Lactate, the early warning signal.
The true metabolic crystal ball. The canary in the coal mine for metabolic-flexibility drift, years before HbA1c catches up.
A walkthrough on continuous lactate monitoring: how the signal works, where it fits as an early warning of metabolic-health drift, what is mechanistically defensible, what is still in front of us, and where Via Negativa Health will and will not go on this conversation.
Read the substrate. Read the asymmetric-risk argument. Read the validation pathway. Read where the engagement starts.
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The substrate
Lactate is not a waste product. It is a central metabolic intermediary.
For most of the twentieth century, lactate was taught as muscle waste, the byproduct of incomplete glucose breakdown when oxygen ran short. That picture is wrong.
Brooks 2018 in Cell Metabolism reframed lactate as a central metabolic intermediary. The lactate-shuttle work showed that lactate moves continuously between cells, tissues, and organs, carrying energy and carbon from where it is made to where it is needed. Fast-twitch muscle fibres produce it; slow-twitch fibres consume it. The liver clears some of it back to glucose via the Cori cycle. The brain uses it as preferential fuel under load. The heart runs on it during exercise. Lactate is the body’s metabolic currency, not its rubbish.
That reframe matters for what we are about to ask of a continuous lactate device. A continuous lactate signal is not a continuous reading of metabolic damage; it is a continuous reading of how well the body is shuttling energy between systems. Metabolic flexibility, the capacity to switch fuels and clear lactate cleanly, is the underlying capacity the signal measures.
The asymmetric-risk argument
Why lactate is a different signal from CGM-for-insulin-dosing.
A continuous glucose monitor that informs an insulin dose lives in a high-risk asymmetric market. The action a person with type 1 diabetes takes on a single reading is a clinical action. The tail of that action is the rare individually catastrophic hypoglycaemia, the rare DKA event, the rare nocturnal under-correction. Wrong calls do not just inconvenience; they kill, occasionally. The accuracy bar is calibrated to that tail. Pemberton 2026 in Diabetes, Obesity and Metabolism lays out the operational shape of that bar; the DSN Forum UK CGM Framework v2 carries the same logic into a chart-of-five every clinician can read.
Continuous lactate sits in a different place. The action a user takes on one lactate reading is a behavioural action: a training adjustment, a session-pacing choice, a conversation with their care team about a pattern. No instant insulin dose follows from one lactate reading. The asymmetric-risk tail is not the same shape.
The wrapper around a continuous lactate sensor is a different shape from the wrapper around a CGM-for-insulin-dosing platform. The accuracy target loosens, the gamification model changes, the regulatory class can sit in a different place, and the route to market can prioritise sports and performance as a commercially mature on-ramp before broader metabolic health. The design has to sit on that asymmetry, not around it.
The canary framing
The canary in the coal mine. What is mechanistically defensible. What is still in front of us.
The canary framing rests on three pillars.
Brooks 2018, the substrate anchor, established lactate as the body’s energy currency. San-Millán and Brooks 2018 in Sports Medicine established lactate threshold and metabolic flexibility as the canonical sports-physiology marker. In athletes the signal is strong, well-validated, and reproducible. The deeper observation, the one that drives the canary framing, is that metabolic flexibility is the same physiological capacity that erodes years before fasting glucose drifts and before HbA1c rises. Broskey 2024 in Diabetes & Metabolic Syndrome extends the lactate signal into the metabolic-health context. Resting lactate, post-load lactate, and lactate kinetics correlate with insulin resistance, fatty-acid handling, and the impaired-fasting-glucose / impaired-postprandial-glucose / pre-type-2-diabetes progression arc.
The mechanistic case is defensible. The lead-time observation is not yet a closed finding. The mechanistic case suggests metabolic-flexibility decline precedes glycaemic decompensation by years. The longitudinal validation against HbA1c progression in cohorts comparable to existing IFG, IPG, and pre-T2D registries is the work that would convert mechanism to evidence. The specific lead-time figure, in months and years, is what that work would quantify. Via Negativa Health does not yet have that figure as a closed finding, and any walkthrough that gives you one is over-claiming.
