{"id":51472,"date":"2023-09-30T10:22:32","date_gmt":"2023-09-30T10:22:32","guid":{"rendered":"https:\/\/biomedpharmajournal.org\/?p=51472"},"modified":"2023-10-07T11:49:51","modified_gmt":"2023-10-07T11:49:51","slug":"relationship-between-cardiovascular-risk-factors-and-development-of-acute-coronary-syndrome","status":"publish","type":"post","link":"https:\/\/biomedpharmajournal.org\/staging\/vol16no3\/relationship-between-cardiovascular-risk-factors-and-development-of-acute-coronary-syndrome\/","title":{"rendered":"Relationship between Cardiovascular Risk Factors and Development of Acute Coronary Syndrome"},"content":{"rendered":"\n

Introduction<\/strong><\/p>\n\n\n\n

Acute coronary\nsyndrome (ACS), a subcategory of ischemic heart disease,  is considered a major cause of mortality.1 In\nSaudi Arabia, the prevalence of ACS among the population is 8.2%, most of them\ndiagnosed with unstable angina (19.2%).2 ACS comprise a group of disorders that\narise from acute myocardial ischemia.3 These disorders include UA, NSTEMI , and\nSTEMI.3-5 Risk factors of coronary artery disease include non-Modifiable RFs which\ncomprise family history, race, age, and gender; modifiable like type2 diabetes\nmellitus, hypertension, smoking, dyslipidemia, chronic kidney disease, Obesity,\nand metabolic syndrome.6.7 Prevention and early detection of risk factors diminished\nthe rate of morbidity and mortality associated with CAD. In spite of the fact\nthat Saudi Arabia is known for its ethnic, and socioeconomic diversity which\nmay contribute to ACS, there is a lack of studies about ACS. Therefore, this\nstudy aims to evaluate the prevalence of cardiovascular RFs among patients\nadmitted to Prince Sultan cardiac center, King Saud Hospital, and Bukayriyah\nGeneral Hospital and to determine their association with different ACS\nsubtypes.<\/p>\n\n\n\n

Research Design and Methods:<\/strong><\/p>\n\n\n\n

Study design<\/strong><\/p>\n\n\n\n

A retrospective\nmulti-center cross-sectional study was conducted on 170 patients admitted to\nPrince Sultan cardiac center, King Saud Hospital, and Bukayriyah General\nHospital in Al Qassim, KSA. The ACS patients were classified into UA, NSTEMI,\nand STEMI. Patients with stable angina or previous MI were excluded from the\nstudy. Participants\u2019 data was retrieved from patients\u2019 medical records in a\npredesigned data collection form focusing on demographic characteristics and RFs\nsuch as family history, hypertension, diabetes mellitus, and smoking. Ethical\napproval for this study was obtained from Al- Qassim Regional Ethical\nCommittee.<\/p>\n\n\n\n

Statistical analysis<\/strong><\/p>\n\n\n\n

The collected data was fed\nto IBM SPSS software version 22 (SPSS, Inc. Chicago, IL). All statistical\nanalysis was done using two-tailed tests. Descriptive analysis performed for\nall variables including patients\u2019 socio-demographic data, weight, height, and\nnationality. Different risk factors of ACS were also displayed such as\ndiabetes, hypertension, smoking, dyslipidemia, and IHD history. Crosstabulation\nwas used to evaluate the distribution of ACS subtypes by reported risk factors\nand patients\u2019 data. Pearson chi-square test and exact probability test for\nsmall frequency distributions were used to assess the associations. P-value\nless than 0.05 was statistically significant.<\/p>\n\n\n\n

Results<\/strong><\/p>\n\n\n\n

A total of 170 patients were\nincluded. Patients’ ages ranged from 28 to 87 years with a mean age of 58.2 \u00b1\n11.9 years old. 125 patients (73.5%) were males and 45 (26.5%) were females. As\nfor nationality, 131 (77%) patients were Saudi. Considering body mass index, 36\n(21.2%) patients had normal weights, 82 (48.2%) were overweight, and 52 (30.6%)\nwere obese (Table 1).<\/p>\n\n\n\n

Table 1: Bio-demographic data of study participants<\/em><\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

