The effect of green cardamom on blood pressure and inflammatory markers among patients with metabolic syndrome and related disorders: A systematic review and meta-analysis of randomized clinical trials.
Bahareh IzadiHassan JoulaeiKamran Bagheri LankaraniReza TabriziErfan TaherifardAli SadeghpourMohebat ValiMaryam AkbariPublished in: Phytotherapy research : PTR (2022)
Research shows that herbal spices, including seeds of Elettaria cardamomum, may exert beneficial effects on unhealthy metabolic status. This study is a systematic review of the effect of green cardamom in patients with metabolic syndrome and its related disorders. PubMed/Medline, Scopus, EMBASE, Web of Science, and Cochrane Library were searched to identify the relevant randomized clinical trials. The data were pooled using the random-effects model, and weighted mean difference (WMD) was considered as summary effect size. Of 625 clinical trials, eight reports with 595 patients (299 in intervention group and 296 in control group) were included. The findings indicated that green cardamom significantly decreased diastolic blood pressure (WMD: -0.91 mmHg, 95%CI; -1.19, -0.62), high-sensitivity C-reactive protein (WMD: -1.21 mg/L, 95%CI; -2.18, -0.24), interleukin 6 levels (WMD: -2.41 ng/L, 95%CI; -4.35, -0.47). However, cardamom supplementation did not significantly affect systolic blood pressure. This meta-analysis demonstrated that green cardamom could improve blood pressure control and exert antiinflammatory effects which could help patients with unhealthy metabolic profile better manage their health. Importantly, there were few eligible randomized trials with quite a low number of participants. Further prospective studies on larger sample sizes and longer duration of supplementation are warranted for its widespread use.
Keyphrases
- blood pressure
- metabolic syndrome
- hypertensive patients
- heart rate
- clinical trial
- systematic review
- public health
- healthcare
- randomized controlled trial
- ejection fraction
- end stage renal disease
- left ventricular
- newly diagnosed
- emergency department
- magnetic resonance imaging
- uric acid
- insulin resistance
- case control
- heart failure
- risk assessment
- climate change
- machine learning
- phase ii
- patient reported outcomes
- health information
- open label
- deep learning
- big data
- artificial intelligence
- double blind
- health promotion
- phase iii
- contrast enhanced