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--- Diabetic controlling blood sugar, Spreadsheet to estimate HbA1c
R. loanguy wrote: > Hello everyone: Hi Loanguy, I don't do spreadsheets but just want to say welcome :)
Thank you Ozgirl "Ozgirl" news:bktdjn$5q5ka$1@ID-139901.news.uni-berlin.de... > R. loanguy wrote: > > Hello everyone: > > Hi Loanguy, I don't do spreadsheets but just want to say welcome :) >
"R. loanguy" news:KPpcb.19237$jO.8921@bignews3.bellsouth.net: > Hello everyone: > > I am relative newcomer to these groups, but I would like to share > something that I came up with to estimate my HbA1c levels. I have > been following the advice about the monitoring after meals in > order to keep good control of blood sugars, but could not find out > anywhere in the net a place that would let me estimate the impact > that said control would have on my HbA1c levels. > > As most of you are aware, a diabetic must try to keep this > percentage under 6.5% in order to get better odds at not > developing complications. Because I could not find a tool to do > this, I came up with one of my own by working a formula to > estimate the average blood sugar using HbA1c. > > I created a small one page site for people to go download it. I > would appreciate it if people with data and an actual HbA1c test > result would try it out and tell me how accurate it is. > > The spreadsheet can be found here: > > http://www.loanuniverse.com/Diabetes/ > > I await your feedback. > > P.S: I am sorry for the cross-posting but I tried to keep the > posts limited to those groups that have a lot of diabetics as > users. FollowUp set to m.h.d. You cannot make a sensible estimate of A1c from finger stick records. There are several issues, I'll just give a short summary. 1. Sampling bias. If you take, for example, only fasting and pre-meal glucose tests you will get a very different average than if you take only 2 hour post prandial tests. This is called sampling bias. Worse than that, different types of diabetes and different types of treatment will vary the sampling bias differently. A type 2 treated with exercise and diet will likely have higher postprandial bg levels than preprandial. For a type 1 with a tight basal/bolus regimen with a fast acting prandial insulin, 2 hour postprandials can be the lowest bg levels of the day. Sampling bias is a difficult issue. 2. Sampling rate. If you assume three meals/day and the possible occurrence of some events overnight (dawn phenomenon, Somoygi), you can think of a time series of blood glucose as having 4 major cycles/day. This is, of course, over simplified. Elementary sampling theory will tell you that you need at least 8 samples/day to characterize the signal. As with most theoretical constructs, elementary sampling theory gives an answer which is insufficient for any real practical use. The practical answer depends on a number of factors, not the least of which is how big you want the error bars to be, but very few data analysts would be happy with less than twice the theoretical limit, i.e. 16 samples/day. Worse than this, if you look at any MiniMed 3 day continuous blood glucose record you will be able to see that there is much variation in bg at much higher frequencies than the 4 cycles in the simple picture above. This, of course, drive up the number of samples/day required to get a sensible average. 3. Normal range. Every lab has its own normal range. There is a movement to standardize on the DCCT normal range (4.0%-6.0%) but it is progressing very slowly. Even if your spread sheet worked, it would work for only labs with the same testing methodology as your lab and the same normal range. Different methods for assaying A1c actually measure slightly different things, so the comparison between labs is difficult. 4. Many of the attempts to correlate daily bg testing rely on the data published by the DCCT. They did a correlation between a 7 stick regimen (3 preprandial, 3 postprandial, and 3 am) and A1c. Ignoring sampling rate considerations, it was an attempt to correlate a standard testing pattern and A1c in a specific population. It is difficult to get even that limited objective accomplished. Several years after the original publication, they found they had botched the original analysis and published a correction. Most of the existing charts of bg vs. A1c are based on the original analysis. There are other more arcane technical issues, but the bottom line is you just can't get there from here. Note, that for an individual with stable blood glucose patterns it is quite possible to develop a correlation between A1c and a stable pattern of bg measurements. If the bg pattern changes, however, in a way masked by the sampling interval or bias, then the resultant A1c changes will not be predicted by the correlation which is no longer valid. This makes it, at best, a futile exercise and, at worst, a misleading indicator. The correlation will not, in general, be valid in any other diabetic. -- ------------- Charly Coughran ccoughran@DELETE_TO_REPLY_UCSD.EDU
