eight domains of the SF-36 quality of life questionnaire compared to married individuals. The most significant difference was observed in the physical functioning domain. [ 18 – 20 ] Coronary artery bypass grafting and percutaneous coronary intervention (PCI) are two prevalent revascularization techniques for treating coronary artery disease. CABG is frequently preferred for patients with multivessel disease, left main coronary artery disease, or diabetes mellitus due to its greater long-term efficacy in decreasing significant adverse cardiac events and the necessity for recurrent revascularization. Conversely, PCI noted for its minimally invasive technique and reduced recovery duration, is often favored for patients with single-vessel disease or those at elevated surgical risk. Research indicates that whereas CABG is superior in enhancing survival and diminishing disease recurrence in high-risk patients, PCI provides similar advantages in alleviating symptoms and improving quality of life in less complicated cases. Notwithstanding these disparities, new research indicates that both therapies improve patients' physical and mental well-being postsurgery. Consequently, the selection between CABG and PCI must be informed by clinical indications, patient comorbidities, and preferences, utilizing a shared decision-making strategy to guarantee optimal personalized care.[ 3 , 21 – 23 ] Limitations Despite our modifications to the SF-36 questionnaire, a reliability test was performed, revealing that Cronbach’s alpha indicates that the questionnaire has good internal consistency, with a significantly good Cronbach's alpha of 0.913. One of our limitations is that we relied on the retrospective collection of patient data from hospital records. This study demonstrated multiple potential biases that could influence the outcomes. Selection bias was considered due to the exclusion of patients with insufficient data, consequently limiting the generalizability of the results. Response bias might have occurred as the sample included only those patients who consented to and engaged with phone calls for participation. Moreover, survivor bias was an issue, as the study exclusively evaluated patients who survived for a minimum of six months postsurgery. Conclusion This study highlights patient quality of life results following coronary artery bypass grafting. The ideal sleep duration (6–8 hours) and mariatal status were significant predictors of improved quality of life postsurgery. This underscores the importance of adjustable lifestyle factors and social support throughout the recovery period. Hypertension negatively impacted quality of life, although other comorbidities, smoking status, and dyslipidemia exhibited no significant correlations. The results highlight the necessity for focused interventions concerning sleep patterns, hypertension control, and social support in postoperative care. Additional comparative studies are needed to evaluate the quality of life among patients who have undergone CABG and PCI. Declarations Ethics approval and consent to participate Ethical approval was obtained from the IRB at Alexandria Main Hospital. Additionaly, verbal consent was obtained from all participants before they submitted the survey. Conflict of interest All the participants declare that they have no conflicts of interest. Funding This research did not receive any funds. Author Contribution Conceptualization, M.F., N.A., H.Y., A.A. and H.H.; Data curation, M.F., M.I., J.G. and B.S.; Formal analysis, S.F.M.; Methodology, M.F., M.I., S.R. and W.H.; Project administration, A.A., M.I., W.H. and H.H.; Supervision, A.A.; Validation, M.F., B.S., S.F.M., H.Y., J.G. and W.H.; Visualization, N.A., A.A. and W.H.; Writing—original draft, S.R., B.S., and S.F.M.; Writing—review & editing, A.A., S.F.M., M.F., M.I. and H.H. All the authors have read and agreed to the published version of the manuscript. Acknowledgement We would like to extend our heartfelt gratitude to our esteemed colleagues, Dr. Helmy Atef Helmy Elwakil, Dr. Noha Mahmoud Hamada, and Dr. Eslam Maher, for their invaluable assistance in data collection for this study. Their dedication, efforts, and collaborative spirit greatly contributed to the success of this research. We deeply appreciate their time and commitment, which have been instrumental in achieving our objectives. Thank you for your outstanding contributions. References Pačarić S, Turk T, Erić I, Orkić Ž, Erić AP, Milostić-Srb A, et al. Assessment of the quality of life in patients before and after coronary artery bypass grafting (CABG): A prospective study. Int J Environ Res Public Health 2020;17. https://doi.org/10.3390/ijerph17041417. Vincelj J, Bitar L. Quality of life 10 years after cardiac surgery in adults: a long-term follow-up study. Health Qual Life Outcomes 2020;18:382. https://doi.org/10.1186/s12955-020-01642-3. 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PCI or CABG for left main coronary artery disease: the SWEDEHEART registry. Eur Heart J 2023;44:2833–42. https://doi.org/10.1093/eurheartj/ehad369. Spadaccio C, Benedetto U. Coronary artery bypass grafting (CABG) vs. percutaneous coronary intervention (PCI) in the treatment of multivessel coronary disease: Quo vadis? -A review of the evidences on coronary artery disease. Ann Cardiothorac Surg 2018;7:506–15. https://doi.org/10.21037/acs.2018.05.17. Additional Declarations No competing interests reported. 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Mohamed","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYBAC+Rkg8oAciGR+kFABopgb8GoxuAHWYgwi2QwenAFpYSSgRQKhhUHyYRuIIqRFuvfhY54zBvIG5w8fMEicVxvN3w7U8qNiG26/zDlubMxzw8Bww4FjCQ8Stx3PnXGYsYGx58xt3NbcSGOT5vnwh3HbwR4Dg8Rtx3IbgFqYGdsIajGw33aY/4NE4pxjufOJ03IDZD4Pg0RiQ03uBkJaDG6kMRvOOWOQvP8Mm5lBwrEDuRuBWg7i84v8jDTGB2+OGdjO7D/8+OGPmrrceecPH3zwowKPw9DAYTB5gGj1QFBHiuJRMApGwSgYIQAABsRiqql5E/sAAAAASUVORK5CYII=","orcid":"","institution":"Alexandria University","correspondingAuthor":true,"prefix":"","firstName":"Shrouk","middleName":"F.","lastName":"Mohamed","suffix":""},{"id":408139813,"identity":"e90b4cc1-cb7d-472d-9bb2-fe85541108e7","order_by":2,"name":"Menna Ibrahim","email":"","orcid":"","institution":"Alexandria University","correspondingAuthor":false,"prefix":"","firstName":"Menna","middleName":"","lastName":"Ibrahim","suffix":""},{"id":408139815,"identity":"e309b0b4-3e12-4af1-aa2d-2a45b309953d","order_by":3,"name":"Belal Shehata","email":"","orcid":"","institution":"Alexandria University","correspondingAuthor":false,"prefix":"","firstName":"Belal","middleName":"","lastName":"Shehata","suffix":""},{"id":408139816,"identity":"c4ee0d0e-4f07-4e85-bc2a-96e85dfe5ab8","order_by":4,"name":"Shahd Radwan","email":"","orcid":"","institution":"Alexandria University","correspondingAuthor":false,"prefix":"","firstName":"Shahd","middleName":"","lastName":"Radwan","suffix":""},{"id":408139820,"identity":"10bceb41-9e16-45f7-aee3-7ed01c5e18ee","order_by":5,"name":"Jana Gado","email":"","orcid":"","institution":"Alexandria University","correspondingAuthor":false,"prefix":"","firstName":"Jana","middleName":"","lastName":"Gado","suffix":""},{"id":408139821,"identity":"99bff9fd-cd62-49b9-b1ad-edade326467b","order_by":6,"name":"Hend A. Yassin","email":"","orcid":"","institution":"Alexandria University","correspondingAuthor":false,"prefix":"","firstName":"Hend","middleName":"A.","lastName":"Yassin","suffix":""},{"id":408139822,"identity":"85647e23-c78f-473a-88cc-5b2ca89f004d","order_by":7,"name":"Wael