Acute myocardial infarction (AMI) following ischaemic heart disease (IHD) is associated with increased morbidity and mortality. The condition remains a management challenge in resource-constrained environments. This study analysed the management and outcomes of patients presenting with AMI at a district hospital in KwaZulu-Natal.
A descriptive study that assessed hospital records of all patients diagnosed with AMI over a 2-year period (01 August 2016 to 31 July 2018). Data extracted recorded patient demographics, risk factors, timing of care, therapeutic interventions, follow up with cardiology and mortality of patients.
Of the 140 patients who were admitted with AMI, 96 hospital records were analysed. The mean (standard deviation [s.d.]) age of patients was 55.8 (±12.7) years. Smoking (73.5%) and hypertension (63.3%) were the most prevalent risk factors for patients with ST elevation myocardial infarction (STEMI) in contrast to dyslipidaemia (70.2%) and hypertension (68.1%) in patients with non-ST elevation myocardial infarction (NSTEMI). Almost 49.5% of patients arrived at hospital more than 6 h after symptom onset. Three (12.5%) patients received thrombolytic therapy within the recommended 30-min time frame. The mean triage-to-needle time was 183 min – range (3; 550). Median time to cardiology appointment was 93 days. The in-hospital mortality of 12 deaths considering 140 admissions was 8.6%.
In a resource-constrained environment with multiple systemic challenges, in-hospital mortality is comparable to that in private sector conditions in South Africa. This entrenches the role of the family physician. There is need for more coordinated systems of care for AMI between district hospitals and tertiary referral centres.
Ischaemic heart disease (IHD) remains a major public health issue and was the leading cause of death globally for every consecutive year between 2000 and 2019.
Acute myocardial infarction (AMI) is defined pathologically as myocardial necrosis, a consequence of prolonged myocardial ischaemia.
The European Society of Cardiology (ESC) has published guidelines for managing patients with AMI.
Immediate transfer should be initiated for patients in cardiogenic shock or heart failure, with urgent transfer for those who have failed reperfusion.
South Africa is a country with a paucity of healthcare resources and unequal distribution of health services in the public and the private sectors.
In the KwaZulu-Natal public sector, patient care is a huge challenge as only two facilities in the province are PCI equipped. Inkosi Albert Luthuli Central Hospital based in Durban and Grey’s Hospital based in Pietermaritzburg serves the entire region as well as parts of the Eastern Cape with a total population exceeding 11.6 million.
The South African district-based health system provides a network of facilities that connects different levels of care to streamline services. Local hospitals, where family physicians play a major role, manage a wide diversity of patients, including those presenting with acute coronary syndromes (ACS). The outcome on morbidity and mortality is unknown due to a paucity of epidemiologic data on AMI.
This study analysed the management of patients presenting with STEMI and NSTEMI as well as the outcomes in a district-level resource-limited environment with no PCI or on-site cardiology service.
This was a descriptive cross-sectional study that assessed hospital records of all patients diagnosed with AMI over a 2-year period from 01 August 2016 to 31 July 2018.
The study was conducted at Wentworth Hospital (WWH) in Durban, KwaZulu-Natal. The hospital is a district-level facility that has 230 beds and serves the Durban South catchment area with an estimated population of 407 000 as at 2013.
The hospital records of all patients either admitted with AMI or managed in the Accident and Emergency unit for the condition were assessed. The ESC criteria for diagnosis of AMI as well as age > 18 years were parameters used to include participants.
The hospital records checked were the admissions, the discharge as well as the death notification registers in both the High Care and Accident and Emergency units. During the study period, 140 patients were admitted with a diagnosis of AMI. A total of 96 outpatient medical records were traced. Of these, 44 records were either not found or had incomplete notes. This may be due to poor record-keeping and file administration processes at the institution. All deaths were traced through a death notification register. In-patient notes were available to confirm the diagnosis of AMI and assess immediate outcome at discharge. These records had insufficient data to describe outpatient care and hence was excluded from the process of care analyses but included to calculate the in-hospital mortality rate.
