specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 012

metric: cv

question: What is the glycemic variability (CV%) for subject 012 in the Big IDEAs dataset over week 5 (2020-05-07 to 2020-05-13)?

answer:
Window: week 5 (2020-05-07 to 2020-05-13) (2020-05-07 00:02 to 2020-05-11 09:31, 1,233 EGV readings spanning 105.5 hours). Coefficient of variation (CV%) was 14.10%, computed as standard deviation / mean x 100. SD = 17.6 mg/dL, mean = 125.1 mg/dL.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 003

metric: gmi

question: What is the Glucose Management Indicator (GMI) for subject 003 in the Big IDEAs dataset over day 2020-02-24?

answer:
Window: day 2020-02-24 (2020-02-24 00:01 to 2020-02-24 23:56, 288 EGV readings spanning 23.9 hours). GMI was 5.87%, computed as 3.31 + 0.02392 x mean_mgdl, where mean_mgdl = 107.1.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet. GMI formula: Bergenstal et al. (2018), "Glucose Management Indicator (GMI): A New Term for Estimating A1C From Continuous Glucose Monitoring," Diabetes Care, 41(11): 2275-2280.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 001

metric: mean

question: What is the average glucose for subject 001 in the Big IDEAs dataset over day 2020-02-19?

answer:
Window: day 2020-02-19 (2020-02-19 00:03 to 2020-02-19 23:38, 284 EGV readings spanning 23.6 hours). Average glucose was 120.3 mg/dL (standard deviation 12.8 mg/dL).

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 016

question: What is the daytime vs nighttime average BG for subject 016 in the Big IDEAs dataset over day 2020-07-19?

answer:
Window: day 2020-07-19 (2020-07-19 00:03 to 2020-07-19 23:58, 288 EGV readings spanning 23.9 hours). Daytime average BG (06:00-21:59) was 101.7 mg/dL (n=192 readings). Nighttime average BG (22:00-05:59) was 106.7 mg/dL (n=96 readings). Daytime minus nighttime = -5.0 mg/dL.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 006

metric: mean

question: What is the average glucose for subject 006 in the Big IDEAs dataset over day 2020-03-04?

answer:
Window: day 2020-03-04 (2020-03-04 00:03 to 2020-03-04 23:58, 288 EGV readings spanning 23.9 hours). Average glucose was 122.9 mg/dL (standard deviation 27.8 mg/dL).

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 005

metric: cv

question: What is the glycemic variability (CV%) for subject 005 in the Big IDEAs dataset over week 4 (2020-03-01 to 2020-03-07)?

answer:
Window: week 4 (2020-03-01 to 2020-03-07) (2020-03-01 00:00 to 2020-03-07 11:46, 1,856 EGV readings spanning 155.8 hours). Coefficient of variation (CV%) was 13.60%, computed as standard deviation / mean x 100. SD = 14.0 mg/dL, mean = 102.6 mg/dL.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 005

metric: tbr

question: What is the time below range (<70 mg/dL) for subject 005 in the Big IDEAs dataset over day 2020-03-05?

answer:
Window: day 2020-03-05 (2020-03-05 00:01 to 2020-03-05 23:56, 288 EGV readings spanning 23.9 hours). Time below range (<70 mg/dL) was 0.0% of CGM readings.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 003

metric: cv

question: What is the glycemic variability (CV%) for subject 003 in the Big IDEAs dataset over week 2 (2020-02-23 to 2020-02-29)?

answer:
Window: week 2 (2020-02-23 to 2020-02-29) (2020-02-23 00:01 to 2020-02-29 23:56, 2,004 EGV readings spanning 167.9 hours). Coefficient of variation (CV%) was 16.17%, computed as standard deviation / mean x 100. SD = 17.3 mg/dL, mean = 107.1 mg/dL.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 016

metric: gmi

question: What is the Glucose Management Indicator (GMI) for subject 016 in the Big IDEAs dataset over day 2020-07-18?

