Experiment Pre-Registration: Measuring the Effect of Sleep on the Blood Glucose Impact of Meals (Replication of Ilmo Stromberg’s Results)

Ilmo Stromberg just posted a fantastic write-up of 100 days of monitoring his blood glucose using a CGM. He had tons of interesting observations, but the three that stood out for me were:

  1. No correlation (R2=0.03) between average glucose and sleep score (Oura ring, R2=0.003)
  2. Slight correlation (R2=0.09) between last glucose value before sleep and deep sleep (Oura ring)
  3. Strong correlations (R2=0.36, 0.92, & 0.98) between total sleep the previous night and “meal scores” (a measure of the blood glucose impact calculated by the Veri app from the CGM data).

From my own data, I also haven’t seen a correlation between average glucose and time asleep, but I never thought to check impact on just meals to reduce noise in the measurement.

For the correlations with specific meals, Ilmo had a relatively small data set (3 meals, 4 datapoints each), but the effect was consistent and strong.

I’m interested to see whether I can detect the same effect. I eat a very consistent breakfast and relatively consistent lunch, so I should be able to get a statistically robust measurement in a relatively short time.

I’m pre-registering the experiment here for data quality & transparency and to get feedback on the experimental design.

Details

Experiment

  • Breakfast:
    • I will take 4.5u of Novolog (fast acting insulin, duration of 2-4h), wait 30 min., then eat 50g ketochow with 2 tbsp. of butter (website, BG testing).
    • This is my standard breakfast and insulin dosage and will be used every day.
  • Lunch:
    • I will take 3u of Novolog (fast acting insulin, duration of 2-4h), wait 15 min., then eat 50g ketochow with 2 tbsp. of butter (website, BG testing).
    • This is my standard lunch and insulin dosage when I’m not doing a food effect experiment. On days when I am doing a food effect experiment or otherwise need to deviate from this meal, I won’t record data.

Measurements

  • Blood glucose will be monitored using a Dexcom G6.
  • Sleep will be measured using the Oura Ring 3
  • For each meal, I will record:
    • Time of insulin injection
    • Amount of insulin injected
    • Time of meal
    • Any additional observations

Analysis

  • I will conduct an analysis after collecting 30 days of data. If the results are inconclusive, I will collect an additional 30 days of data and re-analyze.
  • Peak change in blood glucose and area under the curve will be calculated for the 2h after each meal.
  • Pearson R (with 95% CI) and p-value will be calculated for the following correlations:
    • Peak change in blood glucose vs. time asleep (breakfast & lunch)
    • iAuC vs. time asleep (breakfast & lunch)
    • Average daily glucose vs. time asleep (prev. night)
    • Average daily glucose vs. sleep score (prev. night)

Please let me know if you have any comments or suggestions on the experimental design.

I will start recording data immediately and will report out the results on March 12th


– QD

Experiment Pre-Registration: Testing the Accuracy & Convenience of Innovative/Interesting Blood Glucose Meters

A few weeks ago, I ran across the Pogo “all-in-one” blood glucose meter in this sub. I was intrigued by the concept of a meter that automated lancing, blood draw, and strip changing, so I tried it out. Unfortunately, I found it to be a less accurate and more painful than my trusty FreeStyle Lite meter.

There are a number of other meters I’m interested in trying out, so I decided to expand the study. I’m pre-registering the experiment here for data quality & transparency and to get feedback on the choice of meter and experimental design.

Does anyone have recommendations for interesting blood glucose meters they’d like to see me test?

Details

Meter Selection

To find blood glucose meters to test, I searched Google, Amazon, various diabetes forums, and posted to r/diabetes. I also looked at academic papers testing the accuracy of different meters, the most useful of which was a paper from Russell and co-workers. Based on this, I selected the following meters to test:

  • Control: FreeStyle Freedom Lite
    • This is the meter I’ve been using since I got diabetes ~10 years ago. It ranks 5th on accuracy in the paper from Russell and co-workers and requires very little blood, making it easy and quick to use.
  • Precision: Contour Next & OneTouch Verio Flex
    • These were the two most accurate and precise meters from the paper from Russell and co-workers.
    • The actual OneTouch meter from the paper was the VerioIQ, but that’s no longer available. The Verio Flex is a newer meter from OneTouch, so hopefully it’s as good or better.
  • Low-cost: ReliOn Premier
    • This is Wallmart’s low-cost meter. It didn’t perform well in the paper from Russell and co-workers, but it’s only $18 for 100 strips without insurance, so I’m interested to see how it compares.
  • Innovative Design/Functionality: Dario, Accu-Check Mobile, & Beta-Chek
    • All three of these have the meter, lancets, and strips contained in a single device, making carrying the meter much more convenient.
    • Pogo had the same promise, but was less accurate and more painful, so I’m really interested to see if these work better.
  • Meters that are of interest, but I can’t get: Beurer 50 GL Evo & Glucorx
    • These both look interesting, but are not available where I live. If anyone has a suggestion on how I can get them, I’ll add them to the experiment.

