CGM Device Guide and Teaching Resource
Roche Accu-Chek SmartGuide
9.32pm, midweek. The SmartGuide app lights up before bed: raised probability of glucose under 3.9 between now and the small hours. A small carbohydrate top-up, an alarm set with a wider safety net, and a settled night. The same app gave a 30-minute heads-up earlier in the day, and a two-hour forecast curve before an evening meal that did not quite behave. The SmartGuide is the only CGM in this cluster carrying three prediction layers as a labelled feature, and the overnight one is the layer most people name first.
This page works two ways. The first half is the device profile: framework status, accuracy, prediction layers, AID compatibility, the practical features. The second half is a teaching guide, built around the first UK clinical evaluation Amy Jolley ran in May 2026 (17 people, one week, structured group format). The teaching guide is for anyone bringing the SmartGuide into a clinic, a school, or a family. A printable A4 resource is linked below for clinic packs and onboarding sessions.
Ask Grace
Want to ask how the three prediction layers work in practice, or what the overnight risk score does and does not see? Ask Grace.
“Do not oversell the two-hour accuracy. If you do, people will hate it.”
John Pemberton, GNL Podcast Episode 40. The 45-minute window is the action window; the 45-minute to 2-hour stretch is awareness, not action. Parkes A+B agreement on the 2-hour Glucose Predict curve: 99.3% at 45 minutes, 96.3% at 2 hours (Herrero 2024).
Framework status
Data sufficiency: Met. Mader et al. 2024, Journal of Diabetes Science and Technology, n=48, 139 sensors analysed across three German and Austrian sites. 48 participants sits at the lower bound of the threshold; the three-sensor-per-participant design supports the analysis.
First UK clinical evaluation. Amy Jolley, Lead Educator at the Diabetes Technology Network UK and lead for the Young Adult and Transition Service at Salford NHS, put 17 people onto the SmartGuide in a single week in May 2026 in a structured group evaluation, the first of its kind in the UK. The structured-onboarding format produced a teaching opportunity around day-one calibration and surfaced lived-experience observations on the prediction layers in real-world use.
Device specifications
The headline numbers sit in the framework card above. The full device profile is here for anyone who wants the detail.
Full device profile
Manufacturer: Roche Diabetes Care GmbH, Mannheim. Family: Accu-Chek SmartGuide CGM device, SmartGuide app, SmartGuide Predict app, AC Care HCP platform. CE marked: July 2024, MDR class IIa. UKCA non-adjunctive: MHRA, May 2025, 18 years and older. Wear duration: up to 14 days. Application site: back of the upper arm. Sensor profile: 5.9 mm height with adhesive, 5 g, 33.3 mm diameter on skin (Glatzer 2024). Reading interval: every 5 minutes via Bluetooth Low Energy. Run-in: one hour. Calibration: two paired finger-prick calibrations on day one (around 12 and 14 hours after insertion); factory-style operation thereafter. Display: Accu-Chek SmartGuide app on iOS and Android (no dedicated reader). Indication: non-adjunctive (no confirmatory finger-prick required for insulin dosing once calibration is complete). Age indication: 18 years and older. Hospital use: not intended.
The Predict app, separately. A second app, the Accu-Chek SmartGuide Predict app, is CE-marked MDR class IIa medical software in its own right. It carries the three prediction layers (30-minute, two-hour, overnight) and runs as cloud-supported inference on iOS and Android. The CGM app and the Predict app are distinct downloads with shared data flow.
Accuracy
Mader and colleagues (2024, Journal of Diabetes Science and Technology) reported the SmartGuide pivotal in-clinic accuracy: 90.5% within ±20/20, 99.7% within Parkes consensus error grid zones A and B, and 1.2% outside the ±40/40 safety band. The hypoglycaemia-range agreement (94.3% within ±20/20 below 3.9 mmol/L) is the strongest sub-range performance and a meaningful differentiator, since many CGM systems perform worst in the low range. The reported positive bias of approximately 11% below 3.0 mmol/L is worth knowing: a sensor reading of 4.5 may correspond to a slightly lower true value, so hypoglycaemia thresholds should not be relaxed on the assumption that the sensor over-reads. Cross-CGM agreement comparisons need a comparator-equivalence note: the SmartGuide pivotal used capillary blood (Accu-Chek Guide), Dexcom and Libre pivotals used venous YSI; comparator choice can shift apparent agreement by several percentage points. The full thesis lives on the accuracy page.
Three prediction layers
Three independent machine-learning models packaged into the Predict app (Herrero et al. 2024, Journal of Diabetes Science and Technology): a 30-minute hypo classifier, a two-hour glucose curve, and an overnight risk score. The framing matters. None of these prevents an event; each gives an earlier window to act.
