Peer-reviewed study
Peer-reviewed study
Our research is clinically validated and evidence-based, with results published in several peer-reviewed journals. Explore our studies to learn more about the outcomes and the science driving our care model.
Our research is clinically validated and evidence-based, with results published in several peer-reviewed journals. Explore our studies to learn more about the outcomes and the science driving our care model.
Key results
Key results
2.14%
2.14%
Reduction in HbA1c
Reduction in HbA1c
20.8%
20.8%
Average GluCare app engagement
Average GluCare app engagement
41%
41%
Decrease in cardiovascular disease risk
Decrease in cardiovascular disease risk
Improved lipid profile
17%
17%
Reduction in cholesterol
21%
21%
Reduction in LDL
5.5%
5.5%
Reduction in Triglycerides
High Engagement Drives Better Outcomes
Patients with 11 or more interactions over 90 days saw an average reduction of
5.5%
5.5%
in HbA1c
6 Kg
6 Kg
weight loss
Improved Mental Health
Reflecting lower diabetes-related emotional distress
WHO-5
WHO-5
4%
4%
Score
PAID
PAID
28%
28%
Score
Lipoprotein(a) is a genetic, independent risk factor for cardiovascular disease that remains rarely tested for in routine practice. This study examined its prevalence in 233 adults with diabetes and prediabetes within our hybrid care model, and explored its relationship to our AI-derived Retinal-CVD risk score.
Key findings
32.2%
of patients had elevated Lp(a) (≥30 mg/dL)
Total cholesterol and LDL-C trended higher in the elevated Lp(a) group
(adjusted GMR 1.08, P = 0.162), though this did not reach statistical significance after adjustment
No significant association was found between Lp(a) status and Reti-CVD risk category
(OR 1.14, P = 0.672)
Standard 10-year cardiovascular risk calculators often underestimate risk in younger patients and miss subclinical vascular damage entirely. This study examined our AI-powered retinal cardiovascular scan (Reti-CVD) in 1,461 adults, comparing it against the American Heart Association’s PREVENT equation.
Key findings
1,461 adults screened; higher Reti-CVD risk linked to age, male sex, diabetes, and hypertension (all P < 0.001)
Low-risk patients:
vascular age 4.1 years younger than actual age
High-risk patients:
vascular age matched or exceeded chronological age
49.1%
of PREVENT “low risk” patients reclassified as moderate/high risk by Reti-CVD
uPTM-FetA/Ucr stayed normal in people without diabetes and those with prediabetes, but increased significantly once diabetes was present. It also independently predicted kidney disease risk, even after accounting for medications known to protect the kidneys.
Key findings
No increase seen in
Normal vs Prediabetes groups
No significant difference
(P = NS)
Higher levels seen in both
Type 1 and Type 2 Diabetes
Significant increase compared to Normal individuals
(P < 0.05)
Predicted worsening
kidney disease risk independently
28%
higher odds of being in a more advanced KDIGO risk category
Adjusted OR = 1.28
(P = 0.044)
Remained predictive despite common
kidney-protective treatments
Including SGLT2 inhibitors, ACE inhibitors, and GLP-1 medications
Over three months, integrating CGM and wearable data into routine care was associated with strong glucose control, while highlighting the significant impact of sleep consistency and stress on health outcomes.
Key findings
No increase seen in
Normal vs Prediabetes groups
91.2%
of participants achieved Time in Range ≥70%
94.6%
achieved Time Above Range <25%
90.4%
achieved Time Below Range <4%
Stress and poor sleep slowed progress
Lifestyle factors, not just medication, influenced outcomes
Sleep consistency mattered
Greater sleep variability was significantly associated with weight gain
β = 1.38, p = 0.025
High engagement with the hybrid care model
Median of 23 inbound interactions from patients
Median of 38 outbound interactions from the care team over 3 months
Lipoprotein(a) is a genetic, independent risk factor for cardiovascular disease that remains rarely tested for in routine practice. This study examined its prevalence in 233 adults with diabetes and prediabetes within our hybrid care model, and explored its relationship to our AI-derived Retinal-CVD risk score.
Key findings
32.2%
of patients had elevated Lp(a) (≥30 mg/dL)
Total cholesterol and LDL-C trended higher in the elevated Lp(a) group
(adjusted GMR 1.08, P = 0.162), though this did not reach statistical significance after adjustment
No significant association was found between Lp(a) status and Reti-CVD risk category
(OR 1.14, P = 0.672)
Standard 10-year cardiovascular risk calculators often underestimate risk in younger patients and miss subclinical vascular damage entirely. This study examined our AI-powered retinal cardiovascular scan (Reti-CVD) in 1,461 adults, comparing it against the American Heart Association’s PREVENT equation.
Key findings
1,461 adults screened; higher Reti-CVD risk linked to age, male sex, diabetes, and hypertension (all P < 0.001)
Low-risk patients:
vascular age 4.1 years younger than actual age
High-risk patients:
vascular age matched or exceeded chronological age
49.1%
of PREVENT “low risk” patients reclassified as moderate/high risk by Reti-CVD
uPTM-FetA/Ucr stayed normal in people without diabetes and those with prediabetes, but increased significantly once diabetes was present. It also independently predicted kidney disease risk, even after accounting for medications known to protect the kidneys.
Key findings
No increase seen in
Normal vs Prediabetes groups
No significant difference
(P = NS)
Higher levels seen in both
Type 1 and Type 2 Diabetes
Significant increase compared to Normal individuals
(P < 0.05)
Predicted worsening
kidney disease risk independently
28%
higher odds of being in a more advanced KDIGO risk category
Adjusted OR = 1.28
(P = 0.044)
Remained predictive despite common
kidney-protective treatments
Including SGLT2 inhibitors, ACE inhibitors, and GLP-1 medications
Over three months, integrating CGM and wearable data into routine care was associated with strong glucose control, while highlighting the significant impact of sleep consistency and stress on health outcomes.
Key findings
No increase seen in
Normal vs Prediabetes groups
91.2%
of participants achieved Time in Range ≥70%
94.6%
achieved Time Above Range <25%
90.4%
achieved Time Below Range <4%
Stress and poor sleep slowed progress
Lifestyle factors, not just medication, influenced outcomes
Sleep consistency mattered
Greater sleep variability was significantly associated with weight gain
β = 1.38, p = 0.025
High engagement with the hybrid care model
Median of 23 inbound interactions from patients
Median of 38 outbound interactions from the care team over 3 months
Lipoprotein(a) is a genetic, independent risk factor for cardiovascular disease that remains rarely tested for in routine practice. This study examined its prevalence in 233 adults with diabetes and prediabetes within our hybrid care model, and explored its relationship to our AI-derived Retinal-CVD risk score.
Key findings
32.2%
of patients had elevated Lp(a) (≥30 mg/dL)
Total cholesterol and LDL-C trended higher in the elevated Lp(a) group
(adjusted GMR 1.08, P = 0.162), though this did not reach statistical significance after adjustment
No significant association was found between Lp(a) status and Reti-CVD risk category
(OR 1.14, P = 0.672)
Standard 10-year cardiovascular risk calculators often underestimate risk in younger patients and miss subclinical vascular damage entirely. This study examined our AI-powered retinal cardiovascular scan (Reti-CVD) in 1,461 adults, comparing it against the American Heart Association’s PREVENT equation.
Key findings
1,461 adults screened; higher Reti-CVD risk linked to age, male sex, diabetes, and hypertension (all P < 0.001)
Low-risk patients:
vascular age 4.1 years younger than actual age
High-risk patients:
vascular age matched or exceeded chronological age
49.1%
of PREVENT “low risk” patients reclassified as moderate/high risk by Reti-CVD
uPTM-FetA/Ucr stayed normal in people without diabetes and those with prediabetes, but increased significantly once diabetes was present. It also independently predicted kidney disease risk, even after accounting for medications known to protect the kidneys.
Key findings
No increase seen in
Normal vs Prediabetes groups
No significant difference
(P = NS)
Higher levels seen in both
Type 1 and Type 2 Diabetes
Significant increase compared to Normal individuals
(P < 0.05)
Predicted worsening
kidney disease risk independently
28%
higher odds of being in a more advanced KDIGO risk category
Adjusted OR = 1.28
(P = 0.044)
Remained predictive despite common
kidney-protective treatments
Including SGLT2 inhibitors, ACE inhibitors, and GLP-1 medications
Over three months, integrating CGM and wearable data into routine care was associated with strong glucose control, while highlighting the significant impact of sleep consistency and stress on health outcomes.
Key findings
No increase seen in
Normal vs Prediabetes groups
91.2%
of participants achieved Time in Range ≥70%
94.6%
achieved Time Above Range <25%
90.4%
achieved Time Below Range <4%
Stress and poor sleep slowed progress
Lifestyle factors, not just medication, influenced outcomes
Sleep consistency mattered
Greater sleep variability was significantly associated with weight gain
β = 1.38, p = 0.025
High engagement with the hybrid care model
Median of 23 inbound interactions from patients
Median of 38 outbound interactions from the care team over 3 months
Our hybrid care model integrates both physical and virtual, data-driven components. The physical clinic provides in-person interactions, including direct clinician engagement, unique diagnostic tests and comprehensive blood tests that are conducted on-site. Between visits, patients are supported through a “virtual clinic,” where an expended clinical team continues care remotely. This approach enables real-time metabolic health management, facilitates behavioral modification, enhances patient engagement, optimizes risk stratification due to availability of unique data sets, and allows for more targeted, data-driven interventions.
Key findings
Glycemic outcomes
6.18%
HbA1c at 12 months
Prediabetes reversal
63.6%
Achieved HbA1c <5.7% by 6 months
Weight loss outcomes - by 12 months
60.9%
Achieved ≥5% weight loss
52.2%
Achieved ≥10% weight loss
Digital behavioral biomarker
53.8%
Achieved recommended steps target
71.91
average sleep score reflecting adequate sleep quality
This real-world study evaluated 528 adults treated within a 6-month hybrid care model using either Semaglutide or Tirzepatide, applying the new ICHOM Obesity Standard Set for outcome reporting. Both medications produced clinically meaningful improvements in weight, waist circumference, fat mass, and glycemic markers. However, Tirzepatide consistently outperformed Semaglutide across all measured parameters. The study also demonstrated that structured hybrid care, combined with data-driven titration, drives stronger and more transparent obesity outcomes.
