Baseline laboratory panel (revision 25)
Old revision·23:30, 15 Dec 2025·LipidLedgerLou
| Baseline laboratory panelLaboratory medicine | |
|---|---|
| Purpose | A comparator for later measurements |
| Principle | Same laboratory, same assay, same conditions |
| Common domains | Glycaemic, lipid, hepatic, renal, thyroid |
| List infobox · conventions | |
A baseline laboratory panel is the set of measurements taken before an intervention begins, so that measurements taken later have something to be compared against. Its value lies in the comparison rather than in any individual value.[1]
The principle that makes a baseline useful is consistency: the same analytes, on the same assay platform, under the same collection conditions. A follow-up measurement from a different laboratory may differ from the baseline by more than the intervention changed it. See Fasting insulin for the clearest example of between-assay variation.[2]
The panels discussed in this field typically span glycaemic markers, a lipid panel, hepatic and renal function, and thyroid function, with additions according to the question being asked.[1]
Common components
[edit]| Domain | Typical analytes |
|---|---|
| Glycaemic | Haemoglobin A1c, fasting glucose, Fasting insulin |
| Lipid | Lipid panel, Apolipoprotein B where available |
| Hepatic | Alanine transaminase, Gamma-glutamyl transferase |
| Renal | Creatinine with eGFR, Urine albumin-to-creatinine ratio |
| Thyroid | Thyroid function test |
| Other | Vitamin B12 status, High-sensitivity C-reactive protein |
The table lists analytes that appear in the literature and in the panels people discuss; it is not a recommendation, and which measurements are appropriate for any individual is a clinical question this wiki does not answer.[1]
Derived indices such as HOMA-IR are computed from panel components rather than measured, and inherit the properties of their inputs.[2]
Why consistency matters more than completeness
[edit]A large panel measured inconsistently is less informative than a small one measured consistently. Between-assay differences, fasting state, time of day, recent illness and recent exercise all move values by amounts comparable with the changes being looked for.[1]
Reference intervals are laboratory-specific, derived from that laboratory's own population and assay. A value described as "out of range" is out of that laboratory's range, and a value from another laboratory may sit differently against its own.[2]
Regression to the mean operates on any value selected for being extreme. A repeat measurement after an abnormal one tends to be closer to the mean whether or not anything was done in between — which is why a single abnormal value is weaker evidence than a trend.[3]
Interpretation over time
[edit]The useful output of a baseline is a trajectory. A single follow-up value tells less than a series, and a series on a consistent platform tells more than a longer series across several.[1]
Some analytes move quickly and some slowly. Glycated haemoglobin reflects roughly the preceding three months and cannot show a change over three weeks; lipids respond within weeks; body-weight-associated changes follow the weight.[4]
Nothing on this wiki is medical advice, and compounds sold for research use are not approved for human administration. This article describes a measurement practice, not a monitoring protocol.[1]
See also
References
- ^ a b c d e f American Diabetes Association. "Standards of Care in Diabetes." Diabetes Care 47(Suppl 1) (2024).
- ^ a b c Wallace TM, Levy JC, Matthews DR. "Use and abuse of HOMA modeling." Diabetes Care 27(6):1487–1495 (2004). PMID 15161807.
- ^ Hróbjartsson A, Gøtzsche PC. "Placebo interventions for all clinical conditions." Cochrane Database of Systematic Reviews (1):CD003974 (2010). PMID 20091554.
- ^ Drucker DJ. "Mechanisms of action and therapeutic application of glucagon-like peptide-1." Cell Metabolism 27(4):740–756 (2018). PMID 29617641.