answer:
Window: day 2020-07-18 (2020-07-18 00:03 to 2020-07-18 23:58, 284 EGV readings spanning 23.9 hours). GMI was 5.83%, computed as 3.31 + 0.02392 x mean_mgdl, where mean_mgdl = 105.3.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet. GMI formula: Bergenstal et al. (2018), "Glucose Management Indicator (GMI): A New Term for Estimating A1C From Continuous Glucose Monitoring," Diabetes Care, 41(11): 2275-2280.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 003

window_label: the full subject period

metric: tbr

question: What is the time below range (<70 mg/dL) for subject 003 in the Big IDEAs dataset over the full subject period?

answer:
Window: the full subject period (2020-02-22 10:51 to 2020-03-01 11:36, 2,302 EGV readings spanning 192.7 hours). Time below range (<70 mg/dL) was 0.7% of CGM readings.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 014

metric: tbr

question: What is the time below range (<70 mg/dL) for subject 014 in the Big IDEAs dataset over week 2 (2020-06-06 to 2020-06-12)?

answer:
Window: week 2 (2020-06-06 to 2020-06-12) (2020-06-06 00:03 to 2020-06-12 23:57, 2,016 EGV readings spanning 167.9 hours). Time below range (<70 mg/dL) was 0.0% of CGM readings.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 016

metric: gmi

question: What is the Glucose Management Indicator (GMI) for subject 016 in the Big IDEAs dataset over day 2020-07-19?

answer:
Window: day 2020-07-19 (2020-07-19 00:03 to 2020-07-19 23:58, 288 EGV readings spanning 23.9 hours). GMI was 5.78%, computed as 3.31 + 0.02392 x mean_mgdl, where mean_mgdl = 103.4.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet. GMI formula: Bergenstal et al. (2018), "Glucose Management Indicator (GMI): A New Term for Estimating A1C From Continuous Glucose Monitoring," Diabetes Care, 41(11): 2275-2280.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 011

metric: gmi

question: What is the Glucose Management Indicator (GMI) for subject 011 in the Big IDEAs dataset over day 2020-04-11?

answer:
Window: day 2020-04-11 (2020-04-11 00:01 to 2020-04-11 23:55, 288 EGV readings spanning 23.9 hours). GMI was 6.08%, computed as 3.31 + 0.02392 x mean_mgdl, where mean_mgdl = 115.6.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet. GMI formula: Bergenstal et al. (2018), "Glucose Management Indicator (GMI): A New Term for Estimating A1C From Continuous Glucose Monitoring," Diabetes Care, 41(11): 2275-2280.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 002

metric: tar

question: What is the time above range (>180 mg/dL) for subject 002 in the Big IDEAs dataset over week 1 (2020-02-21 to 2020-02-27)?

answer:
Window: week 1 (2020-02-21 to 2020-02-27) (2020-02-21 11:08 to 2020-02-27 23:58, 1,715 EGV readings spanning 156.8 hours). Time above range (>180 mg/dL) was 1.5% of CGM readings.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 012

window_label: the full subject period

metric: tbr

question: What is the time below range (<70 mg/dL) for subject 012 in the Big IDEAs dataset over the full subject period?

answer:
Window: the full subject period (2020-05-03 17:52 to 2020-05-11 09:31, 2,169 EGV readings spanning 183.7 hours). Time below range (<70 mg/dL) was 0.0% of CGM readings.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 008

metric: tir

question: What is the time in range (70-180 mg/dL) for subject 008 in the Big IDEAs dataset over week 6 (2020-03-19 to 2020-03-25)?

answer:
Window: week 6 (2020-03-19 to 2020-03-25) (2020-03-19 00:04 to 2020-03-23 11:39, 1,263 EGV readings spanning 107.6 hours). Time in range (70-180 mg/dL) was 100.0% of CGM readings.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 001

metric: tbr

question: What is the time below range (<70 mg/dL) for subject 001 in the Big IDEAs dataset over day 2020-02-21?

answer:
Window: day 2020-02-21 (2020-02-21 00:03 to 2020-02-21 23:58, 288 EGV readings spanning 23.9 hours). Time below range (<70 mg/dL) was 0.0% of CGM readings.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 001

metric: cv

question: What is the glycemic variability (CV%) for subject 001 in the Big IDEAs dataset over day 2020-02-20?

