Evidence map›Paper›PMID 30837892›Full record

ArticleFrontiers in physiology2019

The Application of the Extended Poincaré Plot in the Analysis of Physiological Variabilities.

Reem Satti, Noor-Ul-Hoda Abid, Matteo Bottaro, Michele De Rui, Maria Garrido, Mohammad R Raoufy, Sara Montagnese, Ali R Mani

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Frontiers in physiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
4.8field-weighted citation impact, top 4% 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

24 citing papers in PubMed, 58 citations in OpenAlex.

  1. Hierarchical Poincaré analysis for anaesthesia monitoring.Journal of clinical monitoring and computing · 2020
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  17. Nonlinear Dynamics of Reaction Time and Time Estimation during Repetitive Test.International journal of environmental research and public health · 2022
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 3 countries.

Reem SattiUCL Division of Medicine, University College London, London, United Kingdom.
Noor-Ul-Hoda AbidUCL Division of Medicine, University College London, London, United Kingdom.
Matteo BottaroDepartment of Medicine, University of Padova, Padova, Italy.
Michele De RuiDepartment of Medicine, University of Padova, Padova, Italy.
Maria GarridoDepartment of Medicine, University of Padova, Padova, Italy.
Mohammad R RaoufyDepartment of Physiology, Tarbiat Modares University, Tehran, Iran.
Sara MontagneseDepartment of Medicine, University of Padova, Padova, Italy.
Ali R ManiUCL Division of Medicine, University College London, London, United Kingdom.
University of Padua · ITUniversity College London · GBTarbiat Modares University · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Poincaré plot is a geometrical technique used to visualize and quantify the correlation between two consecutive data points in a time-series. Since the dynamics of fluctuations in physiological rhythms exhibit long-term correlation and memory, this study aimed to extend the Poincaré plot by calculating the correlation between sequential data points in a time-series, rather than between two consecutive points. By incorporating this so-called lag, we hope to integrate a temporal aspect into quantifying the correlation, to depict whether a physiological system holds prolonged association between events separated by time. In doing so, it attempts to instantaneously characterize the intrinsic behavior of a complex system. We tested this hypothesis on three different physiological time-series: heart rate variability in patients with liver cirrhosis, respiratory rhythm in asthma and body temperature fluctuation in patients with cirrhosis, to evaluate the potential application of the extended Poincaré method in clinical practice. When studying the cardiac inter-beat intervals, the extended Poincaré plot revealed a stronger autocorrelation for patients with decompensated liver cirrhosis compared to less severe cases using Pearson's correlation coefficient. In addition, long-term variability (known as SD2 in the extended Poincaré plot) appeared as an independent prognostic variable. This holds significance by acting as a non-invasive tool to evaluate patients with chronic liver disease and potentially facilitate transplant selection as an adjuvant to traditional criteria. For asthmatics, employing the extended Poincaré plot allowed for a non-invasive tool to differentially diagnose various classifications of respiratory disease. In the respiratory inter-breath interval analysis, the receiver operating characteristic (ROC) curve provided evidence that the extension of the Poincaré plot holds a greater advantage in the classification of asthmatic patients, over the traditional Poincaré plot. Lastly, the analysis of body temperature from patients using the extended Poincaré plot helped identify inpatients from outpatients with cirrhosis. Through these analyses, the extended Poincaré plot provided unique and additional information which could potentially make a difference in clinical practice. Conclusively, the potential use of our work lies in its possible application of predicting mortality for the organ allocation procedure in patients with cirrhosis and non-invasively distinguish between atopic and non-atopic asthma.

Indexed as

asthmaautocorrelationcirrhosisheart rate variabilityPoincaré plotsurvivaltemperature variability

Identifiers

PMID30837892
PMCPMC6390508
OpenAlexW2916473259

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.