Of the 96 patients, seven were admitted twice for recurrent myocardial infarction. Total admissions were thus 103. For process of care, each admission was regarded as a separate instance, as an individual process has an impact on the outcome. However, for patient demographics, mortality rate and days to referral to central hospital with cardiology service, the patient numbers were used in place of admissions to avoid duplicating data.
All data were collected using a data collection tool that assessed patient demographics, risk factors for IHD, symptoms on presentation, time to Electrocardiogram (ECG) and time to fibrinolysis if indicated. The use of relevant life-saving drugs during high care admission, time taken to follow up with cardiology, and in-hospital mortality of patients with AMI were also tracked. Information was stored electronically on a hard drive in an encrypted file and password protected.
The following statistical parameters were used to determine an appropriate sample size with 80% statistical power. Type 1 error = 0.05 (the probability of rejecting the null hypothesis) which is regardless of the profile of patients there should be no difference in survival. Type 2 error (β) = 0.2 (probability of falsely accepting the null hypothesis). The assumption was that the sample affects the normal distribution, that is, population mean = 0 and σ = 1. A critical
Based on the stated statistical parameters, a sample size of 73 was determined to be sufficient to provide 80% statistical power. Continuous variables were summarised and mean ± standard deviation (s.d.) and medians and interquartile ranges were used for highly skewed variables with prominent asymmetrical outliers. Categorical variables were summarised into proportions and percentages and compared using Pearson’s chi square and Fischer’s exact test as appropriate. IBM Statistical Package for Social Sciences version 25 (SPSS Inc., Chicago, IL, United States [US]) was used to analyse the data. A
Patient characteristics and risk factor profile are presented in
Demographics and risk factor profile of patients with acute myocardial infarction.
Characteristics | STEMI ( |
NSTEMI ( |
All patients ( |
Odds of STEMI compared to NSTEMI |
||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
% | Mean ± s.d. | % | Mean ± s.d. | % | Mean ± s.d. | OR | 95% CI | |||||
Female | 12 | 24.5 | - | 17 | 36.2 | - | 29 | 30.2 | - | 0.60 | 0.2–1.4 | 0.20 |
Male | 37 | 75.5 | - | 30 | 63.8 | - | 67 | 69.8 | - | 1.75 | 0.7–4.2 | 0.20 |
Age | - | - | 55.8 ± 12.7 | - | - | 60.6 ± 12.6 | - | - | 58.2 ± 12.8 | 1.03 | 1.0–1.1 | 0.07 |
≥ 50 | 32 | 65.3 | - | 40 | 85.1 | - | 72 | 75.0 | - | 0.33 | 0.1–0.9 | 0.03 |
Black people | 5 | 10.2 | - | 4 | 8.5 | - | 9 | 9.4 | - | 1.20 | 0.3–4.9 | 0.80 |
Indian people | 23 | 46.9 | - | 32 | 68.1 | - | 55 | 57.3 | - | 0.40 | 0.2–0.9 | 0.04 |
White people | 15 | 30.6 | - | 8 | 17.0 | - | 23 | 24.0 | - | 2.10 | 0.8–5.7 | 0.10 |
Mixed race people | 6 | 12.2 | - | 3 | 6.4 | - | 9 | 9.4 | - | 2.00 | 0.5–8.7 | 0.30 |
Previous IHD | 11 | 22.4 | - | 13 | 27.7 | - | 24 | 25.0 | - | 0.75 | 0.3–1.9 | 0.60 |
Family history of IHD | 19 | 38.8 | - | 14 | 29.8 | - | 3 | 32.0 | - | 1.50 | 0.6–3.5 | 0.40 |
Dyslipidaemia | 28 | 57.1 | - | 33 | 70.2 | - | 61 | 63.5 | - | 0.50 | 0.2–1.3 | 0.20 |
Hypertension | 31 | 63.3 | - | 32 | 68.1 | - | 63 | 65.6 | - | 0.80 | 0.3–1.9 | 0.60 |
Diabetes mellitus | 22 | 44.9 | - | 24 | 51.1 | - | 46 | 47.9 | - | 0.80 | 0.3–1.7 | 0.50 |
Smoking | 36 | 73.5 | - | 26 | 55.3 | - | 62 | 64.6 | - | 2.20 | 0.9–5.3 | 0.07 |
OR, odds ratio; CI, confidence interval; STEMI; ST Elevation Myocardial Infarction; NSTEMI, Non-ST Elevation Myocardial Infarction.
