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In older in-patients with type 2 diabetes and cognitive impairment, CGM showed superior glucose metrics compared to point-of-care testsThe Wearable Glucose Sensor That Catches What Hospital Tests Miss

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Key Takeaway
Consider CGM as a potentially advantageous alternative to POCT for glucose monitoring in older in-patients with type 2 diabetes and cognitive impairment.

This observational study assessed the performance of Dexcom G7 sensors against point-of-care tests (POCT) in a cohort of 30 older in-patients with comorbid type 2 diabetes and cognitive impairment recruited from a UK tertiary care hospital. Participants were monitored for up to 10 days to compare glucose metrics derived from CGM against reference POCT values. The primary analysis focused on time in range (TIR), time above range (TAR), and time below range (TBR), alongside agreement metrics such as mean absolute relative difference (MARD) and Clarke Error Grid analysis.

CGM-derived mean TIR was 36.2% (range 0-90%), compared to a mean POCT-based TIR of 41%. Conversely, CGM indicated a mean TAR of 62.8%, whereas POCT showed a mean TAR of 57.2%. The proportion of CGM readings within +/-20% of reference values was 72%, with 99.3% of paired readings falling within Zones A and B of the Clarke Error Grid. The correlation between CGM and POCT was R2=0.82. MARD was 17.4% and median absolute relative difference was 12.2%. Time below range (TBR) was 1% for CGM versus 2% for POCT.

Safety data, adverse events, and discontinuations were not reported in the provided evidence. The study was observational in nature, limiting causal inference regarding clinical outcomes. The small sample size of 30 completers and the specific high-risk population constrain the generalizability of these findings. While CGM may be a viable alternative to POCT in this setting, the evidence remains early and requires confirmation in larger, randomized trials before routine adoption.

A vulnerable group that's often overlooked

Older adults make up a large share of hospital admissions. Among them, the overlap of diabetes and cognitive impairment (problems with memory, thinking, or decision-making) is significant. Cognitive impairment makes diabetes harder to manage because patients may forget to eat, not report symptoms of low blood sugar, or be unable to communicate how they're feeling.

Standard hospital glucose monitoring relies on point-of-care testing (POCT) — a finger prick that measures blood sugar at that moment in time. Done a few times a day, it misses everything in between. For someone who can't tell you they feel shaky or confused, those gaps can be dangerous.

Why continuous monitoring seems like a natural fit

Continuous glucose monitors (CGMs) are small wearable sensors — usually worn on the upper arm or abdomen — that measure glucose levels under the skin every few minutes, around the clock. They're widely used by people with diabetes at home.

But here's the twist: CGMs have mostly been studied in younger, cognitively intact outpatients. Almost no one had tested them in elderly hospital patients with cognitive impairment. Would they be accurate enough to be clinically useful in that setting?

Think of a CGM as a tiny lifeguard stationed just under the skin. Instead of waiting to be called, it constantly watches the water — sending a reading every few minutes, day and night. When glucose drops or spikes outside a safe range, it logs the event automatically.

Traditional finger-prick testing is more like a snapshot taken a few times a day. It catches what's happening right then, but misses the full story of what glucose levels are doing between checks.

What the study tested

Thirty-two older patients with both type 2 diabetes and cognitive impairment were recruited from a UK tertiary care hospital (a large specialist hospital). All were new to CGM. They wore blinded Dexcom G7 sensors — blinded meaning clinical staff couldn't see the CGM readings in real time — for up to 10 days, while continuing their usual care including standard finger-prick tests. Researchers then compared the CGM readings to the finger-prick results.

The CGM showed clinically acceptable accuracy. The mean absolute relative difference (MARD) — a standard measure of how close sensor readings are to actual blood glucose values — was 17.4%. That's within the range considered acceptable for clinical decision support. A strong correlation was found between the two methods (R²=0.82), and 99.3% of paired readings fell in the two safest accuracy zones.