Key findings
Tirzepatide produced significantly greater weight loss than Semaglutide
(Tirzepatide)
13.12 kg
mean loss at 6 months
VS
(Semaglutide)
9.54 kg
mean loss at 6 months
Superior reductions in central adiposity with Tirzepatide
Waist circumference at 6 months
(Tirzepatide)
11.34 cm
VS
(Semaglutide)
7.24 cm
Fat mass reduction:
(Tirzepatide)
9.67 kg
VS
(Semaglutide)
7.54 kg
All Tirzepatide groups (2.5–5 mg, 5–7.5 mg, 7.5–15 mg) achieved statistically significant weight loss, reinforcing dose-dependent robustness in a real-world setting
Virtual interactions were highest in the first 3 months, when patients communicated most actively with the care team. This period of dense support and feedback strongly correlated with better HbA1c outcomes, especially for those starting with poor control.
Key findings
Patients with poor baseline glycemic control achieved substantial HbA1c reductions (−2.4%, p<0.001), exceeding the typical effect size reported in digital-only programs.
Outbound (provider-initiated) interactions consistently exceeded inbound ones, underscoring the importance of proactive clinician follow-up in sustaining engagement and driving outcomes.
Higher total interaction counts were independently associated with greater HbA1c improvement, even after adjusting for age, BMI, medication use, and baseline control.
A 10-year-old boy with type 1 diabetes developed acute hepatitis from insulin overdose and excessive glucose intake, detected early through continuous engagement, CGM monitoring, and follow-up lab tests, enabling timely intervention under the GluCare hybrid care model
Key findings
Liver enzymes (day of event):
ALT
280 U/L
AST
167 U/L
GGT
50 U/L
HbA1c: 6% (stable)
Outcome: Enzymes normalized; no recurrence of severe hypoglycemia
Glycemic control: TIR 77%, average glucose 113 mg/dL after intervention
This case study highlights the role of continuous remote monitoring using the ŌURA ring in detecting abnormal cardiac patterns - specifically frequent premature ventricular contractions (PVCs) - in a patient with T2D under GluCare’s hybrid care model
Key findings
Early detection
Increased resting heart rate and reduced HRV identified through the ŌURA ring triggered further investigation.
Clinical response
Prompt ECG and cardiology referral confirmed frequent PVCs; diagnosis would have been missed with standard care.
Outcome
Treatment initiated early with lifestyle modifications and medical therapy, leading to resolution of PVCs and improved heart metrics.
10
2025
This 12-month real-world study analyzed outcomes in 208 adults with T2D managed via the GluCare hybrid care model - integrating digital monitoring, virtual engagement, and in-person multidisciplinary care - using International Consortium for Health Outcomes Measurement (ICHOM) standards
Key findings
HbA1c reduced
7.7%
6.55%
73 % achieved target control (< 7 %)
Cardiovascular & metabolic improvements
Significant reductions in blood pressure, lipid profiles, weight, and waist circumference
Medication intensification
Fewer patients required escalation, with insulin usage halved
Healthcare cost impact
Estimated annual cost savings of
US $23,485
Modelling suggests T2D complications may increase long-term costs up to 9.4-fold over 10 years without proper control
This study assessed the use of AI-based retinal imaging (Ret-CAC) to stratify cardiovascular risk in 115 adults with T2D and no prior CVD
Key findings
25.2%
high risk
36.5%
moderate
38.3%
low risk
High risk linked to
OLDER AGE
LONGER DIABETES DURATION
HYPERTENSION
LOWER EGFR.
Adjusted predictors
Age
OR 1.36
eGFR
OR 0.96
Female sex
OR 0.04
protective
This 6-month retrospective observational study evaluated the effectiveness of combining GLP-1 (semaglutide) and dual GIP/GLP-1 (tirzepatide) receptor agonists with a continuous, digitally delivered behavioral-change model by an integrated care team (Zone.Health program) in adults with obesity and metabolic syndrome
Key findings
Waist circumference reduction:
Tirzepatide
–18.08 cm
Semaglutide
–13.04 cm (P < .001)
Triglycerides:
Tirzepatide
–64.42 mg/dL
Semaglutide
–70.70 mg/dL
Improved metabolic markers:
Greater reductions in fasting glucose, blood pressure, and lipids in the tirzepatide group.
This study evaluates the effectiveness of a hybrid care model incorporating continuous glucose monitoring (CGM) and personalized engagement for managing diabetes during Ramadan fasting
Key findings
TIR improvements during Ramadan fasting :
TYPE 2 DIABETES
83.13% → 85.12%
TYPE 1 DIABETES
65.17% → 70.50%
Reduction in Thrombocytopenia-absent radius :
TYPE 2 DIABETES
15.50% → 14.63%
TYPE 1 DIABETES
33.00% → 27.50%
Significant impact of engagement :
Patients with ≥5 virtual interactions had TIR improvement of
+5.00% (p=0.018)
Patients with <5 virtual interactions had TIR of
-1.57%
Comparison to standard care :
Structured Continuous Ramadan Nutrition Therapy achieved a TIR of
82.1%
Standard Care Therapy achieved a TIR of
61.8%
Our hybrid care model integrates both physical and virtual, data-driven components. The physical clinic provides in-person interactions, including direct clinician engagement, unique diagnostic tests and comprehensive blood tests that are conducted on-site. Between visits, patients are supported through a “virtual clinic,” where an expended clinical team continues care remotely. This approach enables real-time metabolic health management, facilitates behavioral modification, enhances patient engagement, optimizes risk stratification due to availability of unique data sets, and allows for more targeted, data-driven interventions.
Key findings
Glycemic outcomes
6.18%
HbA1c at 12 months
Prediabetes reversal
63.6%
Achieved HbA1c <5.7% by 6 months
Weight loss outcomes - by 12 months
60.9%
Achieved ≥5% weight loss
52.2%
Achieved ≥10% weight loss
Digital behavioral biomarker
53.8%
Achieved recommended steps target
71.91
average sleep score reflecting adequate sleep quality
This real-world study evaluated 528 adults treated within a 6-month hybrid care model using either Semaglutide or Tirzepatide, applying the new ICHOM Obesity Standard Set for outcome reporting. Both medications produced clinically meaningful improvements in weight, waist circumference, fat mass, and glycemic markers. However, Tirzepatide consistently outperformed Semaglutide across all measured parameters. The study also demonstrated that structured hybrid care, combined with data-driven titration, drives stronger and more transparent obesity outcomes.
Key findings
Tirzepatide produced significantly greater weight loss than Semaglutide
(Tirzepatide)
13.12 kg
mean loss at 6 months
VS
(Semaglutide)
9.54 kg
mean loss at 6 months
Superior reductions in central adiposity with Tirzepatide
Waist circumference at 6 months
(Tirzepatide)
11.34 cm
VS
(Semaglutide)
7.24 cm
Fat mass reduction:
(Tirzepatide)
9.67 kg
VS
(Semaglutide)
7.54 kg
All Tirzepatide groups (2.5–5 mg, 5–7.5 mg, 7.5–15 mg) achieved statistically significant weight loss, reinforcing dose-dependent robustness in a real-world setting
Virtual interactions were highest in the first 3 months, when patients communicated most actively with the care team. This period of dense support and feedback strongly correlated with better HbA1c outcomes, especially for those starting with poor control.
Key findings
Patients with poor baseline glycemic control achieved substantial HbA1c reductions (−2.4%, p<0.001), exceeding the typical effect size reported in digital-only programs.
Outbound (provider-initiated) interactions consistently exceeded inbound ones, underscoring the importance of proactive clinician follow-up in sustaining engagement and driving outcomes.
Higher total interaction counts were independently associated with greater HbA1c improvement, even after adjusting for age, BMI, medication use, and baseline control.
A 10-year-old boy with type 1 diabetes developed acute hepatitis from insulin overdose and excessive glucose intake, detected early through continuous engagement, CGM monitoring, and follow-up lab tests, enabling timely intervention under the GluCare hybrid care model
Key findings
Liver enzymes (day of event):
ALT
280 U/L
AST
167 U/L
GGT
50 U/L
HbA1c: 6% (stable)
Outcome: Enzymes normalized; no recurrence of severe hypoglycemia
Glycemic control: TIR 77%, average glucose 113 mg/dL after intervention
This case study highlights the role of continuous remote monitoring using the ŌURA ring in detecting abnormal cardiac patterns - specifically frequent premature ventricular contractions (PVCs) - in a patient with T2D under GluCare’s hybrid care model
Key findings
Early detection
Increased resting heart rate and reduced HRV identified through the ŌURA ring triggered further investigation.
Clinical response
Prompt ECG and cardiology referral confirmed frequent PVCs; diagnosis would have been missed with standard care.
Outcome
Treatment initiated early with lifestyle modifications and medical therapy, leading to resolution of PVCs and improved heart metrics.
10
2025
This 12-month real-world study analyzed outcomes in 208 adults with T2D managed via the GluCare hybrid care model - integrating digital monitoring, virtual engagement, and in-person multidisciplinary care - using International Consortium for Health Outcomes Measurement (ICHOM) standards
Key findings
HbA1c reduced
7.7%
6.55%
73 % achieved target control (< 7 %)
Cardiovascular & metabolic improvements
Significant reductions in blood pressure, lipid profiles, weight, and waist circumference
Medication intensification
Fewer patients required escalation, with insulin usage halved
Healthcare cost impact
Estimated annual cost savings of
US $23,485
Modelling suggests T2D complications may increase long-term costs up to 9.4-fold over 10 years without proper control
This study assessed the use of AI-based retinal imaging (Ret-CAC) to stratify cardiovascular risk in 115 adults with T2D and no prior CVD
Key findings
25.2%
high risk
36.5%
moderate
38.3%
low risk
High risk linked to
OLDER AGE
LONGER DIABETES DURATION
HYPERTENSION
LOWER EGFR.
