real time continuous glucose monitoring device Search Results


continuous glucose monitor (cgm) device  (Meiqi Trading Co)
90
Meiqi Trading Co continuous glucose monitor (cgm) device
(A) Flow diagram of study design and participating patients. (B) Changes of daily insulin dose. Data of the same subject at different follow‐up time points are connected by gray lines. False discovery rate (represented as q ‐value) was calculated using repeated‐measures one‐way analysis of variance corrected by Benjamini and Hochberg method for multiple comparisons, n = 14. (C) Postprandial glucose excursions expressed as percentage of baseline during steamed bun meal test (SBMT). All data are represented as mean ± SEM, * q < 0.05 by mixed‐effects model for repeated measures corrected by Benjamini and Hochberg method, n = 9–12. (D–H) Changes of glycemic variability (GV) indices at 1 week (T1W) calculated using continuous glucose monitor <t>(CGM)</t> data: (D) MAGE, (E) SDBG, (F) BG > 11.1 mmol/L, (G) LAGE, and (H) MBG. † p < .05 by paired t test (two‐tailed), n = 14. (I–J) Changes of GV indices at T1W, 1 month (T1M), and 3 months (T3M) calculated using self‐monitoring of blood glucose data: (I) TIR and (J) hypoglycemic episodes. $ q < 0.05 as stated in (B); # q < 0.05 by repeated‐measures Friedman test corrected by Benjamini and Hochberg method, n = 14. (K) Representative CGM 24‐h glucose profiles demonstrating improved glycemic stability in two patients <t>by</t> <t>WMT.</t> Values of some GV indices were the same for different participants. Thus, both points and connecting lines overlapped with each other, exhibiting fewer than 14 points. LAGE, largest amplitude of glycemic excursions; MAGE, mean amplitude of glycemic excursion; MBG, mean blood glucose; SDBG, SD of blood glucose; TIR, time in range; WMT, washed microbiota transplantation.
Continuous Glucose Monitor (Cgm) Device, supplied by Meiqi Trading Co, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/real+time+continuous+glucose+monitoring+device/continuous+glucose+monitor++cgm++device/pmc10859319-55-9-14
Average 90 stars, based on 1 article reviews
continuous glucose monitor (cgm) device - by Bioz Stars, 2026-09
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regulated devices like wearable continuous glucose monitors  (RenderX Inc)
90
RenderX Inc regulated devices like wearable continuous glucose monitors
(A) Flow diagram of study design and participating patients. (B) Changes of daily insulin dose. Data of the same subject at different follow‐up time points are connected by gray lines. False discovery rate (represented as q ‐value) was calculated using repeated‐measures one‐way analysis of variance corrected by Benjamini and Hochberg method for multiple comparisons, n = 14. (C) Postprandial glucose excursions expressed as percentage of baseline during steamed bun meal test (SBMT). All data are represented as mean ± SEM, * q < 0.05 by mixed‐effects model for repeated measures corrected by Benjamini and Hochberg method, n = 9–12. (D–H) Changes of glycemic variability (GV) indices at 1 week (T1W) calculated using continuous glucose monitor <t>(CGM)</t> data: (D) MAGE, (E) SDBG, (F) BG > 11.1 mmol/L, (G) LAGE, and (H) MBG. † p < .05 by paired t test (two‐tailed), n = 14. (I–J) Changes of GV indices at T1W, 1 month (T1M), and 3 months (T3M) calculated using self‐monitoring of blood glucose data: (I) TIR and (J) hypoglycemic episodes. $ q < 0.05 as stated in (B); # q < 0.05 by repeated‐measures Friedman test corrected by Benjamini and Hochberg method, n = 14. (K) Representative CGM 24‐h glucose profiles demonstrating improved glycemic stability in two patients <t>by</t> <t>WMT.</t> Values of some GV indices were the same for different participants. Thus, both points and connecting lines overlapped with each other, exhibiting fewer than 14 points. LAGE, largest amplitude of glycemic excursions; MAGE, mean amplitude of glycemic excursion; MBG, mean blood glucose; SDBG, SD of blood glucose; TIR, time in range; WMT, washed microbiota transplantation.
Regulated Devices Like Wearable Continuous Glucose Monitors, supplied by RenderX Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/real+time+continuous+glucose+monitoring+device/regulated+devices+like+wearable+continuous+glucose+monitors/pm40267475-30-12-13
Average 90 stars, based on 1 article reviews
regulated devices like wearable continuous glucose monitors - by Bioz Stars, 2026-09
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non-invasive continuous glucose monitoring device aprisetm  (Glucon Medical)
90
Glucon Medical non-invasive continuous glucose monitoring device aprisetm
