Evidence map›Paper›PMID 40672995›Full record

ArticleNature and science of sleep2025

Validation of Automated Respiratory Event Scoring in Type 3 Home Sleep Apnea Testing.

Nanako Shiroshita, Ryoko Obata, Fusae Kawana, Mitsue Kato, Akihiro Sato, Sayaki Ishiwata, Shoichiro Yatsu, Hiroki Matsumoto, Jun Shitara, Azusa Murata and 7 more

Abstract read
In one paragraph

Article in Nature and science of sleep, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

17 authors.

Nanako Shiroshita *Cardiovascular Respiratory Sleep Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Ryoko Obata *Cardiovascular Respiratory Sleep Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Fusae KawanaCardiovascular Respiratory Sleep Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.ORCID 0000-0003-2227-0549
Mitsue KatoCardiovascular Respiratory Sleep Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Akihiro SatoDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Sayaki IshiwataDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Shoichiro YatsuDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.ORCID 0000-0002-2624-2898
Hiroki MatsumotoDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Jun ShitaraDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Azusa MurataDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Megumi ShimizuDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Takao KatoDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Shoko SudaCardiovascular Respiratory Sleep Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Yasuhiro TomitaDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Masaru HikiDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Ryo NaitoDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Takatoshi KasaiCardiovascular Respiratory Sleep Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.ORCID 0000-0001-5747-7668

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Home sleep apnea tests (HSATs) using polygraphy devices are becoming increasingly important for evaluating obstructive sleep apnea. Alice NightOne, a widely used polygraphy device, includes automatic scoring software; however, more reliable scoring results can be provided by incorporating advanced algorithmic systems like Somnolyzer. Despite this, the accuracy of automatic scoring of this polygraphy device using such applications has not been specifically investigated. Thus, in this study, we aimed to compare the respiratory event indices (REIs) obtained via automatic scoring versus manual scoring. Patients and Methods: Data of eligible patients who underwent HSAT with this polygraphy device were retrospectively analyzed using the following three methods: 1) manual scoring; 2) default automatic scoring of the analysis software; and 3) automatic scoring with the Somnolyzer system. The REIs were calculated using these three methods and expressed as mREI, aREI, and sREI, respectively. Correlations and agreements between the aREI, sREI, and mREI were assessed. Results: Data from 20 patients were analyzed. The mean mREI, aREI, and sREI were 14.7±13.3, 13.7±11.8, and 14.3±13.4 events/h, respectively. A strong correlation was found between aREI and mREI (coefficient, 0.976; P<0.01), with a mean difference between them of 1.0 and a limit of agreement of -5.3 to 7.3. The correlation between sREI and mREI was more prominent (coefficient, 0.996; P<0.001); their mean difference was 0.1, with a limit of agreement of -2.1 to 2.9. Conclusion: Automatic scoring of REI using this polygraphy device showed good correlation and agreement with manual scoring. The favorable correlation and agreement were more pronounced with the Somnolyzer system.

Indexed as

apneahome sleep testhypopneasleep apneasleep study

Identifiers

PMID40672995
PMCPMC12264349

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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.