[2026 update] Thyroid function tests during substantial weight change posts 31–60
This is a continuation of a long topic, addressed by post number rather than by page. Start at post 1.
Collapsed as off-topic by two members at trust level 3 or above
I read post #30 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.
post #32 is right about the mechanism and I think understates the practical bit.
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.
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.
Coming back to post #34, because the follow-up matters more than the original answer.
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.
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.
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.
This follows post #36 rather than contradicting it.
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.
Two things before anyone answers the substance.
First, the context in the first post is clear and specific. Second, the question is framed so that an answer can actually address it. Both are the norm here and both matter more than they sound.
Picking up post #39: that is the part I would want checked first.
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.
Collapsed as off-topic by two members at trust level 3 or above
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.
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.
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.
Worth separating two things that post #43 runs together.
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.
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.
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.
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.
post #50 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.
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 #52 twice before replying, because I had assumed the opposite.
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.
post #54 answers the question as asked. The question underneath it is different.
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.
On post #52 — agreed on the reasoning, with one qualification.
Two things before anyone answers the substance.
First, the context in the first post is clear and specific. Second, the question is framed so that an answer can actually address it. Both are the norm here and both matter more than they sound.
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.
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.
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.