Crucially, the CGM detected more episodes of low blood sugar (hypoglycemia), particularly overnight. These were events that the standard finger-prick schedule simply didn't catch. In a patient who can't reliably report symptoms, that undetected low blood sugar is a real safety risk.

These overnight lows could cause serious harm in patients who can't recognize or report symptoms on their own.

What the gap in standard testing looks like

The study found that CGM-based and finger-prick-based time-in-range (the proportion of time blood sugar stays in the healthy zone) were broadly similar: about 36% vs. 41%, respectively. But those overall numbers masked an important difference. CGMs revealed low-sugar events at night that were invisible to the daytime-only testing routine.

If you're a caregiver or family member of an older adult with diabetes and cognitive impairment — or if you're planning for your own care — this research matters. CGMs are already commercially available and approved for home use. Their use in hospitals is still evolving, but this study adds evidence that they may be especially valuable in patients who can't self-monitor or communicate symptoms.

If your loved one is admitted to hospital, it's worth asking whether continuous monitoring might be appropriate, especially overnight.

Limitations to be aware of

This was a small study — 30 participants who completed it — at a single hospital. The CGM sensors were blinded, meaning clinicians couldn't use the data in real time during the study. A larger trial where staff can act on CGM readings in real time would give a fuller picture of the benefit. Results may also vary with different CGM devices or in different hospital settings.

This study lays important groundwork for a clinical trial where CGM readings are actually used to guide care decisions in real time for this patient group. If larger trials confirm these findings, CGM could become a standard tool for managing glucose in vulnerable inpatients — reducing silent hypoglycemia and giving clinical teams a much clearer picture, day and night.

Study Details

EvidenceLevel 5
PublishedMar 2026
View Original Abstract ↓
Background: Older in-patients have a higher prevalence of diabetes and cognitive impairment compared to those living without diabetes or cognitive decline. Cognitive impairment can complicate glucose management more challenging, as patients may forget to measure their blood glucose or report symptoms. Investigating the accuracy of continuous glucose monitoring (CGM) compared to usual care will inform clinical decision-making in this vulnerable population. Aim: To compare CGM derived glucose metrics and point-of-care tests (POCT) in older in-patients with type 2 diabetes and cognitive impairment, and to investigate the analytical and clinical accuracy of CGM in the hospital setting. Methods: Thirty-two older people with comorbid type 2 diabetes and cognitive impairment were recruited within a UK tertiary care hospital. All participants were CGM-naive and wore blinded Dexcom G7 sensors for up to 10 days, while receiving. Usual care during their hospital stay including POCT. Key accuracy metrics comprised the mean absolute relative difference (MARD), median absolute relative difference (median ARD), Clarke Error Grid (CEG) and, correlation (R2). The proportion of CGM readings within +/-20% of reference glucose values when the reference was >5.6 mmol/L, or within +/-1.1 mmol/L when >5.6 mmol/L (+/-20%/1.1 mmol/L) was calculated to assess analytical and clinical accuracy. Results: Thirty participants completed the study. CGM-derived mean glucose for time in range (TIR, 4-10 mmol/mol) was 36.2% (range 0-90%), time above range (TAR>=10 mmol/mol) was 62.8% and time below range (TBR<=3.9 mmol/mol) was 1%. Mean POCT-based TIR was 41%, TAR was 57.2% and TBR 2%, showing broadly comparable glucose metrics. CGM accuracy analysis showed a MARD of 17.4%, median ARD of 12.2% and the outcome of +/-20%/1.1 mmol/L was agreement of 72%. CEG analysis revealed that 99.3% of paired readings fell within the clinically acceptable Zones A and B, with a strong correlation between CGM and POCT (R2=0.82). CGM identified more hypoglycaemic readings, particularly at night. Conclusion: CGM and POCT produced largely similar glucose metrics in older in-patients with diabetes and cognitive impairment. CGM demonstrated clinically acceptable accuracy, and captured additional hypoglycaemia, undetected by routine POCT. These findings suggest that CGM may be a viable and potentially advantageous alternative to POCT in this high-risk population.
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