Findings from a study published in Nature Communications assessed the correlation between tear glucose (TG) and blood glucose (BG) using a wireless and soft smart contact lens (SCL) glucose biosensor to continuously monitor TG.
Give me some background.
Studies have shown that diabetic patients have higher levels of TB compared to normal individuals—as such, tears have emerged as a promising alternative to blood for diagnosing diabetes.
However: The exact correlation between TG and BG remains unclear, which limits the clinical usage of tears in BG monitoring.
- Thus: Study authors noted that a likely reason for this disagreement is the variation in the composition of tears depending on the tear collection method.
Talk about this smart contact lens.
The SCL used in this study is capable of quantitatively monitoring TG levels in basal tears—excluding the effect of reflex tears, which might weaken the relationship with BG.
The lenses were made from stretchable and biocompatible materials, similar to those used in commercially available contact lenses, and had a high-sensitivity glucose sensor with a wireless antenna embedded.
The result: This setup provided continuous TG data acquisition at sub-minute intervals that was then transmitted to a mobile device—making real-time monitoring possible and allowing for the precise estimation of lag time between BG and TG levels.
Now let’s hear about the study.
A research team performed three series of experiments and analyses to elucidate the efficacy of SCLs for BG monitoring:
- Assessed whether SCLs induce reflex tearing in rabbit models and examined the impact of reflex tears on TG levels
- Developed the concept of “personalized lag time” to enable the precise identification of the lag time in each individual
- Completed animal testing (in rabbits and dogs) and a human pilot study (in 10 control and 10 diabetic subjects) with SCLs for comparative analysis
Findings?
Of note, there was a stabilization period of 1 to 3 minutes after inserting the lens; following the stabilization period, investigators found that the correlation between TG and BG levels significantly increased.
Additionally, reflex tears (i.e., the tears triggered by eye irritation or intentional stimulation) initially decreased the correlation between TG and BG.
However, this correlation increased after the TG levels stabilized.
What about the personalized time lag?
Accurate estimation of the personalized time lag was crucial for a higher correlation coefficient between BG and TG.
This custom number, in tandem with a Pearson correlation coefficient of 0.9 or above, demonstrated the high accuracy of the SCL technology.
Plus: They also found that the glucose diffusion rate from blood to tears may vary among individuals but can be a unique and lasting feature for each individual over a certain period.
Anything else?
The researchers also used Clarke Error Grid Analysis to confirm that predicted BG levels calculated from tear analyses closely matched with those measured using traditional glucometers.
Expert opinion?
Corresponding author Yong-ho Lee noted, “By introducing the concept of time, we have resolved the issues that had previously hindered tear-based BG analysis and clearly established the correlation between TG and BG levels.”
Tie it all together for me.
These findings suggest that SCLs could be an effective non-invasive approach to real-time monitoring of TG and BG levels in diabetic patients.
Next steps?
Further developments in SCL technology are expected to expand the capabilities of the biosensor for the diagnosis and treatment of other diseases by accurately measuring cholesterol, intraocular pressure (IOP), and other analytes detectable in tears.
Future studies are warranted to elucidate the lag time between TG and BG over an extended period with a larger scale of human participants and to develop an algorithm for calculating personalized lag time.