answer:
Window: day 2020-02-20 (2020-02-20 02:48 to 2020-02-20 23:58, 255 EGV readings spanning 21.2 hours). Coefficient of variation (CV%) was 13.93%, computed as standard deviation / mean x 100. SD = 15.3 mg/dL, mean = 110.0 mg/dL.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 002

metric: dawn

question: What is the dawn phenomenon delta (avg 5-7am minus avg 0-3am) for subject 002 in the Big IDEAs dataset over week 2 (2020-02-22 to 2020-02-28)?

answer:
Window: week 2 (2020-02-22 to 2020-02-28) (2020-02-22 00:03 to 2020-02-28 23:58, 1,848 EGV readings spanning 167.9 hours). Average BG 05:00-06:59 was 150.9 mg/dL (n=144 readings). Average BG 00:00-02:59 was 131.9 mg/dL (n=216 readings). Dawn delta = 18.9 mg/dL (positive = dawn rise).

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 005

metric: dawn

question: What is the dawn phenomenon delta (avg 5-7am minus avg 0-3am) for subject 005 in the Big IDEAs dataset over day 2020-03-03?

answer:
Window: day 2020-03-03 (2020-03-03 00:04 to 2020-03-03 23:49, 286 EGV readings spanning 23.7 hours). Average BG 05:00-06:59 was 114.2 mg/dL (n=24 readings). Average BG 00:00-02:59 was 111.6 mg/dL (n=36 readings). Dawn delta = 2.5 mg/dL (positive = dawn rise).

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 005

metric: gmi

question: What is the Glucose Management Indicator (GMI) for subject 005 in the Big IDEAs dataset over week 1 (2020-02-27 to 2020-03-04)?

answer:
Window: week 1 (2020-02-27 to 2020-03-04) (2020-02-27 13:30 to 2020-03-04 23:56, 1,840 EGV readings spanning 154.4 hours). GMI was 5.86%, computed as 3.31 + 0.02392 x mean_mgdl, where mean_mgdl = 106.5.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet. GMI formula: Bergenstal et al. (2018), "Glucose Management Indicator (GMI): A New Term for Estimating A1C From Continuous Glucose Monitoring," Diabetes Care, 41(11): 2275-2280.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 010

metric: tar

question: What is the time above range (>180 mg/dL) for subject 010 in the Big IDEAs dataset over week 1 (2020-03-22 to 2020-03-28)?

answer:
Window: week 1 (2020-03-22 to 2020-03-28) (2020-03-22 11:24 to 2020-03-28 21:09, 1,767 EGV readings spanning 153.7 hours). Time above range (>180 mg/dL) was 3.1% of CGM readings.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 012

metric: tir

question: What is the time in range (70-180 mg/dL) for subject 012 in the Big IDEAs dataset over day 2020-05-06?

answer:
Window: day 2020-05-06 (2020-05-06 00:02 to 2020-05-06 23:57, 288 EGV readings spanning 23.9 hours). Time in range (70-180 mg/dL) was 91.3% of CGM readings.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 001

question: What is the daytime vs nighttime average BG for subject 001 in the Big IDEAs dataset over day 2020-02-19?

answer:
Window: day 2020-02-19 (2020-02-19 00:03 to 2020-02-19 23:38, 284 EGV readings spanning 23.6 hours). Daytime average BG (06:00-21:59) was 120.8 mg/dL (n=192 readings). Nighttime average BG (22:00-05:59) was 119.2 mg/dL (n=92 readings). Daytime minus nighttime = 1.6 mg/dL.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 011

metric: cv

question: What is the glycemic variability (CV%) for subject 011 in the Big IDEAs dataset over day 2020-04-15?

answer:
Window: day 2020-04-15 (2020-04-15 00:00 to 2020-04-15 23:55, 288 EGV readings spanning 23.9 hours). Coefficient of variation (CV%) was 18.44%, computed as standard deviation / mean x 100. SD = 23.6 mg/dL, mean = 128.2 mg/dL.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 005

window_label: the full subject period

metric: dawn

question: What is the dawn phenomenon delta (avg 5-7am minus avg 0-3am) for subject 005 in the Big IDEAs dataset over the full subject period?

answer:
Window: the full subject period (2020-02-27 13:30 to 2020-03-07 11:46, 2,558 EGV readings spanning 214.3 hours). Average BG 05:00-06:59 was 110.8 mg/dL (n=216 readings). Average BG 00:00-02:59 was 113.3 mg/dL (n=311 readings). Dawn delta = -2.5 mg/dL (positive = dawn rise).

