ArticleEuropean archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery2024
The diagnostic value of image-enhanced endoscopy system in sinonasal inverted papilloma.
Article in European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
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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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Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Identifying sinonasal inverted papilloma by machine learning: a systematic review and meta-analysis.Frontiers in oncology · 2025Pooled it
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5 authors.
Funding
Abstract
purposeThis study aimed to evaluate the diagnostic value of image-enhanced endoscopy (IEE) in detecting sinonasal inverted papilloma (SNIP).
methodsOverall, 86 patients with unilateral nasal papillary or lobulated neoplasms were included between July 2018 and June 2019. All patients underwent IEE examinations, and the diagnosis of all neoplasms was confirmed through postoperative pathology. Logistic regression analysis was conducted to screen for independent predictors of various types of vascular patterns of SNIP. Furthermore, a prognostic nomogram was constructed using the independent predictors screened by logistic regression analysis to evaluate its usefulness in distinguishing SNIP from nasal polyp (NP) and papillary mucosa folds (PMF).
resultsIn total, 86 consecutive cases were observed, including 37 with SNIP, 40 with NP, and 9 with PMF. Logistic regression analysis showed that spot, corkscrew, and multilayered vascular patterns were independent predictors of SNIP diagnosis. Furthermore, a nomogram comprising the three independent risk factors was constructed with scores of 5, 2, and 3. The area under the receiver operating characteristic curve for predicting SNIP was 0.954, 0.66, 0.71, and 0.76 for the nomogram model, spot vascular pattern, corkscrew vascular pattern, and multilayered vascular pattern, respectively.
conclusionThe nomogram model based on spot, corkscrew, and multilayered vascular patterns in SNIP observed using IEE can be a useful diagnostic tool for predicting and distinguishing between NP and PMF.
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