(A) Flow diagram of study design and participating patients. (B) Changes of daily insulin dose. Data of the same subject at different follow‐up time points are connected by gray lines. False discovery rate (represented as q ‐value) was calculated using repeated‐measures one‐way analysis of variance corrected by Benjamini and Hochberg method for multiple comparisons, n = 14. (C) Postprandial glucose excursions expressed as percentage of baseline during steamed bun meal test (SBMT). All data are represented as mean ± SEM, * q < 0.05 by mixed‐effects model for repeated measures corrected by Benjamini and Hochberg method, n = 9–12. (D–H) Changes of glycemic variability (GV) indices at 1 week (T1W) calculated using continuous glucose monitor <t>(CGM)</t> data: (D) MAGE, (E) SDBG, (F) BG > 11.1 mmol/L, (G) LAGE, and (H) MBG. † p < .05 by paired t test (two‐tailed), n = 14. (I–J) Changes of GV indices at T1W, 1 month (T1M), and 3 months (T3M) calculated using self‐monitoring of blood glucose data: (I) TIR and (J) hypoglycemic episodes. $ q < 0.05 as stated in (B); # q < 0.05 by repeated‐measures Friedman test corrected by Benjamini and Hochberg method, n = 14. (K) Representative CGM 24‐h glucose profiles demonstrating improved glycemic stability in two patients <t>by</t> <t>WMT.</t> Values of some GV indices were the same for different participants. Thus, both points and connecting lines overlapped with each other, exhibiting fewer than 14 points. LAGE, largest amplitude of glycemic excursions; MAGE, mean amplitude of glycemic excursion; MBG, mean blood glucose; SDBG, SD of blood glucose; TIR, time in range; WMT, washed microbiota transplantation.
Non Invasive Continuous Glucose Monitoring Device Aprisetm, supplied by Glucon Medical, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/real+time+continuous+glucose+monitoring+device/non+invasive+continuous+glucose+monitoring+device+aprisetm/10__1177_slash_193229680700100219-2818-7-13
Average 90 stars, based on 1 article reviews
non-invasive continuous glucose monitoring device aprisetm - by Bioz Stars, 2026-09
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continuous glucose monitoring devices  (Medtronic inc)
90
Medtronic inc continuous glucose monitoring devices
(A) Flow diagram of study design and participating patients. (B) Changes of daily insulin dose. Data of the same subject at different follow‐up time points are connected by gray lines. False discovery rate (represented as q ‐value) was calculated using repeated‐measures one‐way analysis of variance corrected by Benjamini and Hochberg method for multiple comparisons, n = 14. (C) Postprandial glucose excursions expressed as percentage of baseline during steamed bun meal test (SBMT). All data are represented as mean ± SEM, * q < 0.05 by mixed‐effects model for repeated measures corrected by Benjamini and Hochberg method, n = 9–12. (D–H) Changes of glycemic variability (GV) indices at 1 week (T1W) calculated using continuous glucose monitor <t>(CGM)</t> data: (D) MAGE, (E) SDBG, (F) BG > 11.1 mmol/L, (G) LAGE, and (H) MBG. † p < .05 by paired t test (two‐tailed), n = 14. (I–J) Changes of GV indices at T1W, 1 month (T1M), and 3 months (T3M) calculated using self‐monitoring of blood glucose data: (I) TIR and (J) hypoglycemic episodes. $ q < 0.05 as stated in (B); # q < 0.05 by repeated‐measures Friedman test corrected by Benjamini and Hochberg method, n = 14. (K) Representative CGM 24‐h glucose profiles demonstrating improved glycemic stability in two patients <t>by</t> <t>WMT.</t> Values of some GV indices were the same for different participants. Thus, both points and connecting lines overlapped with each other, exhibiting fewer than 14 points. LAGE, largest amplitude of glycemic excursions; MAGE, mean amplitude of glycemic excursion; MBG, mean blood glucose; SDBG, SD of blood glucose; TIR, time in range; WMT, washed microbiota transplantation.
Continuous Glucose Monitoring Devices, supplied by Medtronic inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/real+time+continuous+glucose+monitoring+device/continuous+glucose+monitoring+devices/pmc11571613-189-7-0
Average 90 stars, based on 1 article reviews
continuous glucose monitoring devices - by Bioz Stars, 2026-09
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implantable continuous glucose monitoring device eversense continuous glucose monitoring (cgm) system  (Senseonics)
90
Senseonics implantable continuous glucose monitoring device eversense continuous glucose monitoring (cgm) system
