Body Mass Index and Mortality, Recurrence and Readmission after Myocardial Infarction: Systematic Review and Meta-Analysis.
Lorenzo De PaolaArnav MehtaTiberiu A PanaBen CarterRoy Louis SoizaMohannad W KafriJohn F PotterMamas A MamasPhyo Kyaw MyintPublished in: Journal of clinical medicine (2022)
The following study aimed to systematically review and meta-analyse the literature on the relations between markers of nutritional status and long-term mortality, recurrence and all-cause hospital readmission following myocardial infarction (MI). Medline, EMBASE and Web of Science were searched for prospective cohort studies reporting the relationship between anthropometric and biochemical markers of nutritional status and nutritional assessment tools on long-term mortality, recurrence and all-cause hospital readmission in adult patients with an MI. Two reviewers conducted screening, data extraction and critical appraisal independently. Random-effects meta-analysis was performed. Twenty-seven studies were included in the qualitative synthesis and twenty-four in the meta-analysis. All eligible studies analysed BMI as their exposure of interest. Relative to normal weight, mortality was highest in underweight patients (adjusted Hazard Ratio (95% confidence interval): 1.42 (1.24-1.62)) and lower in both overweight (0.85 (0.76-0.94)) and obese patients (0.86 (0.81-0.91)), over a mean follow-up ranging from 6 months to 17 years. No statistically significant associations were identified between different BMI categories for the outcomes of recurrence and hospital readmission. Patients with low BMI carried a significant mortality risk post-MI; however due to the known limitations associated with BMI measurement, further evidence regarding the prognostic utility of other nutritional markers is required.
Keyphrases
- systematic review
- body mass index
- weight gain
- cardiovascular events
- case control
- obese patients
- healthcare
- free survival
- end stage renal disease
- bariatric surgery
- adverse drug
- risk factors
- weight loss
- chronic kidney disease
- physical activity
- acute care
- heart failure
- public health
- body composition
- newly diagnosed
- emergency department
- type diabetes
- gastric bypass
- coronary artery disease
- machine learning
- adipose tissue
- peritoneal dialysis
- atrial fibrillation
- artificial intelligence
- patient reported