Evidence map›Paper›PMID 28503375›Full record

ArticlePeerJ2017

Network science meets respiratory medicine for OSAS phenotyping and severity prediction.

Stefan Mihaicuta, Mihai Udrescu, Alexandru Topirceanu, Lucretia Udrescu

Abstract read
In one paragraph

Article in PeerJ, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Fractional Dynamics Foster Deep Learning of COPD Stage Prediction.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Personalised medicine in sleep respiratory disorders: focus on obstructive sleep apnoea diagnosis and treatment.European respiratory review : an official journal of the European Respiratory Society · 2017
    Review
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

4 authors.

Stefan MihaicutaDepartment of Pulmonology, Victor Babes University of Medicine and Pharmacy, Timisoara, Romania.
Mihai UdrescuDepartment of Computer and Information Technology, University Politehnica of Timisoara, Timisoara, Romania.
Alexandru TopirceanuDepartment of Computer and Information Technology, University Politehnica of Timisoara, Timisoara, Romania.
Lucretia UdrescuFaculty of Pharmacy, Victor Babes University of Medicine and Pharmacy, Timisoara, Romania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Obstructive sleep apnea syndrome (OSAS) is a common clinical condition. The way that OSAS risk factors associate and converge is not a random process. As such, defining OSAS phenotypes fosters personalized patient management and population screening. In this paper, we present a network-based observational, retrospective study on a cohort of 1,371 consecutive OSAS patients and 611 non-OSAS control patients in order to explore the risk factor associations and their correlation with OSAS comorbidities. To this end, we construct the Apnea Patients Network (APN) using patient compatibility relationships according to six objective parameters: age, gender, body mass index (BMI), blood pressure (BP), neck circumference (NC) and the Epworth sleepiness score (ESS). By running targeted network clustering algorithms, we identify eight patient phenotypes and corroborate them with the co-morbidity types. Also, by employing machine learning on the uncovered phenotypes, we derive a classification tree and introduce a computational framework which render the Sleep Apnea Syndrome Score (SAS

Indexed as

Network sciencePhenotypesPrediction scorePrediction specificitySleep apnea

Identifiers

PMID28503375
PMCPMC5426352

What OpenQuestion 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 OpenQuestion graph.