Abstract
BACKGROUND:
Gender impacts pre-, intra-, and postoperative parameters and outcomes following coronary artery bypass graft (CABG) with conflicting results. This study aimed to identify differences in preoperative, intraoperative, and postoperative parameters. It also seeks to compare the postoperative complications and mortality between two genders who had CABG surgery.
METHOD:
This prospective observational study included patients who had isolated CABG and were divided based on gender. Demographic information, underlying comorbidities, drug history, clinical and laboratory data at the time of referral, operative characteristics, postoperative variables, and mortality outcomes were tracked during hospitalization and six months after discharge.
RESULTS:
Three hundred twenty patients were enrolled in the study during its duration. 71% were male. Women were older (62.40±9.03 vs. 59.99±9.81 years, p= 0.011) and had more dyslipidemia (p=0.003), hypertension (p=0.000), and diabetes (p=0.001), whereas men admitted with more myocardial infarction (MI) (p=0.011) and had lower Ejection fraction (EF) (p=0.001). They also had lower EF post-surgery (p <0.001) and six months after discharge (p = 0.006). However, the number of vessels involved was not different between genders (p=0.589), but the number of grafts was higher in men (p=0.008).
There was no statistically significant difference in overall mortality rates between the two groups (4.42% and 6.38% in men and women, respectively, p= 0.464).
CONCLUSIONS:
The women had more underlying comorbidities than men. Furthermore, there were some differences in the intra-operative parameters and postoperative complications between the two genders, but there was no difference in postoperative mortality in our setting.
Key Words: Coronary Artery Bypass, Gender Differences, Morbidity, Mortality, Survival
Introduction
Coronary artery bypass graft (CABG) improves survival in patients with severe coronary artery disease who are at high risk for cardiovascular events, including those with left central coronary artery stenosis and three-vessel coronary artery diseases, particularly those with diabetes and higher SYNTAX score 1, 2.
Age and comorbid conditions such as congestive heart failure (CHF), hypertension, peripheral vascular disease (PVD), renal disease, chronic lung disease, and metabolic syndrome are associated with poor outcomes after CABG 3-5. Furthermore, socioeconomic background, medical services quality, environmental conditions, and other socio-cultural differences influence community CABG surgery outcomes 6-9. According to some studies, the risk of mortality and morbidity after CABG surgery is higher in women than in men due to older age at the time of surgery, being at the acute stage of the disease, having smaller coronary arteries, and having a higher incidence of comorbid conditions 6, 10-13.
There have been studies on the disparity of CABG surgery outcomes between two genders in various populations. However, we designed this study to understand better the possible results of inequality between men and women following CABG 6, 11, 13, 14.
Our study aimed to identify differences in preoperative, intraoperative, and postoperative parameters between men and women undergoing CABG surgery. It also seeks to compare postoperative complications and mortality between the two genders.
Materials and Methods
Settings and Study population
From April 2018 to August 2021, this prospective observational study was conducted on adult patients who underwent isolated CABG surgery, either elective or emergent, at the Imam Hossein Medical Center, affiliated with Shahid Beheshti University of Medical Sciences (SBMU) in Tehran, Iran. The patients undergoing concurrent valve surgery or other cardiac procedures were excluded from this study.
The Institutional Review Boards of the Ethics Committee approved this study (IR.SBMU.RETECH.REC.1399.767) and written informed consent was obtained from each patient before enrollment in the study.
Assessments
The patients were divided into two groups based on gender. They were monitored during hospitalization and six months after discharge until they were removed from the study. The removal was due to death or the end of the follow-up period. Data were collected in six categories: demographic data, risk factors, drug history prior to admission, clinical and laboratory data at the time of referral, operative characteristics, postoperative variables, and mortality outcomes.
Demographic data
The demographic data for the patients include age, body mass index (BMI), physical activity level, education, income, and marital status.
The monthly income was recorded in Iranian Rials and, using the exchange rate at the time of this study, was presented in US dollars (USD). Using Iranian Central Bank data, the average USD to Iranian Rial exchange rate during the study was 169814 Iranian Rials. To report data in USD, we divided this parameter by 169814.
Risk factors and drug history before admission
The patients were evaluated for comorbid conditions that predict poor outcomes following CABG surgery and their drug history. These data were obtained from medical records or a primary evaluation during admission.
