The International Diabetes Federation (IDF) guidelines 2021 for Ramadan and Diabetes point out that diabetic patients can suffer from complications such as higher glucose variability, decreased sleep and unhealthy food choices during Ramadan.
GluCare asked patients to conduct a pre-Ramadan assessment which included customized education and connecting them with wearables allowing for continuous data collection. This allowed the care team, with the help of an artificial intelligence platform (to determine other risk predictions) to monitor at-risk patients who wanted to fast during this month.
Two examples of patients who have benefited from the GluCare model of care are provided below.
Type 2 Diabetes
Our first example is that of a 61-year-old obese male with type 2 diabetes. The patient was already being managed under the GluCare program and was connected to the team via a wearable Band and connected weight scale and CGM.
We were previously successful in replacing the patient’s medication from Insulin to oral medication and had also observed significant weight loss. Detailed analysis of his lifestyle choices through the GluCare platform indicated very high glucose spikes when selecting certain dietary choices.
The patient insisted that this was not due to food intake as he was eating significantly less than before.
Pre-Ramadan:
Using our digital therapeutics platform, we observed his glucose time in range
We also overlaid his meals with glucose variability:
During Ramadan:
Having received his pre- Ramadan assessment and given customized educational content before he began fasting, we observed significant improvements in his time in range during Ramadan.
The clinical team also observed his iftar and suhoor choices on a daily basis.
His time in range improved, and glycemic variability spike post meals, even during iftar, was decreased compared to Pre-Ramadan observations.
The continuous data capturing, ability to overlay past and current data, and regular communication allowed us to demonstrate that his less-than-optimal time in range was, in fact, primarily due to his dietary choices.
Post Ramadan:
The patient has continued to improve post Ramadan and has used the information gained during Ramadan to better understand the relationship of his glucose variability to his diet choices.
This was one of the first reported cases using digital therapeutics to observe a patient pre, during and post Ramadan to effectively change behavior leading to better clinical outcomes.
Prediabetes case study:
Our next case study is that of a 46-year-old patient with Prediabetes. This patient had consistently been logging his food using the GluCare app.
We observed a very similar curve to that reported by the IDF’s guidelines:
With intervention and feedback from the clinical team, we worked closely with the patient to help avoid the spike observed during iftar:
In addition to dietary choices, we also looked at two other key parameters that affect glycemic variability; Sleep and Exercise. Our platform shows the decrease of sleep and exercise during Ramadan that need to be considered when looking at overall glucose time in range:
Before Ramadan:
During Ramadan:
This is consistent with the IDF 2021 guidelines. (Glucose variability, physiological changes due to sleep and exercise changes).
To conclude, by performing a pre-Ramadan assessment, providing personalized education, monitoring patients continuously, and regular communication, we have the ability to practice a continuous model of care for patients rather than an episodic care model during the holy month of Ramadan.
The GluCare human and machine team helped patients become aware of what happens to their body and the impact of their lifestyle choices during Ramadan. This promotes successful behavioral changes and allows for certain at-risk patients to be monitored during Ramadan.
The model of using digital therapeutics has shown promising results to help patients actually improve during the month of Ramadan, and importantly, provides our care team with information to help us understand what is happening to patients during the fasting, sleeping, exercise and eating window during the day. This allows for better insights, real-time feedback and improved clinical outcomes.
