Do your lab results fit the pattern?

Hey Reader, Dr Karl here.​
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​Let me introduce you to a different perspective of looking at your lab results with the aim being it will change how you use your results to understand your health… and what action you may need to consider taking.
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Certainly my position has changed over the last 14 years. Having to save your own life has a way of doing that.
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What’s changed exactly? The cloud of collective data has grown from working with clients over the years… a lot.
The database of collective results of a large LabCorp panel has revealed what factors to focus on for long term health, Health span & Lifespan, on a per person basis.
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Here’s how:
When analyzing a person’s lab results, I set their results against the ‘Lab Patterns’ of the group, matched to specific factors like age, insulin-resistance status, blood type, genomics… and show them where their results land among people who look like them on paper.

The part that matters most: where they deviate. When your data sits where the pattern says it shouldn’t for someone with your profile, that’s not noise. That’s the signal — the thing worth chasing. A reference range can never show you that, because a reference range compares you to everyone. I compare your lab results to each other NOT TO A GENERIC RANGE for that single lab test.
Here’s an example of three lab results from my recent lab work. How your doctor sees it and how I see it.

My glucose is in the pre-diabetic range.
My triglycerides are insanely low, and
my HDL would be considered over the top. ​
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The ‘Wow’ Factor That’s why I’m writing. My data laid over today’s cohort would reveal something most doctors have never seen. It’s not a number against a range, but the pattern of my results against the collective pattern.
The question I want to answer is: Do my results fit the pattern?
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​Let’s look.
​I compare fasting glucose (on the bottom) to HDL and Triglycerides.
​Dashed lines are Insulin resistant people Solid lines are Non-Insulin Resistant people

Notice the different patterns between Non IR (non insulin resistant) and IR-people (insulin resistant) groups. They have completely separate patterns …. How’s that possible?

“Set against people like me, my pattern lands squarely in the non-insulin-resistant group; that ‘pre-diabetic’ glucose isn’t what it looks like”

One more thing worth mentioning. This past year I wrote two books on exactly this — how to read the relationships in your own Lab work instead of chasing one value at a time. The thinking on the table is now written down. Another book is on the way for even more granular lab data pattern interpretation to aid you in your pursuit of understanding your health.

I’ll send a couple more notes in the coming weeks on what these overlays reveal. If you already want your numbers read against the dataset again with new lab work, just reply. I read every reply myself.

To your health,
Dr. Karl Goldkamp

Links to our published books are on our website​

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