Hassanein","email":"","orcid":"","institution":"Alexandria University","correspondingAuthor":false,"prefix":"","firstName":"Wael","middleName":"","lastName":"Hassanein","suffix":""},{"id":408139823,"identity":"6a8b8852-55f0-4968-ac55-04c7ea77e50d","order_by":8,"name":"Nora Mamdouh","email":"","orcid":"","institution":"Alexandria University","correspondingAuthor":false,"prefix":"","firstName":"Nora","middleName":"","lastName":"Mamdouh","suffix":""},{"id":408139824,"identity":"9781261a-9961-4fba-84b1-b2b73dc134ab","order_by":9,"name":"Hanan Hemead","email":"","orcid":"","institution":"Alexandria University","correspondingAuthor":false,"prefix":"","firstName":"Hanan","middleName":"","lastName":"Hemead","suffix":""},{"id":408139825,"identity":"fc82b766-0f71-453a-87af-b02135dacf54","order_by":10,"name":"Ahmed Abdelaziz","email":"","orcid":"","institution":"Alexandria University","correspondingAuthor":false,"prefix":"","firstName":"Ahmed","middleName":"","lastName":"Abdelaziz","suffix":""}],"badges":[],"createdAt":"2025-01-24 22:53:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5898468/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5898468/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":75408480,"identity":"264f996d-400c-4f70-bad0-ca8602e54b8f","added_by":"auto","created_at":"2025-02-04 08:59:08","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":36700,"visible":true,"origin":"","legend":"\u003cp\u003eMean overall QOL in cases of hypertension among males and females.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5898468/v1/f5c634b8ad4edd2f7afad83c.jpg"},{"id":75408481,"identity":"8728b90a-ad92-46c9-b14c-427b3d3fda59","added_by":"auto","created_at":"2025-02-04 08:59:08","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":40392,"visible":true,"origin":"","legend":"\u003cp\u003eMean overall QOL among males and females according to smoking status.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5898468/v1/71777893b30f8e43a875adde.jpg"},{"id":75410178,"identity":"f4fda9ff-4a02-4262-bf21-c4d268f5a874","added_by":"auto","created_at":"2025-02-04 09:07:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":862708,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5898468/v1/f07da458-a2cd-40df-9f2f-914e896047ea.pdf"},{"id":75406227,"identity":"e5663fb4-101c-401a-8ce4-186f5a056854","added_by":"auto","created_at":"2025-02-04 08:51:08","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":20637,"visible":true,"origin":"","legend":"","description":"","filename":"SuppCABG.docx","url":"https://assets-eu.researchsquare.com/files/rs-5898468/v1/ba7d8630a15144b34be897c3.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Quality of life for patients after coronary artery bypass grafting surgery","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCoronary artery bypass grafting (CABG) remains the most common treatment for advanced coronary artery disease (CAD), the leading cause of morbidity and mortality globally. Demographic changes and lifestyle factors such as smoking, inactivity, and a poor diet all contribute to the spread of CAD. While CABG is the most commonly used revascularization treatment, some people may benefit from other treatments, including percutaneous coronary interventions (PCIs) or hybrid coronary revascularization. However, CABG is widely chosen because of its superior ability to decrease recurrent ischemic episodes, especially in people with multivessel disease or diabetes. [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] An Italian study conducted in 2009 utilizing the SF-36 questionnaire revealed significant increases in pain relief and physical activity after CABG, stressing the influence on quality of life. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] Furthermore, a 2017 study by Puskas et al. showed that CABG, particularly in diabetic patients, produces better long-term outcomes than does PCI. [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eAccording to preoperative quality of life (QoL) assessments, patients who undergo coronary artery bypass grafting have considerably poorer health status, with symptoms including chronic chest pain, exhaustion, and heightened anxiety about the treatment and its potential results. A 2020 study conducted in Croatia reported significantly low preoperative QoL ratings, emphasizing the importance of thorough preoperative evaluations in identifying and resolving these difficulties. CABG has been proven to considerably enhance QoL at near term, with patients reporting increased physical performance and alleviation from severe symptoms such as chest discomfort. Long-term outcomes may differ on the basis of patient-specific factors such as age, comorbidities, and adherence to lifestyle adjustments following surgery. [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eDespite these improvements, long-term results reveal a more complicated perspective. While many patients maintain good quality of life in the years following surgery, a significant number may experience health decline due to factors such as aging, comorbidities, or inadequate adherence to lifestyle adjustments.[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] Quality-adjusted life years (QALYs) are commonly used to assess long-term success, with some studies reporting values of approximately 0.41. Although this value indicates an increase in life expectancy and quality of life, it is considered moderate when compared with other chronic disease operations, implying that post-CABG care and support should be enhanced.\u0026lrm; Crucially, mental health has a significant effect on these results. According to a Saudi Arabian study, patients who received supportive therapy or had strong family support following surgery reported improved quality of life scores.[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] These findings emphasize the necessity of comprehensive postoperative care that takes into account both psychological and physical factors to optimize long-term success.\u003c/p\u003e \u003cp\u003eEvidence has demonstrated the critical importance of assessing QOL in patients who \u0026lrm;have undergone CABG. However, there is a considerable lack of evidence on the specific impacts of CABG on the Egyptian population, especially in terms of the level of QOL improvement and the impact of numerous influencing factors.[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] Smoking, obesity, hypertension, and diabetes are all risk factors for CAD, which is becoming a rising public health issue in Egypt. Cardiovascular disorders (CADs) are the major cause of death in Egypt, accounting for approxiamtely 46% of all deaths. Limited access to advanced healthcare facilities, financial constraints, diagnostic delays, and inadequate preventive strategies make it difficult to address this burden. [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] These aspects highlight the critical necessity for extensive research to assess CABG outcomes and the role of influencing factors in enhancing the quality of life of Egyptian patients.