ArticleMedical & biological engineering & computing2015
Application of multiscale entropy in arterial waveform contour analysis in healthy and diabetic subjects.
Article in Medical & biological engineering & computing, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Multiparameters of heart rate variability predict symptomatic hemorrhagic transformation in patients following mechanical thrombectomy.BMC neurology · 2026Article
- A novel QTc-RR differential biomarker for the early assessment of autonomic dysfunction in type 2 diabetes.Frontiers in endocrinology · 2026Article
- Automatic directional analysis of cell fluorescence images and morphological modeling of microfilaments.Medical & biological engineering & computing · 2019Article
- Combination of R-R Interval and Crest Time in Assessing Complexity Using Multiscale Cross-Approximate Entropy in Normal and Diabetic Subjects.Entropy (Basel, Switzerland) · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We applied multiscale entropy (MSE) to assess variation in crest time (CT), a parameter in arterial waveform analysis, in diagnosing patients with diabetes. Data on digital volume pulse were obtained from 93 individuals in three groups [Healthy young (Group 1, 20 < age ≤ 40, n = 30), healthy upper-middle-aged (Group 2, age > 40, n = 30), and diabetic (Group 3, n = 33) subjects]. Crest time, normalized crest time, crest time ratio (CTR), small- and large-scale MSE on CT [MSESS(CT) and MSELS(CT), respectively] were computed and correlated with anthropometric (i.e., body weight/height, waist circumference), hemodynamic (i.e., blood pressure), and biochemical parameters (i.e., serum triglyceride, high-density lipoprotein, fasting blood sugar, and glycosylated hemoglobin). The results demonstrated higher variability in CT in healthy subjects (Groups 1 and 2) compared with that in diabetic patients (Group 3) as reflected in significantly elevated MSESS(CT) and MSELS(CT) in the former (p < 0.003 and p < 0.001, respectively). MSELS(CT) also showed significant association with waist circumference and fasting blood sugar (i.e., two diagnostic criteria of metabolic syndrome) as well as glycosylated hemoglobin concentration. In conclusion, using MSE analysis for assessing CT variation successfully distinguished diabetic patients from healthy subjects. MSESS(CT) and MSELS(CT) therefore may serve as noninvasive tools for identifying subjects with diabetes and those at risk.
Indexed as
Identifiers
25351478What OpenQuestion holds
Registered trials
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 OpenQuestion graph.