(A) Flow diagram of study design and participating patients. (B) Changes of daily insulin dose. Data of the same subject at different follow‐up time points are connected by gray lines. False discovery rate (represented as q ‐value) was calculated using repeated‐measures one‐way analysis of variance corrected by Benjamini and Hochberg method for multiple comparisons, n = 14. (C) Postprandial glucose excursions expressed as percentage of baseline during steamed bun meal test (SBMT). All data are represented as mean ± SEM, * q < 0.05 by mixed‐effects model for repeated measures corrected by Benjamini and Hochberg method, n = 9–12. (D–H) Changes of glycemic variability (GV) indices at 1 week (T1W) calculated using continuous glucose monitor <t>(CGM)</t> data: (D) MAGE, (E) SDBG, (F) BG > 11.1 mmol/L, (G) LAGE, and (H) MBG. † p < .05 by paired t test (two‐tailed), n = 14. (I–J) Changes of GV indices at T1W, 1 month (T1M), and 3 months (T3M) calculated using self‐monitoring of blood glucose data: (I) TIR and (J) hypoglycemic episodes. $ q < 0.05 as stated in (B); # q < 0.05 by repeated‐measures Friedman test corrected by Benjamini and Hochberg method, n = 14. (K) Representative CGM 24‐h glucose profiles demonstrating improved glycemic stability in two patients <t>by</t> <t>WMT.</t> Values of some GV indices were the same for different participants. Thus, both points and connecting lines overlapped with each other, exhibiting fewer than 14 points. LAGE, largest amplitude of glycemic excursions; MAGE, mean amplitude of glycemic excursion; MBG, mean blood glucose; SDBG, SD of blood glucose; TIR, time in range; WMT, washed microbiota transplantation.
Implantable Continuous Glucose Monitoring Device Eversense Continuous Glucose Monitoring (Cgm) System, supplied by Senseonics, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/real+time+continuous+glucose+monitoring+device/implantable+continuous+glucose+monitoring+device+eversense+continuous+glucose+monitoring++cgm++system/pmc07304103-218-6-18
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iso/ieee 11073-10425 device specialization—continuous glucose monitor  (Bluetooth SIG)
90
Bluetooth SIG iso/ieee 11073-10425 device specialization—continuous glucose monitor
(A) Flow diagram of study design and participating patients. (B) Changes of daily insulin dose. Data of the same subject at different follow‐up time points are connected by gray lines. False discovery rate (represented as q ‐value) was calculated using repeated‐measures one‐way analysis of variance corrected by Benjamini and Hochberg method for multiple comparisons, n = 14. (C) Postprandial glucose excursions expressed as percentage of baseline during steamed bun meal test (SBMT). All data are represented as mean ± SEM, * q < 0.05 by mixed‐effects model for repeated measures corrected by Benjamini and Hochberg method, n = 9–12. (D–H) Changes of glycemic variability (GV) indices at 1 week (T1W) calculated using continuous glucose monitor <t>(CGM)</t> data: (D) MAGE, (E) SDBG, (F) BG > 11.1 mmol/L, (G) LAGE, and (H) MBG. † p < .05 by paired t test (two‐tailed), n = 14. (I–J) Changes of GV indices at T1W, 1 month (T1M), and 3 months (T3M) calculated using self‐monitoring of blood glucose data: (I) TIR and (J) hypoglycemic episodes. $ q < 0.05 as stated in (B); # q < 0.05 by repeated‐measures Friedman test corrected by Benjamini and Hochberg method, n = 14. (K) Representative CGM 24‐h glucose profiles demonstrating improved glycemic stability in two patients <t>by</t> <t>WMT.</t> Values of some GV indices were the same for different participants. Thus, both points and connecting lines overlapped with each other, exhibiting fewer than 14 points. LAGE, largest amplitude of glycemic excursions; MAGE, mean amplitude of glycemic excursion; MBG, mean blood glucose; SDBG, SD of blood glucose; TIR, time in range; WMT, washed microbiota transplantation.
Iso/Ieee 11073 10425 Device Specialization—Continuous Glucose Monitor, supplied by Bluetooth SIG, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/real+time+continuous+glucose+monitoring+device/iso+ieee+11073+10425+device+specialization+continuous+glucose+monitor/pmc11707763-222-18-47
Average 90 stars, based on 1 article reviews
iso/ieee 11073-10425 device specialization—continuous glucose monitor - by Bioz Stars, 2026-09
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continuous glucose monitoring device  (MiniMed Inc)
90
MiniMed Inc continuous glucose monitoring device
(A) Flow diagram of study design and participating patients. (B) Changes of daily insulin dose. Data of the same subject at different follow‐up time points are connected by gray lines. False discovery rate (represented as q ‐value) was calculated using repeated‐measures one‐way analysis of variance corrected by Benjamini and Hochberg method for multiple comparisons, n = 14. (C) Postprandial glucose excursions expressed as percentage of baseline during steamed bun meal test (SBMT). All data are represented as mean ± SEM, * q < 0.05 by mixed‐effects model for repeated measures corrected by Benjamini and Hochberg method, n = 9–12. (D–H) Changes of glycemic variability (GV) indices at 1 week (T1W) calculated using continuous glucose monitor <t>(CGM)</t> data: (D) MAGE, (E) SDBG, (F) BG > 11.1 mmol/L, (G) LAGE, and (H) MBG. † p < .05 by paired t test (two‐tailed), n = 14. (I–J) Changes of GV indices at T1W, 1 month (T1M), and 3 months (T3M) calculated using self‐monitoring of blood glucose data: (I) TIR and (J) hypoglycemic episodes. $ q < 0.05 as stated in (B); # q < 0.05 by repeated‐measures Friedman test corrected by Benjamini and Hochberg method, n = 14. (K) Representative CGM 24‐h glucose profiles demonstrating improved glycemic stability in two patients <t>by</t> <t>WMT.