The timing, clinical parameters and immediate management of patients with AMI are presented in
Timing, clinical parameters, and immediate management of patients with acute myocardial infarction.
Characteristics | STEMI ( |
NSTEMI ( |
All admissions ( |
Odds of STEMI compared to NSTEMI |
||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
% | Mean ± s.d. | % | Mean ± s.d. | % | Mean ± s.d. | OR | 95% CI | |||||
Own transport | 23 | 45.1 | - | 38 | 73.1 | - | 61 | 56.0 | - | 0.3 | 0.1–0.7 | 0.005 |
Private ambulance | 3 | 5.9 | - | 4 | 7.7 | - | 7 | 7.0 | - | 0.8 | 0.2–3.5 | 0.716 |
Public ambulance | 11 | 21.6 | - | 6 | 11.5 | - | 17 | 18.0 | - | 2.1 | 0.7–6.2 | 0.176 |
Unknown | 14 | 27.5 | - | 4 | 7.7 | - | 18 | 19.0 | - | 4.5 | 1.3–14.9 | 0.013 |
Public hospital | 38 | 74.5 | - | 35 | 67.3 | - | 73 | 70.9 | - | 1.4 | 0.6–3.3 | 0.422 |
Clinic | 1 | 2.0 | - | 1 | 1.9 | - | 2 | 1.9 | - | 1.0 | 0.1–16.8 | 0.989 |
Private GP | 10 | 19.6 | - | 14 | 26.9 | - | 24 | 23.3 | - | 0.7 | 0.3–1.7 | 0.382 |
Private hospital | 1 | 2.0 | - | 2 | 3.8 | - | 3 | 2.9 | - | 0.5 | 0.0–5.7 | 0.577 |
Unknown | 1 | 2.0 | - | 0 | 0.0 | - | 1 | 1.0 | - | 3.1 | 0.1–78.4 | - |
Unknown | 4 | 7.8 | - | 3 | 5.8 | - | 7 | 6.8 | - | 1.4 | 0.3–6.5 | 0.677 |
0–6 h | 25 | 49.0 | - | 20 | 38.5 | - | 45 | 43.7 | - | 1.5 | 0.7–3.4 | 0.281 |
> 6–12 h | 3 | 5.9 | - | 5 | 9.6 | - | 8 | 7.8 | - | 0.6 | 0.1–2.6 | 0.483 |
> 12–24 h | 12 | 23.5 | - | 6 | 11.5 | - | 18 | 17.5 | - | 2.4 | 0.8–6.9 | 0.115 |
> 24 h | 7 | 13.7 | - | 25 | 24.3 | - | 25 | 24.3 | - | 0.3 | 0.1–0.7 | 0.007 |
≤ 10 min | 6 | 11.8 | - | 11 | 21.2 | - | 17 | 16.5 | - | 0.5 | 0.2–1.5 | 0.205 |
> 10–30 min | 10 | 19.6 | - | 4 | 7.7 | - | 14 | 13.6 | - | 2.9 | 0.9–10.0 | 0.088 |
> 30 min | 21 | 41.2 | - | 21 | 40.4 | - | 42 | 40.8 | - | 1.0 | 0.5–2.3 | 0.935 |
Unknown | 6 | 11.8 | - | 6 | 11.5 | - | 12 | 11.7 | - | 1.0 | 0.3–3.4 | 0.972 |
Prehospital ECG | 8 | 15.7 | - | 10 | 19.2 | - | 18 | 17.5 | - | 0.8 | 0.3–2.2 | 0.636 |
Prehospital troponin available | 1 | 2.0 | - | 6 | 11.5 | - | 7 | 6.8 | - | 0.2 | 0.02–1.3 | 0.088 |
Sent home on FMC | 5 | 9.8 | - | 6 | 11.5 | - | 11 | 10.7 | - | 0.8 | 0.2–2.9 | 0.776 |
SBP | - | - | 136 ± 32.6 | - | - | 135 ± 29 | - | - | 136 ± 30.7 | - | - | 0.89 |
DBP | - | - | 88.7 ± 22 | - | - | 84.9 ± 19.9 | - | - | 86.6 ± 20.9 | - | - | 0.4 |
Pulse | - | - | 82.5 ± 21.7 | - | - | 92.9 ± 23.5 | - | - | 87.7 ± 23.1 | - | - | 0.02 |
Atypical chest pain | 16 | 31.4 | - | 20 | 38.5 | - | 36 | 35.0 | - | - | - | 0.25 |