Clinical and laboratory data at the referral time
We evaluated severe symptoms, hemodynamic, echocardiographic, angiographic findings, and laboratory data at the admission time in this category. Drugs prescribed during the admission period were also recorded for all patients.
Operative characteristics
This category included operative details and any complications that arose during the operation.
Postoperative variables
Paraclinical and laboratory data and complications following surgery were tracked during the hospitalization and six months after discharge. The intensive care unit (ICU) and hospital length of stay were also recorded. The total cost of hospitalization was reported in USD.
Mortality outcomes
This category was divided into two subdivisions: mortality during hospitalization and six months follow-up after discharge. Furthermore, the survival probability for each gender was estimated.
Statistical analysis
The Kolmogorov-Smirnov test was used to determine the normality of distributions. Then the unpaired student’s t-test and Mann-Whitney U test were used to compare normal and non-normal distribution data. For comparing the frequency of categories variables between groups based on the frequency of variables, the fisher exact test or chi-square test was used. The quantitative data were presented as mean ±standard deviation (SD) or median (percentile, Q1, Q3) for normal and non-normal distributions and n(%) for qualitative data. SPSS for Windows was used to perform all statistical analyses (Version 21.0; SPSS Inc., Chicago, IL, USA). Also, the Kaplan-Meier method was used to estimate survival probability, and the log-rank test was used to calculate p-values for comparing survival curves. Statistical significance was defined as a two-sided p-value less than 0.05.
Results
Demographic data
Three hundred twenty patients were included in the study.
The majority of patients, 226 (71%), were men, while 29% were women. Women were older than men (62.40±9.03 vs. 59.99±9.81 years, P= 0.011). Because we could not collect information on physical activity level and income for all included patients, we mentioned the number of patients in front of the data in Table 1. Furthermore, the level of physical activity, education, marital status, and income were statistically different between the two groups (P<0.001). Table 1 provides the demographic data of the participants.
Table 1.
Participants’ demographic data based on gender
| Male | Female | p-value a | ||
|---|---|---|---|---|
| Total number | 226 (71.0) | 94 (29.0) | - | |
| Age (year) | 59.9 ± 9.81 | 62.4 ± 9.03 | 0.011 | |
| Body mass index (BMI) | 26.5 ± 4.12 | 26.2 ± 4.68 | 0.259 | |
| Physical activity level b M (180), F (80) |
0-1 day/week | 46 (25.5) | 34 (42.5) | <0.001 |
| 2-5 days/week | 81 (45.0) | 42 (52.5) | ||
| ≥ 5 days/week | 53 (29.4) | 4 (5.0) | ||
| Educational status | Half-educated (lower than 12 years of compulsory education) | 14 (6.19) | 21 (22.3) | <0.001 |
| High school diploma (up to 12 years of compulsory education) | 181 (80.1) | 72 (76.6) | ||
| University education | 31 (13.7) | 1 (1.06) | ||
| Marital status | Married | 224 (99.1) | 78 (82.9) | <0.001 |
| Single | 2 (0.88) | 16 (17.0) | ||
| Income c
M (178), F (76) |
Below 176.6 | 2 (1.12) | 14 (18.4) | <0.001 |
| Between 176.6 to 588.8 | 157 (88.2) | 61 (80.3) | ||
| Above 588.8 | 19 (10. 7) | 1 (1.31) | ||
a, unpaired student’s t test, Mann-Whitney U test ,chi-square test based on the data; b, defined at least 30 minutes of moderate-intensity physical activity on one day; c, based on US dollar(USD), per month. Data presented as the n (%) or mean±SD based on the parameters
Risk factors and drug history before admission
Table 2 provides all related data. Female patients had a higher prevalence of dyslipidemia (24.46% vs. 11.5%, P=0.003), hypertension (85.10% vs. 48.67%, P<0.001), and diabetes (65.95% vs. 44.69%, P=0.001). Meanwhile, the prevalence of dialysis-dependent renal failure was statistically significant in male patients (54.54% vs. 0%, P=0.022). Men had a higher rate of current smoking (51.76% vs. 7.44%, P<0.001), whereas females had a statistically significant higher rate of past smoking (18.08% vs. 9.73%, P=0.038). In addition, women were significantly more likely to use antiplatelet therapy (62.76% vs. 51.32%, P<0.001 for ASA, 34.04% vs. 20.35%, P=0.009 for Clopidogrel, and 31.91% vs. 19.02%, P= 0.012 for dual antiplatelet therapy (DAPT)).
