A team of researchers from the Netherlands, the US and Japan has conducted a systematic review and meta-analysis of observational studies shedding light on the nature of the relationship between severe hypoglycaemia and risk of cardiovascular disease (CVD) in people with type 2 diabetes (studies from acute hospital settings were excluded). As part of their work, the researchers conducted bias analysis in order to examine possible uncontrolled confounding resulting from unmeasured co-morbid severe illness.
Six eligible studies were identified, with a total of 903,510 participants. In the primary meta-analysis, severe hypoglycaemia was found to be strongly associated with a higher risk of CVD (relative risk, 2.05; 95% confidence interval, 1.74–2.42; P<0.001). This analysis used a random-effects model, which is generally considered to be more conservative because it allows for a difference in the expected results of each study, acknowledging the heterogeneity that inevitably exists in the methodology and population characteristics. Indeed, moderate heterogeneity across the studies was suggested (I2=73.1%; P=0.002 for heterogeneity).
The bias analysis, according to the authors, indicated that co-morbid severe illness alone may not explain the association between hypoglycaemia and CVD. While this bias analysis is a strength of this piece of research, it is worth observing that it is not possible to draw definitive conclusions on cause and effect from observational research, either as a stand-alone study or when combined in a meta-analysis.
For the full paper, please visit www.bmj.com/content/347/bmj.f4533.