\u003c/p\u003e"},{"header":"Patients and methods","content":"\u003cp\u003eThis was a retrospective cross-sectional study conducted to assess quality of life in patients who underwent coronary artery bypass grafting surgery at the cardiac surgery unit of the cardiothoracic surgery department of Alexandria University, Egypt. This study explored the factors most significantly affecting post-CABG QOL outcomes. By evaluating changes in symptom burden, psychological well-being, and social functioning, this research aimed to assess QoL scores across different domains (physical, psychological, social, and environmental) in post-CABG patients.\u003c/p\u003e \u003cp\u003eA total of 139 patients, selected through convenience sampling from hospital records, were included in the study. Participants were included if they were aged 18 years or older and had completed six months or more since their surgery at the time of the survey. Patients were excluded if they had missing or incomplete hospital records, or were unable or unwilling to provide informed consent for participation in the study.\u003c/p\u003e \u003cp\u003e Data collection involved telephone interviews lasting 10\u0026ndash;20 minutes, and verbal informed consent was obtained. The SF-36 Health Survey was utilized to evaluate patients' QoL, with modifications made to enhance clarity and relevance. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eThe data sources included demographic information, medical history, and surgical outcomes extracted from hospital records. The variables assessed included independent variables such as age, sex, marital status, severity of pain, mental and physical health, and dependent variables including the ability to perform daily tasks (at home and outside), participation in sports, and social engagement. Responses were scored on a 1\u0026ndash;5 scale, where 1 indicated the worst outcome and 5 the best outcome. For participants who agreed, the questionnaire was completed during the call.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eDue to our modification and removal of questions from the SF-36 questionnaire, we performed a reliability test, revealing that Cronbach\u0026rsquo;s alpha indicates that the questionnaire has good internal consistency. The data were analyzed using descriptive and inferential statistics. Descriptive statistics, including frequencies and percentages, were utilized to delineate the sample characteristics based on socio-demographic and clinical variables. Shapiro-Wilk test was used to assess the normality of the data. The quantitative data were presented as the median and interquartile range (IQR). Fisher's exact, chi-square, Mann-Whitney, and Kruskal-Wallis tests were employed to compare groups across many factors. Fisher's exact and chi-square tests were utilized for categorical variables, whereas Mann-Whitney and Kruskal-Wallis H tests were employed for continuous and ordinal variables. Spearman\u0026rsquo;s correlation coefficient was employed to ascertain independent variables that could affect alterations in the different components of the SF-36 questionnaire following modification. A multivariate regression model was employed to identify independent factors capable of predicting alterations in overall quality of life. The correlation coefficient was computed to assess linear correlations among continuous variables. A p-value less than 0.05 was considered statistically significant. Data analysis was performed via SPSS version 26.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eBaseline Summary\u003c/h2\u003e \u003cp\u003eThe study population included 139 patients, with a median age of 61 years (IQR: 58\u0026ndash;67). The majority of patients were male (79.1%), married (82.7%), and Egyptian (98.6%). The majority consisted of nonsmokers (45.3%) and ex-smokers (40.3%). The predominant comorbidities were hypertension (68.3%), diabetes mellitus (47.5%), and dyslipidemia (57.6%). A considerable proportion of individuals presented with two or more comorbidities. Concerning self-assessed health state, the majority of participants classified their health as either excellent (18.7%) or very good (27.3%). The demographic data are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eHealth-Related Quality of Life (SF-36 QOL) Scores\u003c/h3\u003e\n\u003cp\u003eThe median scores for the six SF-36 domains were as follows: physical functioning (PF) 40 (IQR: 35\u0026ndash;75), general health (GH) 50 (IQR: 45\u0026ndash;60), social functioning (SF) 77.5 (IQR: 50\u0026ndash;100), role limitations due to physical health (RP) 25 (IQR: 0\u0026ndash;75), role limitations due to emotional problems (RE) 100 (IQR: 0\u0026ndash;100), and bodily pain (BP) 67.5 (IQR: 36.25\u0026ndash;100). The median physical component summary (PCS) score was 51.25 (IQR: 35\u0026ndash;70), and the overall quality of life (QOL) score was 60 (IQR: 38.75\u0026ndash;77.08)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of the included participants.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (Median (IQR))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61 (58\u0026ndash;67)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61 (43.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78 (56.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e110 (79.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (20.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (Median (IQR))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81 (72.5\u0026ndash;93)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e115 (82.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidow/widower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (10.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNationality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEgyptian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e137 (98.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNonsmoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63 (45.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent-Smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (14.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEx-smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56 (40.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking-index (Median (IQR))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.50-2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHours of sleep per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than 10 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (10.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u0026ndash;8 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77 (55.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u0026ndash;6 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33 (23.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4 hours or less\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (10.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95 (68.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66 (47.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80 (57.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTwo comorbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension and diabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52 (37.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension and dyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66 (47.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes and dyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 (35.97%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThree comorbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension, diabetes mellitus and dyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (31.