Table 2.
Risk factors and drug history before admission, based on sex
| Male (N=226) | Female (N=94) | p-value a | |
|---|---|---|---|
| Comorbid risk factors | |||
| Dyslipidemia | 26 (11.5) | 23 (24.5) | 0.003 |
| Hypertension | 110 (48.7) | 80 (85.1) | <0.001 |
| Diabetes | 101 (44.69) | 62 (65.9) | 0.001 |
| Insulin-dependent diabetes | 20 (19.8) | 14 (22.6) | 0.67 |
| Renal failure | 11 (4.86) | 7 (7.44) | 0.36 |
| Dialysis-dependent renal failure | 6 (54. 4) | 0 (0.0) | 0.022 |
| Peripheral artery disease (PAD) | 6 (2.65) | 4 (4.25) | 0.49 |
| Chronic obstructive pulmonary disease (COPD) | 23 (10.2) | 9 (9.57) | 0.87 |
| Previous myocardial infarction (MI) | 38 (16.8) | 12 (12.76) | 0.36 |
| History of coronary artery bypass (CABG) surgery | 2 (0.88) | 0 (0.0) | 0.50 |
| History of percutaneous coronary intervention (PCI) | 28 (12.4) | 18 (19.1) | 0.11 |
| Heart failure (HF) | 10 (4.42) | 4 (4.25) | 0.60 |
| Cerebral vascular accidents (CVA) | 13 (5.75) | 4 (4.25) | 0.78 |
| Family history of coronary artery disease (CAD) | 37 (16.4) | 15 (15.9) | 0.93 |
| Current smoking | 117 (51.8) | 7 (7.44) | <0.001 |
| Past smoking | 22 (9.73) | 17 (18.1) | 0.038 |
| Drug history | |||
| ASA | 116 (51.3) | 59 (62.8) | <0.001 |
| Clopidogrel | 46 (20.3) | 32 (34.0) | 0.009 |
| Dual antiplatelet therapy (DAPT) | 43 (19.0) | 30 (31.9) | 0.012 |
| Statin | 91 (40.2) | 48 (51.1) | 0.08 |
| Beta-blockers | 77 (34.1) | 42 (44.7) | 0.07 |
a, chi-square test, fisher exact test based on the data. Data presented as the n (%)
Clinical and laboratory data at the referral time
Men were more likely than women to have a myocardial infarction (MI) at the time of referral (35.84% vs. 21.27%, P=0.011). Male patients had lower systolic and diastolic blood pressure (SBP and DBP) and ejection fraction (EF) (SBP: 125.1±20.84 vs. 133.04±22.52 mmHg, DBP: 75.49±11.53 vs. 80.49±12.63 mmHg, p= 0.001, and EF: 43.67±9.73 vs. 47.18±8.72 %, P=0.001), but higher serum creatinine (Scr) (1.29±0.82 vs. 1.08±0.32 mg/dl, P=0.001). Women had higher fasting blood glucose (FBS), HgbA1C, and cholesterol levels than men (142.44±48.02 vs. 134.75±51.51 mg/dl, P=0.046 for FBS, 8.19±1.97% vs. 7.72±2.18 %, P=0.040 for HgbA1C, and 163.23±42.57 vs. 151.33±40.75 mg/dl, P=0.048 for cholesterol). In addition, the female had lower hemoglobin (Hgb) levels (12.70±1.70 vs. 13.30±1.74 mg/dl, P<0.001). Table 3 depicts the disparity between the two study arms.
Table 3.
