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c/bloodwork·posted 1 year ago by u/lina_falk

tried ApoB for 18 weeks. here is what happened.

Concerning Clean Column ×2 Well Actually ×1 Sourced ×1

tried ApoB for 18 weeks. here is what happened, which sounds obvious until you try to state the evidence for it.

To save the first four comments: 18 weeks.

Compared two draws across two labs and spent a week worrying before finding out the assays were different.

Added ApoB to the panel after a thread here. It told me something the standard lipid panel had been hiding.

If somebody has the same thing measured a different way, post it next to mine and we will see whether they agree.

6,272 up / 2,190 down74% upvoted51 commentsid 21xfeh23 Mar 2025

51 comments

17 in this archive, depth 4

best — the order this archive was captured in

u/emeka_chowdhury723 points·1 year ago

Repeat testing before acting is standard practice for a reason: regression to the mean does a lot of work on single outlying values.

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[removed]524 points·1 year ago

[removed by moderator]

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u/thermal_mass_tom151 points·1 year ago

Brought the whole set to my clinician rather than one flagged value. Completely different conversation.

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u/kaia_kuusela74 points·1 year ago

Same view — ApoB if you add one thing. It answers a question the standard panel only gestures at.

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u/mikkel_kimani121 points·1 year ago

Right, and weight loss itself moves several markers, so attribution is harder than these threads assume.

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u/cormac_erdogan302 points·1 year ago

Did anything else change in that window — training, intake, hydration?

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u/pavel_nkemelu446 points·1 year ago

Disagree with reading anything into that. One value, one morning, and you changed two other things in the same window.

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u/elin_varga129 points·1 year ago

Not convinced by the attribution. Weight loss alone moves that marker and you have no way to separate the two.

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u/isabela_guerrero106 points·1 year ago

Not convinced by the attribution.

This is the sentence to read before anybody panics about a single value.

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u/a1c_arcMOD275 points·1 year ago

Identifying header cropped from the report above. Post the values, not the name and reference number.

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u/nayeli_iyer365 points·1 year ago

Reference intervals are typically the central 95% of a reference population. By construction one person in twenty falls outside one on any given test without anything being wrong.

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u/gentle_correctionnice about it306 points·1 year ago

Agreed on assay changes. A lab switching platforms between your draws is invisible unless you ask.

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u/step_therapy_s212 points·1 year ago

The confounding problem, stated plainly, because this board keeps stepping on it.

Substantial weight loss moves lipids, liver enzymes, insulin sensitivity markers and several others in its own right. If you are losing weight while taking something, any change in those markers has at least two candidate explanations and you cannot separate them from your own panel.

What you can do is standardise, take a baseline, keep the series long, and be honest in your posts about what is and is not attributable. The threads that say "this compound did X to my TSH" almost never have the design to support the claim, mine included.

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u/baseline_drifteranalytical174 points·1 year ago

How many weeks between the two measurements?

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u/intent_to_treat-30 points·1 year ago

ApoB counts atherogenic particles rather than the cholesterol they carry, which is why it can diverge from LDL-C and why it is the addition most worth making.

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u/jarno_karlsen1 point·1 year ago

Different laboratories use different assay platforms with different calibration. Comparing across labs adds a systematic offset that is invisible on the report.

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u/vito_chowdhury1 point·1 year ago·edited

ApoB counts atherogenic particles rather than the cholesterol they carry, which is why it can diverge from LDL-C and why it is the addition most worth

Disagreeing with this bit: that change is confounded by the weight loss itself and cannot be attributed.

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About c/bloodwork

What to measure before you start, what to re-measure, and how to interpret movement without panicking. ApoB over LDL-C, HOMA-IR as a crude free tool, ALT and the fatty-liver story, eGFR noise during rapid loss, and the deficiencies that a 1,100-calorie appetite will hand you.

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