That is the headline. The crystal ball is mechanistically defensible. The longitudinal evidence is still in front of us.
Three signals, not one
Baseline, activity, and the transition between them.
The natural framing of a continuous lactate device parallels the fasting-versus-postprandial-glucose distinction familiar from glycaemic care, but with three signals, not two.
The first is the baseline signal: overnight and pre-activity lactate, when the user is at rest. This is the signal the broader-metabolic-health story rests on, and it is also the signal where the published gen-pop sedentary distribution is documented least well. The clinical and athlete populations have deeper anchors; the sedentary baseline distribution is a real evidence gap.
The second is the activity signal: lactate during exercise. This is the signal with the deepest published anchor across all three. Brooks 2018 and San-Millán and Brooks 2018 carry it. Sports and performance positioning sits naturally here, and it is the commercially mature on-ramp for any continuous lactate device.
The third is the transition signal: the gradient and the speed from baseline to activity, and back to baseline. This is the metabolic-flexibility marker proper. The capacity to switch fuels cleanly, to spike lactate when the demand arrives, and to clear it cleanly when the demand subsides, is what metabolic flexibility looks like in numbers. In athletes the transition signal has a strong anchor. In gen-pop sedentary and pre-T2D populations the literature is thinner.
Four metabolic-flexibility profiles, paired with their HbA1c band. The same two 30-minute walks (10:00, 15:00) trigger progressively higher peaks and progressively slower clearance as the HbA1c band rises.
Healthy
HbA1c <5.7%
<39 mmol/mol IFCC
10+ years out from a T2D diagnosis. Baseline low (~0.3 mmol/L), peak ~1.8, clearance fast.
Pre-T2D
HbA1c 5.7–6.4%
39–46 mmol/mol IFCC
Around 5 years out. Baseline raised (~0.5), peaks ~2.2, slow clearance, residual elevation between walks.
T2D at diagnosis
HbA1c ≥6.5%
≥48 mmol/mol IFCC
Elevated baseline (~1.0), peaks ~3.0–3.4, impaired clearance, plateau between walks.
Uncontrolled T2D
HbA1c 8.0%
64 mmol/mol IFCC
Established disease. Baseline high (~1.5), peaks ~3.2–3.7, minimal clearance, plateau across the day.
HbA1c shown in DCCT-aligned % and IFCC mmol/mol. Conceptual lactate traces (mmol/L); not patient-specific.
Each of these three signals has its own population-specific calibration. A continuous lactate device that treats them as a single signal flattens the information; a device that surfaces them separately, with per-signal honesty about what is known, is doing the work the evidence supports.
The validation pathway
How HbA1c becomes the validation comparator.
If a continuous lactate device wants to claim broader-metabolic-health usefulness, it has to prove itself against a comparator everyone trusts. HbA1c is the natural choice. It is the metric every clinician understands, every guideline references, and every patient sees on their summary.
HbA1c also has known discriminatory limitations in defined sub-populations: iron deficiency anaemia, haemoglobinopathies, recent transfusion, erythropoiesis variation, pregnancy. The discriminatory power is eroded in these contexts. That is part of the case for an additional signal that is not red-cell-dependent. But HbA1c remains the benchmark.
The principle is simple. The execution is not. A longitudinal cohort that tracks lactate metrics alongside HbA1c year-over-year, across normoglycaemia, the impaired-fasting-and-postprandial-glucose middle, early T2D, and insulin-dependent T2D, would tell us how predictive the lactate signal actually is. The cohort design, the primary endpoint framing, the secondary endpoints, the sample-size rationale, the ethics framework, the pre-registration approach are work Via Negativa Health designs under engagement with the manufacturer building the device. The specific design is not on this page. The principle is.
The gamification question
What could “time in normal lactate range” mean.