Charly: I was aware of the sampling bias and sampling rate problems to being with. In fact, as I was writing the spreadsheet I tried to address them in the little FAQ, I created: ".........this model does not properly assign weights to the different measurements. For example, if you measure your blood glucose one hour after lunch you will have a high number, but this number might be short-lived. On the other hand, if you measure before going to bed and get a low number and this number lasts during the whole night the model gives each one of them the same importance....." and here: ".......The more data you have, the better your average will be and therefore the better the model should work in theory. In order to use more data, some colums need to be added. I am using five colums because I try to at least do those five tests if I have the time........" I was not aware that there were problems with the available data that shows a correlation between the average blood glucose and the HbA1c result is flawed. I also did not consider the difference in the ranges as material while I understand the basics of how the ranges are determined in different populations. Frankly, I am not sure if the result is going to be even close to the one that might show on my next HbA1c test. Since I have only been diagnosed for less than three months and I have to make a follow up appointment soon. The reason why I posted here was to see if people out there had been measuring themselves a lot, had access to a recent HbA1c result or were going to get tested soon then it would help test how useful the spreadsheet is. The whole thing might be a "futile exercise", but since some people are already testing themselves a lot and the new meters have memory, it is a matter of just going back and entering the information. Not too much work in my humble opinion, at worst they can print the results and take them as their log for their next doctor's visit. Thanks for you comments P.S: I agree with you that the whole thing is imperfect, it is a matter of trying to come up with as good an estimate as one can with the available data. Personally, I think that it will work best for people that test more often than I do or that at least keep to the number of tests that they set themselves to do everyday. I try to do at least five a day, but I have missed many. While researching the topic, I also read about how the process of binding to hemoglobin accelerates a lot while having really high levels even if they are short-lived so that is another monkey wrench on the whole thing. Fortunately, I have only had one incidence of a reading over 200 in the last couple of months, but for someone with worse control, using this might be completely misleading instead of just a little misleading. "Charly Coughran" news:Xns9401730FF75BFccoughranucsdedu@132.239.1.221... > "R. loanguy" > news:KPpcb.19237$jO.8921@bignews3.bellsouth.net: > > > Hello everyone: > > > > I am relative newcomer to these groups, but I would like to share > > something that I came up with to estimate my HbA1c levels. I have > > been following the advice about the monitoring after meals in > > order to keep good control of blood sugars, but could not find out > > anywhere in the net a place that would let me estimate the impact > > that said control would have on my HbA1c levels. > > > > As most of you are aware, a diabetic must try to keep this > > percentage under 6.5% in order to get better odds at not > > developing complications. Because I could not find a tool to do > > this, I came up with one of my own by working a formula to > > estimate the average blood sugar using HbA1c. > > > > I created a small one page site for people to go download it. I > > would appreciate it if people with data and an actual HbA1c test > > result would try it out and tell me how accurate it is. > > > > The spreadsheet can be found here: > > > > http://www.loanuniverse.com/Diabetes/ > > > > I await your feedback. > > > > P.S: I am sorry for the cross-posting but I tried to keep the > > posts limited to those groups that have a lot of diabetics as > > users. > > FollowUp set to m.h.d. > > You cannot make a sensible estimate of A1c from finger stick records. > There are several issues, I'll just give a short summary. > > 1. Sampling bias. If you take, for example, only fasting and pre-meal > glucose tests you will get a very different average than if you take > only 2 hour post prandial tests. This is called sampling bias. Worse > than that, different types of diabetes and different types of treatment > will vary the sampling bias differently. A type 2 treated with > exercise and diet will likely have higher postprandial bg levels than > preprandial. For a type 1 with a tight basal/bolus regimen with a fast > acting prandial insulin, 2 hour postprandials can be the lowest bg > levels of the day. Sampling bias is a difficult issue. > > 2. Sampling rate. If you assume three meals/day and the possible > occurrence of some events overnight (dawn phenomenon, Somoygi), you can > think of a time series of blood glucose as having 4 major cycles/day. > This is, of course, over simplified. Elementary sampling theory will > tell you that you need at least 8 samples/day to characterize the > signal. As with most theoretical constructs, elementary sampling > theory gives an answer which is insufficient for any real practical > use. The practical answer depends on a number of factors, not the > least of which is how big you want the error bars to be, but very few > data analysts would be happy with less than twice the theoretical > limit, i.e. 16 samples/day. > > Worse than this, if you look at any MiniMed 3 day continuous blood > glucose record you will be able to see that there is much variation in > bg at much higher frequencies than the 4 cycles in the simple picture > above. This, of course, drive up the number of samples/day required to > get a sensible average. > > 3. Normal range. Every lab