Data<\/strong><\/p>\n<\/td>\n

\n

N<\/strong><\/p>\n<\/td>\n

\n

%<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

Age in years<\/strong><\/p>\n<\/td>\n

\n

 <\/p>\n<\/td>\n

\n

 <\/p>\n<\/td>\n<\/tr>\n

\n

< 50<\/em><\/p>\n<\/td>\n

\n

43<\/p>\n<\/td>\n

\n

25.3<\/p>\n<\/td>\n<\/tr>\n

\n

50-59<\/em><\/p>\n<\/td>\n

\n

52<\/p>\n<\/td>\n

\n

30.6<\/p>\n<\/td>\n<\/tr>\n

\n

60-69<\/em><\/p>\n<\/td>\n

\n

45<\/p>\n<\/td>\n

\n

26.5<\/p>\n<\/td>\n<\/tr>\n

\n

70+<\/em><\/p>\n<\/td>\n

\n

30<\/p>\n<\/td>\n

\n

17.6<\/p>\n<\/td>\n<\/tr>\n

\n

Gender<\/strong><\/p>\n<\/td>\n

\n

 <\/p>\n<\/td>\n

\n

 <\/p>\n<\/td>\n<\/tr>\n

\n

Male<\/em><\/p>\n<\/td>\n

\n

125<\/p>\n<\/td>\n

\n

73.5<\/p>\n<\/td>\n<\/tr>\n

\n

Female<\/em><\/p>\n<\/td>\n

\n

45<\/p>\n<\/td>\n

\n

26.5<\/p>\n<\/td>\n<\/tr>\n

\n

Nationality<\/strong><\/p>\n<\/td>\n

\n

 <\/p>\n<\/td>\n

\n

 <\/p>\n<\/td>\n<\/tr>\n

\n

Saudi<\/em><\/p>\n<\/td>\n

\n

131<\/p>\n<\/td>\n

\n

77.1<\/p>\n<\/td>\n<\/tr>\n

\n

Non-Saudi<\/em><\/p>\n<\/td>\n

\n

39<\/p>\n<\/td>\n

\n

22.9<\/p>\n<\/td>\n<\/tr>\n

\n

Body mass index<\/strong><\/p>\n<\/td>\n

\n

 <\/p>\n<\/td>\n

\n

 <\/p>\n<\/td>\n<\/tr>\n

\n

Normal<\/em><\/p>\n<\/td>\n

\n

36<\/p>\n<\/td>\n

\n

21.2<\/p>\n<\/td>\n<\/tr>\n

\n

Overweight<\/em><\/p>\n<\/td>\n

\n

82<\/p>\n<\/td>\n

\n

48.2<\/p>\n<\/td>\n<\/tr>\n

\n

Obese<\/em><\/p>\n<\/td>\n

\n

52<\/p>\n<\/td>\n

\n

30.6<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

A total of 87 patients (51.2%)\nhad STEMI, 47 (27.6%) had NSTEMI, and 36 (21.2%) complained of unstable angina\n(Figure1).<\/p>\n\n\n\n\n\n
\"\"<\/td>\n\n

Figure 1: Distribution of acute coronary syndromes subtypes among study participants.<\/strong><\/p>\n

<\/p>\n

Click here to view Figure<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

Figure 2\ndemonstrates the risk factors prevalence among patients with ACS. The\nmost-reported risk factors were diabetes mellitus, and hypertension (66% each),\nfollowed by dyslipidemia (58%), family history of IHD (25%), smoking (19%), and\nIHD (14%).<\/p>\n\n\n\n\n\n
\"\"<\/td>\n\n

Figure 2: Prevalence of risk factors among study participants<\/strong><\/p>\n

<\/p>\n

Click here to view Figure<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

Table2 shows a significant difference regarding smoking\nstatus by patient\nage as all patients  aged 70 years or more were non-smokers compared to 41.9% of the age group less than 50 years were active smokers (P=.001). All other\nrisk factors were insignificantly associated with patients\u2019 age but all of them were higher\namong old aged patients (70 years\nor more) except for IHD.<\/em><\/strong><\/p>\n\n\n\n

Table 2: Association between risk factors and different age group<\/strong>s<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

