Association between education and major adverse cardiac events among patients with acute coronary syndrome in the Arabian Gulf

Al‐Zakwani, Ibrahim; Mabry, Ruth; Zubaid, Mohammad; Alsheikh‐Ali, Alawi A.; Almahmeed, Wael; Shehab, Abdullah; Rashed, Wafa

doi:10.1136/bmjgh-2018-001278

Cited by 9 publications

(4 citation statements)

References 29 publications

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“…Therefore, it was associated with more cardiovascular events and readmissions within one year. 38 Old patients with anticipated low health literacy require specialized education during admission and upon discharge to encourage treatment satisfaction and medication adherence. Moreover, medications reconciliation is highly recommended upon discharge, 39 along with an early follow-up review to minimize the risk of readmission associated with polypharmacy.…”

Section: Discussionmentioning

confidence: 99%

Incidence and Risk Factors for 28 Days Hospital Readmission: A Retrospective Study from Oman

Alawi¹,

Sibani²,

Al-Maqbali³

et al. 2022

Oman Med J

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Objectives: We sought to evaluate the incidence of 28-day hospital readmission in a tertiary hospital in Oman and identify potential factors associated with increased risk of hospital readmission. Methods: We conducted a retrospective study of all adult patients (≥ 18 years) admitted under the care of the General Internal Medicine unit from 1 June to 31 December 2020 at Sultan Qaboos University Hospital. Elective admissions and COVID-19 infection-related admission were excluded from the study. Results: There were 200 patients admitted during the study period. The mean age was 58.6±19.3 years, and 106 (53.0%) patients were males. Forty-eight (24.0%) patients had unplanned readmission within 28-days after discharge from the hospital. Patients with 28 days unplanned readmission were older (66.6 vs. 56.0 years, p < 0.001) and had a longer length of hospital stay (6.0 vs. 4.0 days, p < 0.001). Also, hypertension (77.1% vs. 55.3%, p =0.007), diabetes mellitus (64.6% vs. 48.0%, p =0.045), and comorbidity (≥ 3 comorbidities, [43.8% vs. 23.8%, p =0.005]) were more prevalent in the unplanned readmission group. Patients with poor functional status (43.7% vs. 26.3%, p < 0.001), requiring feeding tube (25.0% vs. 5.3%, p < 0.001), and with polypharmacy (75.0% vs. 50.0%, p =0.003) were at increased risk of readmission. Conclusions: 28-day hospital readmission is prevalent in our health care setting. Old age, polypharmacy, comorbidities, and poor functional status were associated with an increased risk of hospital readmission. Therefore, evidence-based interventions must be implemented in our health care system to minimize the risk of hospital readmission.

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Section: Discussionmentioning

confidence: 99%

Incidence and Risk Factors for 28 Days Hospital Readmission: A Retrospective Study from Oman

Alawi¹,

Sibani²,

Al-Maqbali³

et al. 2022

Oman Med J

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“… 26 In addition, level of education achieved has been shown to influence rates of major adverse cardiac events in ACS patients. 27 …”

Section: Discussionmentioning

confidence: 99%

Differences in Social Hardships in Women and Men with Acute Myocardial Infarction: Impact on 30-Day Readmission

Haddadin

Beydoun

Sabharwal

et al. 2022

Women's Health Reports

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Background: Studies have shown that women with acute myocardial infarction (AMI) have a higher prevalence of unfavorable social variables then men and have a worse outcome. Less is known regarding the impact of these social variables on 30-day readmission after AMI. Materials and Methods: We analyzed adult patients with AMI enrolled in a Quality Improvement Program intended to improve the peri-discharge care of patients with an AMI, and decrease all-cause 30-day unplanned readmissions. We compared clinical and social variables by gender. Multivariate logistic regression, with separate adjustment for clinical and for social variable, was used to measure adjusted odds for readmission by gender. Results: Among 208 patients included in our project 68 (32.7%) were women. Only 30.9% of women were married or had domestic partner at the time of the interview and only 16.2% were employed. Nearly half of women (48.5%) needed help with medical care, and 39.7% of women did not speak English as their first language. These variables were significantly different by gender. Rates of 30-day readmissions were higher in women than men (22.1% vs. 7.8%, p = 0.024). After adjusting for clinical variables this difference by gender in 30-day readmissions remained significant (odds ratio [OR] 3.34 95% confidence interval [CI] 1.1–11.1, p = 0.049). However, when adjusting for social variables, this difference was no longer noted (OR 0.87 95% CI 0.27–2.78, p = 0.822). Conclusion: Women with AMI are more likely than men to have unfavorable social factors that can impact recovery from AMI and women have a higher 30-day readmission rate. The higher 30-day readmissions in women appears to be influenced by these social factors. Health care interventions aimed at reducing 30-day readmission after AMI should focus on eliciting a detailed social history and providing aid for those requiring additional social support at home.

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“…We used the world health organization (WHO) definition of anemia in adults (Males <13 g/dl, Females <12 g/dl) in our study [ 27 ]. We selected variables (hereafter ‘features’) that were found to be significantly associated with ACS events including variables capturing patient demographics, past medical history, medical status upon admission and in-hospital ACS outcomes ( Table 1 ) [ 28 – 30 ]. We used infarction/reinfarction, percutaneous coronary intervention (PCI), heart failure, stroke, bleeding, and mortality as independent outcomes for our predictive models (6 ML models in total).…”

Section: Methodsmentioning

confidence: 99%

Anemia or other comorbidities? using machine learning to reveal deeper insights into the drivers of acute coronary syndromes in hospital admitted patients

et al. 2022

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Acute coronary syndromes (ACS) are a leading cause of deaths worldwide, yet the diagnosis and treatment of this group of diseases represent a significant challenge for clinicians. The epidemiology of ACS is extremely complex and the relationship between ACS and patient risk factors is typically non-linear and highly variable across patient lifespan. Here, we aim to uncover deeper insights into the factors that shape ACS outcomes in hospitals across four Arabian Gulf countries. Further, because anemia is one of the most observed comorbidities, we explored its role in the prognosis of most prevalent ACS in-hospital outcomes (mortality, heart failure, and bleeding) in the region. We used a robust multi-algorithm interpretable machine learning (ML) pipeline, and 20 relevant risk factors to fit predictive models to 4,044 patients presenting with ACS between 2012 and 2013. We found that in-hospital heart failure followed by anemia was the most important predictor of mortality. However, anemia was the first most important predictor for both in-hospital heart failure, and bleeding. For all in-hospital outcome, anemia had remarkably non-linear relationships with both ACS outcomes and patients’ baseline characteristics. With minimal statistical assumptions, our ML models had reasonable predictive performance (AUCs > 0.75) and substantially outperformed commonly used statistical and risk stratification methods. Moreover, our pipeline was able to elucidate ACS risk of individual patients based on their unique risk factors. Fully interpretable ML approaches are rarely used in clinical settings, particularly in the Middle East, but have the potential to improve clinicians’ prognostic efforts and guide policymakers in reducing the health and economic burdens of ACS worldwide.

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Association between education and major adverse cardiac events among patients with acute coronary syndrome in the Arabian Gulf

Cited by 9 publications

References 29 publications

Incidence and Risk Factors for 28 Days Hospital Readmission: A Retrospective Study from Oman

Incidence and Risk Factors for 28 Days Hospital Readmission: A Retrospective Study from Oman

Differences in Social Hardships in Women and Men with Acute Myocardial Infarction: Impact on 30-Day Readmission

Anemia or other comorbidities? using machine learning to reveal deeper insights into the drivers of acute coronary syndromes in hospital admitted patients

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