METHODS: A systematic search with Embase, Cochrane CENTRAL, Google scholar, and PubMed was conducted. Studies conducted in patients with STEMI presented to non PCI-capable settings and compared fibrinolytic injection with no injection before referring patients to PCI-capable settings were included. The primary outcome was the composite outcomes of major adverse cardiac events (MACEs) at 30 days. Meta-analyses were performed using random-effect model.
RESULTS: Of 912 articles, three RCTs and three non-RCTs were included. Based on RCTs, fibrinolytic injection before the referral has failed to decrease MACEs compared to non-fibrinolytic injection [relative risk (RR) 1.18; 95% confidence interval (CI), 0.89-1.57, p = 0.237]. Fibrinolytic injection has also failed to decrease mortality, re-infarction, and ischemic stroke. On the other hand, fibrinolytic injection was associated with a higher risk of major bleeding.
CONCLUSIONS: In non PCI-capable settings, fibrinolytic injection before referring patients with STEMI to PCI-capable settings has no clinical benefit but could increase risk of major bleeding. Clinicians might more carefully consider whether fibrinolytic injection should be used in patients with STEMI before the referral.
Methods: This retrospective prevalence study was based on medical records of the heart center of Mazandaran Province on all patients diagnosed with AMI in Mazandaran, northern Iran between 2013 and 2015. Patients' sex and the day, month, year and time of hospital admission were extracted from patients' records. Moreover, the meteorological reports were gathered.
Results: A statistically significant difference was found between the distributions of AMI cases across 12 months of the year (P < 0.01). Fuzzy clustering analysis using 16 different climatic variables showed that March, April, and May were in the same cluster together. The other 9 months were in different clusters.
Conclusion: Significant increase in AMI was seen in March, April and May (cold to hot weather).
Methods: A quasi-experimental study was conducted in Kuala Lumpur Hospital, Malaysia. Data were collected from November 2014 to January 2015 with a total of 58 respondents who met the inclusion criteria. The respondents received a 20-min one-on-one education programme regarding coronary heart disease, treatment and prevention, and healthy lifestyle. A questionnaire comprising demographic data was administered and the cardiovascular health index was measured before and after four weeks of the education programme. Data were analysed with descriptive and inferential statistics.
Results: There were statistically significant decreases in the score of anxiety, stress, depression, body mass index, and smoking status (P < 0.001) between pre-test and post-test.
Conclusion: The findings suggest that the one-on-one education programme could improve the cardiovascular health index of patients with MI. Furthermore, nurses need to develop and implement a standard education structure programme for patients with MI to improve health outcomes.
METHODS: 10 010 high-risk noncardiac surgical patients were randomized aspirin or placebo and clonidine or placebo. Neuraxial block was defined as intraoperative spinal anaesthesia, or thoracic or lumbar epidural anaesthesia. Postoperative epidural analgesia was defined as postoperative epidural local anaesthetic and/or opioid administration. We used logistic regression with weighting using estimated propensity scores.
RESULTS: Neuraxial block was not associated with the primary outcome [7.5% vs 6.5%; odds ratio (OR), 0.89; 95% CI (confidence interval), 0.73-1.08; P=0.24], death (1.0% vs 1.4%; OR, 0.84; 95% CI, 0.53-1.35; P=0.48), myocardial infarction (6.9% vs 5.5%; OR, 0.91; 95% CI, 0.74-1.12; P=0.36) or stroke (0.3% vs 0.4%; OR, 1.05; 95% CI, 0.44-2.49; P=0.91). Neuraxial block was associated with less clinically important hypotension (39% vs 46%; OR, 0.90; 95% CI, 0.81-1.00; P=0.04). Postoperative epidural analgesia was not associated with the primary outcome (11.8% vs 6.2%; OR, 1.48; 95% CI, 0.89-2.48; P=0.13), death (1.3% vs 0.8%; OR, 0.84; 95% CI, 0.35-1.99; P=0.68], myocardial infarction (11.0% vs 5.7%; OR, 1.53; 95% CI, 0.90-2.61; P=0.11], stroke (0.4% vs 0.4%; OR, 0.65; 95% CI, 0.18-2.32; P=0.50] or clinically important hypotension (63% vs 36%; OR, 1.40; 95% CI, 0.95-2.09; P=0.09).