Adjusted predictors
Age
OR 1.36
eGFR
OR 0.96
Female sex
OR 0.04
protective
This 6-month retrospective observational study evaluated the effectiveness of combining GLP-1 (semaglutide) and dual GIP/GLP-1 (tirzepatide) receptor agonists with a continuous, digitally delivered behavioral-change model by an integrated care team (Zone.Health program) in adults with obesity and metabolic syndrome
Key findings
Waist circumference reduction:
Tirzepatide
–18.08 cm
Semaglutide
–13.04 cm (P < .001)
Triglycerides:
Tirzepatide
–64.42 mg/dL
Semaglutide
–70.70 mg/dL
Improved metabolic markers:
Greater reductions in fasting glucose, blood pressure, and lipids in the tirzepatide group.
This study evaluates the effectiveness of a hybrid care model incorporating continuous glucose monitoring (CGM) and personalized engagement for managing diabetes during Ramadan fasting
Key findings
TIR improvements during Ramadan fasting :
TYPE 2 DIABETES
83.13% → 85.12%
TYPE 1 DIABETES
65.17% → 70.50%
Reduction in Thrombocytopenia-absent radius :
TYPE 2 DIABETES
15.50% → 14.63%
TYPE 1 DIABETES
33.00% → 27.50%
Significant impact of engagement :
Patients with ≥5 virtual interactions had TIR improvement of
+5.00% (p=0.018)
Patients with <5 virtual interactions had TIR of
-1.57%
Comparison to standard care :
Structured Continuous Ramadan Nutrition Therapy achieved a TIR of
82.1%
Standard Care Therapy achieved a TIR of
61.8%
Our hybrid care model integrates both physical and virtual, data-driven components. The physical clinic provides in-person interactions, including direct clinician engagement, unique diagnostic tests and comprehensive blood tests that are conducted on-site. Between visits, patients are supported through a “virtual clinic,” where an expended clinical team continues care remotely. This approach enables real-time metabolic health management, facilitates behavioral modification, enhances patient engagement, optimizes risk stratification due to availability of unique data sets, and allows for more targeted, data-driven interventions.
Key findings
Glycemic outcomes
6.18%
HbA1c at 12 months
Prediabetes reversal
63.6%
Achieved HbA1c <5.7% by 6 months
Weight loss outcomes - by 12 months
60.9%
Achieved ≥5% weight loss
52.2%
Achieved ≥10% weight loss
Digital behavioral biomarker
53.8%
Achieved recommended steps target
71.91
average sleep score reflecting adequate sleep quality
This real-world study evaluated 528 adults treated within a 6-month hybrid care model using either Semaglutide or Tirzepatide, applying the new ICHOM Obesity Standard Set for outcome reporting. Both medications produced clinically meaningful improvements in weight, waist circumference, fat mass, and glycemic markers. However, Tirzepatide consistently outperformed Semaglutide across all measured parameters. The study also demonstrated that structured hybrid care, combined with data-driven titration, drives stronger and more transparent obesity outcomes.
Key findings
Tirzepatide produced significantly greater weight loss than Semaglutide
(Tirzepatide)
13.12 kg
mean loss at 6 months
VS
(Semaglutide)
9.54 kg
mean loss at 6 months
Superior reductions in central adiposity with Tirzepatide
Waist circumference at 6 months
(Tirzepatide)
11.34 cm
VS
(Semaglutide)
7.24 cm
Fat mass reduction:
(Tirzepatide)
9.67 kg
VS
(Semaglutide)
7.54 kg
All Tirzepatide groups (2.5–5 mg, 5–7.5 mg, 7.5–15 mg) achieved statistically significant weight loss, reinforcing dose-dependent robustness in a real-world setting
Virtual interactions were highest in the first 3 months, when patients communicated most actively with the care team. This period of dense support and feedback strongly correlated with better HbA1c outcomes, especially for those starting with poor control.
Key findings
Patients with poor baseline glycemic control achieved substantial HbA1c reductions (−2.4%, p<0.001), exceeding the typical effect size reported in digital-only programs.
Outbound (provider-initiated) interactions consistently exceeded inbound ones, underscoring the importance of proactive clinician follow-up in sustaining engagement and driving outcomes.
Higher total interaction counts were independently associated with greater HbA1c improvement, even after adjusting for age, BMI, medication use, and baseline control.
A 10-year-old boy with type 1 diabetes developed acute hepatitis from insulin overdose and excessive glucose intake, detected early through continuous engagement, CGM monitoring, and follow-up lab tests, enabling timely intervention under the GluCare hybrid care model
Key findings
Liver enzymes (day of event):
ALT
280 U/L
AST
167 U/L
GGT
50 U/L
HbA1c: 6% (stable)
Outcome: Enzymes normalized; no recurrence of severe hypoglycemia
Glycemic control: TIR 77%, average glucose 113 mg/dL after intervention
This case study highlights the role of continuous remote monitoring using the ŌURA ring in detecting abnormal cardiac patterns - specifically frequent premature ventricular contractions (PVCs) - in a patient with T2D under GluCare’s hybrid care model
Key findings
Early detection
Increased resting heart rate and reduced HRV identified through the ŌURA ring triggered further investigation.
Clinical response
Prompt ECG and cardiology referral confirmed frequent PVCs; diagnosis would have been missed with standard care.
Outcome
Treatment initiated early with lifestyle modifications and medical therapy, leading to resolution of PVCs and improved heart metrics.
10
2025
This 12-month real-world study analyzed outcomes in 208 adults with T2D managed via the GluCare hybrid care model - integrating digital monitoring, virtual engagement, and in-person multidisciplinary care - using International Consortium for Health Outcomes Measurement (ICHOM) standards
Key findings
HbA1c reduced
7.7%
6.55%
73 % achieved target control (< 7 %)
Cardiovascular & metabolic improvements
Significant reductions in blood pressure, lipid profiles, weight, and waist circumference
Medication intensification
Fewer patients required escalation, with insulin usage halved
Healthcare cost impact
Estimated annual cost savings of
US $23,485
Modelling suggests T2D complications may increase long-term costs up to 9.4-fold over 10 years without proper control
This study assessed the use of AI-based retinal imaging (Ret-CAC) to stratify cardiovascular risk in 115 adults with T2D and no prior CVD
Key findings
25.2%
high risk
36.5%
moderate
38.3%
low risk
High risk linked to
OLDER AGE
LONGER DIABETES DURATION
HYPERTENSION
LOWER EGFR.
Adjusted predictors
Age
OR 1.36
eGFR
OR 0.96
Female sex
OR 0.04
protective
This 6-month retrospective observational study evaluated the effectiveness of combining GLP-1 (semaglutide) and dual GIP/GLP-1 (tirzepatide) receptor agonists with a continuous, digitally delivered behavioral-change model by an integrated care team (Zone.Health program) in adults with obesity and metabolic syndrome
Key findings
Waist circumference reduction:
Tirzepatide
–18.08 cm
Semaglutide
–13.04 cm (P < .001)
Triglycerides:
Tirzepatide
–64.42 mg/dL
Semaglutide
–70.70 mg/dL
Improved metabolic markers:
Greater reductions in fasting glucose, blood pressure, and lipids in the tirzepatide group.
This study evaluates the effectiveness of a hybrid care model incorporating continuous glucose monitoring (CGM) and personalized engagement for managing diabetes during Ramadan fasting
Key findings
TIR improvements during Ramadan fasting :
TYPE 2 DIABETES
83.13% → 85.12%
TYPE 1 DIABETES
65.17% → 70.50%
Reduction in Thrombocytopenia-absent radius :
TYPE 2 DIABETES
15.50% → 14.63%
TYPE 1 DIABETES
33.00% → 27.50%
Significant impact of engagement :
Patients with ≥5 virtual interactions had TIR improvement of
+5.00% (p=0.018)
Patients with <5 virtual interactions had TIR of
-1.57%
Comparison to standard care :
Structured Continuous Ramadan Nutrition Therapy achieved a TIR of
82.1%
Standard Care Therapy achieved a TIR of
61.8%
The findings of this study underscore the potential of integrating GLP-1 medications with digitally delivered multidisciplinary engagement to optimize cardiovascular health outcomes
Key findings
12.3%
reduction in 10-year ASCVD risk
Baseline : 2.92 ± 2.86 → 2.56 ± 2.83 (p = 0.024).
13%
weight and BMI reduction
Significant decrease in weight and BMI (p < 0.001).
Improvements in key CVD markers :
-15
LDL
-26
Triglycerides
-12
Total cholesterol (all p < 0.001)
23%
fat mass reduction
Combined impact of GLP-1 agonists and digital lifestyle interventions.
The findings of this study demonstrate significant improvements in glycemic control, cardiovascular risk factors, and overall quality of life
Key findings
0.9%
reduction in 10-year ASCVD risk
Baseline : 7.66% → 6.76% (p=0.038)
BMI and waist circumference reduction :
BMI Circumference
29.64 → 27.96 (p=0.018)
Waist Circumference
103.07 cm → 97.25 cm (p=0.003)
Improved lipid and liver profiles :
LDL
8.06 mg/dL (p=0.028)
Triglycerides
-37.60 mg/dL (p=0.038)
ALT
26.72 → 18.46.
Enhanced patient engagement :
192.62
total interactions per patient
117.81
outgoing
74.81
incoming
facilitated by digital tools and continuous monitoring.
Improved mental health scores :
WHO-5
23.50
Increased
PHQ-9
1.67
Decreased
PAID
1.33
Lowered
The findings of this study demonstrate significant improvements in glycemic control, cardiovascular risk factors, and overall quality of life
Key findings
Global need
Addresses the rising diabetes burden
Innovative approach
Combines physical clinics with continuous digital engagement
Proven results
Significant health gains within 3 months
Future focus
Overcoming scalability and adoption hurdles
Zone.Health’s 6-month program, combining GLP-1 therapy, lifestyle changes, and digital tools, delivered remarkable outcomes in fatty liver disease management
Key findings
17.4%
MASH
10.2%
MASLD
Patients achieved reversal to normal ranges within 3 months
Weight
20.6%
Dropped
Fat mass
14.1%
Reduced
Total Cholesterol
20.6%
Dropped
ALT Levels
20.6%
Reduced
UAP
5.3%
Decreased
Both medications, as part of a hybrid program including pharmacotherapy, dietary guidance, and behavioral counseling, resulted in significant improvements in clinical parameters, with tirzepatide demonstrating superior effectiveness over semaglutide
Key findings
Significant reductions in weight, fat mass, and cholesterol, with tirzepatide showing greater effectiveness in reducing waist circumference
-7.5%
-4.9%
p=0.025
Tirzepatide led to more substantial decreases in HbA1c levels
-5.7%
-3.3%
p=0.034
Uric acid levels were reduced by -3.2% with tirzepatide
Uric Acid
3.2%
Reduced
Semaglutide saw an increase of +11.9% (p = 0.007).