</t> Values of some GV indices were the same for different participants. Thus, both points and connecting lines overlapped with each other, exhibiting fewer than 14 points. LAGE, largest amplitude of glycemic excursions; MAGE, mean amplitude of glycemic excursion; MBG, mean blood glucose; SDBG, SD of blood glucose; TIR, time in range; WMT, washed microbiota transplantation.
Continuous Glucose Monitoring Device, supplied by MiniMed Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/real+time+continuous+glucose+monitoring+device/continuous+glucose+monitoring+device/pmc02769686-30-10-16
Average 90 stars, based on 1 article reviews
continuous glucose monitoring device - by Bioz Stars, 2026-09
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continuous glucose monitoring device  (Cellnovo Inc)
90
Cellnovo Inc continuous glucose monitoring device
(A) Flow diagram of study design and participating patients. (B) Changes of daily insulin dose. Data of the same subject at different follow‐up time points are connected by gray lines. False discovery rate (represented as q ‐value) was calculated using repeated‐measures one‐way analysis of variance corrected by Benjamini and Hochberg method for multiple comparisons, n = 14. (C) Postprandial glucose excursions expressed as percentage of baseline during steamed bun meal test (SBMT). All data are represented as mean ± SEM, * q < 0.05 by mixed‐effects model for repeated measures corrected by Benjamini and Hochberg method, n = 9–12. (D–H) Changes of glycemic variability (GV) indices at 1 week (T1W) calculated using continuous glucose monitor <t>(CGM)</t> data: (D) MAGE, (E) SDBG, (F) BG > 11.1 mmol/L, (G) LAGE, and (H) MBG. † p < .05 by paired t test (two‐tailed), n = 14. (I–J) Changes of GV indices at T1W, 1 month (T1M), and 3 months (T3M) calculated using self‐monitoring of blood glucose data: (I) TIR and (J) hypoglycemic episodes. $ q < 0.05 as stated in (B); # q < 0.05 by repeated‐measures Friedman test corrected by Benjamini and Hochberg method, n = 14. (K) Representative CGM 24‐h glucose profiles demonstrating improved glycemic stability in two patients <t>by</t> <t>WMT.</t> Values of some GV indices were the same for different participants. Thus, both points and connecting lines overlapped with each other, exhibiting fewer than 14 points. LAGE, largest amplitude of glycemic excursions; MAGE, mean amplitude of glycemic excursion; MBG, mean blood glucose; SDBG, SD of blood glucose; TIR, time in range; WMT, washed microbiota transplantation.
Continuous Glucose Monitoring Device, supplied by Cellnovo Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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continuous glucose monitoring device - by Bioz Stars, 2026-09
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g7 continuous glucose monitoring device in comparison to dexcom g6 andreas pfützner1 2 3  (Dexcom Inc)
86
Dexcom Inc g7 continuous glucose monitoring device in comparison to dexcom g6 andreas pfützner1 2 3
(A) Flow diagram of study design and participating patients. (B) Changes of daily insulin dose. Data of the same subject at different follow‐up time points are connected by gray lines. False discovery rate (represented as q ‐value) was calculated using repeated‐measures one‐way analysis of variance corrected by Benjamini and Hochberg method for multiple comparisons, n = 14. (C) Postprandial glucose excursions expressed as percentage of baseline during steamed bun meal test (SBMT). All data are represented as mean ± SEM, * q < 0.05 by mixed‐effects model for repeated measures corrected by Benjamini and Hochberg method, n = 9–12. (D–H) Changes of glycemic variability (GV) indices at 1 week (T1W) calculated using continuous glucose monitor <t>(CGM)</t> data: (D) MAGE, (E) SDBG, (F) BG > 11.1 mmol/L, (G) LAGE, and (H) MBG. † p < .05 by paired t test (two‐tailed), n = 14. (I–J) Changes of GV indices at T1W, 1 month (T1M), and 3 months (T3M) calculated using self‐monitoring of blood glucose data: (I) TIR and (J) hypoglycemic episodes. $ q < 0.05 as stated in (B); # q < 0.05 by repeated‐measures Friedman test corrected by Benjamini and Hochberg method, n = 14. (K) Representative CGM 24‐h glucose profiles demonstrating improved glycemic stability in two patients <t>by</t> <t>WMT.</t> Values of some GV indices were the same for different participants. Thus, both points and connecting lines overlapped with each other, exhibiting fewer than 14 points. LAGE, largest amplitude of glycemic excursions; MAGE, mean amplitude of glycemic excursion; MBG, mean blood glucose; SDBG, SD of blood glucose; TIR, time in range; WMT, washed microbiota transplantation.
