Evidence map›Paper›PMID 42630933›Full record

ArticleNature and science of sleep2026

Development and Internal Evaluation of a Nomogram for Clinically Significant Depressive Symptoms in Obstructive Sleep Apnea-Hypopnea Syndrome.

Fan Yi, Jie Zhang, Qing Feng, Xiaopei Wang, Rongrong Zhang, Jinqiao Zhang, Lingyu Song, Jihua Zhang

Abstract read
In one paragraph

Article in Nature and science of sleep, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Fan YiGraduate School, Hebei Medical University, Shijiazhuang, Hebei, People's Republic of China.
Jie ZhangDepartment of Otolaryngology, The First Hospital of Hebei Medical University, Shijiazhuang, Hebei, People's Republic of China.
Qing FengDepartment of Otolaryngology, The First Hospital of Hebei Medical University, Shijiazhuang, Hebei, People's Republic of China.
Xiaopei WangDepartment of Otolaryngology, The First Hospital of Hebei Medical University, Shijiazhuang, Hebei, People's Republic of China.
Rongrong ZhangDepartment of Otolaryngology, The First Hospital of Hebei Medical University, Shijiazhuang, Hebei, People's Republic of China.
Jinqiao ZhangDepartment of Otolaryngology, The First Hospital of Hebei Medical University, Shijiazhuang, Hebei, People's Republic of China.
Lingyu SongDepartment of Otolaryngology, The First Hospital of Hebei Medical University, Shijiazhuang, Hebei, People's Republic of China.
Jihua ZhangDepartment of Otolaryngology, The First Hospital of Hebei Medical University, Shijiazhuang, Hebei, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To develop and internally evaluate a nomogram for identifying clinically significant depressive symptoms in hospitalized patients with obstructive sleep apnea-hypopnea syndrome (OSAHS). Methods: A single-center retrospective study included adults hospitalized at the First Hospital of Hebei Medical University between January and December 2025. OSAHS was confirmed by overnight polysomnography (PSG) and defined as an apnea-hypopnea index (AHI) ≥5 events/h. Depressive symptoms were assessed using the Zung Self-Rating Depression Scale (SDS), with a standardized score ≥53 defining clinically significant depressive symptoms. Thirty-six candidate predictors were extracted from electronic medical records and laboratory information systems. The cohort was randomly divided into a training cohort (n=574) and an internal validation cohort (n=246). Least absolute shrinkage and selection operator (LASSO) logistic regression with 10-fold cross-validation, followed by post-LASSO multivariable logistic regression, was used to select predictors and construct the nomogram. Discrimination, calibration, and clinical utility were assessed using the area under the curve (AUC), calibration analyses, and decision curve analysis. Results: Among 820 patients, 88 (10.7%) had clinically significant depressive symptoms, including 62 events in the training cohort and 26 in the internal validation cohort. LASSO initially retained seven candidate predictors. Five predictors remained statistically significant after post-LASSO multivariable logistic regression and were included in the final nomogram: oxygen desaturation index (ODI), Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), thyroid-stimulating hormone (TSH), and free triiodothyronine (FT3). The model showed favorable discrimination in the training cohort (AUC=0.910, 95% confidence interval [CI] 0.869-0.950) and internal validation cohort (AUC=0.915, 95% CI 0.853-0.977). Calibration was acceptable, with calibration intercepts of approximately 0.000 and -0.438 and calibration slopes of 1.000 and 0.814, respectively. Conclusion: This internally evaluated nomogram integrating ODI, PSQI, ESS, TSH, and FT3 showed favorable performance for identifying SDS-defined clinically significant depressive symptoms in hospitalized patients with OSAHS. Prospective multicenter and temporal external validation is required to assess its generalizability and clinical applicability.

Indexed as

depressive symptomsnomogramobstructive sleep apnea-hypopnea syndromeoxygen desaturation indexprediction modelthyroid axis

Identifiers

PMID42630933
PMCPMC13496143

What Socratic holds

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LicenceCC BY-NC
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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 Socratic graph.