This is a continuation of a long topic, addressed by post number rather than by page. Start at post 1.
post #30 is right about the mechanism and I think understates the practical bit.
Thank you for the correction. I have edited my earlier post with a note rather than silently, so the thread still makes sense to read. The error was mine and it was the kind that comes from remembering a figure instead of looking it up.
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.
I read post #32 twice before replying, because I had assumed the opposite.
Liver enzymes: elevation does not specify cause. ALT and AST can rise from many things. Bilirubin helps narrow down the cause. Multiple markers together are more informative than one alone.
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.
Picking up post #34: that is the part I would want checked first.
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.
Coming back to post #36, 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.
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.
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.
Worth separating two things that post #37 runs together.
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.
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.
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.
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.
Picking up post #45: that is the part I would want checked first.
Thank you for the correction. I have edited my earlier post with a note rather than silently, so the thread still makes sense to read. The error was mine and it was the kind that comes from remembering a figure instead of looking it up.
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.
post #49 is right about the mechanism and I think understates the practical bit.
Liver enzymes: elevation does not specify cause. ALT and AST can rise from many things. Bilirubin helps narrow down the cause. Multiple markers together are more informative than one alone.
I read post #50 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.
post #52 is right about the mechanism and I think understates the practical bit.
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.
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.
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.
post #56 answers the question as asked. The question underneath it is different.
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.
On post #54 — agreed on the reasoning, with one qualification.
Practical note that does not fit anywhere else. Whatever you conclude from this topic, write down what you did and when. The single most useful thing in your own records is not any individual result; it is that they are dated and consecutive.
This follows post #56 rather than contradicting it.
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.