Continuous glucose monitoring has a single dominant gamification metric: time-in-range. The 3.9 to 10.0 mmol/L range (70 to 180 mg/dL) is the international consensus target, and percent-time-in-range is the metric a person with diabetes sees on their phone, talks about with their clinician, and tracks across weeks.
Continuous lactate does not yet have an equivalent. The question is what such a metric should look like.
The shape of the answer has several candidates. Time-in-normal-lactate-range, defined in the absence of activity, is the natural analogue: a percentage of overnight and rest hours where the lactate signal sits inside a reference distribution. Baseline-relative scoring compares the user’s current pattern against their own baseline window, surfacing drift rather than absolute level. Transition-gradient scoring rewards clean and prompt lactate clearance after activity, which is what metabolic flexibility looks like in numbers.
The metric matters because it drives behaviour change. A user who can see a clear, personally-relevant signal moving in response to their actions has a feedback loop. A user looking at numbers they cannot interpret has noise. The metric has to be tight enough that it moves on real change and loose enough that it does not panic on transient variation.
The specific Via Negativa-designed metric, the cut-points, the display logic, and the alert thresholds are work that lands under engagement with the manufacturer building the device. This walkthrough surfaces the question; the engagement holds the answer.
The unit-measurement question
mmol/L is the clinical scale. nmol/L is a million times finer.
Whole-blood and plasma lactate is currently measured in millimoles per litre (mmol/L). Typical resting values sit around 0.5 to 1.5 mmol/L; light exercise lifts to 2 to 3 mmol/L; the lactate threshold in athletes runs around 4 mmol/L; sepsis triggers run above 4 mmol/L. The clinical scale is built around these numbers.
A continuous wearable lactate sensor with the right electrochemistry could in principle report at a much finer resolution. Reporting in nanomoles per litre (nmol/L) would surface variation a thousand-fold smaller than the current clinical scale shows. The question is whether the additional resolution carries signal or carries noise.
The trade-offs sit on three axes. Accuracy. The sensor’s accuracy bar has to be tight enough that the finer resolution carries real biological signal and not electrochemical noise. Clinician fluency. Clinicians, guidelines, and existing literature are built around mmol/L. Reporting in nmol/L means the device speaks a language the rest of the system does not. Behavioural usefulness. Does the user actually need finer resolution to change behaviour, or does the existing clinical scale already carry enough signal for the time-in-normal-range pattern to work.
The answer is not yet locked. The walkthrough surfaces the question because the answer shapes the device, and the device shapes the engagement. Reporting in mmol/L with a tight accuracy bar may turn out to be the right answer; reporting in nmol/L with a clear translation layer back to mmol/L may turn out to be the right answer; reporting in both, switching between them by use-case, may turn out to be the right answer. The engagement work resolves it.
Tail risks
The asymmetric-risk frame loosens, but the tails do not disappear.
The tails of elevated lactate include cases a wearable cannot adjudicate alone.
- Sepsis. Lactate is the marker of choice on the Sepsis-6 bundle, and a person fighting sepsis has elevated lactate for a reason that has nothing to do with metabolic flexibility.
- Hepatic dysfunction. Impaired lactate clearance lifts the baseline.
- Mitochondrial cytopathies. Primary disorders of oxidative phosphorylation.
- B12 and thiamine deficiency. Substrate-driven elevation.
- Post-exercise rebound. Transient elevation that is physiological, not pathological.
- Medications. Metformin in renal impairment, certain antiretroviral therapies, propofol infusions in specific clinical contexts.
The structural protection. An elevated baseline lactate over a defined window prompts a “talk to your care team about this pattern” route, not a “do X” route. The device surfaces context (recent exertion, recent illness, sleep, medication start dates) before it surfaces a flag. The user-education layer names the alternative causes in plain English.
The routing-to-care-team mechanism is non-negotiable on any continuous lactate device that extends beyond the sports and performance positioning. A wellness app that reassures a person fighting sepsis with “your lactate is improving” is a worse outcome than no device at all. This is the safety architecture that lets a continuous lactate device serve the person rather than the principal of the work. It is a feature, not a constraint.