Experiment

  • I will test my blood glucose once per day for 15 days, rotating between three times: pre-lunch, pre-dinner, and before bed.
  • At each time, I will take 3 measurements with each meter and record the results from my Dexcom G6, along with any failed test strips and observations on convenience, pain, and other user experience.
  • This will result in 15 sets of 3 measurements for each meter, for a total of 45 measurements/meter or 315 total blood glucose measurements (more if I get additional meters).

Analysis

  • For each meter I will calculate the pooled standard deviation, bias (vs. Freestyle Freedom Lite), and mean absolute difference (vs. FreeStyle Freedom Lite).
  • All values will be reported with 95% confidence intervals & data will be visualized using Tableau.

Please let me know if you have any comments or suggestions on the choice of meters or experimental design.

The last meter should be arriving by February 13th, so I will report out the results on March 5th.


– QD

Inspiratory Muscle Training to Reduce Blood Pressure: Interim Results (No Effect so Far)

This post is an update on my experiment testing whether inspiratory muscle training reduces my blood pressure. Below is an interim analysis of the first 3 weeks of the 6 week, pre-registered experiment. So far, I’m seeing a large improvement in inspiratory muscle strength, but no effect on blood pressure. Not looking good, but hopefully I’ll start seeing an effect on blood pressure in the next few weeks.

Summary

  • Measurement Precision:
    • The Aerofit shows sufficient precision for measuring inspiratory volume and maximum inspiratory & expiratory pressure (see Table below), with a standard deviation < the week-to-week improvement.
  • Strength Improvement:
    • I was able to significantly increase the resistance setting on the PowerBreath. In week 1, I couldn’t complete the full set of breaths at setting 5. By week 3, I could do so for setting 6.25.
    • This correlated with a large increase maximum inspiratory & expiratory pressure, but a reduction in inspiratory volume.
      • Maximum inspiratory pressure: 81 -> 146 mmH2O
      • Maximum expiratory pressure: 87 -> 142 mmH2O
      • Maximum inspiratory volume: 5.2 -> 4.0 L
  • Blood Pressure:
    • Despite the large improvement in inspiratory muscle strength, I’ve seen a no improvement in my blood pressure in the first 3 weeks. In fact, it’s gotten slightly worse (see graph).
      • Systolic: 130 -> 132 mmHg
      • Diastolic: 80 -> 84 mmHg
  • Conclusions & Next Steps:
    • The experiment was pre-registered for 6 weeks, so I will complete the remaining 3 weeks and a full analysis of the results.


– QD

Methods

Pre-registration

Here.

Differences from original pre-registration:

  • I increased the PowerBreath setting by 1 unit per day until I was unable to maintain full pressure for all 5 sets. After that, I followed the pre-registered protocol of increasing by 0.25 when I was able to complete all 5 sets without struggle.
    • Reason: the lowest settings were way too easy and I wanted to get to a setting that would be a challenge more quickly.
  • AeroFit measurements frequency varies from the planned frequency of every 3 days.
    • Reason: I sometimes forgot.

Blinding

This experiment was not blinded

Procedure

  • Once per day, I did 5 sets of 6 breaths, with 1 min. rest in-between sets using the PowerBreathe HR.
  • If I struggled to complete all sets, I left the load setting as-is. If not, I increased by 0.25 turns of the load setting knob.
  • Every 3-5 days, I measured my maximum inspiratory pressure, expiratory pressure, and inspiratory volume using an Aerofit Pro.
  • Each morning at ~6am, I measured my blood pressure and pulse using an Omron Evolve

Measurements

  • Blood Pressure
    • Instrument: Omron Evolve blood pressure meter
    • Method:
      • For each measurement, I placed the meter on my left arm, ~4 cm above my elbow.
      • Measurements were taken seated, with my feet on the ground and arms resting on a flat surface at a comfortable height (same every time).
      • 5 measurements were taken with no pause in-between measurements (other than to write down the result) and the average of the 5 measurements was used.
  • Breathing:
    • Instrument: AeroFit Pro
    • Method:
      • Following the instruction in the AeroFit app
      • 3 measurements were taken with no pause in-between measurements (other than to write down the result) and the average of the 3 measurements was used.