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 (34.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily history of cardiac diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63 (45.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth-status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExcellent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26 (18.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery good\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (27.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49 (35.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot bad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (10.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (7.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSF-36 questionnaire domains (Median (IQR))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical functioning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (35\u0026ndash;75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneral Health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 (45\u0026ndash;60)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial functioning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77.5 (50\u0026ndash;100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRole limitations due to physical health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (0\u0026ndash;75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRole limitations due to emotional problems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100 (0-100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67.5 (36.25\u0026ndash;100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical Component Summary (PCS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.25 (35\u0026ndash;70)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall Quality of Life (QOL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60 (38.75\u0026ndash;77.08)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRelationship between SF-36 domains and overall quality of life\u003c/p\u003e \u003cp\u003eSpearman\u0026rsquo;s correlation analysis revealed a positive correlations between QOL and various health domains, including the PCS (r\u0026thinsp;=\u0026thinsp;0.921, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), PF (r\u0026thinsp;=\u0026thinsp;0.679, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), RP (r\u0026thinsp;=\u0026thinsp;0.834, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), BP (r\u0026thinsp;=\u0026thinsp;0.724, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and SF (r\u0026thinsp;=\u0026thinsp;0.735, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eA moderate positive correlation was observed between emotional role limitations (r\u0026thinsp;=\u0026thinsp;0.775, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The general health domain showed a weaker positive correlation with overall QOL (r\u0026thinsp;=\u0026thinsp;0.184, p\u0026thinsp;=\u0026thinsp;0.03). (Table\u0026nbsp;2 in Supplements)\u003c/p\u003e\n\u003ch3\u003eSex-Based Differences in Quality of Life\u003c/h3\u003e\n\u003cp\u003eComparisons between male and female patients were made. While both genders reported similar general health and social functioning levels, significant differences were observed in median physical functioning scores (60 vs. 45, p\u0026thinsp;=\u0026thinsp;0.007), where males had higher scores. No significant differences were observed between the sexes for RE, PCS, or overall QOL. (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e) Males and females who had no hypertension had better QOL scores, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. While comparing the overall QOL scores in the case of smoking status, we found that in females, there were better results in nonsmokers, whereas in males, ex-smokers had higher scores, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between questionnaire domains based on sex.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale (n\u0026thinsp;=\u0026thinsp;110)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale (n\u0026thinsp;=\u0026thinsp;29)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMann-Whitney U\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP values\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical functioning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60 (43.75-80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (17.5\u0026ndash;67.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2113.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneral Health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.5 (45\u0026ndash;60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (42.5\u0026ndash;60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1750.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.511\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial functioning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77.5 (50\u0026ndash;100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80 (50\u0026ndash;95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1645.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.790\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRole limitations due to physical health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (0\u0026ndash;75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0\u0026ndash;75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.352\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRole limitations due to emotional problems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100 (0-100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100 (50\u0026ndash;100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1399.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.257\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70 (37.5\u0026ndash;100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (30\u0026ndash;100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1805\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.271\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall-QOL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61.25 (37.4-79.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57.50 (42.083\u0026ndash;68.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.507\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eSignificant results refer to p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThere were significant differences in health dimensions, including physical functioning, social functioning, general health, physical role, emotional, bodily pain, and sleep duration. The group with 6\u0026ndash;8 hours exhibited the highest median score for RP. Furthermore, no substantial changes in overall health were observed across the various sleep duration groups. These results suggest that enough sleep (especially 6\u0026ndash;8 hours) is linked to better physical and emotional health, whereas shorter sleep durations are associated with poorer outcomes. (Table\u0026nbsp;4 in Supplement)\u003c/p\u003e \u003cp\u003eThe Kruskal-Wallis Test was done according to smoking status. There were no significant differences between the different questionnaire domains and smoking statuses (nonsmoker, current-smoker, and ex-smoker) for PF, SF, BP, RP, RE, and GH, with p-values of 0.098, 0.54, 0.794, 0.857, 0.067, and 0.373, respectively.