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Ambiguity of sugar measurement types and data ...
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<blockquote data-quote="jksuresh60" data-source="post: 2542239" data-attributes="member: 559472"><p>I'm a 62 yo male, displaying a classic phenotype of Asian mid-region obesity, with low metabolic activity and sedentary life style.</p><p></p><p>I have been struggling with a dietary approach to reduction of blood sugar for around fifteen months now.</p><p></p><p>Now for some data.</p><p></p><p>During this period, I observed through multiple tests and data points a significant difference between HBA1C and regular daily tests using a blood glucose monitor (BGM).</p><p></p><p>Aiming to resolve the matter, around 10 days ago, I opted for the insertion of a CGM device (Freestyle Libre) for a 14 day test. Since I don't have a reader, I obtained printouts from my clinic every 3 days to understand the time variation of glucose over the day.</p><p></p><p>As a parallel data acquisition process, I downloaded Glimp on my Android phone and have been using it in real time to check effects of food on sugar variations.</p><p></p><p>My problem is as follows:</p><p></p><p>I have compared results between capillary blood sugar (BGM based) with that of libre and Glimp and find huge variations. Many random points in time and specific points corresponding to post prandial conditions have been considered by me in the comparison. In most of them there are large differences. I've taken care to show for 20-30 minute difference between blood sugar and ISF (where CGM device measurements originate) data.</p><p></p><p>For the moment, putting aside the BGM values, what is extremely puzzling is a 20-40% difference across the spectrum between Libre data and Glimp data as derived from the respective curves. How can the same data, apparently correctly captured through NFC from the insert, be so different in data? Note that my data has been obtained from the graph for Libre data and read of the graph on the Glimp app.</p><p></p><p>Can some of the experienced and knowledgeable folks in the forum let me know how to resolve this?</p><p></p><p>To give an example, if the Libre data shows 140 mg/dL two hours after food, and Glimp shows 120 mg/dL, diabetes may not be indicated. However, if Libre shows 80 mg/dL during early morning, but Glimp shows 50 mg/dL, hypoglycemia is deduced.</p><p></p><p>Similarly if Libre shows 220 post prandial, diabetes is indicated whereas if Glimp shows 175, only prediabetes may be diagnosed.</p><p></p><p>Most doctors are unable to disambiguate this. Any help from this forum will be deeply appreciated.</p></blockquote><p></p>
[QUOTE="jksuresh60, post: 2542239, member: 559472"] I'm a 62 yo male, displaying a classic phenotype of Asian mid-region obesity, with low metabolic activity and sedentary life style. I have been struggling with a dietary approach to reduction of blood sugar for around fifteen months now. Now for some data. During this period, I observed through multiple tests and data points a significant difference between HBA1C and regular daily tests using a blood glucose monitor (BGM). Aiming to resolve the matter, around 10 days ago, I opted for the insertion of a CGM device (Freestyle Libre) for a 14 day test. Since I don't have a reader, I obtained printouts from my clinic every 3 days to understand the time variation of glucose over the day. As a parallel data acquisition process, I downloaded Glimp on my Android phone and have been using it in real time to check effects of food on sugar variations. My problem is as follows: I have compared results between capillary blood sugar (BGM based) with that of libre and Glimp and find huge variations. Many random points in time and specific points corresponding to post prandial conditions have been considered by me in the comparison. In most of them there are large differences. I've taken care to show for 20-30 minute difference between blood sugar and ISF (where CGM device measurements originate) data. For the moment, putting aside the BGM values, what is extremely puzzling is a 20-40% difference across the spectrum between Libre data and Glimp data as derived from the respective curves. How can the same data, apparently correctly captured through NFC from the insert, be so different in data? Note that my data has been obtained from the graph for Libre data and read of the graph on the Glimp app. Can some of the experienced and knowledgeable folks in the forum let me know how to resolve this? To give an example, if the Libre data shows 140 mg/dL two hours after food, and Glimp shows 120 mg/dL, diabetes may not be indicated. However, if Libre shows 80 mg/dL during early morning, but Glimp shows 50 mg/dL, hypoglycemia is deduced. Similarly if Libre shows 220 post prandial, diabetes is indicated whereas if Glimp shows 175, only prediabetes may be diagnosed. Most doctors are unable to disambiguate this. Any help from this forum will be deeply appreciated. [/QUOTE]
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