Second pass at: Fasting versus non-fasting and which tests care

On the subject in the title: Second pass at: Fasting versus non-fasting and which tests care Working notes rather than a conclusion.

General question, not a request for advice about my own care — I know the difference and I would rather be told to see my prescriber than get an answer that pretends otherwise.

I have a panel in front of me with one value outside the reference interval and everything else within it. My instinct is that a single out-of-range result on a single draw is close to uninformative, and I would like to understand how the people who read these professionally think about that.

What I am actually asking is how to tell an interesting result from an uninteresting one before booking an appointment about it.

I read the opening post twice before replying, because I had assumed the opposite.

Renal function markers: eGFR is estimated, not measured. It depends on creatinine, age, and weight. A small change in creatinine might not mean a real change in kidney function.

I disagree with the reply above, and I think the disagreement is substantive rather than terminological.

The distinction being drawn does not survive when you look at the published data for this specific question. I would be glad to be shown wrong on this, because the version I am arguing against is more convenient.

HbA1c and glucose: HbA1c reflects average glucose over months; a spot glucose measurement reflects the moment. Trending glucose downward while HbA1c stays flat is a different picture than glucose going up with HbA1c.

Time of day: some biomarkers vary across the day. Cortisol in the morning differs from cortisol in the evening. Comparing results from different times of day is comparing things that are not the same.

Coming back to post #4, because the follow-up matters more than the original answer.

Fasting state: some lab tests require fasting; others do not. Lipids on a fasting draw differ from lipids on a fed draw. Always note whether the test was fasting when comparing results.

Analytical imprecision: any measurement has an error margin. A small difference in consecutive tests is usually measurement noise, not a real change. Knowing the imprecision helps distinguish noise from signal.

Biological variation: the person-to-person variation in a biomarker for a healthy person is larger than most people realize. Comparing your result to the reference interval is one thing; comparing your result today to your result from months ago is more sensitive to change.

A single value outside interval: usually uninformative on a single draw. What makes a result interesting: a trend across multiple draws, a magnitude well beyond the interval, a pattern that coheres with other values, or symptoms that fit.

Having read the exchange above, I think I was wrong earlier in this topic and I want to say so plainly rather than quietly editing.

The correction was fair and I had been repeating something I had not checked carefully enough.

TSH and free hormones: TSH is a reasonable screening test but does not tell you about actual free hormone levels. If TSH is abnormal, free thyroid hormones confirm whether there is a real thyroid problem.

For anyone arriving from a search: the marked solution above is the direct answer, and the replies underneath it add the caveats that make it safe to use.

I read post #11 twice before replying, because I had assumed the opposite.

Reference intervals: constructed to contain the central 95% of a reference population, which means one in twenty healthy people falls outside one by definition. Add biological variation and analytical imprecision and the base rate of a meaningless flag is substantial.

This follows post #11 rather than contradicting it.

Lipid panel interpretation: total, LDL, HDL, triglycerides all on one panel. Reading them together is more informative than reading one value in isolation. An elevated triglyceride with low HDL is different from triglyceride elevation alone.