\u003c/p\u003e \u003cp\u003eMoreover, marital status strongly influences various health categories. The findings indicated notable PF, SF, BP, RP, and RE variations among marital status groups, with p-values of 0.003, 0.027, 0.011, 0.035, and 0.003, respectively. No significant variation in GH was observed among the marital status categories, with a p-value of 0.165.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDemographic and Health-Related Factors Associated with Quality of Life\u003c/h3\u003e\n\u003cp\u003eBased on socio-demographic factors, the association of QOL categories revealed that marital status, sleep duration, and comorbidities were significantly associated with QOL. The sex distribution was similar across groups, with no statistically significant difference (χ\u0026sup2;=0.085, p\u0026thinsp;=\u0026thinsp;0.834). Additionally, smoking status did not significantly correlate with QOL (χ\u0026sup2;=0.668, p\u0026thinsp;=\u0026thinsp;0.716). Nevertheless, nonsmokers composed the largest subgroup in both QOL categories. Marital status was significantly associated with QOL (χ\u0026sup2;=9.45, p\u0026thinsp;=\u0026thinsp;0.024); married individuals were more common in the low-QOL group, whereas single participants were found exclusively in the high-QOL group.\u003c/p\u003e \u003cp\u003eSleep duration was also significantly correlated with QOL (χ\u0026sup2;=12.077, p\u0026thinsp;=\u0026thinsp;0.017). Most individuals in the high-QOL group reported 6\u0026ndash;8 hours of sleep per night, whereas shorter or longer sleep patterns were more common in the low-QOL group.\u003c/p\u003e \u003cp\u003eHypertension was significantly associated with lower QOL (F\u0026thinsp;=\u0026thinsp;4.386, p\u0026thinsp;=\u0026thinsp;0.043). While diabetes mellitus did not considerably affect QOL (F\u0026thinsp;=\u0026thinsp;0.479, p\u0026thinsp;=\u0026thinsp;0.498), dyslipidemia had a marginal effect (F\u0026thinsp;=\u0026thinsp;3.066, p\u0026thinsp;=\u0026thinsp;0.086). Notably, other health conditions (e.g., respiratory or gastrointestinal issues) were more prevalent among those with lower QOL (F\u0026thinsp;=\u0026thinsp;9.692, p\u0026thinsp;=\u0026thinsp;0.002), indicating that additional comorbidities may have a negative impact on life quality. A family history of cardiac disease showed no significant association with QOL (F\u0026thinsp;=\u0026thinsp;0.188, p\u0026thinsp;=\u0026thinsp;0.731). (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRelation between patients' socio-demographic characteristics and quality of life.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh-QOL (n\u0026thinsp;=\u0026thinsp;80)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow-QOL (n\u0026thinsp;=\u0026thinsp;59)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP values\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge-Median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63 (58.50\u0026ndash;66.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61.50 (53.50\u0026ndash;66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMann-Whitney U\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.773\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight-Median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86 (74.50\u0026ndash;95.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85.50 (75\u0026ndash;101)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMann-Whitney U\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.783\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking index- Median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.5-2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.5-3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMann-Whitney U\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.883\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u0026thinsp;=\u0026thinsp;0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.834\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64 (80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46 (78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.668\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.716\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNonsmoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (47.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (42.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent-Smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (12.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (16.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEx-smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (40.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;9.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71 (88.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (74.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidow/widower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (11.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (8.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (5.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHours of sleep per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;12.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than 10 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (8.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (13.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u0026ndash;8 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52 (65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (42.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u0026ndash;6 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (22.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (25.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4 hours or less\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49 (61.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46 (78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u0026thinsp;=\u0026thinsp;4.386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (44.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u0026thinsp;=\u0026thinsp;0.479\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.498\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (51.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (66.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u0026thinsp;=\u0026thinsp;3.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (23.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (49.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u0026thinsp;=\u0026thinsp;9.692\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily history of cardiac diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (43.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (47.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u0026thinsp;=\u0026thinsp;0.188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.731\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eF refers to Fisher\u0026rsquo;s test.\u003c/p\u003e \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;Chi-square test.