Evidence map›Paper›PMID 32974101›Full record

ArticlePeerJ2020

A prediction modeling based on SNOT-22 score for endoscopic nasal septoplasty: a retrospective study.

Xue-Ran Kang, Bin Chen, Yi-Sheng Chen, Bin Yi, Xiaojun Yan, Chenyan Jiang, Shulun Wang, Lixing Lu, Runjie Shi

Abstract read
In one paragraph

Article in PeerJ, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Trial
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  7. Frontiers in neurology · 2022
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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

9 authors.

Xue-Ran Kang *Department of Otorhinolaryngology Head and Neck Surgery, Shanghai ninth people's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Bin Chen *Department of Otorhinolaryngology Head and Neck Surgery, Shanghai ninth people's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yi-Sheng ChenDepartment of Orthopedics, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Bin YiDepartment of Otorhinolaryngology Head and Neck Surgery, Shanghai ninth people's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xiaojun YanDepartment of Otorhinolaryngology Head and Neck Surgery, Shanghai ninth people's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Chenyan JiangDepartment of Otorhinolaryngology Head and Neck Surgery, Shanghai ninth people's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Shulun WangDepartment of Otorhinolaryngology Head and Neck Surgery, Shanghai ninth people's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Lixing LuDepartment of Otorhinolaryngology Head and Neck Surgery, Shanghai ninth people's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Runjie ShiDepartment of Otorhinolaryngology Head and Neck Surgery, Shanghai ninth people's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo create a nomogram prediction model for the efficacy of endoscopic nasal septoplasty, and the likelihood of patient benefiting from the operation.

methodsA retrospective analysis of 155 patients with nasal septum deviation (NSD) was performed to develop a predictive model for the efficacy of endoscopic nasal septoplasty. Quality of life (QoL) data was collected before and after surgery using Sinonasal Outcome Test-22 (SNOT-22) scores to evaluate the surgical outcome. An effective surgical outcome was defined as a SNOT-22 score change ≥ 9 points after surgery. Multivariate logistic regression analysis was then used to establish a predictive model for the NSD treatment. The predictive quality and clinical utility of the predictive model were assessed by C-index, calibration plots, and decision curve analysis.

resultsThe identified risk factors for inclusion in the predictive model were included. The model had a good predictive power, with a AUC of 0.920 in the training group and a C index of 0.911 in the overall sample. Decision curve analysis revealed that the prediction model had a good clinical applicability.

conclusionsOur prediction model is efficient in predicting the efficacy of endoscopic surgery for NSD through evaluation of factors including: history of nasal surgery, preoperative SNOT-22 score, sinusitis, middle turbinate plasty, BMI, smoking, follow-up time, seasonal allergies, and advanced age. Therefore, it can be cost-effective for individualized preoperative assessment.

Indexed as

Nasal septum deviation (NSD)Nomogram prediction modelQuality of lifeSeptoplastySNOT-22 score

Identifiers

PMID32974101
PMCPMC7489239

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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.