Clinical and laboratory data of patients in admission time, based on sex
| Male (N=226) | Female (N=94) | p-value a | ||
|---|---|---|---|---|
| Severe symptoms | ||||
| Pulmonary edema | 3 (1.32) | 0 (0.0) | 0.558 | |
| Cardiogenic shock | 1 (0.44) | 0 (0.0) | 0.706 | |
| Cardiogenic syncope | 4 (1.76) | 0 (0.0) | 0.325 | |
| Heart failure (HF) | 8 (3.53) | 6 (6.38) | 0.257 | |
| Myocardial infarction (MI) | 81 (35.8) | 20 (21.3) | 0.011 | |
| Hemodynamic finding | ||||
| Systolic blood pressure (mmHg) | 125.1 ± 20.8 | 133.0 ± 22.5 | 0.001 | |
| Diastolic blood pressure (mmHg) | 75.5 ± 11.5 | 80.5 ± 12.6 | 0.001 | |
| Heart rate (beats/min) | 78.6 ± 12.3 | 78.8 ± 10.1 | 0.941 | |
| Echocardiographic findings | ||||
| Ejection fraction (EF) (%) | 43.7 ± 9.73 | 47.2 ± 8.72 | 0.001 | |
| Pulmonary artery pressure (PAP)(mmHg) | 26.6 ± 7.71 | 26.7 ± 7.7 | 0.759 | |
| laboratory data | ||||
| Hemoglobin (Hgb)(g/dl) | 13.3 ± 1.74 | 12.7 ± 1.70 | <0.001 | |
| Serum creatinine (Scr), (mg/dl) | 1.29 ± 0.82 | 1.08 ± 0.32 | 0.001 | |
| Fasting blood sugar (FBS) (mg/dl) | 134.7 ± 51.5 | 142.4 ± 48.0 | 0.046 | |
| Hgb A1C (%) | 7.72 ± 2.18 | 8.19 ± 1.97 | 0.040 | |
| LDL-C (mg/dl) | 93.1 ± 29.6 | 100.4 ± 35.8 | 0.097 | |
| HDL-C (mg/dl) | 34.3 ± 7.34 | 36.5 ± 9.27 | 0.061 | |
| TG (mg/dl) | 136.2 ± 85.3 | 140.3 ± 70.0 | 0.328 | |
| Cholesterol (mg/dl) | 151.3 ± 40.7 | 163.2 ± 42.6 | 0.048 | |
| Prescribe drugs in admission | ||||
| ASA | 223 (98.2) | 93 (98.9) | 0.847 | |
| Clopidogrel | 113 (50.0) | 48 (51.1) | 0.862 | |
| Dual antiplatelet therapy (DAPT) | 113 (50.0) | 48 (51.1) | 0.862 | |
| Glycoprotein IIb/IIIa inhibitors | 17 (7.52) | 8 (8.51) | 0.764 | |
| Statin | 226 (100) | 94 (100) | - | |
| Beta-blockers | 201 (88.9) | 89 (94.7) | 0.108 | |
| Angiographic findings | ||||
| Number of vessel involvement | One vessel | 11 (4.86) | 7 (7.44) | 0.589 |
| Two vessels | 30 (13.3) | 14 (14.9) | ||
| Three vessels | 185 (81.8) | 73 (77.7) | ||
| Left main diseases | 43 (19.0) | 10 (10.6) | 0.066 | |
a, unpaired student’s t test, Mann-Whitney U test, chi-square test, fisher exact test based on the data. Data presented as the n (%) or mean±SD based on the parameters
Operative characteristics
There was no statistically significant difference in operative characteristics between men and women, except for the unit of packed red blood cells transfused during surgery, which was higher in female patients (3(2-4) vs. 2(2-4), P=0.041), and the number of grafts, which was higher in men (men vs. women, 3(3,4) vs. 3(2,4), P=0.008) (Table 4).
Table 4.
Operative characteristics of patients, based on sex
| Male (N=226) | Female (N=94) | p-value a | |
|---|---|---|---|
| Emergent CABG | 11 (4.86) | 1 (1.06) | 0.12 |
| Off-pump procedure | 19 (8.40) | 11 (11.7) | 0.36 |
| Cardiopulmonary bypass time, (min) |
117.4 ± 44.9 | 112.7 ± 45.4 | 0.12 |
| Aortic cross-clamp time (min) | 71.6 ± 28.3 | 71.0 ± 24.6 | 0.62 |
| Number of grafts | 3 (3,4) | 3 (2,4) | 0.008 |
| Blood transfusion | 200 (88.5) | 87 (92.5) | 0.28 |
| Units of packed red blood cells transfused | 2 (2,4) | 3 (2,4) | 0.041 |
| Repeated sternotomy | 2 (0.88) | 3 (3.19) | 0.08 |
a, unpaired student’s t test, Mann-Whitney U test, chi-square test, fisher exact test based on the data based on the data. Data presented as the n (%), mean±SD or median (Q1, Q2) based on the parameters
Postoperative variables
Except for re-percutaneous coronary intervention (PCI), which was more common in women (2.22% vs. 0%, P=0.032), there was no statistically significant difference in postoperative complications between the two arms of the study. Table 5 displays the data.EF was significantly lower in men during hospitalization (post-surgery and before discharge) and six months after discharge (43.40±9.98% vs. 48.02±7.46%, P<0.001 post-surgery and 43.18±11.89% vs. 49.52±8.79%, P= 0.006 after six months). Serum creatinine (Scr) was higher in men (1.49±1.07 vs. 1.28±0.6 mg/dl post-surgery and 1.32±1.03 vs. 1.02±0.32mg/dl before discharge, P<0.001) while hemoglobin (Hgb) was lower in women (8.78±1.37 vs. 9.36±1.83 mg/dl, P=0.009 post-surgery and 9.93±1.09 vs. 10.28±1.33 mg/dl, P=0.046 before discharge).