\u003c/p\u003e \u003cp\u003eSignificant results refer to p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eMultivariate analysis\u003c/h3\u003e\n\u003cp\u003eA multilinear regression model evaluating the influence of demographic and health variables on overall quality of life indicated that the predictors accounted for 64.3% of the variance in quality of life (adjusted R\u0026sup2; = 0.643). Sleep duration (6\u0026ndash;8 hours) emerged as the most significant predictor of quality of life, with a strong positive correlation (B\u0026thinsp;=\u0026thinsp;39.526, Beta\u0026thinsp;=\u0026thinsp;0.750, p\u0026thinsp;=\u0026thinsp;0.005). Additionally, high cholesterol was negatively correlated with quality of life (B = -18.096, Beta = -0.346, p\u0026thinsp;=\u0026thinsp;0.041), indicating that effective management of high cholesterol could enhance quality of life. (Table\u0026nbsp;6 in Supplements)\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study assessed the improvement in quality of life after 6 months or more in patients who underwent coronary artery bypass grafting surgery. This is essential because various clinical and sociodemographic factors influence postsurgical QOL. Our research revealed that while patients often experience an initial decline in health-related QOL shortly after surgery, significant improvements can occur within six months or more.\u003c/p\u003e \u003cp\u003eAccording to gender influence, coronary heart disease is more common in males than in females. While considering gender differences in outcomes, we found no statistically significant difference in overall quality of life scores in most domains except for physical function. Yildiz et al. reported that females had lower mean scores than males did in the subdimensions of energy and vitality, social functioning, and pain, with the difference between the groups being statistically significant. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]Peric et al. found that male patients also generated higher scores than female patients did. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] However, the small number of female patients included in the present study may have affected the findings.\u003c/p\u003e \u003cp\u003eWhile some studies suggest that elderly patients might experience poorer overall quality of life after CABG, our findings showed no relationship between overall QOL and age. Similarly, our findings are consistent with those of a multicenter study in the Netherlands that found no significant association between age and lower physical or mental component scores one year postsurgery. However, the study revealed a decline in mental quality of life in a substantial proportion of patients aged 80 years. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eAdequate sleep duration, particularly 6\u0026ndash;8 hours per night, is positively associated with better physical and emotional health outcomes post-CABG. Our results also supported that sleeping 6\u0026ndash;8 hours was significantly associated with better QOL. In contrast, individuals with shorter or longer sleep durations reported a lower quality of life. Sleep disturbances are common in the postoperative period following CABG and often last several weeks. Factors such as pain, anxiety, and environmental conditions contribute to these disturbances, which can adversely affect recovery and QoL.[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eSmoking is consistently identified as a risk factor, which is associated with lower QOL after CABG. Surprisingly, our findings showed that there was no association between smoking status and overall QOL. Numerous studies have shown that smokers usually report lower scores in various quality of life domains, including emotional role, social functioning, and general health, than nonsmokers do. In addition, continued smoking after CABG is associated with a greater risk of death. Interestingly, our study found that ex-smoker males were of better QOL in comparison to other statuses (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Smoking cessation is associated with lower rates of postoperative complications and better overall survival rates. [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eMultiple comorbidities are linked to a lower quality of life. Our study revealed that HTN was a risk factor for QOL following CABG. Interestingly, we did not find statistically significant associations between QOL and dyslipidemia, DM, or family history of cardiac diseases.\u003c/p\u003e \u003cp\u003eSeveral studies have the positive influence of marriage on various aspects of quality of life after CABG. Our study results revealed that being married, single, divorced, or widowed was significantly associated with QOL, supporting that married person had high quality (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e5\u003c/span\u003e). One study found that single individuals had lower mean values across all eight domains of the SF-36 quality of life questionnaire compared to married individuals. The most significant difference was observed in the physical functioning domain. [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eCoronary artery bypass grafting and percutaneous coronary intervention (PCI) are two prevalent revascularization techniques for treating coronary artery disease. CABG is frequently preferred for patients with multivessel disease, left main coronary artery disease, or diabetes mellitus due to its greater long-term efficacy in decreasing significant adverse cardiac events and the necessity for recurrent revascularization. Conversely, PCI noted for its minimally invasive technique and reduced recovery duration, is often favored for patients with single-vessel disease or those at elevated surgical risk. Research indicates that whereas CABG is superior in enhancing survival and diminishing disease recurrence in high-risk patients, PCI provides similar advantages in alleviating symptoms and improving quality of life in less complicated cases. Notwithstanding these disparities, new research indicates that both therapies improve patients' physical and mental well-being postsurgery. Consequently, the selection between CABG and PCI must be informed by clinical indications, patient comorbidities, and preferences, utilizing a shared decision-making strategy to guarantee optimal personalized care.[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eDespite our modifications to the SF-36 questionnaire, a reliability test was performed, revealing that Cronbach\u0026rsquo;s alpha indicates that the questionnaire has good internal consistency, with a significantly good Cronbach's alpha of 0.913. One of our limitations is that we relied on the retrospective collection of patient data from hospital records. This study demonstrated multiple potential biases that could influence the outcomes. Selection bias was considered due to the exclusion of patients with insufficient data, consequently limiting the generalizability of the results. Response bias might have occurred as the sample included only those patients who consented to and engaged with phone calls for participation. Moreover, survivor bias was an issue, as the study exclusively evaluated patients who survived for a minimum of six months postsurgery.