Evidence map›Paper›PMID 38264231›Full record

ArticleDiabetology international2024

Association of scan frequency with CGM-derived metrics and influential factors in adults with type 1 diabetes mellitus.

Naoki Sakane, Yushi Hirota, Akane Yamamoto, Junnosuke Miura, Hiroko Takaike, Sari Hoshina, Masao Toyoda, Nobumichi Saito, Kiminori Hosoda, Masaki Matsubara and 8 more

Abstract read
In one paragraph

Article in Diabetology international, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Observational
  3. Article
  4. Article
  5. 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

18 authors.

Naoki SakaneDivision of Preventive Medicine, Clinical Research Institute, National Hospital Organization Kyoto Medical Center, 1-1 Mukaihata-cho, Fukakusa, Fushimi-ku, Kyoto, 612-8555 Japan.ORCID 0000-0002-2625-571X
Yushi HirotaDivision of Diabetes and Endocrinology, The Department of Internal Medicine, Kobe University Graduate School of Medicine Hyogo, 7-5-1 Kusunoki-cho, Chuo-ku, Kobe City, Hyogo, 650-0017 Japan.
Akane YamamotoDivision of Diabetes and Endocrinology, The Department of Internal Medicine, Kobe University Graduate School of Medicine Hyogo, 7-5-1 Kusunoki-cho, Chuo-ku, Kobe City, Hyogo, 650-0017 Japan.
Junnosuke MiuraDivision of Diabetology and Metabolism, Department of Internal Medicine Tokyo Women's Medical University School of Medicine, 8-1 Kawada-cho, Shinjuku-ku, Tokyo, 162-8666 Japan.
Hiroko TakaikeDivision of Diabetology and Metabolism, Department of Internal Medicine Tokyo Women's Medical University School of Medicine, 8-1 Kawada-cho, Shinjuku-ku, Tokyo, 162-8666 Japan.
Sari HoshinaDivision of Diabetology and Metabolism, Department of Internal Medicine Tokyo Women's Medical University School of Medicine, 8-1 Kawada-cho, Shinjuku-ku, Tokyo, 162-8666 Japan.
Masao ToyodaDivision of Nephrology, Endocrinology and Metabolism, Department of Internal Medicine, Tokai University School of Medicine, 143 Shimokasuya, Isehara-shi, Kanagawa, 259-1143 Japan.
Nobumichi SaitoDivision of Nephrology, Endocrinology and Metabolism, Department of Internal Medicine, Tokai University School of Medicine, 143 Shimokasuya, Isehara-shi, Kanagawa, 259-1143 Japan.
Kiminori HosodaDivision of Diabetes and Lipid Metabolism, National Cerebral and Cardiovascular Center, 6-1 Kishibe-Shimmachi, Suita, Osaka, 564-8565 Japan.
Masaki MatsubaraDivision of Diabetes and Lipid Metabolism, National Cerebral and Cardiovascular Center, 6-1 Kishibe-Shimmachi, Suita, Osaka, 564-8565 Japan.
Atsuhito ToneDepartment of Internal Medicine, Okayama Saiseikai General Hospital, 2-25 Kokutai-cho, Kita-ku, Okayama-shi, Okayama, 700-8511 Japan.
Satoshi KawashimaKanda Naika Clinic, 5-21-3 Hannan-cho, Abeno-ku, Osaka-shi, Osaka, 545-0021 Japan.
Hideaki SawakiSawaki Internal Medicine And Diabetes Clinic, 1-1-501A Konyamachi, Takatsuki-shi, Osaka, 569-0804 Japan.
Tomokazu MatsudaMatsuda Diabetes Clinic, 78-7 Ohtsukadai, Nishi-ku, Kobe City, Hyogo, 651-2135 Japan.
Masayuki DomichiDivision of Preventive Medicine, Clinical Research Institute, National Hospital Organization Kyoto Medical Center, 1-1 Mukaihata-cho, Fukakusa, Fushimi-ku, Kyoto, 612-8555 Japan.
Akiko SuganumaDivision of Preventive Medicine, Clinical Research Institute, National Hospital Organization Kyoto Medical Center, 1-1 Mukaihata-cho, Fukakusa, Fushimi-ku, Kyoto, 612-8555 Japan.
Seiko SakaneDivision of Preventive Medicine, Clinical Research Institute, National Hospital Organization Kyoto Medical Center, 1-1 Mukaihata-cho, Fukakusa, Fushimi-ku, Kyoto, 612-8555 Japan.
Takashi MurataDepartment of Clinical Nutrition, National Hospital Organization Kyoto Medical Center, 1-1 Mukaihata-cho, Fukakusa, Fushimi-ku, Kyoto, 612-8555 Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: This study aimed to investigate the association between scan frequency and intermittently scanned continuous glucose monitoring (isCGM) metrics and to clarify the factors affecting scan frequency in adults with type 1 diabetes mellitus (T1D). Methods: We enrolled adults with T1D who used FreeStyle® Libre. Scan and self-monitoring of blood glucose (SMBG) frequency and CGM metrics from the past 90-day glucose data were collected. The receiver operating characteristic curve was plotted to obtain the optimal cutoff values of scan frequency for the target values of time in range (TIR), time above range (TAR), and time below range (TBR). Results: The study was conducted on 211 adults with T1D (mean age, 50.9 ± 15.2 years; male, 40.8%; diabetes duration, 16.4 ± 11.9 years; duration of CGM use, 2.1 ± 1.0 years; and mean HbA1c, 7.6 ± 0.9%). The average scan frequency was 10.5 ± 3.3 scan/day. Scan frequency was positively correlated with TIR and negatively correlated with TAR, although it was not significantly correlated with TBR. Scan frequency was positively correlated with the hypoglycemia fear survey-behavior score, while it was negatively correlated with some glycemic variability metrics. Adult patients with T1D and good exercise habits had a higher scan frequency than those without exercise habits. The AUC for > 70% of the TIR was 0.653, with an optimal cutoff of 11 scan/day. Conclusions: In real-world conditions, frequent scans were linked to improved CGM metrics, including increased TIR, reduced TAR, and some glycemic variability metrics. Exercise habits and hypoglycemia fear-related behavior might affect scan frequency. Our findings could help healthcare professionals use isCGM to support adults with T1D.Clinical Trial Registry No. UMIN000039376.

Indexed as

Blood glucose monitoring frequencyFlash glucose monitoringReal-world dataType 1 diabetes

Identifiers

PMID38264231
PMCPMC10800315

What Socratic holds

Textmetadata
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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.