has its own normal range. There is a > movement to standardize on the DCCT normal range (4.0%-6.0%) but it is > progressing very slowly. Even if your spread sheet worked, it would > work for only labs with the same testing methodology as your lab and > the same normal range. Different methods for assaying A1c actually > measure slightly different things, so the comparison between labs is > difficult. > > 4. Many of the attempts to correlate daily bg testing rely on the data > published by the DCCT. They did a correlation between a 7 stick > regimen (3 preprandial, 3 postprandial, and 3 am) and A1c. Ignoring > sampling rate considerations, it was an attempt to correlate a standard > testing pattern and A1c in a specific population. It is difficult to > get even that limited objective accomplished. Several years after the > original publication, they found they had botched the original analysis > and published a correction. Most of the existing charts of bg vs. A1c > are based on the original analysis. > > There are other more arcane technical issues, but the bottom line is > you just can't get there from here. Note, that for an individual with > stable blood glucose patterns it is quite possible to develop a > correlation between A1c and a stable pattern of bg measurements. If > the bg pattern changes, however, in a way masked by the sampling > interval or bias, then the resultant A1c changes will not be predicted > by the correlation which is no longer valid. This makes it, at best, a > futile exercise and, at worst, a misleading indicator. > The correlation will not, in general, be valid in any other diabetic. > > -- > ------------- > Charly Coughran > ccoughran@DELETE_TO_REPLY_UCSD.EDU
The list of problems I gave you was not exhaustive. Spend the time and effort learning as much as you can about your disease instead. If you wish to understand the difficulties I didn't mention, I would strongly suggest you read the FAQ section on A1c and look up the references cited there. The A1c reaction cannot be modeled as a simple reaction. It is a two step reaction with differing forward and reverse reaction constants for both steps. The average that A1c represents is quasi- exponentially weighted in time and, if the models are to be believed, not particularly sensitive to short term glucose fluctuations. -- ------------- Charly Coughran ccoughran@DELETE_TO_REPLY_UCSD.EDU "R. loanguy" news:6bKcb.20533$jO.310@bignews3.bellsouth.net: > Charly: I was aware of the sampling bias and sampling rate > problems to being with. In fact, as I was writing the spreadsheet > I tried to address them in the little FAQ, I created: > > ".........this model does not properly assign weights to the > different measurements. For example, if you measure your blood > glucose one hour after lunch you will have a high number, but this > number might be short-lived. On the other hand, if you measure > before going to bed and get a low number and this number lasts > during the whole night the model gives each one of them the same > importance....." > > and here: > > ".......The more data you have, the better your average will be > and therefore the better the model should work in theory. In order > to use more data, some colums need to be added. I am using five > colums because I try to at least do those five tests if I have the > time........" > > I was not aware that there were problems with the available data > that shows a correlation between the average blood glucose and the > HbA1c result is flawed. I also did not consider the difference in > the ranges as material while I understand the basics of how the > ranges are determined in different populations. > > Frankly, I am not sure if the result is going to be even close to > the one that might show on my next HbA1c test. Since I have only > been diagnosed for less than three months and I have to make a > follow up appointment soon. The reason why I posted here was to > see if people out there had been measuring themselves a lot, had > access to a recent HbA1c result or were going to get tested soon > then it would help test how useful the spreadsheet is. The whole > thing might be a "futile exercise", but since some people are > already testing themselves a lot and the new meters have memory, > it is a matter of just going back and entering the information. > > Not too much work in my humble opinion, at worst they can print > the results and take them as their log for their next doctor's > visit. > > Thanks for you comments > > P.S: I agree with you that the whole thing is imperfect, it is a > matter of trying to come up with as good an estimate as one can > with the available data. Personally, I think that it will work > best for people that test more often than I do or that at least > keep to the number of tests that they set themselves to do > everyday. I try to do at least five a day, but I have missed many. > > While researching the topic, I also read about how the process of > binding to hemoglobin accelerates a lot while having really high > levels even if they are short-lived so that is another monkey > wrench on the whole thing. Fortunately, I have only had one > incidence of a reading over 200 in the last couple of months, but > for someone with worse control, using this might be completely > misleading instead of just a little misleading. > > "Charly Coughran" > message news:Xns9401730FF75BFccoughranucsdedu@132.239.1.221... >> "R. loanguy" >> news:KPpcb.19237$jO.8921@bignews3.bellsouth.net: >> >> > Hello