Initial troponin |
164 | 50–618 | - | 317 | 75–760 | - | 180 | 50–715 | - | - | - | < 0.001 |
Peak troponin |
1797 | 895–2000 | - | 556 | 319–1390 | - | 1069 | 386–2000 | - | - | - | 0.02 |
OR, odds ratio; CI, confidence interval; STEMI; ST Elevation Myocardial Infarction; NSTEMI, Non ST Elevation Myocardial Infarction; SBP, systolic blood pressure; DBP, diastolic blood pressure; ECG, electrocardiogram; FMC, first medical contact.
The therapeutic interventions are demonstrated in
Medical management of acute myocardial infarction.
The clinical outcomes of the study patients are presented in
Tertiary involvement and outcomes of patients with acute myocardial infarction.
Characteristics | STEMI ( |
NSTEMI ( |
All patients ( |
Odds of STEMI compared to NSTEMI |
||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
% | Mean ± s.d. | % | Mean ± s.d. | % | Mean ± s.d. | OR | 95% CI | |||||
Transferred during admission | 12 | 24.5 | - | 2 | 4.3 | - | 14 | 14.6 | - | 7.3 | 1.5–34.7 | 0.012 |
Patients booked for cardiology | 35 | 71.4 | - | 33 | 70.2 | - | 68 | 70.8 | - | 1.1 | 0.4–2.6 | 0.896 |
Angiography done | 16 | 32.7 | - | 6 | 12.8 | - | 22 | 22.9 | - | 3.3 | 1.2–9.4 | 0.025 |
MIBI | 22 | 44.9 | - | 12 | 25.5 | - | 34 | 35.4 | - | 2.4 | 1.0–5.6 | 0.05 |
CABG done | 5 | 10.2 | - | 1 | 2.1 | - | 6 | 6.25 | - | - | - | - |
Arrhythmia | 6 | 12.24 | - | 5 | 10.6 | - | 11 | 11.4 | - | 1.2 | 0.3–4.1 | 0.805 |
Cardiogenic shock | 5 | 10.20 | - | 1 | 2.1 | - | 6 | 6.2 | - | 5.2 | 0.6–46.5 | 0.138 |
Post infarct angina | 1 | 2.0 | - | 2 | 4.2 | - | 3 | 3.1 | - | 0.5 | 0.0–5.3 | 0.541 |
Pulmonary oedema | 0 | 0.0 | - | 2 | 4.2 | - | 2 | 2.1 | - | 0.2 | 0.0–3.9 | 0.279 |
Recurrent MI | 4 | 8.2 | - | 3 | 6.4 | - | 7 | 7.3 | - | 1.3 | 0.3–6.2 | 0.738 |
CCF | 4 | 8.2 | - | 6 | 12.8 | - | 10 | 10.4 | - | 0.6 | 0.2–2.3 | 0.464 |
CVA | 0 | 0.0 | - | 1 | 2.1 | - | 1 | 1.0 | - | 0.3 | 0.0–7.9 | 0.481 |
LV thrombus | 2 | 4.1 | - | 0 | 0.0 | - | 2 | 2.1 | - | 5.0 | 0.2–107 | 0.303 |
Total | 22 | 44.5 | - | 20 | 42.5 | - | 4 | 43.8 | - | 1.1 | 0.5–2.5 | 0.817 |
Alive | 40 | 81.6 | - | 44 | 93.6 | - | 84 | 87.5 | - | 0.3 | 0.1–1.2 | 0.089 |
Demised | 9 | 18.4 | - | 3 | 6.4 | - | 12 | 12.5 | - | 3.3 | 0.8–13.1 | 0.089 |
Echo EF | 29 | - | 48.6 ± 7.1 | 26 | - | 50.9 ± 11.4 | 55 | - | 49.7 ± 9.4 | - | - | 0.360 |
EF < 45% | 8 | 27.6 | - | 6 | 23.1 | - | 14 | 25.5 | - | 1.2 | 0.4–3.9 | 0.768 |