Semaglutide
11.9%
Increased
By integrating in-clinic visits with continuous remote monitoring and multidisciplinary engagement, the study also demonstrated significant improvements in glycemic control, blood pressure, and cardiovascular risk
Key findings
21% HbA1c improvement
21%
HbA1c improvement
Baseline : 8.63 ± 1.80 → 6.83 ± 1.58 after 6 months
7% weight loss accompanied by a 7% increase in fat-free mass.
Weight
7%
Decreased
Fat-free mass
7%
Increased
43% cardiovascular risk reduction
43%
cardiovascular risk reduction
-7%
systolic
-7%
diastolic
Promising renal outcomes: ACR improved slightly (from 373.74 ± 651.57 to 365.47 ± 1287.07), with further studies needed for assessing long-term impact.
ACR IMPROVED
373.74 ± 651.57
365.47 ± 1287.07
Early results from a 6-month program demonstrate significant weight loss and metabolic improvements, with continuous remote monitoring and multidisciplinary support showing promise in managing both obesity and pre-diabetes
Key findings
Average weight reduction of 8%, with significant reductions in BMI, fat mass, and cholesterol
8%
weight reduction
BMI
Fat mass
Cholesterol
20% of patients lost ≥5% of body weight, 47.8% lost ≥10%, and 31.3% lost ≥15%
20% Patients
5%
Body weight
47.8% Patients
10%
Body weight
31.3% Patients
15%
Body weight
80.6% of pre-diabetic patients showed control of pre-diabetes, with HbA1c returning to normoglycemia (5.39 ± 0.27)
80.6%
patients showed control over pre-diabetes
HbA1c returned to normoglycemia
5.39 ± 0.27
The integration of digital technology and a multidisciplinary care team facilitated continuous monitoring and personalized care
The hybrid model proves to be more effective than traditional or digital-only approaches, underscoring the importance of patient engagement
Key findings
HbA1c
-2.19%
Improved
with more significant reductions seen in patients with higher baseline levels
Showed notable improvements in the case group
WEIGHT
BMI
LDL
TOTAL CHOLESTEROL
CVD
Patients with ≥11 digital interactions had a
-2.38% reduction in HbA1c
Patients with ≥11 digital interactions had a
-6.00 kg weight loss
The hybrid model, combining in-clinic visits and remote monitoring, led to more substantial clinical improvements than digital-only interventions
The study reveals significant improvements in glycemic control, insulin reduction, and weight loss when these therapies are integrated with a hybrid care model
Key findings
Prandial insulin
25.24%
Reduction
Basal insulin
29.16%
Reduction
HbA1c decreased from 8.28% to
6.95% over 3 months
Time in Range increased by
42.11% (p=0.018)
Overweight/obese patients lost an average of
5.64kg (p<0.001)
23
2024
The findings reveal significant improvements in mental well-being, as well as key health markers, emphasizing the potential of continuous, multidisciplinary care in managing both physical and emotional challenges associated with T2D
Key findings
Weight
-4.0 ± 5.3
Reduction
Waist Circumference
-4.74 ± 7.8
Reduction
HbA1c
1.00 ± 1.3
Reduction
Mental health improvements:
WHO-5
4%
Increased
PAID
-28%
Decreased
PHQ9
-29%
Dropped
Hybrid care models improve both biomarkers and quality of life, addressing mental health issues often overlooked in traditional care
The findings highlight the variations in these glycemic measures and their impact on diabetes management, especially when continuous remote monitoring is integrated with in-clinic visits
Key findings
86.4%
patients showed significant differences in HbA1c
86.4%
patients showed significant differences in GMI
Patients with Type 1 diabetes (T1D) demonstrated a higher proportion of variation between HbA1c and GMI compared to T2D and prediabetes
Time in range (TIR)
Average glucose (AG)
% coefficient of variation (% CV)
differed significantly across patient groups (p < 0.001)
Hybrid care, combining in-clinic and remote monitoring, offers immediate decision-making potential for diabetes management
25
2024
The results demonstrate that hybrid care significantly improves HbA1c, weight, and other health parameters, highlighting the benefit of continuous monitoring and remote engagement in diabetes management
Key findings
Hybrid care group showed a significant reduction of
-2.19% in HbA1c
Control group showed only a reduction of
-0.10% in HbA1c
-3.67%
Patients with a baseline HbA1c ≥ 9.0% in the hybrid group experienced a greater reduction in HbA1c than those in the control group
Patients with ≥11 remote engagements in the hybrid group showed
-2.38% reduction in HbA1c
Patients with ≥11 remote engagements in the hybrid group showed
-6.00 kg reduction in weight
26
2024
Conducted over six months, the program demonstrated significant improvements in weight loss, glycemic control, and cardiovascular health markers
Key findings
-7.89 kg (-8.24%)
weight loss
2.79 unit
BMI reduction
Remission of pre-diabetes in 80% of participants
HbA1c improved by
-2.38%
Improved fat mass and lipid profiles
Fat mass improved by
-5.46 kg (-12.5%)
Total cholesterol improved by
-16.08 mg/dL (-8.3%)
16.2%
greater weight reduction compared to STEP-2 trial
Findings reveal a strong association between better sleep quality and lower HbA1c levels, emphasizing the critical role of sleep in diabetes management
Key findings
65.6% of participants reported poor sleep quality
PSQI score
7.91 ± 4.5
Patients with better sleep quality had 17.4% lower HbA1c levels
Poor sleep
7.48%
Good sleep
6.18%
Shorter diabetes duration linked to poorer sleep quality
0-5 years
More likely to have a PSQI > 5
Gender differences in sleep quality
Males reported poorer sleep more frequently than females
The findings underscore the value of personalized, technology-driven engagement in enhancing outcomes and ROI in obesity treatment
Key findings
Statistically significant improvements in 3 months
-7.12 kg
weight loss
-2.51
BMI reduction
Higher engagement improves results
Patients with ≥10 interactions lost
-7.12 kg
Less engaged patients
-4.95 kg
Digital engagement distribution
Diet habits related inquiries
28.8%
Medication related inquiries
28.9%
Lifestyle messages
21.1%
CGM and tech issues
21.2%
Over a 12-month period, adherent patients demonstrated significant improvements in HbA1c, lipid profiles, and Time in Range (TIR), highlighting the limitations of traditional care and the benefits of a hyper-personalized, continuous approach
Key findings
HbA1c
-1.53%
Improved
Significant improvement in adherent patients compared to non-adherent (-0.18%, p=0.490)
Improved lipid profiles
Total Cholesterol
-16.6 mg/dL (p=0.034)
LDL
-18.65 mg/dL (p=0.006)
TIR exceeding ADA target
Adherent patients achieved a mean TIR of
80%
Hybrid model effectiveness
Demonstrated superior outcomes in poorly controlled T2D patients compared to traditional care.
The study demonstrates that patients using the Medtronic 780G AID under this model achieved significantly better glycemic outcomes than traditional self-care approaches
Key findings
15.58%
increase in Time in Range
Baseline : 59.17% → 74.75% post-intervention
1.72%
reduction in HbA1c
Baseline:
8.04% → 6.75%
8.91 unit
reduction in insulin requirements
Average daily insulin usage decreased significantly.
5-7x
more patient engagement
Hybrid model facilitated consistent education and behavioral improvements.
The results show significant improvements in glycemic control, weight, and blood pressure, with a notable difference between adherent and non-adherent patients, emphasizing the importance of continuous, personalized care
Key findings
Significant weight loss
-4.0 ± 5.3 kg
Reduced waist circumference
-4.74 ± 7.8 cm
HbA1c levels decreased by
-1.00 ± 1.3%
Systolic BP decreased by
-3.1 ± 13.1 mg/dL
Diastolic BP decreased by
-3.4 ± 9.9 mg/dL
Reductions in HbA1c
-1.53 ± 1.5%
Reductions in total cholesterol
-16.6 ± 50.3 mg/dL
Reductions in LDL
-18.65 ± 42.6 mg/dL
The study demonstrates the effectiveness of a personalized, continuous approach, highlighting its superiority over traditional care models
The findings of this study underscore the potential of integrating GLP-1 medications with digitally delivered multidisciplinary engagement to optimize cardiovascular health outcomes
Key findings
12.3%
reduction in 10-year ASCVD risk
Baseline : 2.92 ± 2.86 → 2.56 ± 2.83 (p = 0.024).
13%
weight and BMI reduction
Significant decrease in weight and BMI (p < 0.001).
Improvements in key CVD markers :
-15
LDL
-26
Triglycerides
-12
Total cholesterol (all p < 0.001)
23%
fat mass reduction
Combined impact of GLP-1 agonists and digital lifestyle interventions.
The findings of this study demonstrate significant improvements in glycemic control, cardiovascular risk factors, and overall quality of life
Key findings
0.9%
reduction in 10-year ASCVD risk
Baseline : 7.66% → 6.76% (p=0.038)
BMI and waist circumference reduction :
BMI Circumference
29.64 → 27.96 (p=0.018)
Waist Circumference
103.07 cm → 97.25 cm (p=0.003)
Improved lipid and liver profiles :
LDL
8.06 mg/dL (p=0.028)
Triglycerides
-37.60 mg/dL (p=0.038)
ALT
26.72 → 18.46.
Enhanced patient engagement :
192.62
total interactions per patient
117.81
outgoing
74.81
incoming
facilitated by digital tools and continuous monitoring.