G7 Continuous Glucose Monitoring Device In Comparison To Dexcom G6 Andreas Pfützner1 2 3, supplied by Dexcom Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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continuous glucose monitoring device  (Institute for Clinical Pharmacodynamics)
90
Institute for Clinical Pharmacodynamics continuous glucose monitoring device
(A) Flow diagram of study design and participating patients. (B) Changes of daily insulin dose. Data of the same subject at different follow‐up time points are connected by gray lines. False discovery rate (represented as q ‐value) was calculated using repeated‐measures one‐way analysis of variance corrected by Benjamini and Hochberg method for multiple comparisons, n = 14. (C) Postprandial glucose excursions expressed as percentage of baseline during steamed bun meal test (SBMT). All data are represented as mean ± SEM, * q < 0.05 by mixed‐effects model for repeated measures corrected by Benjamini and Hochberg method, n = 9–12. (D–H) Changes of glycemic variability (GV) indices at 1 week (T1W) calculated using continuous glucose monitor <t>(CGM)</t> data: (D) MAGE, (E) SDBG, (F) BG > 11.1 mmol/L, (G) LAGE, and (H) MBG. † p < .05 by paired t test (two‐tailed), n = 14. (I–J) Changes of GV indices at T1W, 1 month (T1M), and 3 months (T3M) calculated using self‐monitoring of blood glucose data: (I) TIR and (J) hypoglycemic episodes. $ q < 0.05 as stated in (B); # q < 0.05 by repeated‐measures Friedman test corrected by Benjamini and Hochberg method, n = 14. (K) Representative CGM 24‐h glucose profiles demonstrating improved glycemic stability in two patients <t>by</t> <t>WMT.</t> Values of some GV indices were the same for different participants. Thus, both points and connecting lines overlapped with each other, exhibiting fewer than 14 points. LAGE, largest amplitude of glycemic excursions; MAGE, mean amplitude of glycemic excursion; MBG, mean blood glucose; SDBG, SD of blood glucose; TIR, time in range; WMT, washed microbiota transplantation.
Continuous Glucose Monitoring Device, supplied by Institute for Clinical Pharmacodynamics, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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continuous glucose monitoring device - by Bioz Stars, 2026-09
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manufacturing real time glucose lactate monitoring using integrated maven sensors in g rex bioreactors  (908 Devices)
86
908 Devices manufacturing real time glucose lactate monitoring using integrated maven sensors in g rex bioreactors
(A) Flow diagram of study design and participating patients. (B) Changes of daily insulin dose. Data of the same subject at different follow‐up time points are connected by gray lines. False discovery rate (represented as q ‐value) was calculated using repeated‐measures one‐way analysis of variance corrected by Benjamini and Hochberg method for multiple comparisons, n = 14. (C) Postprandial glucose excursions expressed as percentage of baseline during steamed bun meal test (SBMT). All data are represented as mean ± SEM, * q < 0.05 by mixed‐effects model for repeated measures corrected by Benjamini and Hochberg method, n = 9–12. (D–H) Changes of glycemic variability (GV) indices at 1 week (T1W) calculated using continuous glucose monitor <t>(CGM)</t> data: (D) MAGE, (E) SDBG, (F) BG > 11.1 mmol/L, (G) LAGE, and (H) MBG. † p < .05 by paired t test (two‐tailed), n = 14. (I–J) Changes of GV indices at T1W, 1 month (T1M), and 3 months (T3M) calculated using self‐monitoring of blood glucose data: (I) TIR and (J) hypoglycemic episodes. $ q < 0.05 as stated in (B); # q < 0.05 by repeated‐measures Friedman test corrected by Benjamini and Hochberg method, n = 14. (K) Representative CGM 24‐h glucose profiles demonstrating improved glycemic stability in two patients <t>by</t> <t>WMT.</t> Values of some GV indices were the same for different participants. Thus, both points and connecting lines overlapped with each other, exhibiting fewer than 14 points. LAGE, largest amplitude of glycemic excursions; MAGE, mean amplitude of glycemic excursion; MBG, mean blood glucose; SDBG, SD of blood glucose; TIR, time in range; WMT, washed microbiota transplantation.
Manufacturing Real Time Glucose Lactate Monitoring Using Integrated Maven Sensors In G Rex Bioreactors, supplied by 908 Devices, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


