ArticleNature and science of sleep2025
Predictive Value of Neutrophil-to-Lymphocyte Ratio for Cerebral Infarction in Obstructive Sleep Apnea: A Nomogram-Based Analysis.
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. Cited by 2 papers.
What it found
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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.
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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.
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Who cites it
2 citing papers in PubMed.
- Letter to the Editor Regarding "Predictive Value of Neutrophil-to-Lymphocyte Ratio for Cerebral Infarction in Obstructive Sleep Apnea: A Nomogram-Based Analysis" [Response to Letter].Nature and science of sleep · 2025Article
- Letter to the Editor Regarding "Predictive Value of Neutrophil-to-Lymphocyte Ratio for Cerebral Infarction in Obstructive Sleep Apnea: A Nomogram-Based Analysis" [Letter].Nature and science of sleep · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Obstructive sleep apnea (OSA) is associated with cerebral infarction (CIF) through inflammatory pathways. The neutrophil-to-lymphocyte ratio (NLR) serves as an inflammation biomarker, but its relationship with CIF in OSA patients remains unclear. Methods: A total of 188 OSA patients from The Affiliated Cardiovascular Hospital of Shanxi Medical University (January 2022 to December 2023) were included, consisting of 68 patients with CIF (case group) and 120 without CIF (control group). Data on admission, biochemical tests, and clinical characteristics were collected and compared. Multivariate logistic regression and a nomogram model were employed to identify risk factors, evaluated using receiver operating characteristic (ROC) curves, calibration curves and decision curve analysis (DCA). Results: Elevated log-transformed NLR (LnNLR), CRP, age, and reduced albumin levels were independently associated with increased CIF risk. The developed nomogram demonstrated excellent discriminative performance (AUC = 0.9372), superior to LnNLR alone (AUC = 0.665). At the optimal cutoff, the model achieved a sensitivity of 82.35% and specificity of 92.50%. Calibration plots showed good agreement between predicted and observed outcomes, and DCA confirmed the model's potential clinical utility. Conclusion: High NLR can be used as an emerging criterion for evaluating CIF risk in OSA. The nomogram model is capable of estimating CIF risk accurately, providing useful aid to clinical decision-making. The developed nomogram can be implemented in practice as an aid to help healthcare personnel identify high-risk OSA participants who would be offered early intervention in terms of increased monitoring and prophylaxis. External validation in larger, multi-center cohorts is warranted.
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Registered trials
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