Improved mental health scores :
WHO-5
23.50
Increased
PHQ-9
1.67
Decreased
PAID
1.33
Lowered
The findings of this study demonstrate significant improvements in glycemic control, cardiovascular risk factors, and overall quality of life
Key findings
Global need
Addresses the rising diabetes burden
Innovative approach
Combines physical clinics with continuous digital engagement
Proven results
Significant health gains within 3 months
Future focus
Overcoming scalability and adoption hurdles
Zone.Health’s 6-month program, combining GLP-1 therapy, lifestyle changes, and digital tools, delivered remarkable outcomes in fatty liver disease management
Key findings
17.4%
MASH
10.2%
MASLD
Patients achieved reversal to normal ranges within 3 months
Weight
20.6%
Dropped
Fat mass
14.1%
Reduced
Total Cholesterol
20.6%
Dropped
ALT Levels
20.6%
Reduced
UAP
5.3%
Decreased
Both medications, as part of a hybrid program including pharmacotherapy, dietary guidance, and behavioral counseling, resulted in significant improvements in clinical parameters, with tirzepatide demonstrating superior effectiveness over semaglutide
Key findings
Significant reductions in weight, fat mass, and cholesterol, with tirzepatide showing greater effectiveness in reducing waist circumference
-7.5%
-4.9%
p=0.025
Tirzepatide led to more substantial decreases in HbA1c levels
-5.7%
-3.3%
p=0.034
Uric acid levels were reduced by -3.2% with tirzepatide
Uric Acid
3.2%
Reduced
Semaglutide saw an increase of +11.9% (p = 0.007).
Semaglutide
11.9%
Increased
By integrating in-clinic visits with continuous remote monitoring and multidisciplinary engagement, the study also demonstrated significant improvements in glycemic control, blood pressure, and cardiovascular risk
Key findings
21% HbA1c improvement
21%
HbA1c improvement
Baseline : 8.63 ± 1.80 → 6.83 ± 1.58 after 6 months
7% weight loss accompanied by a 7% increase in fat-free mass.
Weight
7%
Decreased
Fat-free mass
7%
Increased
43% cardiovascular risk reduction
43%
cardiovascular risk reduction
-7%
systolic
-7%
diastolic
Promising renal outcomes: ACR improved slightly (from 373.74 ± 651.57 to 365.47 ± 1287.07), with further studies needed for assessing long-term impact.
ACR IMPROVED
373.74 ± 651.57
365.47 ± 1287.07
Early results from a 6-month program demonstrate significant weight loss and metabolic improvements, with continuous remote monitoring and multidisciplinary support showing promise in managing both obesity and pre-diabetes
Key findings
Average weight reduction of 8%, with significant reductions in BMI, fat mass, and cholesterol
8%
weight reduction
BMI
Fat mass
Cholesterol
20% of patients lost ≥5% of body weight, 47.8% lost ≥10%, and 31.3% lost ≥15%
20% Patients
5%
Body weight
47.8% Patients
10%
Body weight
31.3% Patients
15%
Body weight
80.6% of pre-diabetic patients showed control of pre-diabetes, with HbA1c returning to normoglycemia (5.39 ± 0.27)
80.6%
patients showed control over pre-diabetes
HbA1c returned to normoglycemia
5.39 ± 0.27
The integration of digital technology and a multidisciplinary care team facilitated continuous monitoring and personalized care
The hybrid model proves to be more effective than traditional or digital-only approaches, underscoring the importance of patient engagement
Key findings
HbA1c
-2.19%
Improved
with more significant reductions seen in patients with higher baseline levels
Showed notable improvements in the case group
WEIGHT
BMI
LDL
TOTAL CHOLESTEROL
CVD
Patients with ≥11 digital interactions had a
-2.38% reduction in HbA1c
Patients with ≥11 digital interactions had a
-6.00 kg weight loss
The hybrid model, combining in-clinic visits and remote monitoring, led to more substantial clinical improvements than digital-only interventions
The study reveals significant improvements in glycemic control, insulin reduction, and weight loss when these therapies are integrated with a hybrid care model
Key findings
Prandial insulin
25.24%
Reduction
Basal insulin
29.16%
Reduction
HbA1c decreased from 8.28% to
6.95% over 3 months
Time in Range increased by
42.11% (p=0.018)
Overweight/obese patients lost an average of
5.64kg (p<0.001)
23
2024
The findings reveal significant improvements in mental well-being, as well as key health markers, emphasizing the potential of continuous, multidisciplinary care in managing both physical and emotional challenges associated with T2D
Key findings
Weight
-4.0 ± 5.3
Reduction
Waist Circumference
-4.74 ± 7.8
Reduction
HbA1c
1.00 ± 1.3
Reduction
Mental health improvements:
WHO-5
4%
Increased
PAID
-28%
Decreased
PHQ9
-29%
Dropped
Hybrid care models improve both biomarkers and quality of life, addressing mental health issues often overlooked in traditional care
The findings highlight the variations in these glycemic measures and their impact on diabetes management, especially when continuous remote monitoring is integrated with in-clinic visits
Key findings
86.4%
patients showed significant differences in HbA1c
86.4%
patients showed significant differences in GMI
Patients with Type 1 diabetes (T1D) demonstrated a higher proportion of variation between HbA1c and GMI compared to T2D and prediabetes
Time in range (TIR)
Average glucose (AG)
% coefficient of variation (% CV)
differed significantly across patient groups (p < 0.001)
Hybrid care, combining in-clinic and remote monitoring, offers immediate decision-making potential for diabetes management
25
2024
The results demonstrate that hybrid care significantly improves HbA1c, weight, and other health parameters, highlighting the benefit of continuous monitoring and remote engagement in diabetes management
Key findings
Hybrid care group showed a significant reduction of
-2.19% in HbA1c
Control group showed only a reduction of
-0.10% in HbA1c
-3.67%
Patients with a baseline HbA1c ≥ 9.0% in the hybrid group experienced a greater reduction in HbA1c than those in the control group
Patients with ≥11 remote engagements in the hybrid group showed
-2.38% reduction in HbA1c
Patients with ≥11 remote engagements in the hybrid group showed
-6.00 kg reduction in weight
26
2024
Conducted over six months, the program demonstrated significant improvements in weight loss, glycemic control, and cardiovascular health markers
Key findings
-7.89 kg (-8.24%)
weight loss
2.79 unit
BMI reduction
Remission of pre-diabetes in 80% of participants
HbA1c improved by
-2.38%
Improved fat mass and lipid profiles
Fat mass improved by
-5.46 kg (-12.5%)
Total cholesterol improved by
-16.08 mg/dL (-8.3%)
16.2%
greater weight reduction compared to STEP-2 trial
Findings reveal a strong association between better sleep quality and lower HbA1c levels, emphasizing the critical role of sleep in diabetes management
Key findings
65.6% of participants reported poor sleep quality
PSQI score
7.91 ± 4.5
Patients with better sleep quality had 17.4% lower HbA1c levels
Poor sleep
7.48%
Good sleep
6.18%
Shorter diabetes duration linked to poorer sleep quality
0-5 years
More likely to have a PSQI > 5
Gender differences in sleep quality
Males reported poorer sleep more frequently than females
The findings underscore the value of personalized, technology-driven engagement in enhancing outcomes and ROI in obesity treatment
Key findings
Statistically significant improvements in 3 months
-7.12 kg
weight loss
-2.51
BMI reduction
Higher engagement improves results
Patients with ≥10 interactions lost
-7.12 kg
Less engaged patients
-4.95 kg
Digital engagement distribution
Diet habits related inquiries
28.8%
Medication related inquiries
28.9%
Lifestyle messages
21.1%
CGM and tech issues
21.2%
Over a 12-month period, adherent patients demonstrated significant improvements in HbA1c, lipid profiles, and Time in Range (TIR), highlighting the limitations of traditional care and the benefits of a hyper-personalized, continuous approach
Key findings
HbA1c
-1.53%
Improved
Significant improvement in adherent patients compared to non-adherent (-0.18%, p=0.490)
Improved lipid profiles
Total Cholesterol
-16.6 mg/dL (p=0.034)
LDL
-18.65 mg/dL (p=0.006)
TIR exceeding ADA target
Adherent patients achieved a mean TIR of
80%
Hybrid model effectiveness
Demonstrated superior outcomes in poorly controlled T2D patients compared to traditional care.
The study demonstrates that patients using the Medtronic 780G AID under this model achieved significantly better glycemic outcomes than traditional self-care approaches
Key findings
15.58%
increase in Time in Range
Baseline : 59.17% → 74.75% post-intervention
1.72%
reduction in HbA1c
Baseline:
8.04% → 6.75%
8.91 unit
reduction in insulin requirements
Average daily insulin usage decreased significantly.
5-7x
more patient engagement
Hybrid model facilitated consistent education and behavioral improvements.
The results show significant improvements in glycemic control, weight, and blood pressure, with a notable difference between adherent and non-adherent patients, emphasizing the importance of continuous, personalized care
Key findings
Significant weight loss
-4.0 ± 5.3 kg
Reduced waist circumference
-4.74 ± 7.8 cm
HbA1c levels decreased by
-1.00 ± 1.3%
Systolic BP decreased by
-3.1 ± 13.1 mg/dL
Diastolic BP decreased by
-3.4 ± 9.9 mg/dL
Reductions in HbA1c
-1.53 ± 1.5%
Reductions in total cholesterol
-16.6 ± 50.3 mg/dL
Reductions in LDL
-18.65 ± 42.6 mg/dL
The study demonstrates the effectiveness of a personalized, continuous approach, highlighting its superiority over traditional care models
The findings of this study underscore the potential of integrating GLP-1 medications with digitally delivered multidisciplinary engagement to optimize cardiovascular health outcomes
Key findings
12.3%
reduction in 10-year ASCVD risk
Baseline : 2.92 ± 2.86 → 2.56 ± 2.83 (p = 0.024).
13%
weight and BMI reduction
Significant decrease in weight and BMI (p < 0.001).
Improvements in key CVD markers :
-15
LDL
-26
Triglycerides
-12
Total cholesterol (all p < 0.001)
23%
fat mass reduction
Combined impact of GLP-1 agonists and digital lifestyle interventions.
The findings of this study demonstrate significant improvements in glycemic control, cardiovascular risk factors, and overall quality of life
Key findings
0.9%
reduction in 10-year ASCVD risk
Baseline : 7.66% → 6.76% (p=0.038)
BMI and waist circumference reduction :
BMI Circumference
29.64 → 27.96 (p=0.018)
Waist Circumference
103.07 cm → 97.25 cm (p=0.003)
Improved lipid and liver profiles :
LDL
8.06 mg/dL (p=0.028)
Triglycerides
-37.60 mg/dL (p=0.038)
ALT
26.72 → 18.46.