(A) Flow diagram of study design and participating patients. (B) Changes of daily insulin dose. Data of the same subject at different follow‐up time points are connected by gray lines. False discovery rate (represented as q ‐value) was calculated using repeated‐measures one‐way analysis of variance corrected by Benjamini and Hochberg method for multiple comparisons, n = 14. (C) Postprandial glucose excursions expressed as percentage of baseline during steamed bun meal test (SBMT). All data are represented as mean ± SEM, * q < 0.05 by mixed‐effects model for repeated measures corrected by Benjamini and Hochberg method, n = 9–12. (D–H) Changes of glycemic variability (GV) indices at 1 week (T1W) calculated using continuous glucose monitor (CGM) data: (D) MAGE, (E) SDBG, (F) BG > 11.1 mmol/L, (G) LAGE, and (H) MBG. † p < .05 by paired t test (two‐tailed), n = 14. (I–J) Changes of GV indices at T1W, 1 month (T1M), and 3 months (T3M) calculated using self‐monitoring of blood glucose data: (I) TIR and (J) hypoglycemic episodes. $ q < 0.05 as stated in (B); # q < 0.05 by repeated‐measures Friedman test corrected by Benjamini and Hochberg method, n = 14. (K) Representative CGM 24‐h glucose profiles demonstrating improved glycemic stability in two patients by WMT. Values of some GV indices were the same for different participants. Thus, both points and connecting lines overlapped with each other, exhibiting fewer than 14 points. LAGE, largest amplitude of glycemic excursions; MAGE, mean amplitude of glycemic excursion; MBG, mean blood glucose; SDBG, SD of blood glucose; TIR, time in range; WMT, washed microbiota transplantation.