Risk factors<\/strong><\/p>\n<\/td>\n

\n

Age in years<\/strong><\/p>\n<\/td>\n

\n

p-value<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

< 50<\/strong><\/p>\n<\/td>\n

\n

50-59<\/strong><\/p>\n<\/td>\n

\n

60-69<\/strong><\/p>\n<\/td>\n

\n

70+<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

N (%)<\/strong><\/p>\n<\/td>\n

\n

N (%)<\/strong><\/p>\n<\/td>\n

\n

N (%)<\/strong><\/p>\n<\/td>\n

\n

N (%)<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

Active smoker<\/strong><\/p>\n<\/td>\n

\n

.001<\/u><\/p>\n<\/td>\n<\/tr>\n

\n

Yes<\/em><\/p>\n<\/td>\n

\n

18 (41.9)<\/p>\n<\/td>\n

\n

10 (19.2)<\/p>\n<\/td>\n

\n

4 (9.1)<\/p>\n<\/td>\n

\n

0 (0)<\/p>\n<\/td>\n<\/tr>\n

\n

No<\/em><\/p>\n<\/td>\n

\n

25 (58.1)<\/p>\n<\/td>\n

\n

42 (80.8)<\/p>\n<\/td>\n

\n

40 (90.9)<\/p>\n<\/td>\n

\n

30 (100)<\/p>\n<\/td>\n<\/tr>\n

\n

Hypertension<\/strong><\/p>\n<\/td>\n

\n

.818<\/p>\n<\/td>\n<\/tr>\n

\n

Yes<\/em><\/p>\n<\/td>\n

\n

26 (60.5)<\/p>\n<\/td>\n

\n

35 (67.3)<\/p>\n<\/td>\n

\n

30 (68.2)<\/p>\n<\/td>\n

\n

21 (70)<\/p>\n<\/td>\n<\/tr>\n

\n

No<\/em><\/p>\n<\/td>\n

\n

17 (39.5)<\/p>\n<\/td>\n

\n

17 (32.7)<\/p>\n<\/td>\n

\n

14 (31.8)<\/p>\n<\/td>\n

\n

9 (30)<\/p>\n<\/td>\n<\/tr>\n

\n

Diabetes<\/strong><\/p>\n<\/td>\n

\n

.221<\/p>\n<\/td>\n<\/tr>\n

\n

Yes<\/em><\/p>\n<\/td>\n

\n

27 (62.8)<\/p>\n<\/td>\n

\n

30 (57.7)<\/p>\n<\/td>\n

\n

33 (73.3)<\/p>\n<\/td>\n

\n

23 (76.7)<\/p>\n<\/td>\n<\/tr>\n

\n

No<\/em><\/p>\n<\/td>\n

\n

16 (37.2)<\/p>\n<\/td>\n

\n

22 (42.3)<\/p>\n<\/td>\n

\n

12 (26.7)<\/p>\n<\/td>\n

\n

7 (23.3)<\/p>\n<\/td>\n<\/tr>\n

\n

Dyslipidaemia<\/strong><\/p>\n<\/td>\n

\n

.980<\/p>\n<\/td>\n<\/tr>\n

\n

Yes<\/em><\/p>\n<\/td>\n

\n

24 (55.8)<\/p>\n<\/td>\n

\n

31 (59.6)<\/p>\n<\/td>\n

\n

26 (57.8)<\/p>\n<\/td>\n

\n

18 (60)<\/p>\n<\/td>\n<\/tr>\n

\n

No<\/em><\/p>\n<\/td>\n

\n

19 (44.2)<\/p>\n<\/td>\n

\n

21 (40.4)<\/p>\n<\/td>\n

\n

19 (42.2)<\/p>\n<\/td>\n

\n

12 (40)<\/p>\n<\/td>\n<\/tr>\n

\n

Family history of IHDa<\/sup><\/strong><\/p>\n<\/td>\n

\n

.526$<\/sup><\/p>\n<\/td>\n<\/tr>\n

\n

Yes<\/em><\/p>\n<\/td>\n

\n

1 (11.1)<\/p>\n<\/td>\n

\n

2 (28.6)<\/p>\n<\/td>\n

\n

1 (20)<\/p>\n<\/td>\n

\n

3 (42.9)<\/p>\n<\/td>\n<\/tr>\n

\n

No<\/em><\/p>\n<\/td>\n

\n

8 (88.9)<\/p>\n<\/td>\n

\n

5 (71.4)<\/p>\n<\/td>\n

\n

4 (80)<\/p>\n<\/td>\n

\n

4 (57.1)<\/p>\n<\/td>\n<\/tr>\n

\n

IHDa<\/sup><\/strong><\/p>\n<\/td>\n

\n

.368$<\/sup><\/p>\n<\/td>\n<\/tr>\n

\n

 <\/p>\n

Yes<\/em><\/p>\n<\/td>\n

\n

7 (33.3)<\/p>\n<\/td>\n

\n

2 (11.8)<\/p>\n<\/td>\n

\n

3 (21.4)<\/p>\n<\/td>\n

\n

2 (14.3)<\/p>\n<\/td>\n<\/tr>\n

\n

No<\/em><\/p>\n<\/td>\n

\n

14 (66.7)<\/p>\n<\/td>\n

\n

15 (88.2)<\/p>\n<\/td>\n

\n

11 (78.6)<\/p>\n<\/td>\n

\n

12 (85.7)<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

P: Pearson X2 test  $: Exact probability test  N: number<\/p>\n

P-value < 0.05 considered significant<\/p>\n

a, IHD: ischemic heart disease<\/p>\n\n\n

Table 3 shows the distribution of different ACS subtypes by age, gender, and  BMI. 65.1% of young aged patients (< 50 years) had STEMI while 40% of old aged patients (70+) had NSTEMI with no statistical significance (P=.188). A total of 52.8% of males had STEMI versus 46.7% of female patients (P=.375). Also, 61.1% of patients with normal body weight had STEMI compared to 52.4% of overweight and 42.3% of obese patients (P=.229).<\/p>\n\n\n\n

Table 3: Distribution of acute coronary syndrome subtypes by age, gender, BMI<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