Table 5.
Postoperative variables and mortality outcome, based on sex
| Male (N=226) | Female (N=94) | p-value a | |
|---|---|---|---|
| Para clinical and laboratory data | |||
| Pulmonary artery pressure (PAP) post-surgery (mmHg) | 26.4 ± 7.03 | 26.4 ± 6.06 | 0.636 |
| Ejection fraction (EF) post-surgery (%) | 43.4 ± 9.98 | 48.0 ± 7.46 | <0.001 |
| Ejection fraction (EF) after six months (%) | 43.2 ± 11.9 | 49.5 ± 8.79 | 0.006 |
| Differences in EF before and post-surgery (%) | 0 (-5,0) | 0 (0,5) | 0.258 |
| Differences in EF post-surgery and after six months (%) | 0 (-5,5) | 0 (0,2.5) | 0.888 |
| Hemoglobin (Hgb) post-surgery(g/dl) | 9.36 ± 1.83 | 8.78 ± 1.37 | 0.009 |
| Hemoglobin (Hgb) before discharge (g/dl) | 10.3 ± 1.33 | 9.93 ± 1.09 | 0.046 |
| Serum creatinine (Scr), post-surgery (mg/dl) | 1.49 ± 1.07 | 1.28 ± 0.6 | <0.001 |
| Serum creatinine (Scr), before discharge (mg/dl) | 1.32 ± 1.03 | 1.02 ± 0.32 | <0.001 |
| Complications during hospitalization | |||
| Male (N=226) | Female (N=94) | p-value a | |
| Recurrent myocardial infarction (MI) | 1 (0.44) | 0 | 0.709 |
| Cerebral vascular attack | 7 (3.09) | 2 (2.12) | 0.478 |
| Gastrointestinal (GI) bleeding | 0 | 0 | - |
| Intracranial hemorrhage (ICH) | 0 | 0 | - |
| Complications after six months | |||
| Male (N=220) | Female (N=90) | ||
| Cerebral vascular attack | 1 (0.45) | 0 | 0.711 |
| Gastrointestinal (GI) bleeding | 2 (0.90) | 0 | 0.505 |
| Re-angiography | 3 (1.36) | 4 (4.44) | 0.416 |
| Re-percutaneous coronary intervention (PCI) | 0 | 2 (2.22) | 0.032 |
| Re-coronary artery bypass (CABG) surgery | 0 | 0 | - |
| Hospital assessment | |||
| Male (N=226) | Female (N=94) | ||
| Intensive care unit (ICU) length of stay (day) | 6.06 ± 3.17 | 5.56 ± 2.01 | 0.411 |
| Hospital length of stay(day) | 14.5 ± 9.39 | 14.4 ± 5.53 | 0.591 |
| Total Hospitalization costs b | 1655.3 ± 550.8 | 1641.3 ± 447.8 | 0.666 |
| Mortality outcome | |||
| Male (N=226) | Female (N=94) | p-value a | |
| During hospitalization | 6 (2.65) | 4 (4.25) | 0.545 |
| Male (N=220) | Female (N=90) | ||
| After six months | 4 (1.81) | 2 (2.22) | 0.557 |
| Male (N=226) | Female (N=94) | ||
| Overall mortality | 10 (4.42) | 6 (6.38) | 0.464 |
a, unpaired student’s t test, Mann-Whitney U test, chi-square test, fisher exact test based on the data based on the data. Data presented as the n (%), mean±SD or median (Q1, Q2) based on the parameters. b, based on US dollar (USD)
Mortality outcomes
During the study period, the overall mortality rate in our setting was 4.42% and 6.38% in men and women, with no statistically significant difference between the two groups (P= 0.464).