CONCLUSIONS: Neuraxial block and postoperative epidural analgesia were not associated with adverse cardiovascular outcomes among POISE-2 subjects.
METHODS: Out of 105 patients with IHD, 76 completed self-administration of HeartQoL at the clinic followed by at home within a 2-week interval. In retest, patients responded using non-interview methods (phone messaging, email, fax, and post). Phone interviewing was reserved for non-respondents to reminder.
RESULTS: Reliability of HeartQoL was good (intraclass correlation coefficients = 0.78-0.82), was supported in the Bland-Altman plot, and was comparable to five studies on MacNew of similar retest interval (MacNew-English = 0.70-0.75; translated MacNew = 0.72-0.91). Applicability of its standard error of measurement (0.20-0.25) and smallest detectable change (0.55-0.70) will depend on availability of normative data in future.
CONCLUSION: The reliability of HeartQoL is comparable to its parent instrument, the MacNew. The HeartQoL is a potentially reliable core IHD-specific HRQoL instrument in measuring group change.
METHODS: This cross sectional study was conducted in December 2019 in cardiology ward of a 1000-bed tertiary care hospital of Bangladesh. Patients admitted in the ward with the diagnosis of myocardial infarction were included in the study. Socio demographic data, clinical features and patients' health seeking behavior was collected in a structured questionnaire from the patients. Median with interquartile range (IQR) of pre hospital delay were calculated and compared between different groups. Chi-square (χ2) test and binary logistic regression were used to estimate the determinants of pre-hospital delay and effect of pre-hospital delay on in-hospital mortality.
RESULTS: Three hundred thirty-seven patients was enrolled in the study and their median (IQR) pre-hospital delay was 9.0 (13.0) hours. 39.5% patients admitted in the specialized hospital within 6 h. In logistic regression, determinants of pre-hospital delay were patients age (for
METHODS: We surveyed 16 512 adults from July 2020 to August 2021 in 30 territories. Participants self-reported their medical histories and the perceived impact of COVID-19 on 18 lifestyle factors and 13 health outcomes. For each disease subgroup, we generated lifestyle, health outcome, and bridge networks. Variables with the highest centrality indices in each were identified central or bridge. We validated these networks using nonparametric and case-dropping subset bootstrapping and confirmed central and bridge variables' significantly higher indices through a centrality difference test.
FINDINGS: Among the 48 networks, 44 were validated (all correlation-stability coefficients >0.25). Six central lifestyle factors were identified: less consumption of snacks (for the chronic disease: anxiety), less sugary drinks (cancer, gastric ulcer, hypertension, insomnia, and pre-diabetes), less smoking tobacco (chronic obstructive pulmonary disease), frequency of exercise (depression and fatty liver disease), duration of exercise (irritable bowel syndrome), and overall amount of exercise (autoimmune disease, diabetes, eczema, heart attack, and high cholesterol). Two central health outcomes emerged: less emotional distress (chronic obstructive pulmonary disease, eczema, fatty liver disease, gastric ulcer, heart attack, high cholesterol, hypertension, insomnia, and pre-diabetes) and quality of life (anxiety, autoimmune disease, cancer, depression, diabetes, and irritable bowel syndrome). Four bridge lifestyles were identified: consumption of fruits and vegetables (diabetes, high cholesterol, hypertension, and insomnia), less duration of sitting (eczema, fatty liver disease, and heart attack), frequency of exercise (autoimmune disease, depression, and heart attack), and overall amount of exercise (anxiety, gastric ulcer, and insomnia). The centrality difference test showed the central and bridge variables had significantly higher centrality indices than others in their networks (P