Personal data<\/strong><\/p>\n<\/td>\n

\n

Type<\/strong><\/p>\n<\/td>\n

\n

p-value<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

NSTEMIb<\/sup><\/strong><\/p>\n<\/td>\n

\n

STEMIa<\/sup><\/strong><\/p>\n<\/td>\n

\n

Unstable angina<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

N (%)<\/strong><\/p>\n<\/td>\n

\n

N (%)<\/strong><\/p>\n<\/td>\n

\n

N (%)<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

Age in years<\/strong><\/p>\n<\/td>\n

\n

.188<\/p>\n<\/td>\n<\/tr>\n

\n

< 50<\/em><\/p>\n<\/td>\n

\n

10 (23.3)<\/p>\n<\/td>\n

\n

28 (65.1)<\/p>\n<\/td>\n

\n

5 (11.6)<\/p>\n<\/td>\n<\/tr>\n

\n

50-59<\/em><\/p>\n<\/td>\n

\n

11 (21.2)<\/p>\n<\/td>\n

\n

27 (51.9)<\/p>\n<\/td>\n

\n

14 (26.9)<\/p>\n<\/td>\n<\/tr>\n

\n

60-69<\/em><\/p>\n<\/td>\n

\n

14 (31.1)<\/p>\n<\/td>\n

\n

21 (46.7)<\/p>\n<\/td>\n

\n

10 (22.2)<\/p>\n<\/td>\n<\/tr>\n

\n

70+<\/em><\/p>\n<\/td>\n

\n

12 (40.0)<\/p>\n<\/td>\n

\n

11 (36.7)<\/p>\n<\/td>\n

\n

7 (23.3)<\/p>\n<\/td>\n<\/tr>\n

\n

Gender<\/strong><\/p>\n<\/td>\n

\n

.375<\/p>\n<\/td>\n<\/tr>\n

\n

Male<\/em><\/p>\n<\/td>\n

\n

31 (24.8)<\/p>\n<\/td>\n

\n

66 (52.8)<\/p>\n<\/td>\n

\n

28 (22.4)<\/p>\n<\/td>\n<\/tr>\n

\n

Female<\/em><\/p>\n<\/td>\n

\n

16 (35.6)<\/p>\n<\/td>\n

\n

21 (46.7)<\/p>\n<\/td>\n

\n

8 (17.8)<\/p>\n<\/td>\n<\/tr>\n

\n

Body mass index<\/strong><\/p>\n<\/td>\n

\n

.229<\/p>\n<\/td>\n<\/tr>\n

\n

Normal<\/em><\/p>\n<\/td>\n

\n

10 (27.8)<\/p>\n<\/td>\n

\n

22 (61.1)<\/p>\n<\/td>\n

\n

4 (11.1)<\/p>\n<\/td>\n<\/tr>\n

\n

Overweight<\/em><\/p>\n<\/td>\n

\n

23 (28.0)<\/p>\n<\/td>\n

\n

43 (52.4)<\/p>\n<\/td>\n

\n

16 (19.5)<\/p>\n<\/td>\n<\/tr>\n

\n

Obese<\/em><\/p>\n<\/td>\n

\n

14 (26.9)<\/p>\n<\/td>\n

\n

22 (42.3)<\/p>\n<\/td>\n

\n

16 (30.8)<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

Regarding Association between different ACS subtypes and cardiovascular risk factors (Table4).\nThe exact 65.6% of active smokers had STEMI compared to 48.2% of non-smokers\nwith no statistical significance (P=0.190). Also, 50% of patients with\nhypertension complained of STEMI versus 54.4% of non- hypertensive (P=0.158). STEMI was diagnosed among 52.6% of\nnon-diabetic patients compared to 50.4% of diabetic patients (P=0.542).\nAdditionally, 54.5% of patients with dyslipidemia complained of STEMI versus\n46.5% of others without (P=0.308). Family history of IHD was associated with developing\nNSTEMI (42.9%) compared to 28.6% of patients\nwithout (P=0.550). A total of 52.2% of patients with IHD developed STEMI\ncompared to 51% of others without (0.351).<\/p>\n\n\n\n

Table 4: Association between different acute coronary syndrome subtypes and cardiovascular risk factor<\/strong>s.<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

