Diabetes as an Accelerator of Cognitive Impairment and Alzheimer's Disease

This randomized controlled trial is aimed at studying the effects of an eHealth intervention on improving metabolic control and other cardiovascular risk factors (obesity, lipidic profile and hypertension) as the approach to prevent or delay the process of cognitive impairment, and to reduce conversion rates to Alzheimer's disease (AD) in a sample of patients diagnosed of type 2 diabetes mellitus (T2D) and with mild cognitive impairment (MCI).

For these purposes, the standard clinical treatment for this type of patients will be compared with two types of interventions (parallel groups): one aimed at promoting adherence to treatment through the use of a smart pillbox; and the other intervention will be based on the use of the smart pillbox plus and interactive digital platform allowing communication between patients and caregivers with healthcare professionals. Both interventions are targeted to improve adherence to treatment.

The hypothesis is that the rate of conversion from MCI to AD will be higher in the control group than in the intervention groups (higher conversion rates are expected in control group, followed by the smart pillbox group, and lower conversion rates are expected in the group using the interactive digital platform and the smart pillbox).

The objective of the DIALCAT randomized controlled trial is to study the effects of an eHealth intervention (smart pillbox, digital platform) on the progression of cognitive impairment evaluated by means of a neuropsychological examination, in a sample of elderly patients with type II diabetes (T2D) and mild cognitive impairment (MCI). As secondary goals, this research is intended to:

1. Assess if the intervention improves the metabolic control of the study sample.
2. Evaluate the effects of the intervention on the conversion rate (yes vs. no) from MCI to Alzheimer's' disease (AD).
3. Compare the effectiveness of the interventions to reduce functional decline (quantified by a battery of neuropsychological tests \[see detailed description below\]) and the conversion rate to AD.
4. Identify the clinical and analytical predictors (biomarkers) of conversion from MCI to AD.

To this purposes, a total of 174 T2D patients with MCI (MMSE≥24) will be recruited with a 18-month follow-up. Eligible patients will be randomized in a 1:1:1 ratio in one of the arms of the RCT (for randomization, a sex-by-sex-swapped sequence and the ApoE genotype will be used). The three groups will receive the following interventions:

Arm 1: T2D patients (n = 58) with MCI, receiving treatment as usual (TAU) by their primary care physician/endocrinologist.

Arm 2: T2D patients (n = 58) with MCI, receiving TAU and using a smart pillbox that allows to monitor adherence to treatment.

Arm 3: T2D patients (n = 58) with MCI, receiving TAU, using the smart pillbox and receiving periodic feedback on their metabolic control and how to improve it by an endocrinologist via a digital platform.

Since it is expected that the different factors related to the intervention will have an additive or synergistic effect, the hypothesis is that the cognitive impairment and progression of MCI to AD would be higher in arm 1, followed by arm 2 and, finally, arm 3.

Eligibility Criteria:
Inclusion criteria:

1. Patients diagnosed of diabetes mellitus type 2 with time evolution ⋝5 years.
2. Age between 65 and 85 years old (both included).
3. Ability to read and write.
4. Active treatment with hypoglycemic agents.
5. Diagnosed with mild cognitive impairment.

Exclusion Criteria:

1. Familiar history of Alzheimer's' disease.
2. Patients with any type of dementia.
3. History of neurological or psychiatric conditions not stabilized that can substantially affect cognition.
4. Severe metabolic or systemic disease that affects the cognitive state. This includes:

   * Unstable acute cardiovascular disease.
   * Renal failure with glomerular filtration rate \<30 ml/min/m2.
   * Decompensated cirrhosis or liver failure.
   * Untreated hypothyroidism or vitamin B12 deficiency. If known.
   * Active cancer or chemotherapy treatment the previous year.
5. Treatment with drugs that alter the cognitive state, for example:

   * Antipsychotic.
   * Daily consumption of opioids.
   * Benzodiazepines (BZD) long action (for example Diazepam). Benzodiazepines (BZD) short-acting at high doses such as Alprazolam at doses greater than 1 mg / day; Lorazepam at doses greater than 1 mg / day and Lormetazepam at doses greater than 1 mg / day.
   * Fentanil patches in doses greater than 2.5 mg every 72 h.
   * Gabapentin in doses greater than 600 mg / day.
   * Pregabalin in doses greater than 50 mg / day.
   * Amitriptyline in doses greater than 25 mg / day.
6. Limitations of mobility that can avoid or restrict the application or evaluation of the intervention.
7. Patients with other types of diabetes: diabetic mellitus type 1, LADA; MODY
8. Unstable advanced diabetic retinopathy
9. Patients with serious uncorrected sensory deficits that make assessment impossible (blindness, deafness).
10. Patients with access to other online platforms for patients.
11. Patients with access to other intelligent electronic dispensing devices for improved adherence to treatment.