Enhanced patient engagement :
192.62
total interactions per patient
117.81
outgoing
74.81
incoming
facilitated by digital tools and continuous monitoring.
Improved mental health scores :
WHO-5
23.50
Increased
PHQ-9
1.67
Decreased
PAID
1.33
Lowered
The findings of this study demonstrate significant improvements in glycemic control, cardiovascular risk factors, and overall quality of life
Key findings
Global need
Addresses the rising diabetes burden
Innovative approach
Combines physical clinics with continuous digital engagement
Proven results
Significant health gains within 3 months
Future focus
Overcoming scalability and adoption hurdles
Zone.Health’s 6-month program, combining GLP-1 therapy, lifestyle changes, and digital tools, delivered remarkable outcomes in fatty liver disease management
Key findings
17.4%
MASH
10.2%
MASLD
Patients achieved reversal to normal ranges within 3 months
Weight
20.6%
Dropped
Fat mass
14.1%
Reduced
Total Cholesterol
20.6%
Dropped
ALT Levels
20.6%
Reduced
UAP
5.3%
Decreased
Both medications, as part of a hybrid program including pharmacotherapy, dietary guidance, and behavioral counseling, resulted in significant improvements in clinical parameters, with tirzepatide demonstrating superior effectiveness over semaglutide
Key findings
Significant reductions in weight, fat mass, and cholesterol, with tirzepatide showing greater effectiveness in reducing waist circumference
-7.5%
-4.9%
p=0.025
Tirzepatide led to more substantial decreases in HbA1c levels
-5.7%
-3.3%
p=0.034
Uric acid levels were reduced by -3.2% with tirzepatide
Uric Acid
3.2%
Reduced
Semaglutide saw an increase of +11.9% (p = 0.007).
Semaglutide
11.9%
Increased
By integrating in-clinic visits with continuous remote monitoring and multidisciplinary engagement, the study also demonstrated significant improvements in glycemic control, blood pressure, and cardiovascular risk
Key findings
21% HbA1c improvement
21%
HbA1c improvement
Baseline : 8.63 ± 1.80 → 6.83 ± 1.58 after 6 months
7% weight loss accompanied by a 7% increase in fat-free mass.
Weight
7%
Decreased
Fat-free mass
7%
Increased
43% cardiovascular risk reduction
43%
cardiovascular risk reduction
-7%
systolic
-7%
diastolic
Promising renal outcomes: ACR improved slightly (from 373.74 ± 651.57 to 365.47 ± 1287.07), with further studies needed for assessing long-term impact.
ACR IMPROVED
373.74 ± 651.57
365.47 ± 1287.07
Early results from a 6-month program demonstrate significant weight loss and metabolic improvements, with continuous remote monitoring and multidisciplinary support showing promise in managing both obesity and pre-diabetes
Key findings
Average weight reduction of 8%, with significant reductions in BMI, fat mass, and cholesterol
8%
weight reduction
BMI
Fat mass
Cholesterol
20% of patients lost ≥5% of body weight, 47.8% lost ≥10%, and 31.3% lost ≥15%
20% Patients
5%
Body weight
47.8% Patients
10%
Body weight
31.3% Patients
15%
Body weight
80.6% of pre-diabetic patients showed control of pre-diabetes, with HbA1c returning to normoglycemia (5.39 ± 0.27)
80.6%
patients showed control over pre-diabetes
HbA1c returned to normoglycemia
5.39 ± 0.27
The integration of digital technology and a multidisciplinary care team facilitated continuous monitoring and personalized care
The hybrid model proves to be more effective than traditional or digital-only approaches, underscoring the importance of patient engagement
Key findings
HbA1c
-2.19%
Improved
with more significant reductions seen in patients with higher baseline levels
Showed notable improvements in the case group
WEIGHT
BMI
LDL
TOTAL CHOLESTEROL
CVD
Patients with ≥11 digital interactions had a
-2.38% reduction in HbA1c
Patients with ≥11 digital interactions had a
-6.00 kg weight loss
The hybrid model, combining in-clinic visits and remote monitoring, led to more substantial clinical improvements than digital-only interventions
The study reveals significant improvements in glycemic control, insulin reduction, and weight loss when these therapies are integrated with a hybrid care model
Key findings
Prandial insulin
25.24%
Reduction
Basal insulin
29.16%
Reduction
HbA1c decreased from 8.28% to
6.95% over 3 months
Time in Range increased by
42.11% (p=0.018)
Overweight/obese patients lost an average of
5.64kg (p<0.001)
23
2024
The findings reveal significant improvements in mental well-being, as well as key health markers, emphasizing the potential of continuous, multidisciplinary care in managing both physical and emotional challenges associated with T2D
Key findings
Weight
-4.0 ± 5.3
Reduction
Waist Circumference
-4.74 ± 7.8
Reduction
HbA1c
1.00 ± 1.3
Reduction
Mental health improvements:
WHO-5
4%
Increased
PAID
-28%
Decreased
PHQ9
-29%
Dropped
Hybrid care models improve both biomarkers and quality of life, addressing mental health issues often overlooked in traditional care
The findings highlight the variations in these glycemic measures and their impact on diabetes management, especially when continuous remote monitoring is integrated with in-clinic visits
Key findings
86.4%
patients showed significant differences in HbA1c
86.4%
patients showed significant differences in GMI
Patients with Type 1 diabetes (T1D) demonstrated a higher proportion of variation between HbA1c and GMI compared to T2D and prediabetes
Time in range (TIR)
Average glucose (AG)
% coefficient of variation (% CV)
differed significantly across patient groups (p < 0.001)
Hybrid care, combining in-clinic and remote monitoring, offers immediate decision-making potential for diabetes management
25
2024
The results demonstrate that hybrid care significantly improves HbA1c, weight, and other health parameters, highlighting the benefit of continuous monitoring and remote engagement in diabetes management
Key findings
Hybrid care group showed a significant reduction of
-2.19% in HbA1c
Control group showed only a reduction of
-0.10% in HbA1c
-3.67%
Patients with a baseline HbA1c ≥ 9.0% in the hybrid group experienced a greater reduction in HbA1c than those in the control group
Patients with ≥11 remote engagements in the hybrid group showed
-2.38% reduction in HbA1c
Patients with ≥11 remote engagements in the hybrid group showed
-6.00 kg reduction in weight
26
2024
Conducted over six months, the program demonstrated significant improvements in weight loss, glycemic control, and cardiovascular health markers
Key findings
-7.89 kg (-8.24%)
weight loss
2.79 unit
BMI reduction
Remission of pre-diabetes in 80% of participants
HbA1c improved by
-2.38%
Improved fat mass and lipid profiles
Fat mass improved by
-5.46 kg (-12.5%)
Total cholesterol improved by
-16.08 mg/dL (-8.3%)
16.2%
greater weight reduction compared to STEP-2 trial
Findings reveal a strong association between better sleep quality and lower HbA1c levels, emphasizing the critical role of sleep in diabetes management
Key findings
65.6% of participants reported poor sleep quality
PSQI score
7.91 ± 4.5
Patients with better sleep quality had 17.4% lower HbA1c levels
Poor sleep
7.48%
Good sleep
6.18%
Shorter diabetes duration linked to poorer sleep quality
0-5 years
More likely to have a PSQI > 5
Gender differences in sleep quality
Males reported poorer sleep more frequently than females
The findings underscore the value of personalized, technology-driven engagement in enhancing outcomes and ROI in obesity treatment
Key findings
Statistically significant improvements in 3 months
-7.12 kg
weight loss
-2.51
BMI reduction
Higher engagement improves results
Patients with ≥10 interactions lost
-7.12 kg
Less engaged patients
-4.95 kg
Digital engagement distribution
Diet habits related inquiries
28.8%
Medication related inquiries
28.9%
Lifestyle messages
21.1%
CGM and tech issues
21.2%
Over a 12-month period, adherent patients demonstrated significant improvements in HbA1c, lipid profiles, and Time in Range (TIR), highlighting the limitations of traditional care and the benefits of a hyper-personalized, continuous approach
Key findings
HbA1c
-1.53%
Improved
Significant improvement in adherent patients compared to non-adherent (-0.18%, p=0.490)
Improved lipid profiles
Total Cholesterol
-16.6 mg/dL (p=0.034)
LDL
-18.65 mg/dL (p=0.006)
TIR exceeding ADA target
Adherent patients achieved a mean TIR of
80%
Hybrid model effectiveness
Demonstrated superior outcomes in poorly controlled T2D patients compared to traditional care.
The study demonstrates that patients using the Medtronic 780G AID under this model achieved significantly better glycemic outcomes than traditional self-care approaches
Key findings
15.58%
increase in Time in Range
Baseline : 59.17% → 74.75% post-intervention
1.72%
reduction in HbA1c
Baseline:
8.04% → 6.75%
8.91 unit
reduction in insulin requirements
Average daily insulin usage decreased significantly.
5-7x
more patient engagement
Hybrid model facilitated consistent education and behavioral improvements.