Risk factors<\/strong><\/p>\n<\/td>\n

\n

Type<\/strong><\/p>\n<\/td>\n

\n

p-value<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

NSTEMIb<\/sup><\/strong><\/p>\n<\/td>\n

\n

STEMIa<\/sup><\/strong><\/p>\n<\/td>\n

\n

Unstable angina<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

N (%)<\/strong><\/p>\n<\/td>\n

\n

N (%)<\/strong><\/p>\n<\/td>\n

\n

N (%)<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

Active smoker<\/strong><\/p>\n<\/td>\n

 <\/td>\n\n

.190<\/p>\n<\/td>\n<\/tr>\n

\n

Yes<\/em><\/p>\n<\/td>\n

\n

7 (21.9)<\/p>\n<\/td>\n

\n

21 (65.6)<\/p>\n<\/td>\n

\n

4 (12.5)<\/p>\n<\/td>\n<\/tr>\n

\n

No<\/em><\/p>\n<\/td>\n

\n

40 (29.2)<\/p>\n<\/td>\n

\n

66 (48.2)<\/p>\n<\/td>\n

\n

31 (22.6)<\/p>\n<\/td>\n<\/tr>\n

\n

Hypertension<\/strong><\/p>\n<\/td>\n

\n

.158<\/p>\n<\/td>\n<\/tr>\n

\n

Yes<\/em><\/p>\n<\/td>\n

\n

36 (32.1)<\/p>\n<\/td>\n

\n

56 (50.0)<\/p>\n<\/td>\n

\n

20 (17.9)<\/p>\n<\/td>\n<\/tr>\n

\n

No<\/em><\/p>\n<\/td>\n

\n

11 (19.3)<\/p>\n<\/td>\n

\n

31 (54.4)<\/p>\n<\/td>\n

\n

15 (26.3)<\/p>\n<\/td>\n<\/tr>\n

\n

Diabetes<\/strong><\/p>\n<\/td>\n

 <\/td>\n\n

.542<\/p>\n<\/td>\n<\/tr>\n

\n

Yes<\/em><\/p>\n<\/td>\n

\n

34 (30.1)<\/p>\n<\/td>\n

\n

57 (50.4)<\/p>\n<\/td>\n

\n

22 (19.5)<\/p>\n<\/td>\n<\/tr>\n

\n

No<\/em><\/p>\n<\/td>\n

\n

13 (22.8)<\/p>\n<\/td>\n

\n

30 (52.6)<\/p>\n<\/td>\n

\n

14 (24.6)<\/p>\n<\/td>\n<\/tr>\n

\n

Dyslipidaemia<\/strong><\/p>\n<\/td>\n

\n

.308<\/p>\n<\/td>\n<\/tr>\n

\n

Yes<\/em><\/p>\n<\/td>\n

\n

28 (28.3)<\/p>\n<\/td>\n

\n

54 (54.5)<\/p>\n<\/td>\n

\n

17 (17.2)<\/p>\n<\/td>\n<\/tr>\n

\n

No<\/em><\/p>\n<\/td>\n

\n

19 (26.8)<\/p>\n<\/td>\n

\n

33 (46.5)<\/p>\n<\/td>\n

\n

19 (26.8)<\/p>\n<\/td>\n<\/tr>\n

\n

Family history of IHDc<\/sup><\/strong><\/p>\n<\/td>\n

\n

.550$<\/sup><\/p>\n<\/td>\n<\/tr>\n

\n

Yes<\/em><\/p>\n<\/td>\n

\n

3 (42.9)<\/p>\n<\/td>\n

\n

2 (28.6)<\/p>\n<\/td>\n

\n

2 (28.6)<\/p>\n<\/td>\n<\/tr>\n

\n

No<\/em><\/p>\n<\/td>\n

\n

6 (28.6)<\/p>\n<\/td>\n

\n

11 (52.4)<\/p>\n<\/td>\n

\n

4 (19)<\/p>\n<\/td>\n<\/tr>\n

\n

IHDc<\/sup><\/strong><\/p>\n<\/td>\n

\n

.351<\/p>\n<\/td>\n<\/tr>\n

\n

Yes<\/em><\/p>\n<\/td>\n

\n

4 (17.4)<\/p>\n<\/td>\n

\n

12 (52.2)<\/p>\n<\/td>\n

\n

7 (30.4)<\/p>\n<\/td>\n<\/tr>\n

\n

No<\/em><\/p>\n<\/td>\n

\n

43 (29.3)<\/p>\n<\/td>\n

\n

75 (51)<\/p>\n<\/td>\n

\n

29 (19.7)<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

Discussion <\/strong><\/p>\n\n\n\n