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study highlights patient quality of life results following coronary artery bypass grafting. The ideal sleep duration (6\u0026ndash;8 hours) and mariatal status were significant predictors of improved quality of life postsurgery. This underscores the importance of adjustable lifestyle factors and social support throughout the recovery period. Hypertension negatively impacted quality of life, although other comorbidities, smoking status, and dyslipidemia exhibited no significant correlations. The results highlight the necessity for focused interventions concerning sleep patterns, hypertension control, and social support in postoperative care. Additional comparative studies are needed to evaluate the quality of life among patients who have undergone CABG and PCI.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e \u003cp\u003e Ethical approval was obtained from the IRB at Alexandria Main Hospital. Additionaly, verbal consent was obtained from all participants before they submitted the survey.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConflict of interest\u003c/strong\u003e \u003cp\u003eAll the participants declare that they have no conflicts of interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research did not receive any funds.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization, M.F., N.A., H.Y., A.A. and H.H.; Data curation, M.F., M.I., J.G. and B.S.; Formal analysis, S.F.M.; Methodology, M.F., M.I., S.R. and W.H.; Project administration, A.A., M.I., W.H. and H.H.; Supervision, A.A.; Validation, M.F., B.S., S.F.M., H.Y., J.G. and W.H.; Visualization, N.A., A.A. and W.H.; Writing\u0026mdash;original draft, S.R., B.S., and S.F.M.; Writing\u0026mdash;review \u0026amp; editing, A.A., S.F.M., M.F., M.I. and H.H. All the authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe would like to extend our heartfelt gratitude to our esteemed colleagues, Dr. Helmy Atef Helmy Elwakil, Dr. Noha Mahmoud Hamada, and Dr. Eslam Maher, for their invaluable assistance in data collection for this study. Their dedication, efforts, and collaborative spirit greatly contributed to the success of this research. We deeply appreciate their time and commitment, which have been instrumental in achieving our objectives. Thank you for your outstanding contributions.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePačarić S, Turk T, Erić I, Orkić Ž, Erić AP, Milostić-Srb A, et al. Assessment of the quality of life in patients before and after coronary artery bypass grafting (CABG): A prospective study. Int J Environ Res Public Health 2020;17. https://doi.org/10.3390/ijerph17041417.\u003c/li\u003e\n\u003cli\u003eVincelj J, Bitar L. Quality of life 10 years after cardiac surgery in adults: a long-term follow-up study. Health Qual Life Outcomes 2020;18:382. https://doi.org/10.1186/s12955-020-01642-3.\u003c/li\u003e\n\u003cli\u003eThuijs D, Kappetein A, Serruys P, Mohr F, Morice M, Mack M, et al. Percutaneous coronary intervention versus coronary artery bypass grafting in patients with three-vessel or left main coronary artery disease: 10-year follow-up of the multicentre randomised controlled SYNTAX trial. The Lancet 2019;394.\u003c/li\u003e\n\u003cli\u003eEmamzadehashemi KR, Khanghah AG, Azizi A, Paryad E, Noveiri MJS. Quality of life and activities of daily living one year after Coronary Artery Bypass Graft (CABG) surgery: a cross-sectional study. J Cardiothorac Surg 2024;19:367. https://doi.org/10.1186/s13019-024-02848-y.\u003c/li\u003e\n\u003cli\u003eCreber RM, Dimagli A, Spadaccio C, Myers A, Moscarelli M, Demetres M, et al. Effect of coronary artery bypass grafting on quality of life: a meta-analysis of randomized trials. Eur Heart J Qual Care Clin Outcomes 2022;8:259\u0026ndash;68. https://doi.org/10.1093/ehjqcco/qcab075.\u003c/li\u003e\n\u003cli\u003emansor fairouz mohamed, Abo-El- Ata AB, Sobeh DE tabay. QUALITY OF LIFE FOR PATIENTS AFTER CORONARY ARTERY BYPASS GRAFTING. Port Said Scientific Journal of Nursing 2021;8:169\u0026ndash;94. https://doi.org/10.21608/pssjn.2021.69629.1099.\u003c/li\u003e\n\u003cli\u003eJamal Murshid S, Zayed AlGarmoushi O, Salem Aljezani K, Mohammed Albarakati R, Abdullah Bawazir K, Sultan I, et al. Post-cardiac surgery health related quality of life: A Saudi cross sectional study in Jeddah. WORLD FAMILY MEDICINE/MIDDLE EAST JOURNAL OF FAMILY MEDICINE 2020;18:119\u0026ndash;24. https://doi.org/10.5742MEWFM.2020.93743.\u003c/li\u003e\n\u003cli\u003eAbd El-Moneam Ahmed S, Mohamed Helmy Emam N, Mohammed Ahmed Mohammed E. Relationship between Symptom Burden Clusters and Quality of Life in Patients with Coronary Artery Bypass Grafting Surgeries. Egyptian Journal of Health Care 2022;13:1574\u0026ndash;87. https://doi.org/10.21608/ejhc.2022.273505.\u003c/li\u003e\n\u003cli\u003eAmin M, Radwan A, Hemeda A. Cardio-metabolic problem in Egypt. Intern Emerg Med 2020;15:549\u0026ndash;52. https://doi.org/10.1007/s11739-020-02346-8.\u003c/li\u003e\n\u003cli\u003eMcHorney CA, Ware JEJr, Rachel Lu JF, Sherbourne CD. The MOS 36-ltem Short-Form Health Survey (SF-36): III. Tests of Data Quality, Scaling Assumptions, and Reliability Across Diverse Patient Groups. Med Care 1994;32.\u003c/li\u003e\n\u003cli\u003eYildiz E, Yildiz Z, Dayapoğlu N. Investigation of Quality of Life After Coronary Artery Bypass Surgery: A 10-Year Long-Term Follow-Up Study Badanie jakości życia po operacji pomostowania aortalno-wieńcowego: 10-letnie długoterminowe badanie kontrolne 2023:2023.\u003c/li\u003e\n\u003cli\u003ePeric V, Borzanovic M, Stolic R, Jovanovic A, Sovtic S, Djikic D, et al. Quality of life in patients related to gender differences before and after coronary artery bypass surgery☆. Interact Cardiovasc Thorac Surg 2010;10:232\u0026ndash;8. https://doi.org/10.1510/icvts.2009.208462.\u003c/li\u003e\n\u003cli\u003eBlokzijl F, Houterman S, van Straten BHM, Daeter E, Brandon Bravo Bruinsma GJ, Dieperink W, et al. Quality of life after coronary bypass: a multicentre study of routinely collected health data in the Netherlands\u0026dagger;. European Journal of Cardio-Thoracic Surgery 2019;56:526\u0026ndash;33. https://doi.org/10.1093/ejcts/ezz051.\u003c/li\u003e\n\u003cli\u003eG\u0026ouml;kbayrak R, Koyuncu A, Yava A. Investigation of Sleep and Affecting Factors in Coronary Artery Bypass Graft Surgery. Journal of Turkish Sleep Medicine 2024:101\u0026ndash;7. https://doi.org/10.4274/jtsm.galenos.2023.30922.\u003c/li\u003e\n\u003cli\u003eNerbass FB, Feltrim MIZ, de Souza SA, Ykeda DS, Lorenzi-Filho G. Effects of massage therapy on sleep quality after coronary artery bypass graft surgery. Clinics 2010;65:1105\u0026ndash;10. https://doi.org/10.1590/S1807-59322010001100008.\u003c/li\u003e\n\u003cli\u003evan Domburg RT, Meeter K, van Berkel DFM, Veldkamp RF, van Herwerden LA, Bogers AJJC. Smoking cessation reduces mortality after coronary artery bypass surgery: a 20-year follow-up study. J Am Coll Cardiol 2000;36:878\u0026ndash;83. https://doi.org/https://doi.org/10.1016/S0735-1097(00)00810-X.\u003c/li\u003e\n\u003cli\u003eAbo-El-Ata AB, Al-Tabey Sobeh D, Mansor FM. QUALITY OF LIFE FOR PATIENTS AFTER CORONARY ARTERY BYPASS GRAFTING. vol. 8. 2021.\u003c/li\u003e\n\u003cli\u003eWhitsitt DR. The Relationship Between Marital Quality and Coronary Artery Bypass Graft Surgery as Experienced by 3 Couples. J Cardiopulm Rehabil Prev 2010;30.\u003c/li\u003e\n\u003cli\u003eNielsen S, Giang KW, Wallinder A, Rosengren A, Pivodic A, Jeppsson A, et al. Social Factors, Sex, and Mortality Risk After Coronary Artery Bypass Grafting: A Population‐Based Cohort Study. J Am Heart Assoc 2019;8:e011490. https://doi.org/10.1161/JAHA.118.011490.