Journal: Journal of Diabetes

Article Title: Washed microbiota transplantation reduces glycemic variability in unstable diabetes

doi: 10.1111/1753-0407.13485

Figure Lengend Snippet: (A) Flow diagram of study design and participating patients. (B) Changes of daily insulin dose. Data of the same subject at different follow‐up time points are connected by gray lines. False discovery rate (represented as q ‐value) was calculated using repeated‐measures one‐way analysis of variance corrected by Benjamini and Hochberg method for multiple comparisons, n = 14. (C) Postprandial glucose excursions expressed as percentage of baseline during steamed bun meal test (SBMT). All data are represented as mean ± SEM, * q < 0.05 by mixed‐effects model for repeated measures corrected by Benjamini and Hochberg method, n = 9–12. (D–H) Changes of glycemic variability (GV) indices at 1 week (T1W) calculated using continuous glucose monitor (CGM) data: (D) MAGE, (E) SDBG, (F) BG > 11.1 mmol/L, (G) LAGE, and (H) MBG. † p < .05 by paired t test (two‐tailed), n = 14. (I–J) Changes of GV indices at T1W, 1 month (T1M), and 3 months (T3M) calculated using self‐monitoring of blood glucose data: (I) TIR and (J) hypoglycemic episodes. $ q < 0.05 as stated in (B); # q < 0.05 by repeated‐measures Friedman test corrected by Benjamini and Hochberg method, n = 14. (K) Representative CGM 24‐h glucose profiles demonstrating improved glycemic stability in two patients by WMT. Values of some GV indices were the same for different participants. Thus, both points and connecting lines overlapped with each other, exhibiting fewer than 14 points. LAGE, largest amplitude of glycemic excursions; MAGE, mean amplitude of glycemic excursion; MBG, mean blood glucose; SDBG, SD of blood glucose; TIR, time in range; WMT, washed microbiota transplantation.

Article Snippet: Three days before WMT, patients were implanted with a continuous glucose monitor (CGM) device (MeiQi Medical Instruments Co., Ltd., Huzhou, China).

Techniques: Two Tailed Test, Transplantation Assay

Washed microbiota transplantation (WMT) alters profiles of serum metabolites. (A) Heatmap showing changes of serum metabolites determined by non‐targeted metabolomics, n = 11–14. (B) Heatmap of Spearman's correlation coefficients between serum metabolites and glycemic variability (GV) indices. (C) The 8 positively correlated metabolites between fecal and serum compartments. Color range varies from light red (weaker correlation) to dark red (stronger correlation). Statistical methods were the same as stated in Figure . AUC, area under the curve; BG, blood glucose; CGM, continuous glucose monitor; CV, coefficient of variation; HbA1c, glycated hemoglobin; LAGE, largest amplitude of glycemic excursions; MBG, mean blood glucose; PPGE, postprandial glucose excursion; SBMT, steamed bun meal test; SMBG, self‐monitoring of blood glucose; TIR, time in range.

Journal: Journal of Diabetes

Article Title: Washed microbiota transplantation reduces glycemic variability in unstable diabetes

doi: 10.1111/1753-0407.13485

Figure Lengend Snippet: Washed microbiota transplantation (WMT) alters profiles of serum metabolites. (A) Heatmap showing changes of serum metabolites determined by non‐targeted metabolomics, n = 11–14. (B) Heatmap of Spearman's correlation coefficients between serum metabolites and glycemic variability (GV) indices. (C) The 8 positively correlated metabolites between fecal and serum compartments. Color range varies from light red (weaker correlation) to dark red (stronger correlation). Statistical methods were the same as stated in Figure . AUC, area under the curve; BG, blood glucose; CGM, continuous glucose monitor; CV, coefficient of variation; HbA1c, glycated hemoglobin; LAGE, largest amplitude of glycemic excursions; MBG, mean blood glucose; PPGE, postprandial glucose excursion; SBMT, steamed bun meal test; SMBG, self‐monitoring of blood glucose; TIR, time in range.

Article Snippet: Three days before WMT, patients were implanted with a continuous glucose monitor (CGM) device (MeiQi Medical Instruments Co., Ltd., Huzhou, China).

Techniques: Transplantation Assay