Out of the total number of patients included in the current study, 51.2% of them presented with STEMI, while 27.6% and 21.2%\nof them presented with NSTEMI\nand UA respectively. The distribution of ACS subtypes was as expected\naccording to previous\nstudies which reported that STEMI was the most common presentation in\nACS patients, followed by NSTEMI, and UA. 8,9<\/sup> STARS-1\nProgram (The first survey of the Saudi\nAcute Myocardial Infarction Registry Program ) reported that among 2233 patients with ACS,\n65.9% of them had STEMI\nand 34.1% had NSTEMI.\nThey attributed this distribution\nto the relatively young age of ACS appearance in their sample.10<\/sup> However, in contrast to their\nfindings, the current study revealed that younger patients have the lowest risk\nfactors.<\/p>\n\n\n\n

According to the current study, 73.5% of the patients were\nmales, while 26.5% were females. These findings align with various studies that\nhave indicated a higher prevalence of all risk factors among males.11,12,13,14<\/sup> Despite the fact that more than half of male patients\npresent with STEMI, the occurrence of NSTEMI is lower compared to female\npatients, as confirmed by multiple studies.15,16<\/sup> However, the gender association with ACS\nprogression remains uncertain.<\/p>\n\n\n\n

Most of the ACS patients in the current\nstudy were 50 years\nold or older (74.7%),\nand among all age groups,\nSTEMI was higher in the younger age. In agreement with this finding,\nearlier studies documented inverse relationship between STEMI and patients’ age.9,17<\/sup><\/p>\n\n\n\n

Considering body mass index four publications examined CVD prevalence rates\naccording to obesity\nstatus and discovered a favorable\ncorrelation between obesity and elevated CVD prevalence.18, 19,<\/sup> 20,\n21.<\/sup> <\/p>\n\n\n\n

Based on the patients\u2019 BMI data our results showed that\nobese and overweight patients were at higher risk for ACS compared to\nnormal-weight patients and most of them presented with STEMI. And our claim was\nsupported by a study performed locally that demonstrated that even a mild\nelevation in a patient’s BMI was considered as a risk factor for developing ACS.22,\n23, 24.<\/sup> Interestingly our results showed that overweight patients were at\nhigher risk of ACS (48.2%) compared to obese patients (30.6%). However,\nunexpectedly normal weight patients were the most diagnosed with STEMI (61.1%)\ncompared to both overweight and obese patients. In our study, the BMI\nrelationship with UA has a predictable pattern which exhibits that with each\nincrease in BMI the percentage of UA cases increases. <\/p>\n\n\n\n

