Related Experiment Video
Updated: Feb 5, 2026
High-Speed Human Temporal Bone Sectioning for the Assessment of COVID-19-Associated Middle Ear Pathology
Published on: May 18, 2022
Diagnosing Middle Ear Pathology in 6- to 9-Month-Old Infants Using Wideband Absorbance: A Risk Prediction Model
Joshua Myers1,2, Joseph Kei2, Sreedevi Aithal1,2
1Department of Audiology, Townsville Hospital and Health Service, Australia.
Insights
A new risk prediction model accurately detects middle ear pathology in infants using wideband absorbance measures. This model shows promise for improving infant hearing diagnostics and screening programs.
Area of Science:
- Audiology
- Pediatric Otolaryngology
- Biomedical Engineering
Background:
- Middle ear pathology is common in infants and can impact hearing development.
- Early detection of middle ear issues is crucial for timely intervention and management.
- Wideband absorbance measures offer a detailed assessment of middle ear function.
Purpose of the Study:
- To develop and validate a risk prediction model for identifying middle ear pathology in infants aged 6 to 9 months.
- To utilize wideband absorbance measures as the primary data source for the prediction model.
- To ensure the model's generalizability and accuracy in a clinical setting.
Main Methods:
- Logistic regression was employed to build the risk prediction model using wideband absorbance data from 249 infants.
- Principal component analysis and penalized fitting were used to refine the model for better generalization.
- Model performance was assessed using area under the receiver operating characteristic curve (AUC) and calibration curves, with validation on opposite ears and bootstrap resampling.
Main Results:
- The developed risk prediction model demonstrated strong discrimination, with an AUC of 0.887 for the fitted model.
- Validation using opposite ears (AUC = 0.852) and bootstrap resampling (AUC = 0.874) confirmed the model's robustness.
- Satisfactory calibration indicated high agreement between the model's predicted probabilities and observed middle ear dysfunction.
Conclusions:
- The risk prediction model exhibits accurate discrimination and calibration, suggesting good generalizability to new infant populations.
- The model holds potential for application in both diagnostic and screening settings for infant middle ear pathology.
- Further research is recommended to evaluate the model's real-world performance and clinical impact in screening and diagnostic contexts.
Purpose:
The aim of this study was to develop a risk prediction model for detecting middle ear pathology in 6- to 9-month-old infants using wideband absorbance measures.
Method:
Two hundred forty-nine infants aged 23-39 weeks (Mdn = 28 weeks) participated in the study. Distortion product otoacoustic emissions and high-frequency tympanometry were tested in both ears of each infant to assess middle ear function. Wideband absorbance was measured at ambient pressure in each participant from 226 to 8000 Hz. Absorbance results from 1 ear of each infant were used to predict middle ear dysfunction, using logistic regression. To develop a model likely to generalize to new infants, the number of variables was reduced using principal component analysis, and a penalty was applied when fitting the model. The model was validated using the opposite ears and with bootstrap resampling. Model performance was evaluated through measures of discrimination and calibration. Discrimination was assessed with the area under the receiver operating characteristic curve (AUC); and calibration, with calibration curves, which plotted actual against predicted probabilities.
Results:
AUC of the fitted model was 0.887. The model validated adequately when applied to the opposite ears (AUC = 0.852) and with bootstrap resampling (AUC = 0.874). Calibration was satisfactory, with high agreement between predictions and observed results.
Conclusions:
The risk prediction model had accurate discrimination and satisfactory calibration. Validation results indicate that it may generalize well to new infants. The model could potentially be used in diagnostic and screening settings. In the context of screening, probabilities provide an intuitive and flexible mechanism for setting the referral threshold that is sensitive to the costs associated with true and false-positive outcomes. In a diagnostic setting, predictions could be used to supplement visual inspection of absorbance for individualized diagnoses. Further research assessing the performance and impact of the model in these contexts is warranted.
More Related Videos
05:35Experience is Instrumental in Tuning a Link Between Language and Cognition: Evidence from 6- to 7- Month-Old Infants' Object Categorization
Published on: April 19, 2017
03:05Author Spotlight: Advancing Early Detection and Treatment of Gastrointestinal Tumors
Published on: February 16, 2024
Related Concept Videos
01:24Diagnosing Acidosis and Alkalosis
First, the pH level is assessed to determine whether the blood pH is normal (7.35–7.45), low (acidosis), or high (alkalosis).
Next, the PCO2 and...
02:27Predicting Molecular Geometry
01:16Anatomy of the Ear
01:12Relative Risk
01:03Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
01:26Factors Affecting the Risk of Infection
The integrity and count of the white blood cells help the body resist pathogens and fight infection. When impaired, it reduces the body's resistance to pathogens. The acidic pH levels of the gastrointestinal, genitourinary tracts, and skin...