Where we will not go
The refusals stated up front.
Via Negativa Health is a Via Negativa company. Clarity by subtraction, not coverage by addition. The work that is in scope is in scope because we can defend it; the work that is out of scope is out of scope because we cannot. We say so before the conversation starts.
CGM for non-diabetes wellness
Via Negativa Health does not work continuous glucose monitoring for the non-diabetes-wellness market. Accuracy in the usual glucose range is not good enough to discern signal from noise for a person without diabetes; the Type 1 and Type 2 error rate is too high for the population taking action on it. Continuous lactate sits in a different place because the mechanistic case is different and the asymmetric-risk tail is different.
Insulin-dosing decisions from a lactate signal
A continuous lactate signal is not an insulin-dosing input. It is a context signal that informs behaviour and care-team conversations. The dose decision in T1D is a CGM-driven decision; Via Negativa Health is interested in lactate paired with CGM for insulin dosing as a context layer alongside the dose, never as a primary input.
Lactate as preventive or curative for type 2 diabetes
Lactate is a discriminatory signal. A discriminatory signal that detects metabolic-flexibility drift earlier than HbA1c is a useful tool for routing a person to a clinical conversation and to behaviour-change support. It is not a preventive intervention and it is not a cure. Devices, apps, and copy that frame lactate as therapeutic are over-claiming, and Via Negativa Health refuses to support that framing.
Closed lead-time claims without the longitudinal evidence
The mechanistic case suggests metabolic-flexibility decline precedes glycaemic decompensation by years. The specific lead-time figure in months or years is not yet quantified in published longitudinal cohorts. Via Negativa Health will not publish a headline lead-time figure as a closed finding until the validation work runs. Until it runs, the framing stays mechanistic-case + validation-pending.
FDA-route as lead regulatory frame
Via Negativa Health’s regulatory focus is CE marking and UKCA marking. For an engagement that needs an FDA pathway in addition, we either run CE-only with a written carve-out or refer the FDA work to a partner consultancy with that specialism. The reason is structural: 510(k) / De Novo / PMA depth is not where the substrate sits.
How we work on this
If you are a manufacturer building a continuous lactate device.
If you are a person living with diabetes or a clinician working in the diabetes space, lactate is unlikely to be a daily-life metric for you in 2026. The technology is not yet there in shape. What is in front of us, in the next five to ten years, is the slow arrival of continuous lactate as a wearable signal, alongside CGM, alongside heart-rate variability, alongside sleep. This walkthrough is our position on how that signal should be framed when it arrives, so that it serves the person and not the device.
If you are a manufacturer building a continuous lactate device, the work Via Negativa Health does is the wrapper. The accuracy-evaluation paradigm. The canary narrative. The validation pathway against HbA1c progression. The gamification metric. The unit-measurement question. The routing-to-care-team mechanism. The regulatory positioning under CE or UKCA. Each of these sits on the same substrate authority: a published CGM accuracy and transparency line stretching from Pemberton 2023 to Pemberton 2026, ten years of paediatric T1D clinical practice anchoring the asymmetric-risk frame, and a Grace evidence engine that holds the depth on demand.
If you are a researcher or a standards body and you want a conversation about how the methodology should land, that conversation is open. The IFCC consultation routes work the way they always have: publish, build the evidence base, attend the right scientific meetings, contribute to standards discussions, and let the Working Group reach you on the merits.
Manufacturer enquiries on continuous lactate route through the single inbox. The first conversation is rarely about what we sell; it is about whether the engagement fits the substrate. No tier sheet, no commitment, no expectation of payment for an introductory call.
Start a scoping conversation Read the services pageOne inbox: john@theglucoseneverlies.com
This page is an educational walkthrough on continuous lactate monitoring. It is not medical advice and cannot replace individual clinical guidance from your diabetes care team or general-practice team. Devices referenced are described at the concept level; specific accuracy figures and validation outcomes belong to the device manufacturers and to peer-reviewed publications.