Evidence map›Paper›PMID 39207665›Full record

ArticleSleep & breathing = Schlaf & Atmung2024

Construction and evaluation of a predictive model for the types of sleep respiratory events in patients with OSA based on hypoxic parameters.

Cheng Peng, Shaorong Xu, Yan Wang, Baoyuan Chen, Dan Liu, Yu Shi, Jing Zhang, Zhongxing Zhou

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Article in Sleep & breathing = Schlaf & Atmung, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

8 authors.

Cheng Peng *Department of Respiratory and Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, China.
Shaorong Xu *The Affiliated Hospital of Guizhou Medical University, Guizhou, China.
Yan Wang *Department of Respiratory and Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, China. wangy0504@126.com.ORCID 0000-0002-2798-7103
Baoyuan ChenDepartment of Respiratory and Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, China.
Dan LiuDepartment of Respiratory and Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, China.
Yu ShiDepartment of Respiratory and Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, China.
Jing ZhangBiomedical Engineering, School of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin, 300072, China.
Zhongxing Zhou *Biomedical Engineering, School of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin, 300072, China. zhouzhongxing2023@126.com.

Funding

The Youth Program of National Natural Science Foundation of China 82000097
6 · The paper itself

Abstract

objectiveTo explore the differences and associations of hypoxic parameters among distinct types of respiratory events in patients with obstructive sleep apnea (OSA) and to construct prediction models for the types of respiratory events based on hypoxic parameters.

methodsA retrospective analysis was conducted on a cohort of 67 patients with polysomnography (PSG). All overnight recorded respiratory events with pulse oxygen saturation (SpO

resultsBoth ANN and BLR models suggested that 13 hypoxic parameters significantly influenced the classification of respiratory event types; The area under the ROC curves of the ANN models surpassed those of traditional BLR models respiratory event types.

conclusionThe ANN models constructed based on the 13 hypoxic parameters exhibited superior predictive capabilities for distinct types of respiratory events, providing a feasible new tool for automatic identification of respiratory event types using sleep SpO

Indexed as

HypoxiaNeural Networks, ComputerPolysomnographySleep Apnea, ObstructiveAdultFemaleHumansMaleMiddle AgedOxygen SaturationRetrospective StudiesHypoxic parametersObstructive sleep apneaPredictive modelRespiratory events

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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.