We generally recognize risk factors through\nepidemiological findings.25<\/sup> The high prevalence of the\ncardiovascular disease is due to specific lifestyle characteristics and related\nrisk factors.\nMany cardiovascular risk\nfactors contribute to ACS. These factors are classified into modifiable and\nnon-modifiable risk factors.26<\/sup> In Saudi Arabia according to the\nProspective Urban Rural Epidemiology study (PURE-Saudi) which focus on the\nepidemiology of cardiovascular disease risk factors demonstrated that the most\ncommon risk factor was physical inactivity (69.4%) followed by obesity 34.4%,\nunhealthy eating 32.1%, dyslipidemia (32.1%), hypertension (30.3%), diabetes\n(25.1%) and low percentage of the population were active smokers (12.2%).27<\/sup><\/p>\n\n\n\n

In the present study, a significant percentage of ACS\npatients had DM (66%) and HTN (66%) as risk factors, followed by dyslipidemia\nwith a percentage of 58%. However, we observed a low percentage of active\nsmokers among the patients. This could be due to the fact that the average age\nof our sample is 58 years old, with the majority of patients being above 40\nyears old. Previous studies conducted in Saudi Arabia have shown that the\nyounger age group (40 years old or younger) has the highest percentage of\nsmokers, reaching 84.8%.28<\/sup><\/p>\n\n\n\n

The main concern\nof our study was to find the association between cardiovascular risk factors\nand ACS subtypes, and we focus on six main\nrisk factors. Starting\nwith smoking which is considered a crucial risk factor.29<\/sup> Most\nof the smokers\u2019 patients in our sample were at higher risk for developing STEMI (65.6%)\ncompared to non-smokers. Out of studies\nthat have supported this association, one study\nshowed that smoking raises the risk of developing ACS even in those who smoke\nless than 5 cigarettes per day.30,\n31<\/sup><\/p>\n\n\n\n

HTN along with DM appears\nto be higher in NSTEMI compared with other ACS subtypes.\nThese results were consistent with\nsome previous studies.\nAn epidemiological study conducted on patients\nwith NSTEMI shows that two-thirds of the population was suffering from\nchronic HTN. 32<\/sup><\/p>\n\n\n\n

According to the Saudi Project\nfor Assessment of Coronary Events\n(SPACE)\nstudy HTN was the second most risk factor\nfound in CAD patients in Saudi\nArabia with a percent of 48%.8<\/sup> Hypertension prevalence increases\nwith age.33 <\/sup>Seeing that most of our patients were older, it is no strange that HTN was one of the most risk factors along\nwith DM according\nto our results.<\/p>\n\n\n\n

In Saudi Arabia\naccording to the latest edition\nof \u201cIDF Diabetes Atlas\u201d the prevalence of adults with diabetes currently\nis 18.7%. And Saudi Arabia\nclassified as the seventh-highest country\nwith new cases\nof diabetes type 1.34<\/sup> In general, men with diabetes\nwere twice more susceptible to CVD than nondiabetic . Among diabetic\nwomen, the prevalence of CVD was about three\ntimes that those who were nondiabetic .35<\/sup> Dyslipidemia also appeared\nto be a critical risk factor for ACS according to our findings and previous studies.33,36<\/sup> By comparing dyslipidemia presence with ACS\nsubtypes it showed\nan increased presentation of patients with\nSTEMI and NSTEMI. These outcomes were\ncompatible with earlier\nstudies.36, 37 <\/sup> In one\nstudy that was conducted on ACS patients\nwith a mean age of 59 years old\nwhich is similar\nto what we got (58 years) shows that most of them presented mostly with STEMI (61%)\nfollowed by NSTEMI\n(25.7%)  and with a lower percentage of UA (13.3%).37<\/sup>Finally Based on our results, having\nan IHD or a family\nhistory of IHD was\nassociated with a higher percentage of UA but particularly IHD as a risk factor was associated with a higher occurrence of STEMI unlike\nthe family history\nof IHD where\nmost patients presented\nwith NSTEMI. 24<\/sup><\/p>\n\n\n\n

Conclusion<\/strong><\/p>\n\n\n\n

To conclude, out of 170 patients with ACS included\nin the study most of them were males, at the age of 50 years old or more, with elevated\nBMI. Furthermore, 51.21% of them presented with STEMI followed by 27.6% with NSTEMI and 21.2%\nwith UA. <\/strong>Among the cardiovascular\nrisk factors, HTN, DM, and dyslipidemia were presented in more than half of the patients\nwhich strongly suggests an association with developing ACS.<\/strong><\/p>\n\n\n\n

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