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 015

metric: tar

question: What is the time above range (>180 mg/dL) for subject 015 in the Big IDEAs dataset over week 2 (2020-07-20 to 2020-07-26)?

answer:
Window: week 2 (2020-07-20 to 2020-07-26) (2020-07-20 00:03 to 2020-07-26 23:58, 1,468 EGV readings spanning 167.9 hours). Time above range (>180 mg/dL) was 0.0% of CGM readings.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 014

metric: tar

question: What is the time above range (>180 mg/dL) for subject 014 in the Big IDEAs dataset over day 2020-06-07?

answer:
Window: day 2020-06-07 (2020-06-07 00:03 to 2020-06-07 23:58, 288 EGV readings spanning 23.9 hours). Time above range (>180 mg/dL) was 0.0% of CGM readings.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 015

metric: gmi

question: What is the Glucose Management Indicator (GMI) for subject 015 in the Big IDEAs dataset over day 2020-07-22?

answer:
Window: day 2020-07-22 (2020-07-22 00:03 to 2020-07-22 23:58, 288 EGV readings spanning 23.9 hours). GMI was 5.94%, computed as 3.31 + 0.02392 x mean_mgdl, where mean_mgdl = 110.0.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet. GMI formula: Bergenstal et al. (2018), "Glucose Management Indicator (GMI): A New Term for Estimating A1C From Continuous Glucose Monitoring," Diabetes Care, 41(11): 2275-2280.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 008

metric: mean

question: What is the average glucose for subject 008 in the Big IDEAs dataset over week 5 (2020-03-18 to 2020-03-24)?

answer:
Window: week 5 (2020-03-18 to 2020-03-24) (2020-03-18 00:04 to 2020-03-23 11:39, 1,551 EGV readings spanning 131.6 hours). Average glucose was 116.3 mg/dL (standard deviation 14.8 mg/dL).

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 005

metric: mean

question: What is the average glucose for subject 005 in the Big IDEAs dataset over day 2020-03-04?

answer:
Window: day 2020-03-04 (2020-03-04 01:06 to 2020-03-04 23:56, 275 EGV readings spanning 22.8 hours). Average glucose was 109.5 mg/dL (standard deviation 13.6 mg/dL).

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 009

metric: dawn

question: What is the dawn phenomenon delta (avg 5-7am minus avg 0-3am) for subject 009 in the Big IDEAs dataset over day 2020-03-26?

answer:
Window: day 2020-03-26 (2020-03-26 00:01 to 2020-03-26 23:56, 288 EGV readings spanning 23.9 hours). Average BG 05:00-06:59 was 127.1 mg/dL (n=24 readings). Average BG 00:00-02:59 was 131.5 mg/dL (n=36 readings). Dawn delta = -4.4 mg/dL (positive = dawn rise).

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 011

question: What is the daytime vs nighttime average BG for subject 011 in the Big IDEAs dataset over week 7 (2020-04-12 to 2020-04-18)?

answer:
Window: week 7 (2020-04-12 to 2020-04-18) (2020-04-12 00:00 to 2020-04-16 07:20, 1,241 EGV readings spanning 103.3 hours). Daytime average BG (06:00-21:59) was 118.4 mg/dL (n=785 readings). Nighttime average BG (22:00-05:59) was 132.7 mg/dL (n=456 readings). Daytime minus nighttime = -14.3 mg/dL.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 006

metric: tbr

question: What is the time below range (<70 mg/dL) for subject 006 in the Big IDEAs dataset over day 2020-03-05?

