ArticleBMC research notes2024
Prediction of pure tone thresholds using the speech reception threshold and age in elderly individuals with hearing loss.
Article in BMC research notes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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 citations in OpenAlex.
- Efficacy of ossiculoplasty in patients with chronic otitis media with severe to profound hearing loss.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveEarly detection and effective management of hearing loss constitute the key to improving the quality of life of individuals with hearing loss. However, in standardized pure tone audiometry, it is sometimes difficult for elderly patients to understand and follow all instructions. Audiologists also require time, expertise, and patience to ensure that an elderly can identify the faintest levels of stimuli during a hearing test. Therefore, this study aimed to devise and validate a formula to predict the pure tone threshold at each frequency across 0.5-4 kHz (PTTs) using speech reception threshold.
methodsThe 1226 audiograms of hearing-impaired individuals aged 60-90 years were reviewed. The random sample function randomly assigned 613 participants to the training and testing sets each. A linear model was created to predict the PTT value at each frequency based on variables significant at all frequencies across 0.5-4 kHz. The adjusted-R2 value was considered to indicate the performance of the predictive model. Pearson's correlation coefficient was used to describe the relationship between the actual and predicted PTT at 0.5, 1, 2, and 4 kHz among the testing set to measure the performance of the proposed model.
resultsThe predictive model was devised using variables based on the speech recognition threshold (SRT) after adjusting with age in the training set. The overall prediction accuracy demonstrated a higher adjusted-R
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