The results show significant improvements in glycemic control, weight, and blood pressure, with a notable difference between adherent and non-adherent patients, emphasizing the importance of continuous, personalized care
Key findings
Significant weight loss
-4.0 ± 5.3 kg
Reduced waist circumference
-4.74 ± 7.8 cm
HbA1c levels decreased by
-1.00 ± 1.3%
Systolic BP decreased by
-3.1 ± 13.1 mg/dL
Diastolic BP decreased by
-3.4 ± 9.9 mg/dL
Reductions in HbA1c
-1.53 ± 1.5%
Reductions in total cholesterol
-16.6 ± 50.3 mg/dL
Reductions in LDL
-18.65 ± 42.6 mg/dL
The study demonstrates the effectiveness of a personalized, continuous approach, highlighting its superiority over traditional care models
Accurate diagnosis through antibody testing and tailored management significantly improves patient outcomes by addressing the unique pathophysiology of LADA
Key findings
Average delay in LADA diagnosis was
5.72 years
with patients presenting at a mean age of 41.86 ± 5.73 years
Initial HbA1c levels averaged
11.10 ± 2.52%
indicating poor glycemic control at the time of misdiagnosis
HbA1c levels improved significantly within
3-6 months
Routine GAD antibody testing at GluCare led to accurate diagnosis and optimized management for all identified cases
This study evaluates the effectiveness of GluCare Health’s vertically integrated, hyper-personalized approach to managing type 1 diabetes and obesity using a combination of injectable Semaglutide, lifestyle modifications, and continuous remote data monitoring
Key findings
GluCare Health’s model resulted in an average weight loss of 7.4 kg (TWL), with 40% greater weight loss in 60% less time compared to previous studies
HbA1c dropped by
1.02%
Semaglutide plus adjunct meds improved weight and glucose in
18 patients
The GluCare Health platform’s integrated approach to continuous monitoring and data-driven insights led to enhanced patient compliance and outcomes
By combining continuous monitoring, behavioral interventions, and value-based contracts, the program demonstrated significant improvements in weight loss, metabolic parameters, and patient compliance
Key findings
7.88%
BMI reduction
8.13%
Weight reduction
HbA1c
-0.48%
(p=0.0001)
Total cholesterol
-12.25%
(p=0.0008)
LDL
-8.84%
(p=0.05)
ALT
-17.72%
(p=0.05)
Fat mass -15.2%
with minimal muscle loss
Average meals logged
87/month
High compliance with program criteria : All participants adhered to engagement, food logging, and data collection requirements.
Findings suggest significant BMI reduction and a potential effect on nonalcoholic fatty liver disease (NAFLD) parameters through continuous monitoring and data-driven care
Key findings
Significant BMI reduction over
3 months (p<0.001)
Each 1-unit BMI drop linked to
7.23 dB/m UAP reduction (p<0.05)
Liver stiffness changes were not statistically significant (p>0.1)
Moderately strong correlation (r=0.38) between BMI reduction and liver stiffness improvement
Findings indicate that integrating food monitoring and remote specialist guidance significantly improves BMI and HbA1c outcomes
Key findings
Opt-in group cut BMI by
2.89
Opt-out group cut BMI by
1.21 kg/m²
HbA1c fell
17%
in opt-in (p=0.002)
HbA1c fell
3.4%
in opt-out (p=0.117)
Opt-in participants logged an average of
71.29 food records/month
The combination of CMM and personalized dietary guidance enhanced outcomes over traditional care
Accurate diagnosis through antibody testing and tailored management significantly improves patient outcomes by addressing the unique pathophysiology of LADA
Key findings
Average delay in LADA diagnosis was
5.72 years
with patients presenting at a mean age of 41.86 ± 5.73 years
Initial HbA1c levels averaged
11.10 ± 2.52%
indicating poor glycemic control at the time of misdiagnosis
HbA1c levels improved significantly within
3-6 months
Routine GAD antibody testing at GluCare led to accurate diagnosis and optimized management for all identified cases
This study evaluates the effectiveness of GluCare Health’s vertically integrated, hyper-personalized approach to managing type 1 diabetes and obesity using a combination of injectable Semaglutide, lifestyle modifications, and continuous remote data monitoring
Key findings
GluCare Health’s model resulted in an average weight loss of 7.4 kg (TWL), with 40% greater weight loss in 60% less time compared to previous studies
HbA1c dropped by
1.02%
Semaglutide plus adjunct meds improved weight and glucose in
18 patients
The GluCare Health platform’s integrated approach to continuous monitoring and data-driven insights led to enhanced patient compliance and outcomes
By combining continuous monitoring, behavioral interventions, and value-based contracts, the program demonstrated significant improvements in weight loss, metabolic parameters, and patient compliance
Key findings
7.88%
BMI reduction
8.13%
Weight reduction
HbA1c
-0.48%
(p=0.0001)
Total cholesterol
-12.25%
(p=0.0008)
LDL
-8.84%
(p=0.05)
ALT
-17.72%
(p=0.05)
Fat mass -15.2%
with minimal muscle loss
Average meals logged
87/month
High compliance with program criteria : All participants adhered to engagement, food logging, and data collection requirements.
Findings suggest significant BMI reduction and a potential effect on nonalcoholic fatty liver disease (NAFLD) parameters through continuous monitoring and data-driven care
Key findings
Significant BMI reduction over
3 months (p<0.001)
Each 1-unit BMI drop linked to
7.23 dB/m UAP reduction (p<0.05)
Liver stiffness changes were not statistically significant (p>0.1)
Moderately strong correlation (r=0.38) between BMI reduction and liver stiffness improvement
Findings indicate that integrating food monitoring and remote specialist guidance significantly improves BMI and HbA1c outcomes
Key findings
Opt-in group cut BMI by
2.89
Opt-out group cut BMI by
1.21 kg/m²
HbA1c fell
17%
in opt-in (p=0.002)
HbA1c fell
3.4%
in opt-out (p=0.117)
Opt-in participants logged an average of
71.29 food records/month
The combination of CMM and personalized dietary guidance enhanced outcomes over traditional care
Accurate diagnosis through antibody testing and tailored management significantly improves patient outcomes by addressing the unique pathophysiology of LADA
Key findings
Average delay in LADA diagnosis was
5.72 years
with patients presenting at a mean age of 41.86 ± 5.73 years
Initial HbA1c levels averaged
11.10 ± 2.52%
indicating poor glycemic control at the time of misdiagnosis
HbA1c levels improved significantly within
3-6 months
Routine GAD antibody testing at GluCare led to accurate diagnosis and optimized management for all identified cases
This study evaluates the effectiveness of GluCare Health’s vertically integrated, hyper-personalized approach to managing type 1 diabetes and obesity using a combination of injectable Semaglutide, lifestyle modifications, and continuous remote data monitoring
Key findings
GluCare Health’s model resulted in an average weight loss of 7.4 kg (TWL), with 40% greater weight loss in 60% less time compared to previous studies
HbA1c dropped by
1.02%
Semaglutide plus adjunct meds improved weight and glucose in
18 patients
The GluCare Health platform’s integrated approach to continuous monitoring and data-driven insights led to enhanced patient compliance and outcomes
By combining continuous monitoring, behavioral interventions, and value-based contracts, the program demonstrated significant improvements in weight loss, metabolic parameters, and patient compliance
Key findings
7.88%
BMI reduction
8.13%
Weight reduction
HbA1c
-0.48%
(p=0.0001)
Total cholesterol
-12.25%
(p=0.0008)
LDL
-8.84%
(p=0.05)
ALT
-17.72%
(p=0.05)
Fat mass -15.2%
with minimal muscle loss
Average meals logged
87/month
High compliance with program criteria : All participants adhered to engagement, food logging, and data collection requirements.
Findings suggest significant BMI reduction and a potential effect on nonalcoholic fatty liver disease (NAFLD) parameters through continuous monitoring and data-driven care
Key findings
Significant BMI reduction over
3 months (p<0.001)
Each 1-unit BMI drop linked to
7.23 dB/m UAP reduction (p<0.05)
Liver stiffness changes were not statistically significant (p>0.1)
Moderately strong correlation (r=0.38) between BMI reduction and liver stiffness improvement
Findings indicate that integrating food monitoring and remote specialist guidance significantly improves BMI and HbA1c outcomes
Key findings
Opt-in group cut BMI by
2.89
Opt-out group cut BMI by
1.21 kg/m²
HbA1c fell
17%
in opt-in (p=0.002)
HbA1c fell
3.4%
in opt-out (p=0.117)
Opt-in participants logged an average of
71.29 food records/month
The combination of CMM and personalized dietary guidance enhanced outcomes over traditional care
By combining continuous monitoring, digital health solutions, and personalized care, the intervention demonstrated significant improvements in medication management and glycemic control within a short timeframe, providing a promising, cost-effective approach to chronic disease management
Key findings
Significant medication reduction within 3 months: Reduction observed as early as 3 months (p = 0.002) and sustained after one year (p = 0.02).
Improved medication adherence: Enhanced patient compliance through continuous monitoring and personalized engagement.
Cost-effective solution for T2D management: Reduction in medication use paired with improved clinical biomarkers, including glycated hemoglobin levels.
Hyper-personalized care model impact: Technology-enabled interventions delivered measurable benefits in a short timeframe.
Results demonstrate that Continuous Metabolic Monitoring significantly improves weight loss and BMI reduction, underscoring the importance of personalized, technology-driven interventions in obesity management
Key findings
8.5 kg
average weight loss in CMM patients
VS
3.4 kg
in traditional care (p < 0.05)
2.89
BMI reduction with CMM
VS
1.21
with usual care (p<0.05)
Improved patient engagement through food logging: Personalized dietary feedback facilitated better macronutrient understanding and adherence.
Holistic monitoring with CMM: Integrated tools like CGM, meal logging, and communication with healthcare providers enhanced patient outcomes.