answer:
Window: day 2020-03-05 (2020-03-05 00:03 to 2020-03-05 23:58, 288 EGV readings spanning 23.9 hours). Time below range (<70 mg/dL) was 0.0% of CGM readings.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 001

metric: cv

question: What is the glycemic variability (CV%) for subject 001 in the Big IDEAs dataset over day 2020-02-14?

answer:
Window: day 2020-02-14 (2020-02-14 00:03 to 2020-02-14 23:58, 288 EGV readings spanning 23.9 hours). Coefficient of variation (CV%) was 15.53%, computed as standard deviation / mean x 100. SD = 15.5 mg/dL, mean = 100.0 mg/dL.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 016

metric: tar

question: What is the time above range (>180 mg/dL) for subject 016 in the Big IDEAs dataset over week 1 (2020-07-16 to 2020-07-22)?

answer:
Window: week 1 (2020-07-16 to 2020-07-22) (2020-07-16 10:43 to 2020-07-22 23:58, 1,865 EGV readings spanning 157.2 hours). Time above range (>180 mg/dL) was 0.0% of CGM readings.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 004

question: What is the daytime vs nighttime average BG for subject 004 in the Big IDEAs dataset over day 2020-02-28?

answer:
Window: day 2020-02-28 (2020-02-28 00:01 to 2020-02-28 23:56, 288 EGV readings spanning 23.9 hours). Daytime average BG (06:00-21:59) was 110.7 mg/dL (n=192 readings). Nighttime average BG (22:00-05:59) was 110.4 mg/dL (n=96 readings). Daytime minus nighttime = 0.3 mg/dL.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 015

metric: cv

question: What is the glycemic variability (CV%) for subject 015 in the Big IDEAs dataset over day 2020-07-21?

answer:
Window: day 2020-07-21 (2020-07-21 00:03 to 2020-07-21 23:58, 255 EGV readings spanning 23.9 hours). Coefficient of variation (CV%) was 12.87%, computed as standard deviation / mean x 100. SD = 14.4 mg/dL, mean = 111.6 mg/dL.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 008

metric: tbr

question: What is the time below range (<70 mg/dL) for subject 008 in the Big IDEAs dataset over week 6 (2020-03-19 to 2020-03-25)?

answer:
Window: week 6 (2020-03-19 to 2020-03-25) (2020-03-19 00:04 to 2020-03-23 11:39, 1,263 EGV readings spanning 107.6 hours). Time below range (<70 mg/dL) was 0.0% of CGM readings.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 007

metric: tir

question: What is the time in range (70-180 mg/dL) for subject 007 in the Big IDEAs dataset over day 2020-03-20?

answer:
Window: day 2020-03-20 (2020-03-20 00:02 to 2020-03-20 23:57, 288 EGV readings spanning 23.9 hours). Time in range (70-180 mg/dL) was 94.4% of CGM readings.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 004

window_label: the full subject period

question: What is the daytime vs nighttime average BG for subject 004 in the Big IDEAs dataset over the full subject period?

answer:
Window: the full subject period (2020-02-27 10:51 to 2020-03-06 06:51, 2,164 EGV readings spanning 188.0 hours). Daytime average BG (06:00-21:59) was 110.4 mg/dL (n=1,484 readings). Nighttime average BG (22:00-05:59) was 117.6 mg/dL (n=680 readings). Daytime minus nighttime = -7.3 mg/dL.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 005

metric: tir

question: What is the time in range (70-180 mg/dL) for subject 005 in the Big IDEAs dataset over day 2020-03-03?

answer:
Window: day 2020-03-03 (2020-03-03 00:04 to 2020-03-03 23:49, 286 EGV readings spanning 23.7 hours). Time in range (70-180 mg/dL) was 100.0% of CGM readings.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 016

metric: mean

question: What is the average glucose for subject 016 in the Big IDEAs dataset over week 2 (2020-07-17 to 2020-07-23)?

answer:
Window: week 2 (2020-07-17 to 2020-07-23) (2020-07-17 00:03 to 2020-07-23 23:58, 1,993 EGV readings spanning 167.9 hours). Average glucose was 104.8 mg/dL (standard deviation 16.8 mg/dL).

