Evidence mapPaperPMID 40926388Full record

ReviewCNS spectrums2025

The role of continuous glucose monitoring (CGM) in psychiatric symptom management.

Melanie C Zhang, Roger S McIntyre

Abstract readReview
In one paragraph

Review in CNS spectrums, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Melanie C ZhangDepartment of Psychiatry, https://ror.org/03dbr7087University of Toronto, Toronto, ON, Canada.ORCID 0009-0002-0638-8184
Roger S McIntyreDepartment of Psychiatry, https://ror.org/03dbr7087University of Toronto, Toronto, ON, Canada.ORCID 0000-0003-4733-2523

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Continuous glucose monitoring (CGM) has revolutionized diabetes management by providing real-time data on blood glucose fluctuations. Unlike traditional methods, CGM systems offer continuous feedback, enabling individuals to better regulate glucose levels in response to lifestyle factors such as diet, exercise, and stress. This technology has been shown to improve glycemic control and stabilize HbA1c levels. Beyond its primary role in diabetes management, emerging research highlights the relationship between metabolic health and mental wellbeing. Glucose dysregulation has been implicated in mood instability, and fluctuations in blood glucose levels may directly influence emotional states. Notably, some researchers have proposed reclassifying major depressive disorder (MDD) as "Metabolic Syndrome Type II" due to shared pathophysiological mechanisms involving glucose homeostasis and inflammation. Given these connections, CGM technology may offer mental health benefits by promoting glucose stability. For individuals with diabetes who also experience psychiatric conditions such as MDD or generalized anxiety disorder (GAD), CGM use may contribute to improved mood regulation and reduced psychiatric symptoms. By addressing both metabolic and mental health concerns, CGM holds promise as a valuable tool in enhancing overall wellbeing. Further research is warranted to explore the full potential of CGM in supporting mental health outcomes in individuals with metabolic disorders.

Indexed as

Blood GlucoseBlood Glucose Self-MonitoringMental DisordersAnxiety DisordersContinuous Glucose MonitoringHumansMajor Depressive DisorderBlood Glucoseblood glucose fluctuationsContinuous glucose monitoringdiabetes mellitusgeneralized anxiety disordermajor depressive disorder

Identifiers

PMID40926388
PMCPMC13064731

What Socratic holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.