Data Visualization

Data was visualized using Tableau.

Data

Link

Get new posts by email or rss feed

Testing the Pogo Blood Glucose Meter: Less Precise, More Painful, and Slower than the FreeStyle Lite

A few weeks ago I saw an article about an interesting new blood glucose meter, the Pogo Automatic Blood Glucose Meter. According to Pogo’s website, the device:

  • Contains the meter, lancets, and strips in a single, compact device
  • Automates changing of lancets and test strips
  • Automates pricking your finger, drawing of blood, and transferring the blood to the test strip
  • Uses less blood than traditional meters (0.25 μL)
  • Meets FDA accuracy requirements (±15% vs. reference meter)

Carrying around a bag with my meter, lancing device, extra lancets, and strips is mildly annoying, so the Pogo sounded like it could be a nice upgrade. To see whether the Pogo was a good as claimed, I bought one and tested it vs. my current meter (FreeStyle Lite) and CGM (Dexcom G6).

Summary

  • I tested 14 sets of 3 measurements each with the Pogo and FreeStyle Lite (98 total)
  • Good
    • The Pogo is very easy to use and could be a big improvement for someone with poor manual dexterity
  • Bad
    • Less reliable: 7 out of 49 failed measurements (14%) vs. 0 for the FreeStyle Lite
    • Less precise: standard deviation of 7 vs. 2.5 mg/dL for the FreeStyle Lite
    • Hurts more: both during lancing & caused sore fingers afterwards
    • Prolonged bleeding: often bled for >1 min. after lancing
    • Slow: >10s to take a measurement vs. <5s for the FreeStyle Lite

Overall, while having everything in a single device is convenient, it’s not even close to worth the poor reliability, reduced precision, and increased pain & bleeding.

Conclusion: I’ll be sticking with my FreeStyle Lite.

This is the first “product review” I’ve done and I’m curious if it’s interesting/useful for people. If you have diabetes or other quantified self products you’d like me to test, please let me know in the comments.

Details

Experiment

  • Over the course of 9 days, I did 14 sets blood glucose measurements and random times.
  • Each time, I took 3 measurements each with the Pogo and FreeStyle Lite, and recorded the result from my Dexcom G6.
  • I also recorded any failed test strips or other observations.
  • For each meter, I calculated the difference pooled standard deviation, bias (vs. Lite), and mean absolute difference (vs. Lite).

Raw data & analysis: link

General Observations

Good

  • It took me a couple tries to get the hang of the technique, but the Pogo is very easy to use. You just turn it on, press your finger on the lancing area, and the Pogo handles the rest.
  • The 10 strip/lancet cartridge is easily inserted into the device, no finesse required.
  • If you have poor manual dexterity, the fact that everything is automated might be a big advantage.

Bad

  • The Pogo is much slower than a normal meter. It takes a few seconds to turn on and waits a few seconds each before lancing and collecting blood. Overall, it takes >10 seconds to get a reading on the Pogo vs. <5 seconds on my FreeStyle Lite. Not terrible, but very noticeable.
  • Lancing hurts a lot more than my normal meter. This seems to be due to a combination of the fact that I can’t control the lance depth and that I’m not in control of when the lancing occurs, which is psychologically more difficult for me.
  • My fingers were often sore where I used the Pogo. I never had any soreness where I used the Freestyle Lite
  • The Pogo was less reliable in drawing blood. In 6 out of 42 tests (14%), the Pogo asked me to “milk” my finger for more blood.
  • Wounds from the Pogo often bled for much longer than my normal lancing device (sometimes >1 min). I had to be careful not to touch anything for a few minutes after testing to avoid getting blood on things.

Precision

Summary statistics are showing in the table above. The Pogo was:

  • Well calibrated: small and not statistically significant bias vs. the FreeStyle Lite
  • Less reliable: 14% failed tests vs. 0 for the Freestyle Lite
  • Less precise: standard deviation of 7.0 [5.0, 11.2] vs. 2.4 [1.8, 3.9] for the FreeStyle Lite

Importantly, the Pogo showed about the same mean absolute difference as the Dexcom G6, indicating that it wouldn’t add much value as a secondary check of my CGM, which is the main reason I carry a fingerstick meter.

