Evidence mapPaperPMID 33707491Full record

ArticleScientific reports2021

Oscillatory pattern of glycemic control in patients with diabetes mellitus.

Manuel Vasquez-Muñoz, Alexis Arce-Alvarez, Magdalena von Igel, Carlos Veliz, Gonzalo Ruiz-Esquide, Rodrigo Ramirez-Campillo, Cristian Alvarez, Robinson Ramirez-Velez, Fernando A Crespo, Mikel Izquierdo and 2 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.3field-weighted citation impact, top 19% of its field
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

7 citing papers in PubMed, 11 citations in OpenAlex.

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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

12 authors at 8 institutions in 2 countries.

Manuel Vasquez-Muñoz *Clínica Santa María, Santiago, Chile.
Alexis Arce-Alvarez *Escuela de Kinesiología, Facultad de Salud, Universidad Católica Silva Henríquez, Santiago, Chile.
Magdalena von IgelCentro de Investigación en Fisiología del Ejercicio, Facultad de Ciencias, Universidad Mayor, Santiago, Chile.
Carlos VelizCentro de Investigación en Fisiología del Ejercicio, Facultad de Ciencias, Universidad Mayor, Santiago, Chile.
Gonzalo Ruiz-EsquideClínica Santa María, Santiago, Chile.
Rodrigo Ramirez-CampilloCentro de Investigación en Fisiología del Ejercicio, Facultad de Ciencias, Universidad Mayor, Santiago, Chile.
Cristian AlvarezHuman Performance Laboratory, Quality of Life and Wellness Research Group, Department of Physical Activity Sciences, Universidad de Los Lagos, Osorno, Chile.
Robinson Ramirez-VelezNavarrabiomed, Complejo Hospitalario de Navarra (CHN), Universidad Pública de Navarra (UPNA), IdiSNA, Pamplona, Navarra, Spain.
Fernando A CrespoDAiTA Lab, Facultad de Estudios Interdisciplinarios, Universidad Mayor, Santiago, Chile.
Mikel IzquierdoNavarrabiomed, Complejo Hospitalario de Navarra (CHN), Universidad Pública de Navarra (UPNA), IdiSNA, Pamplona, Navarra, Spain.
Rodrigo Del RioLaboratory of Cardiorespiratory Control, Department of Physiology, Pontificia Universidad Católica de Chile, Santiago, Chile.
David C AndradeCentro de Investigación en Fisiología del Ejercicio, Facultad de Ciencias, Universidad Mayor, Santiago, Chile. dcandrade@uc.cl.
Universidad Mayor · CLPontificia Universidad Católica de Chile · CLCentro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable · ESClinica Santa Maria · CLComplejo Hospitalario de Navarra · ESNavarrabiomed · ESUniversidad Católica Silva Henríquez · CLUniversidad de Los Lagos · CL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Daily glucose variability is higher in diabetic mellitus (DM) patients which has been related to the severity of the disease. However, it is unclear whether glycemic variability displays a specific pattern oscillation or if it is completely random. Thus, to determine glycemic variability pattern, we measured and analyzed continuous glucose monitoring (CGM) data, in control subjects and patients with DM type-1 (T1D). CGM data was assessed for 6 days (day: 08:00-20:00-h; and night: 20:00-08:00-h). Participants (n = 172; age = 18-80 years) were assigned to T1D (n = 144, females = 65) and Control (i.e., healthy; n = 28, females = 22) groups. Anthropometry, pharmacologic treatments, glycosylated hemoglobin (HbA1c) and years of evolution were determined. T1D females displayed a higher glycemia at 10:00-14:00-h vs. T1D males and Control females. DM patients displays mainly stationary oscillations (deterministic), with circadian rhythm characteristics. The glycemia oscillated between 2 and 6 days. The predictive model of glycemia showed that it is possible to predict hyper and hypoglycemia (R

Indexed as

Glycemic ControlAdultBlood GlucoseCase-Control StudiesCircadian RhythmDiabetes Mellitus, Type 1FemaleGlycated HemoglobinHumansHyperglycemiaHypoglycemiaMaleMiddle AgedModels, BiologicalBlood GlucoseGlycated Hemoglobin

Identifiers

PMID33707491
PMCPMC7970978
OpenAlexW3134636733

What Socratic holds

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Registered trials

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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.