EF ≥ 45% | 21 | 72.4 | - | 20 | 76.9 | - | 41 | 74.5 | - | 0.9 | 0.4–2.1 | 0.883 |
Class I | 17 | 44.7 | - | 14 | 33.3 | - | 31 | 38.8 | - | 1.3 | 0.6–3.1 | 0.488 |
Class II | 14 | 36.8 | - | 17 | 40.5 | - | 31 | 38.8 | - | 0.9 | 0.4–2.1 | 0.825 |
Class III | 4 | 10.5 | - | 3 | 7.1 | - | 7 | 8.8 | - | 1.5 | 0.3–7.0 | 0.626 |
Class IV | 1 | 2.6 | - | 0 | 0.0 | - | 1 | 1.3 | - | 3.3 | 0.1–83.7 | 0.467 |
Unknown | 2 | 5.3 | - | 8 | 19 | - | 10 | 12.5 | - | 0.3 | 0.1–1.4 | 0.118 |
Class I | 26 | 68.4 | - | 23 | 54.8 | - | 31 | 38.8 | - | 1.3 | 0.6–2.5 | 0.540 |
Class II | 8 | 21.1 | - | 11 | 26.2 | - | 31 | 38.8 | - | 0.8 | 0.3–2.2 | 0.672 |
Class III | 2 | 5.3 | - | 0 | 0.0 | - | 7 | 8.8 | - | 5.5 | 0.3–119 | 0.275 |
Unknown | 2 | 5.3 | - | 8 | 19 | - | 10 | 12.5 | - | 0.3 | 0.1–1.4 | 0.118 |
OR, odds ratio; CI, confidence interval; STEMI; ST Elevation Myocardial Infarction; NSTEMI, Non ST Elevation Myocardial Infarction; MIBI, myocardial perfusion imaging scan; CABG, coronary artery bypass graft; MI, myocardial infarction; CCF, congestive cardiac failure; CVA, cerebrovascular accident; LV, left ventricular; EF, ejection fraction
, 30-day outcome in patients with follow up investigations: STEMI –
, 30-day outcome in patients with follow up – NYHA Class: STEMI –
, 30-day outcome in patients with follow up – CCS Class: STEMI –
Transfer for higher level of care was affected for 24.5% of patients with STEMI compared to 4.3% with NSTEMI. [OR: 7.3, 95% CI: 1.5 – 34.7,
Fewer than 30% of patients were not booked for cardiology due to frailty, renal dysfunction, or patient refusal. Median time to cardiology appointment was 93 days (range: 0–180 days). Sixty-eight patients (70.8%) were given a cardiology appointment. Time to angiography from index presentation was in the range of (1–193) days with 22.9% undergoing the procedure. A myocardial perfusion imaging scan (MIBI) was done on 35.4% of the patients.
Of those patients who were alive, 55 (55/84, 65.5%) had an echo report. The mean Ejection Fraction (EF) was 49.7% s.d. (45–55.5). Of the 12 inpatient deaths, 18.4% were due to STEMI and 6.4% due to NSTEMI. The mean age was 66 years with a range of 41–87. There was no association between > 12-h delay in presentation and mortality (
The odds of death in hospital were 3.3 times higher in STEMI than in NSTEMI (
The demographics describing this cohort of patients are similar to other centres in KwaZulu-Natal, where Indian people factor as the major race group at risk for AMI.