Predicts the night, no AID partnership. The overnight risk score is the only one of its kind in this cluster. The trade-off the page sits on is between proactive overnight protection and access to algorithm-driven insulin delivery: SmartGuide does not yet pair with Omnipod 5, Tandem Control-IQ, CamAPS FX, or the MiniMed 780G. The prediction layers do not see exercise, alcohol, illness, or future meals or insulin doses; they are reactive to the data the user logs.
What the layers do not do. They do not see exercise, alcohol, or illness. They do not anticipate meals or insulin doses the user has not entered. The Night Low Predict model misses approximately 45% of overnight hypoglycaemia events at the published threshold, which is why the 30-minute Low Glucose Predict alarm is the active safety net during the night, not a substitute. Honest framing, in line with Roche’s own published descriptions: these layers reduce the likelihood of a low and give a window to act before one. They do not prevent.
What 17 people reported in the first UK clinical evaluation
Amy Jolley, Lead Educator at the Diabetes Technology Network UK and lead for the Young Adult and Transition Service at Salford NHS, put 17 people onto the SmartGuide in a single week in May 2026 and asked them to come back and report what happened. Two findings shaped the teaching order. First, the day-one calibration did not cause friction; it gave clinicians a concrete reason to re-establish the value of finger prick testing in a group setting. Second, two of the 17 reported stopping post-meal correction boluses entirely after seeing Glucose Predict show the glucose already coming down. The double-arrow-up reflex, the impulse to bolus immediately on a high reading, is one of the most persistent frustrations in T1D self-management, and the 45-minute action window from Glucose Predict gives a reason to wait.
Teaching the three prediction layers
A clinic-ready breakdown of what each layer does, what it does not do, when to teach it, and what to do when it fires. Open each layer in turn; the order below is the order the wearer should meet them in their first onboarding session. For the printable A4 version that drops into a group session pack, use the link below.
Open the printable A4 teaching resource
Layer 1, Low Glucose Predict, 30-minute hypo classifier (the active safety net)
What it does. Classifies the next 30 minutes as high-risk or not for hypoglycaemia. When high-risk, an alarm fires on the SmartGuide app.
What it does not do. It does not predict the size or depth of the low; it does not catch every event. It is reactive, not preventive.
When to teach it. First. This is the active safety net the wearer relies on while learning the longer-horizon layers.
What to do when it fires. Finger prick if uncertain, treat per usual hypo plan, plan the next 30 minutes (driving, meeting, sleep), re-check after the response window.
Pitfall. Wearers who silenced “predictive low” alerts on previous CGMs because they fired too often. The SmartGuide LGP fires meaningfully less; ask them to keep it on for two weeks before deciding.
Layer 2, Glucose Predict, 2-hour forecast (action plus awareness)
What it does. Projects a glucose trace 2 hours forward, with a 50% confidence band drawn around it. Refreshes every 5 minutes.
What it does not do. It does not see meals or insulin doses the wearer has not entered. It does not account for alcohol, exercise, or illness. A wide band means low confidence.
When to teach it. Second. Frame it as “the curve you plan around for the next hour, the curve you act on for the next forty-five minutes”. The split is the teach. Parkes A+B agreement is 99.3% at 45 min and 96.3% at 2 hours (Herrero 2024).
What to do when it lights up. 0 to 45 min, act on the curve direction (eat ahead of a low, defer a correction if a fall is shown). 45 min to 2 h, plan around it (meeting timing, drive, exam, run).
Pitfall. Selling the 2-hour mark as reliable. It is not. Wearers who treat the 2-hour endpoint as actionable will be disappointed quickly, and that disappointment is the form factor of a sensor falling out of routine wear.
Layer 3, Night Low Predict, 9pm-to-2am overnight risk score
What it does. Issues a Red, Amber, or Green prediction of overnight low risk between 9pm and 2am, refreshable every 20 minutes. Personalises over around 28 days of input data.
What it does not do. It is a population-level confidence band, not a personal probability. It misses approximately 45% of overnight hypoglycaemia events at the published threshold; LGP remains the active safety net during the night.
When to teach it. Third. The wearer should already trust the LGP alarm and the GP curve. The night plan is what unlocks confidence to sleep.
What to do when it lights up. Red, first half of the night (model ROC AUC 0.902): fast carbohydrates before bed are the option most aligned with the risk; discuss with the care team. Red, second half (ROC AUC 0.730, lower confidence): a conversation about protein, slow-acting carbohydrates, or a temporary basal reduction (if on a pump). Amber: re-check in 20 minutes, watch for trend.
Pitfall. Treating both halves of the night identically. The ROC AUC asymmetry means a red light at 1am and a red light at 4am are not the same signal. Land that at onboarding.
Practical exploration
For people living with type 1 diabetes and their families
The SmartGuide rewards a 28-day onboarding pattern that current CGM marketing does not always reflect.
- Night Low Predict needs around 28 days of input data before it reaches its full personalised accuracy. The first few weeks may be less reliable; do not draw conclusions from the first night.
