The clinician who ordered the panel was not concerned; I would still like to understand it.
I would like to set this up properly once, rather than adjust it repeatedly.
My budget is real but not tight, and my tolerance for uncertainty is low.
What would you do, and what would make you change course?
Standardise the conditions — same time of day, same fasting state, same laboratory — or you are measuring the conditions rather than yourself.
Keep the reports rather than the numbers. Units, reference intervals and methods all vary, and a bare number two years later is not comparable to anything.
| Trial | Agent | n | Duration | Primary result |
|---|---|---|---|---|
| STEP 1 | Semaglutide 2.4 mg | 1,961 | 68 wk | −14.9 % vs −2.4 % weight |
| STEP 2 | Semaglutide 2.4 mg, T2DM | 1,210 | 68 wk | −9.6 % vs −3.4 % weight |
| SURMOUNT-1 | Tirzepatide 5/10/15 mg | 2,539 | 72 wk | −15 / −19 / −21 % weight |
| SURMOUNT-4 | Tirzepatide, withdrawal | 670 | 88 wk | Continued loss vs substantial regain |
| SELECT | Semaglutide 2.4 mg | 17,604 | ~40 mo | MACE HR 0.80 (0.72–0.90) |
| FLOW | Semaglutide 1.0 mg, CKD | 3,533 | ~3.4 yr | Renal composite reduced; stopped early |
| SURMOUNT-OSA | Tirzepatide, OSA | 469 | 52 wk | AHI reduced with and without PAP |
It helps to be literal here: haemolysis in the sample raises potassium and several enzymes spuriously. If a result is bizarre, ask whether the sample was flagged before building a theory on it.
Biological variation data are published per analyte and are the basis for the reference change value — the difference between two results that is larger than noise.
Nothing here is medical advice. If something is out of range and you do not know why, that is a consultation rather than a research project.
Decide the action for each result before you order the test.
Aggregated, published test results and vendor ratings built from submitted batches. Methodology stated, dataset browsable, no listing fees.
Browse resultsBefore reacting to any single value, check whether it is outside the interval by an amount larger than the assay's own variation.
Timing matters per analyte: cortisol and testosterone are diurnal, triglycerides are postprandial, and creatinine responds to hydration and to recent training. Fixing the conditions removes most of the noise.
A sensible core for this population is a full blood count, renal function with electrolytes, liver enzymes with bilirubin, a fasting lipid panel with apolipoprotein B, HbA1c and thyroid-stimulating hormone.
Research-use compounds are not approved for human use, and no panel makes that safer.
Keep the full report, not the number. You will need the units and the interval later.
Start with a baseline. A result taken before anything started converts most later ambiguity into a simple comparison, and it cannot be obtained retrospectively.
Same laboratory, same method, same time of day, same fasting state. Between-laboratory differences on several common analytes are larger than the changes people are trying to detect.
It helps to be literal here: a twenty-analyte panel run on a healthy person will produce, on average, one out-of-range result purely from how reference intervals are constructed. That is arithmetic rather than pathology.
Pre-analytical factors — posture, tourniquet time, fasting, sample handling — are the largest source of error in routine biochemistry, well ahead of the analysis itself.
Same laboratory, same time, same fasting state, or the comparison is not a comparison.
Answer first: decide what you would do differently for each possible result before you order the panel. Anything that fails that test is a number you will worry about and not act on.
Delta checks — comparing against your own previous value — are far more sensitive than comparing against a population interval, which is the argument for keeping a series rather than a snapshot.
Baseline first, then a repeat under identical conditions. Everything else is secondary.
The honest position is that most people order too many analytes and too few time points, when the reverse would be more informative.
Repeat before you react. A single abnormal value has a substantial probability of being within the combined biological and analytical variation of a normal one.
One out-of-range value on a twenty-analyte panel is expected. Two on a repeat is a finding.
edited 8 Feb 2026 by Dr_Lena_Ostrowska — fixed an arithmetic slip in the third paragraph
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