The lower incidence of AMI in women is consistent with international findings. In the United States (US) men were 6.8 years younger than women with an average age of 65.0 years at first AMI for men compared to 71.8 years for women.
The data indicates that there is a chasm in developing countries with regard to preventative healthcare. High prevalence of obesity, cigarette smoking, recreational drug use and poor control of comorbidities points to upstream factors that need attention to improve cardiovascular health.
The diabetes and hypertension prevalence were 13% and 45%, respectively.
A significant proportion of admissions (25%) used emergency medical services to arrive at hospital. Although 23.3% of admissions with AMI were first seen by a private GP, only 17.5% of patients admitted arrived with a prehospital ECG. Patients with NSTEMI (73.1%) were more likely to use own transport to reach the hospital than patients with STEMI (45.1%) (OR: 0.3; 95% CI: 0.1–0.7;
Even though not statistically significant, delayed presentation and intervals post FMC impact morbidity and mortality.
Comparing door-to-needle times in South Africa, three previous studies showed poor compliance with guidelines. Data was captured for hospitals in three cities. At Steve Biko Hospital in Pretoria, only 3% of patients received thrombolytic therapy within 1 h.
A quality improvement project (QIP) addressed this at a rural district hospital by developing a protocol and displaying it in key clinical areas. In-service training with medical and nursing teams focused on recognition, investigation and management of STEMI and off-site ECG interpretation in a setting of clinical uncertainty.
Medical management is protocol driven; 94.7% of medications indicated were administered. This may account for the unexpected comparable in-hospital mortality to that seen in private sector in South Africa (9.7%).
Resource limitations pose ethical challenges in healthcare service delivery. Only 68% of patients in this study cohort were seen by a cardiologist. After a patient is logged with cardiology, feedback is only given when a consultant has reviewed the case. A minimum of three calls are made before a patient is given an appointment date – usually within three months. The median waiting period of 93 days implies that pharmacologic non-invasive strategy is the status quo at WWH.
Only 22.9% of patients underwent angiography in a 2-year period and only 57.3% had an echo report. The burden of illness calls for the need to realign the health system and mobilise the private sector or alternatively, upskill cardiology fellows to perform interventional cardiology. The odds of death in hospital were 6.2 times higher in STEMI than NSTEMI (
As Gouda and colleagues suggest,
This study also highlights the role of family physician in the management of clinical complexity. Family physicians lead a team at the district hospital where, from admission to discharge and follow-up, patients with AMI are managed sometimes without seeing a cardiologist. Although gaps in care are noted, these are correctable with QIPs. The in-hospital mortality of 12 deaths out of 140 admissions was 8.6% compared to the private sector in-hospital mortality of 9.7%. The scientific value of this study is that it reflects the quality of care in patients who have sustained myocardial infarction at a district public hospital. The social value of this study is that it provides a baseline that can influence subsequent changes to policies and guidelines improving overall care of patients with myocardial infarction.
This was a retrospective study and was limited by the data present in patient notes. Of the 140 admissions identified, only 96 could be used for data analysis as 44 records were either missing or had incomplete notes. The large number of missing files stresses the need for upgrade of record-keeping to electronic platforms. This study did not report on long-term outcomes with AMI. There was limited data to calculate BMI, and lack of extensive documentation led to many non-pharmacological interventions not being assessed.
Despite resource constraints with multiple systemic challenges of a public hospital, where in-hospital care can be provided for AMI patients, mortality is comparable to that in private facilities in South Africa. This entrenches the role of the family physician. There is a need for more coordinated systems of care for AMI between district hospitals and the tertiary referral centres.
The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.
Z.B. was the principal researcher with the conceptualisation of the research topic and methodology, while S.R supervised the research and provided useful critique and editing of both the protocol and the final article.
The study was granted ethical approval by the Biomedical Research Ethics Committee (BE085/19) at University of KwaZulu-Natal as well as the provincial Department of Health.
This research received received funding from the Discovery Foundation.
The data that supports this study will be available upon request to the corresponding author, S.R.
The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy of their affiliated institutions.