This case report highlights the utility of Continuous Metabolic Monitoring (CMM) in managing type 2 diabetes and addressing acute complications such as hypoglycemia. The personalized and continuous engagement provided by the GluCare Health model enabled early detection and resolution of hypoglycemia, showcasing its potential to optimize diabetes care
Key findings
Low blood glucose values were detected via CGM and confirmed with home monitoring in week three of follow-up Tirzepatide was discontinued, and the patient maintained glycemic stability with empagliflozin/metformin, avoiding further hypoglycemia
The patient achieved
Time in range (TIR)
95%
Glucose management indicator (GMI)
5.9%
Real-time feedback on nutrition, exercise, and sleep through the GluCare platform was integral to managing the patient’s condition effectively
The GluCare Health model demonstrated significant GV reduction, highlighting the effectiveness of continuous, personalized care in managing prediabetes
Key findings
GV significantly decreased from
15.7% to 13.97% (p<0.01)
GV reduction was significant in the Dexcom G6 group
17.07% to 14.77% (p=0.03)
But not in the Freestyle Libre group
13.84% to 12.90% (p=0.06)
Females showed significant GV reduction
15.16% to 13.59% (p=0.01)
Males showed improvement but did not reach statistical significance
15.74% to 14.0% (p=0.06)
Personalized feedback on nutritional choices was integral to GV reduction
By shifting from episodic to continuous care, RCDM demonstrated significant improvements in glycemic control and other metabolic parameters over three months
Key findings
-2.38
point HbA1c reduction
RCDM opt-in group showed a significant decrease compared to the opt-out group (p < 0.001)
Improved BMI and lipid profile
BMI
Significant reduction (p = 0.046)
Triglycerides
Reduced significantly (p = 0.018)
Cardiovascular risk reduction: Marked improvement in CVD risk metrics for opt-in patients (p = 0.001)
RCDM effectiveness: Demonstrated superior results compared to standard episodic care at three months
The results highlight the advantages of integrating continuous monitoring, data-driven insights, and multidisciplinary engagement to enhance outcomes. Participants achieved significant weight loss and improved glycemic control in less time compared to traditional episodic care models
Key findings
7.4 kg
Total weight loss (TWL) Achieved in 60% less time compared to previous studies
40%
Greater weight loss Demonstrated improvement with Semaglutide and the hybrid care model
1.02%
HbA1c reduction Enhanced glycemic control alongside weight management
Improved patient engagement and adherence: The hybrid model drove better compliance with treatment and lifestyle modifications
Initial findings from a 3-month study indicate that patient engagement with GluCare led to significant improvements in metabolic health
Key findings
HbA1c
-2.14%
(p=0.00013)
LDL
-17.25%
(p=0.0071)
BMI
-4.55%
(p=0.0003)
Triglycerides
-18.52%
(p=0.0165)
Uric acid
-20.4%
(p=0.0052)
By combining continuous monitoring, digital health solutions, and personalized care, the intervention demonstrated significant improvements in medication management and glycemic control within a short timeframe, providing a promising, cost-effective approach to chronic disease management
Key findings
Significant medication reduction within 3 months: Reduction observed as early as 3 months (p = 0.002) and sustained after one year (p = 0.02).
Improved medication adherence: Enhanced patient compliance through continuous monitoring and personalized engagement.
Cost-effective solution for T2D management: Reduction in medication use paired with improved clinical biomarkers, including glycated hemoglobin levels.
Hyper-personalized care model impact: Technology-enabled interventions delivered measurable benefits in a short timeframe.
Results demonstrate that Continuous Metabolic Monitoring significantly improves weight loss and BMI reduction, underscoring the importance of personalized, technology-driven interventions in obesity management
Key findings
8.5 kg
average weight loss in CMM patients
VS
3.4 kg
in traditional care (p < 0.05)
2.89
BMI reduction with CMM
VS
1.21
with usual care (p<0.05)
Improved patient engagement through food logging: Personalized dietary feedback facilitated better macronutrient understanding and adherence.
Holistic monitoring with CMM: Integrated tools like CGM, meal logging, and communication with healthcare providers enhanced patient outcomes.
This case report highlights the utility of Continuous Metabolic Monitoring (CMM) in managing type 2 diabetes and addressing acute complications such as hypoglycemia. The personalized and continuous engagement provided by the GluCare Health model enabled early detection and resolution of hypoglycemia, showcasing its potential to optimize diabetes care
Key findings
Low blood glucose values were detected via CGM and confirmed with home monitoring in week three of follow-up Tirzepatide was discontinued, and the patient maintained glycemic stability with empagliflozin/metformin, avoiding further hypoglycemia
The patient achieved
Time in range (TIR)
95%
Glucose management indicator (GMI)
5.9%
Real-time feedback on nutrition, exercise, and sleep through the GluCare platform was integral to managing the patient’s condition effectively
The GluCare Health model demonstrated significant GV reduction, highlighting the effectiveness of continuous, personalized care in managing prediabetes
Key findings
GV significantly decreased from
15.7% to 13.97% (p<0.01)
GV reduction was significant in the Dexcom G6 group
17.07% to 14.77% (p=0.03)
But not in the Freestyle Libre group
13.84% to 12.90% (p=0.06)
Females showed significant GV reduction
15.16% to 13.59% (p=0.01)
Males showed improvement but did not reach statistical significance
15.74% to 14.0% (p=0.06)
Personalized feedback on nutritional choices was integral to GV reduction
By shifting from episodic to continuous care, RCDM demonstrated significant improvements in glycemic control and other metabolic parameters over three months
Key findings
-2.38
point HbA1c reduction
RCDM opt-in group showed a significant decrease compared to the opt-out group (p < 0.001)
Improved BMI and lipid profile
BMI
Significant reduction (p = 0.046)
Triglycerides
Reduced significantly (p = 0.018)
Cardiovascular risk reduction: Marked improvement in CVD risk metrics for opt-in patients (p = 0.001)
RCDM effectiveness: Demonstrated superior results compared to standard episodic care at three months
The results highlight the advantages of integrating continuous monitoring, data-driven insights, and multidisciplinary engagement to enhance outcomes. Participants achieved significant weight loss and improved glycemic control in less time compared to traditional episodic care models
Key findings
7.4 kg
Total weight loss (TWL) Achieved in 60% less time compared to previous studies
40%
Greater weight loss Demonstrated improvement with Semaglutide and the hybrid care model
1.02%
HbA1c reduction Enhanced glycemic control alongside weight management
Improved patient engagement and adherence: The hybrid model drove better compliance with treatment and lifestyle modifications
Initial findings from a 3-month study indicate that patient engagement with GluCare led to significant improvements in metabolic health
Key findings
HbA1c
-2.14%
(p=0.00013)
LDL
-17.25%
(p=0.0071)
BMI
-4.55%
(p=0.0003)
Triglycerides
-18.52%
(p=0.0165)
Uric acid
-20.4%
(p=0.0052)
By combining continuous monitoring, digital health solutions, and personalized care, the intervention demonstrated significant improvements in medication management and glycemic control within a short timeframe, providing a promising, cost-effective approach to chronic disease management
Key findings
Significant medication reduction within 3 months: Reduction observed as early as 3 months (p = 0.002) and sustained after one year (p = 0.02).
Improved medication adherence: Enhanced patient compliance through continuous monitoring and personalized engagement.
Cost-effective solution for T2D management: Reduction in medication use paired with improved clinical biomarkers, including glycated hemoglobin levels.
Hyper-personalized care model impact: Technology-enabled interventions delivered measurable benefits in a short timeframe.
Results demonstrate that Continuous Metabolic Monitoring significantly improves weight loss and BMI reduction, underscoring the importance of personalized, technology-driven interventions in obesity management
Key findings
8.5 kg
average weight loss in CMM patients
VS
3.4 kg
in traditional care (p < 0.05)
2.89
BMI reduction with CMM
VS
1.21
with usual care (p<0.05)
Improved patient engagement through food logging: Personalized dietary feedback facilitated better macronutrient understanding and adherence.
Holistic monitoring with CMM: Integrated tools like CGM, meal logging, and communication with healthcare providers enhanced patient outcomes.
This case report highlights the utility of Continuous Metabolic Monitoring (CMM) in managing type 2 diabetes and addressing acute complications such as hypoglycemia. The personalized and continuous engagement provided by the GluCare Health model enabled early detection and resolution of hypoglycemia, showcasing its potential to optimize diabetes care
Key findings
Low blood glucose values were detected via CGM and confirmed with home monitoring in week three of follow-up Tirzepatide was discontinued, and the patient maintained glycemic stability with empagliflozin/metformin, avoiding further hypoglycemia
The patient achieved
Time in range (TIR)
95%
Glucose management indicator (GMI)
5.9%
Real-time feedback on nutrition, exercise, and sleep through the GluCare platform was integral to managing the patient’s condition effectively
The GluCare Health model demonstrated significant GV reduction, highlighting the effectiveness of continuous, personalized care in managing prediabetes
Key findings
GV significantly decreased from
15.7% to 13.97% (p<0.01)
GV reduction was significant in the Dexcom G6 group
17.07% to 14.77% (p=0.03)
But not in the Freestyle Libre group
13.84% to 12.90% (p=0.06)
Females showed significant GV reduction
15.16% to 13.59% (p=0.01)
Males showed improvement but did not reach statistical significance
15.74% to 14.0% (p=0.06)
Personalized feedback on nutritional choices was integral to GV reduction
By shifting from episodic to continuous care, RCDM demonstrated significant improvements in glycemic control and other metabolic parameters over three months
Key findings
-2.38
point HbA1c reduction
RCDM opt-in group showed a significant decrease compared to the opt-out group (p < 0.001)
Improved BMI and lipid profile
BMI
Significant reduction (p = 0.046)
Triglycerides
Reduced significantly (p = 0.018)
Cardiovascular risk reduction: Marked improvement in CVD risk metrics for opt-in patients (p = 0.001)
RCDM effectiveness: Demonstrated superior results compared to standard episodic care at three months
The results highlight the advantages of integrating continuous monitoring, data-driven insights, and multidisciplinary engagement to enhance outcomes. Participants achieved significant weight loss and improved glycemic control in less time compared to traditional episodic care models
Key findings
7.4 kg
Total weight loss (TWL) Achieved in 60% less time compared to previous studies
40%
Greater weight loss Demonstrated improvement with Semaglutide and the hybrid care model
1.02%
HbA1c reduction Enhanced glycemic control alongside weight management
Improved patient engagement and adherence: The hybrid model drove better compliance with treatment and lifestyle modifications
Initial findings from a 3-month study indicate that patient engagement with GluCare led to significant improvements in metabolic health
Key findings
HbA1c
-2.14%
(p=0.00013)
LDL
-17.25%
(p=0.0071)
BMI
-4.55%
(p=0.0003)
Triglycerides
-18.52%
(p=0.0165)
Uric acid
-20.4%
(p=0.0052)
Locations
Locations
Locations
UAE
UK (coming soon)
1 Knightsbridge, Unit A
SW1X 7LX London
1 Knightsbridge, Unit A SW1X 7LX London
Contact Details
Contact Details
Contact Details
Newsletter
Newsletter
Newsletter
Subscribe to receive marketing updates. Opt out anytime. See our Privacy Policy.
Subscribe to receive marketing updates. Opt out anytime. See our Privacy Policy.
GluCare Integrated Diabetes Center L.L.C. (Trading as Metabolic) | Copyright © Metabolic Health. All Rights Reserved. | MOHAP License Number: MAW5UUEI-201025
GluCare Integrated Diabetes Center L.L.C. (Trading as Metabolic) | Copyright © Metabolic Health. All Rights Reserved. | MOHAP License Number: MAW5UUEI-201025