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 007

metric: tbr

question: What is the time below range (<70 mg/dL) for subject 007 in the Big IDEAs dataset over day 2020-03-19?

answer:
Window: day 2020-03-19 (2020-03-19 00:02 to 2020-03-19 23:57, 288 EGV readings spanning 23.9 hours). Time below range (<70 mg/dL) was 4.5% of CGM readings.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 002

metric: cv

question: What is the glycemic variability (CV%) for subject 002 in the Big IDEAs dataset over week 2 (2020-02-22 to 2020-02-28)?

answer:
Window: week 2 (2020-02-22 to 2020-02-28) (2020-02-22 00:03 to 2020-02-28 23:58, 1,848 EGV readings spanning 167.9 hours). Coefficient of variation (CV%) was 15.79%, computed as standard deviation / mean x 100. SD = 20.4 mg/dL, mean = 129.3 mg/dL.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 008

metric: tar

question: What is the time above range (>180 mg/dL) for subject 008 in the Big IDEAs dataset over day 2020-03-17?

answer:
Window: day 2020-03-17 (2020-03-17 00:04 to 2020-03-17 23:59, 275 EGV readings spanning 23.9 hours). Time above range (>180 mg/dL) was 0.0% of CGM readings.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 002

question: What is the daytime vs nighttime average BG for subject 002 in the Big IDEAs dataset over week 3 (2020-02-23 to 2020-02-29)?

answer:
Window: week 3 (2020-02-23 to 2020-02-29) (2020-02-23 00:03 to 2020-02-29 09:38, 1,676 EGV readings spanning 153.6 hours). Daytime average BG (06:00-21:59) was 128.3 mg/dL (n=1,116 readings). Nighttime average BG (22:00-05:59) was 136.8 mg/dL (n=560 readings). Daytime minus nighttime = -8.5 mg/dL.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 007

metric: dawn

question: What is the dawn phenomenon delta (avg 5-7am minus avg 0-3am) for subject 007 in the Big IDEAs dataset over week 3 (2020-03-16 to 2020-03-22)?

answer:
Window: week 3 (2020-03-16 to 2020-03-22) (2020-03-16 00:02 to 2020-03-22 11:06, 1,783 EGV readings spanning 155.1 hours). Average BG 05:00-06:59 was 91.4 mg/dL (n=144 readings). Average BG 00:00-02:59 was 93.3 mg/dL (n=252 readings). Dawn delta = -1.9 mg/dL (positive = dawn rise).

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 007

metric: tir

question: What is the time in range (70-180 mg/dL) for subject 007 in the Big IDEAs dataset over day 2020-03-21?

answer:
Window: day 2020-03-21 (2020-03-21 00:02 to 2020-03-21 23:56, 288 EGV readings spanning 23.9 hours). Time in range (70-180 mg/dL) was 87.2% of CGM readings.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.


specialty: diabetic-nutrition

domain: diabetes

tier: royal-jelly

bucket: bigideas-cgm-pattern

citation: Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet.

subject: 012

metric: gmi

question: What is the Glucose Management Indicator (GMI) for subject 012 in the Big IDEAs dataset over day 2020-05-06?

answer:
Window: day 2020-05-06 (2020-05-06 00:02 to 2020-05-06 23:57, 288 EGV readings spanning 23.9 hours). GMI was 6.24%, computed as 3.31 + 0.02392 x mean_mgdl, where mean_mgdl = 122.4.

Data from the Big IDEAs Lab Glycemic Variability Database (PhysioNet). Cho et al., Big IDEAs Lab Glycemic Variability Database, PhysioNet. GMI formula: Bergenstal et al. (2018), "Glucose Management Indicator (GMI): A New Term for Estimating A1C From Continuous Glucose Monitoring," Diabetes Care, 41(11): 2275-2280.

This describes computed metrics from one subject in a published research dataset. It is not advice. Your individual CGM metrics, and what they mean for you, are a conversation with your healthcare provider.