- If the prediction shows red in the first half of the night, fast-acting carbohydrates are the option most aligned with that risk; discuss with your care team. If red in the second half, the model’s confidence is lower; protein, slow-acting carbohydrates, or a temporary basal reduction (if on a pump) are the conversations to have, again with the care team.
- You can re-request a Night Low Predict every 20 minutes between 9pm and 2am. If you take action, check whether the risk rating changes.
- The 45-minute Glucose Predict window is more reliable than the two-hour window (Parkes A+B 99.3% at 45 min vs 96.3% at 2 hours; Herrero 2024). Treat 45 minutes as an action window and the two hours as awareness and context.
- The predictions do not account for alcohol, exercise, or illness. Adjust your interpretation if any of these applies.
- If the worm is wide at two hours, confidence is lower. Do not treat it as a reliable forecast.
- The two day-one finger pricks (at approximately 12 and 14 hours after insertion) take a few minutes each and activate the full predictive features. Good hand washing and technique matter.
For clinicians and educators
The teaching shape of the SmartGuide differs from a standard CGM in ways that matter at the first appointment.
- Teach the first-half versus second-half distinction for Night Low Predict from the outset. The model’s ROC AUC is meaningfully higher for first-half risk than second-half (0.902 vs 0.730; Herrero 2024); the action menu and the confidence band differ accordingly.
- Group onboarding sessions generate richer learning than one-to-one. The calibration conversation lands differently when people hear from peers who still finger prick routinely.
- The mandatory day-one calibration is an opportunity to re-establish the value of finger prick testing, not a device drawback.
- Send people away to use it and come back to report. The most useful education comes from early adopters describing what they actually did, not from the manual.
- Current indication is adults 18 and older only. No paediatric licence and no AID compatibility in current form.
- The DTN Competency Assessment Framework is being uploaded to the DTN website shortly. It maps team skill mix against a four-tier national standard and links to annual appraisal documentation.
AID system compatibility
The SmartGuide does not currently pair with any AID system. For people on or considering Omnipod 5, Tandem Control-IQ, CamAPS FX, or the MiniMed 780G, the device choice is currently driven by the AID system first. The CGM Guide hub carries the AID compatibility overview across the cluster.
What SmartGuide brings beyond accuracy
Strong hypoglycaemia-range accuracy
The 94.3% within ±20/20 below 3.9 mmol/L (Mader 2024) is the strongest sub-range performance of any device in the cluster, and is unusual: many CGMs perform worst in hypoglycaemia. This sits well with the prediction layers, the device whose accuracy is best in the low range is also the one labelling overnight low risk before bed.
Mandatory day-one calibration
Two paired finger-prick calibrations on day one, taken around 12 and 14 hours after insertion. This is the structural difference from Dexcom and Libre, which are factory-calibrated end-to-end. The trade-off is real-world: an extra-step at start-of-wear in exchange for the day-one calibration anchor that supports the accuracy profile. After the first day, no further finger-pricks are needed.
AC Care, into the clinical record
The AC Care platform produces AGP-standard outputs (Time in Range, Glucose Management Indicator, coefficient of variation) for clinical review. As CGM grows in primary care for insulin-treated type 2 diabetes, having the data in a recognisable AGP format inside the diabetes review matters for audit and the way reviews are run.
End-of-wear stability holds
Mader 2024 reports 85.9% within ±20/20 on days 13 to 14, compared to 92.8% on day 2. A roughly seven-percentage-point drop end-of-wear, comparable to other 14-day sensors, supports the labelled wear duration without surprise.
Adults only, by labelling
The CE mark and UKCA non-adjunctive indication cover adults 18 years and older. Paediatric labelling has not been pursued in the published evidence. This is a structural gap in the family / paediatric / adolescent space that the CGMs higher up the cluster (Dexcom, Libre) do not have.
The GNL Podcast, Episode 40
CGM Series, Episode 40
Accu-Chek SmartGuide with Amy Jolley
The first UK clinical evaluation of the SmartGuide in a structured group setting. Amy Jolley, Lead Educator at the Diabetes Technology Network UK and lead for the Young Adult and Transition Service at Salford NHS, put 17 people onto the device in a single week and used their feedback to shape how it is taught. The episode covers the MDI generation gap, the three prediction layers in clinical practice, the post-meal correction reflex that two early adopters reported losing, and the DTN Competency Assessment Framework Amy developed with the Leicester team.
“Should we not expect more from the technology for people using this type of therapy?” Amy Jolley, GNL Podcast Episode 40.
Survive and Thrive, SmartGuide
A one-page A4 resource for the first two weeks on the SmartGuide, built from Episode 40 with Amy Jolley (Diabetes Technology Network UK) and the 17-person UK clinical evaluation. Sensor placement, day-one calibration, the three prediction layers, and what to do when the overnight risk score lights up.
Device 3 of 5
Roche Accu-Chek SmartGuide