Conclusions

See summary above.


– QD

Get new posts by email or rss feed

Inspiratory Muscle Training to Reduce Blood Pressure: Pre-Registration of Self-Experiment

On a previous post in my blood pressure series, u/OrganicTransistor suggested trying to strengthen my respiratory muscles based on the results in this paper by Seals and co-workers.

The paper, the authors report a pre-registered, sham-controlled, double-blind RCT of whether inspiratory muscle strength training lowers blood pressure. Here’s a quick summary:

  • 36 participants, all with blood pressure >120 mmHg systolic and no indication of uncontrolled diabetes, cholesterol, or thyroid disease or severe obesity.
  • Participants underwent 6 weeks of IMST using a PowerBreathe K3
    • Each week, the experimenters measured the participants max inspiratory pressure
    • The experimental group trained daily at 75% of max inspiratory pressure (5 sets of 6 breaths with 1 min. rest in-between)
    • The control group trained at very low resistance.
  • Results:
    • Systolic: experimental group saw a decrease of 9 mmHg systolic vs. 3 mmHg systolic for the sham-training group (P < 0.01 for difference of means).
    • Diastolic: experimental group saw a decrease of 2 mmHg systolic vs. 0 mmHg systolic for the sham-training group (P = 0.03 for difference of means).
    • Results were similar in magnitude and statistically significant when stratified by sex.
    • Effect persisted 6 weeks after training was stopped.

This is a huge effect size for blood pressure reduction. Given that it was pre-registered, blinded, and sham-controlled, I think it’s worth trying to see if it works for me.

Towards that end, I’m pre-registering the following self experiment:

  • Approach
    • I will replicate the published procedure as much as possible, with the following changes:
      • Instead of a PowerBreathe K3, I will use a PowerBreathe HR for training and an AeroFit Pro for measuring my progress
        • Reason: The K3 is ~$500, out of my price range for an initial replication
      • Instead of setting the resistance to a percentage of my max inspiratory pressure, I will increase the load until it is difficult to maintain steady, high pressure for the full 5 sets. Then I will increase by 0.25 turns of the load setting knob whenever I feel able to do so.
        • Reason: The HR does not have the ability to set a specific load force. The procedure I’m using is the one recommended for training in the PowerBreath HR manual
  • Procedure
    • Once per day, I will do 5 sets of 6 breaths, with 1 min. rest in-between sets using the PowerBreathe HR.
    • If I struggle to complete all sets, I will leave the load setting as-is. If not, I will increase by 0.25 turns of the load setting knob.
    • Every 3 days, I will measure my maximum inspiratory pressure, expiratory pressure, and inspiratory volume using an Aerofit Pro
    • Each morning at ~6am, I will measure my blood pressure and pulse using an Omron Evolve
  • Measurements
    • Blood pressure:
      • Instrument: Omron Evolve blood pressure meter
      • Method:
        • For each measurement, I will place the meter on my left arm, ~4 cm above my elbow. Measurements will be taken seated, with my feet on the ground and arms resting on a flat surface at a comfortable height (same every time).
        • 5 measurements will be taken with no pause in-between measurements (other than to write down the result) and the average of the 5 measurements will be used.
    • Breathing:
      • Instrument: AeroFit Pro
      • Method:
        • I will follow the instructions provided by the AeroFit app
        • 3 measurements will be taken with no pause in-between measurements (other than to write down the result) and the average of the 3 measurements will be used.
  • Analysis
    • Primary endpoints will be systolic and diastolic pressure for the week prior to and immediately after 6 weeks of training.
    • Secondary endpoints will be:
      • maximum inspiratory pressure, expiratory pressure, and inspiratory volume, and pulse for the week prior to and immediately after 6 weeks of training.
      • All primary and secondary endpoints every two weeks during training
      • If any significant effects are observed, I will continue tracking for an additional 6 weeks to see if the effect persists.
    • Effects will be considered of significant magnitude if a reduction of at least 3 mmHg is observed with a p-value of < 0.05.

These experiments started ~1 week ago, though I haven’t looked at the data. I expect to have the first interim analysis in 2 weeks and the full study results in 7 weeks.


– QD

Get new posts by email or rss feed