everyone: >> > >> > I am relative newcomer to these groups, but I would like to >> > share something that I came up with to estimate my HbA1c >> > levels. I have been following the advice about the monitoring >> > after meals in order to keep good control of blood sugars, but >> > could not find out anywhere in the net a place that would let >> > me estimate the impact that said control would have on my HbA1c >> > levels. >> > >> > As most of you are aware, a diabetic must try to keep this >> > percentage under 6.5% in order to get better odds at not >> > developing complications. Because I could not find a tool to do >> > this, I came up with one of my own by working a formula to >> > estimate the average blood sugar using HbA1c. >> > >> > I created a small one page site for people to go download it. I >> > would appreciate it if people with data and an actual HbA1c >> > test result would try it out and tell me how accurate it is. >> > >> > The spreadsheet can be found here: >> > >> > http://www.loanuniverse.com/Diabetes/ >> > >> > I await your feedback. >> > >> > P.S: I am sorry for the cross-posting but I tried to keep the >> > posts limited to those groups that have a lot of diabetics as >> > users. >> >> FollowUp set to m.h.d. >> >> You cannot make a sensible estimate of A1c from finger stick >> records. There are several issues, I'll just give a short >> summary. >> >> 1. Sampling bias. If you take, for example, only fasting and >> pre-meal glucose tests you will get a very different average than >> if you take only 2 hour post prandial tests. This is called >> sampling bias. Worse than that, different types of diabetes and >> different types of treatment will vary the sampling bias >> differently. A type 2 treated with exercise and diet will likely >> have higher postprandial bg levels than preprandial. For a type >> 1 with a tight basal/bolus regimen with a fast acting prandial >> insulin, 2 hour postprandials can be the lowest bg levels of the >> day. Sampling bias is a difficult issue. >> >> 2. Sampling rate. If you assume three meals/day and the >> possible occurrence of some events overnight (dawn phenomenon, >> Somoygi), you can think of a time series of blood glucose as >> having 4 major cycles/day. This is, of course, over simplified. >> Elementary sampling theory will tell you that you need at least 8 >> samples/day to characterize the signal. As with most theoretical >> constructs, elementary sampling theory gives an answer which is >> insufficient for any real practical use. The practical answer >> depends on a number of factors, not the least of which is how big >> you want the error bars to be, but very few data analysts would >> be happy with less than twice the theoretical limit, i.e. 16 >> samples/day. >> >> Worse than this, if you look at any MiniMed 3 day continuous >> blood glucose record you will be able to see that there is much >> variation in bg at much higher frequencies than the 4 cycles in >> the simple picture above. This, of course, drive up the number >> of samples/day required to get a sensible average. >> >> 3. Normal range. Every lab has its own normal range. There is >> a movement to standardize on the DCCT normal range (4.0%-6.0%) >> but it is progressing very slowly. Even if your spread sheet >> worked, it would work for only labs with the same testing >> methodology as your lab and the same normal range. Different >> methods for assaying A1c actually measure slightly different >> things, so the comparison between labs is difficult. >> >> 4. Many of the attempts to correlate daily bg testing rely on >> the data published by the DCCT. They did a correlation between a >> 7 stick regimen (3 preprandial, 3 postprandial, and 3 am) and >> A1c. Ignoring sampling rate considerations, it was an attempt to >> correlate a standard testing pattern and A1c in a specific >> population. It is difficult to get even that limited objective >> accomplished. Several years after the original publication, they >> found they had botched the original analysis and published a >> correction. Most of the existing charts of bg vs. A1c are based >> on the original analysis. >> >> There are other more arcane technical issues, but the bottom line >> is you just can't get there from here. Note, that for an >> individual with stable blood glucose patterns it is quite >> possible to develop a correlation between A1c and a stable >> pattern of bg measurements. If the bg pattern changes, however, >> in a way masked by the sampling interval or bias, then the >> resultant A1c changes will not be predicted by the correlation >> which is no longer valid. This makes it, at best, a futile >> exercise and, at worst, a misleading indicator. The correlation >> will not, in general, be valid in any other diabetic. >> >> -- >> ------------- >> Charly Coughran >> ccoughran@DELETE_TO_REPLY_UCSD.EDU > > 1 2 Next » Related Discussion: Aleve heart attack and stroke (1 posts) Health (1 posts) Baxter Infusion Pump problem (1 posts) The rising costs of healthcare (3 posts) Top Discussions From Our Archives Grafts help heal diabetic foot ulcers Duragesic fentanyl patch overdose Pain-Relief Patch Is Investigated in Patient Deaths Carbs, low-carbs: A Mayo Clinic specialist cuts through the confusion Please stop psychiatry violence Other Discussion Categories Diabetes Symptoms Health Care Policy Health Care Providers HMO Arthritis Symptoms Oops!!! Unexpected Error While Reading the Feed
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