Evidence map›Paper›PMID 34886032›Full record

ArticleInternational journal of environmental research and public health2021

Construction and Evaluation of a High-Frequency Hearing Loss Screening Tool for Community Residents.

Yi Wang, Chengyin Ye, Dahui Wang, Chenhui Li, Shichang Wang, Jinmei Li, Jinghua Wu, Xiaozhen Wang, Liangwen Xu

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Age-Related Hearing Decline and Resting-State Networks.American journal of audiology · 2025
    Article
  2. Article
  3. 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

9 authors.

Yi WangDepartment of Prevention Medicine, Hangzhou Normal University, Hangzhou 311121, China.ORCID 0000-0002-7690-1660
Chengyin YeDepartment of Prevention Medicine, Hangzhou Normal University, Hangzhou 311121, China.
Dahui WangDepartment of Prevention Medicine, Hangzhou Normal University, Hangzhou 311121, China.
Chenhui LiDepartment of Prevention Medicine, Hangzhou Normal University, Hangzhou 311121, China.
Shichang WangDepartment of Prevention Medicine, Hangzhou Normal University, Hangzhou 311121, China.
Jinmei LiDepartment of Prevention Medicine, Hangzhou Normal University, Hangzhou 311121, China.
Jinghua WuDepartment of Prevention Medicine, Hangzhou Normal University, Hangzhou 311121, China.
Xiaozhen WangDepartment of Prevention Medicine, Hangzhou Normal University, Hangzhou 311121, China.
Liangwen XuDepartment of Prevention Medicine, Hangzhou Normal University, Hangzhou 311121, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Early screening and detection of individuals at high risk of high-frequency hearing loss and identification of risk factors are critical to reduce the prevalence at community level. However, unlike those for individuals facing occupational auditory hazards, a limited number of hearing loss screening models have been developed for community residents. Therefore, this study used lasso regression with 10-fold cross-validation for feature selection and model construction on 38 questionnaire-based variables of 4010 subjects and applied the model to training and testing cohorts to obtain a risk score. The model achieved an area under the curve (AUC) of 0.844 in the model validation stage and individuals' risk scores were subsequently stratified into low-, medium-, and high-risk categories. A total of 92.79% (1094/1179) of subjects in the high-risk category were confirmed to have hearing loss by audiometry test, which was 3.7 times higher than that in the low-risk group (25.18%, 457/1815). Half of the key indicators were related to modifiable contexts, and they were identified as significantly associated with the incident hearing loss. These results demonstrated that the developed model would be feasible to identify residents at high risk of hearing loss via regular community-level health examinations and detecting individualized risk factors, and eventually provide precision interventions.

Indexed as

AudiometryHearing Loss, High-FrequencyArea Under CurveHumansMass ScreeningRisk Factorscommunity residentshigh-frequency hearing losslasso regressionrisk assessment modelrisk factor

Identifiers

PMID34886032
PMCPMC8657277

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.