Furthermore, there were no statistically significant differences between genders regarding in-hospital and six-months-after-discharge mortality (P=0.545 for in-hospital mortality and P=0.557 for six months after discharge). Table 5 summarizes the findings.Figure 1 depicts the survival probability during the study period. Survival probability was 0.92 (95% CI, 0.84 – 0.96) and 0.79 (95% CI, 0.46 – 0.93) in females and males, respectively, with no statistically significant difference between genders according to the Log Ranks test (P= 0.469). In addition, the total survival probability was 0.83 (95% CI, 0.60 – 0.93).
Table 1.
Demographic data of participation, based on sex
Discussion
Several studies have been conducted to assess sex differences in outcomes following CABG surgery 6, 11-15. As a result, ours is not the first study, but it is one of the few conducted on the Iranian population 16-18.
Women who presented for cardiac surgery were older than men, and the onset of symptomatic coronary artery diseases (CAD) was delayed in females 11-14, 19. Female patients were also older in this study. Possible explanations for this finding include the delayed onset of CAD after menopause and delayed diagnosis and treatment of CAD in women compared to men 19. As in previous studies 11, 13, 14, 19, the incidence of comorbid conditions, such as dyslipidemia, hypertension, and diabetes, was significantly higher in females in our study. Women had higher fasting blood glucose (FBS) and HgbA1C levels, indicating that the incidence of diabetes was more significant in females. In contrast, men were more likely to have MI and had lower EF in our study.
In contrast to other studies, there was no statistically significant difference between the two genders in comorbidities such as chronic lung disease, PVD, cerebral vascular diseases, CHF, previous MI, and cardiac surgery [11-13]. Females received more units of packed red blood cells transfused, according to statistics. A higher incidence of anemia in women and lower preoperative Hgb levels could explain this disparity. In line with our findings, deNeto et al. investigated postoperative complications following CABG surgery and concluded that the rate of transfusion in the operating room is significantly higher in women 14.
In our study, the male gender had a high incidence of dialysis-dependent renal failure and a higher serum creatinine level at referral time. However, this finding contradicts a previous study conducted in the Iranian population, which found lower mean creatinine clearance in women at the referral time. Additionally, unlike the mentioned study, there was no difference in our study’s incidence of previous MI 16.
Other studies did not evaluate income, educational and marital status, and physical activity level. However, we did evaluate and find statistical differences between the two groups. These findings revealed socioeconomic differences between the two genders. In the study conducted by Bagheri et al. 16, there was no difference in operative variables. However, this study showed a statistical difference in the units of packed red blood cells transfused, with females receiving more. Differences could explain this result in surgeon experience, and socioeconomic status among Iranian populations admitted to different hospitals.
The impact of gender on early and long-term mortality after CABG yields contradictory results. According to observational studies, the female gender is an independent risk factor for morbidity and mortality after CABG 6, 11-13, 20. Women’s gender differences in outcomes after CABG surgery are explained by older age, smaller body size and coronary artery diameters, a higher incidence of comorbid complications, a more frequent need for postoperative inotropic support, preoperative blood transfusions, and longer lengths of hospital stay 6, 11, 12, 21.
However, despite differences in pre, during, and postoperative variables, there was no difference in mortality between the two genders in other studies [14, 22]. We found no significant difference between the study’s two arms.
Because the risk of mortality following CABG surgery depends on multiple risk factors, such as comorbid diseases, postoperative complications, and the hospital and surgeon experience, differences in these factors in various communities may be associated with this confounding results about the mortality.We also acknowledge the study’s potential limitations. First, the current study had an unequal number of two groups, which could limit group comparability. Second, because our hospital is one of the crucial public referral centers for low socioeconomic status patients, it may possess biased effects as a confounding factor on the patient’s selection and the study results.
In conclusion, there were some differences in the preoperative, intra-operative, and postoperative CABG parameters between the two genders, but there was no difference in postoperative mortality in our setting.
Authors’ Contribution
RM and RS designed the study, and MS. RH and RS conducted the research and drafted the proposal. NK and RS assisted in data collection. RH examined the data. RS, RH, and MS were responsible for data interpretation and original draft preparation. The preparation was reviewed and edited by RH, MS, and RS. All authors contributed to the manuscript’s improvement and finalization of the article for publication.
Acknowledgment
We are grateful to Niloufar Taherpour for her assistance with this project. This study received no specific grant from the public, commercial, or non-profit funding agencies.
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