\u003c/li\u003e\n\u003cli\u003eAlzahrani AA, AlAssiri AK, Al-Ebrahim KE, Ganbou ZT, Alsudais MM, Khafagy AM. Impact of Clinical and Sociodemographic Factors on Quality of Life Following Coronary Artery Bypass Grafting: A Mixed-Methods Study. Cureus 2024. https://doi.org/10.7759/cureus.56781.\u003c/li\u003e\n\u003cli\u003eSipahi I, Akay MH, Dagdelen S, Blitz A, Alhan C. Coronary Artery Bypass Grafting vs Percutaneous Coronary Intervention and Long-term Mortality and Morbidity in Multivessel Disease: Meta-analysis of Randomized Clinical Trials of the Arterial Grafting and Stenting Era. JAMA Intern Med 2014;174:230. https://doi.org/10.1001/jamainternmed.2013.12844.\u003c/li\u003e\n\u003cli\u003ePersson J, Yan J, Anger\u0026aring;s O, Venetsanos D, Jeppsson A, Sj\u0026ouml;gren I, et al. PCI or CABG for left main coronary artery disease: the SWEDEHEART registry. Eur Heart J 2023;44:2833\u0026ndash;42. https://doi.org/10.1093/eurheartj/ehad369.\u003c/li\u003e\n\u003cli\u003eSpadaccio C, Benedetto U. Coronary artery bypass grafting (CABG) vs. percutaneous coronary intervention (PCI) in the treatment of multivessel coronary disease: Quo vadis? -A review of the evidences on coronary artery disease. Ann Cardiothorac Surg 2018;7:506\u0026ndash;15. https://doi.org/10.21037/acs.2018.05.17.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-cardiothoracic-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jcts","sideBox":"Learn more about [Journal of Cardiothoracic Surgery](http://cardiothoracicsurgery.biomedcentral.com)","snPcode":"13019","submissionUrl":"https://submission.nature.com/new-submission/13019/3","title":"Journal of Cardiothoracic Surgery","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Coronary artery bypass grafting, quality of life, cardiac surgery, ischemic heart disease.","lastPublishedDoi":"10.21203/rs.3.rs-5898468/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5898468/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eUnderstanding the quality of life of patients following coronary artery bypass grafting is crucial for improving g post-operative management and long-term patient outcomes. Our study aimed to assess the QoL of patients post-CABG and identify the factors that influence their ability to perform daily activities.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis retrospective cross-sectional study was conducted at our cardiac surgery unit. Patients aged 18 years or older who underwent coronary artery bypass grafting surgery and who had completed at least six months of recovery following their surgery were selected through convenience sampling from hospital records. The collected data were reviewed and followed up through phone interviews via the SF-36 questionnaire.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe study evaluated 139 patients (median age: 61 years; 79.1% male), predominantly Egyptian (98.6%) and married (82.7%). The majority were nonsmokers (45.3%) or ex-smokers (40.3%), with common comorbidities including hypertension (68.3%), dyslipidemia (57.6%), and diabetes mellitus (47.5%). Self-assessed health status was rated as excellent or very good by 46% of the patients. Quality of life, assessed via the SF-36, revealed median scores for physical functioning (40), general health (50), social functioning (77.5), and overall QOL (60). QOL was positively correlated with multiple health domains, particularly physical and role limitations (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Gender analysis indicated that males scored higher in physical functioning (p\u0026thinsp;=\u0026thinsp;0.007), but no significant differences were observed in overall QOL. Marital status, sleep duration, and hypertension were significant factors influencing QOL, with optimal outcomes linked to 6\u0026ndash;8 hours of sleep. Smoking status and family cardiac history had no significant impact on QOL.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study highlights quality of life post-CABG, and reveals that ideal sleep duration (6\u0026ndash;8 hours), marital status and ex-smoking are key predictors of improved QoL. Hypertension negatively affected QoL, whereas factors, such as comorbidities, smoking, and dyslipidemia were not significantly correlated. The findings stress the need for interventions targeting sleep, hypertension control, and social support during recovery. Further comparative studies are needed to assess QoL in patients undergoing both CABG and PCI.\u003c/p\u003e","manuscriptTitle":"Quality of life for patients after coronary artery bypass grafting surgery","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-04 08:51:03","doi":"10.21203/rs.3.rs-5898468/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-26T06:41:53+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-10T12:49:21+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-08T10:47:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-08T09:39:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"154982252327631196211483111703500409672","date":"2025-06-08T09:22:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-06T15:46:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-06T11:52:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"93228012867089630461241915586816406666","date":"2025-06-05T07:47:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"308338661630911659377963530702424220792","date":"2025-06-04T16:44:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"326554819413092238788274908428302475359","date":"2025-06-04T16:16:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"59837526857627734781613693947039179070","date":"2025-06-04T15:54:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"157241362409402125783817072878519486202","date":"2025-05-30T06:55:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"304800627683722335422515104565847744675","date":"2025-05-29T10:15:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"7919718454599668693717146427085813094","date":"2025-05-29T05:23:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"261194556023701365467942219539822750000","date":"2025-05-29T04:12:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"286524518649786915036653190899869876471","date":"2025-05-28T19:12:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"155029269437991017564492475707824465408","date":"2025-05-28T14:06:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-28T13:53:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-01-28T11:00:50+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-01-28T10:59:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Cardiothoracic Surgery","date":"2025-01-24T22:43:49+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-cardiothoracic-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jcts","sideBox":"Learn more about [Journal of Cardiothoracic Surgery](http://cardiothoracicsurgery.biomedcentral.com)","snPcode":"13019","submissionUrl":"https://submission.nature.com/new-submission/13019/3","title":"Journal of Cardiothoracic Surgery","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"897a0f29-b99d-4694-b3f4-2a80a5626c35","owner":[],"postedDate":"February 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-10-27T12:45:53+00:00","versionOfRecord":[],"versionCreatedAt":"2025-02-04 08:51:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5898468","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5898468","identity":"rs-5898468","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}