Retinal age gap as a predictive biomarker for mortality risk. Issue 4 (18th January 2022)
- Record Type:
- Journal Article
- Title:
- Retinal age gap as a predictive biomarker for mortality risk. Issue 4 (18th January 2022)
- Main Title:
- Retinal age gap as a predictive biomarker for mortality risk
- Authors:
- Zhu, Zhuoting
Shi, Danli
Guankai, Peng
Tan, Zachary
Shang, Xianwen
Hu, Wenyi
Liao, Huan
Zhang, Xueli
Huang, Yu
Yu, Honghua
Meng, Wei
Wang, Wei
Ge, Zongyuan
Yang, Xiaohong
He, Mingguang - Abstract:
- Abstract : Aim: To develop a deep learning (DL) model that predicts age from fundus images (retinal age) and to investigate the association between retinal age gap (retinal age predicted by DL model minus chronological age) and mortality risk. Methods: A total of 80 169 fundus images taken from 46 969 participants in the UK Biobank with reasonable quality were included in this study. Of these, 19 200 fundus images from 11 052 participants without prior medical history at the baseline examination were used to train and validate the DL model for age prediction using fivefold cross-validation. A total of 35 913 of the remaining 35 917 participants had available mortality data and were used to investigate the association between retinal age gap and mortality. Results: The DL model achieved a strong correlation of 0.81 (p<0·001) between retinal age and chronological age, and an overall mean absolute error of 3.55 years. Cox regression models showed that each 1 year increase in the retinal age gap was associated with a 2% increase in risk of all-cause mortality (hazard ratio (HR)=1.02, 95% CI 1.00 to 1.03, p=0.020) and a 3% increase in risk of cause-specific mortality attributable to non-cardiovascular and non-cancer disease (HR=1.03, 95% CI 1.00 to 1.05, p=0.041) after multivariable adjustments. No significant association was identified between retinal age gap and cardiovascular- or cancer-related mortality. Conclusions: Our findings indicate that retinal age gap might be aAbstract : Aim: To develop a deep learning (DL) model that predicts age from fundus images (retinal age) and to investigate the association between retinal age gap (retinal age predicted by DL model minus chronological age) and mortality risk. Methods: A total of 80 169 fundus images taken from 46 969 participants in the UK Biobank with reasonable quality were included in this study. Of these, 19 200 fundus images from 11 052 participants without prior medical history at the baseline examination were used to train and validate the DL model for age prediction using fivefold cross-validation. A total of 35 913 of the remaining 35 917 participants had available mortality data and were used to investigate the association between retinal age gap and mortality. Results: The DL model achieved a strong correlation of 0.81 (p<0·001) between retinal age and chronological age, and an overall mean absolute error of 3.55 years. Cox regression models showed that each 1 year increase in the retinal age gap was associated with a 2% increase in risk of all-cause mortality (hazard ratio (HR)=1.02, 95% CI 1.00 to 1.03, p=0.020) and a 3% increase in risk of cause-specific mortality attributable to non-cardiovascular and non-cancer disease (HR=1.03, 95% CI 1.00 to 1.05, p=0.041) after multivariable adjustments. No significant association was identified between retinal age gap and cardiovascular- or cancer-related mortality. Conclusions: Our findings indicate that retinal age gap might be a potential biomarker of ageing that is closely related to risk of mortality, implying the potential of retinal image as a screening tool for risk stratification and delivery of tailored interventions. … (more)
- Is Part Of:
- British journal of ophthalmology. Volume 107:Issue 4(2023)
- Journal:
- British journal of ophthalmology
- Issue:
- Volume 107:Issue 4(2023)
- Issue Display:
- Volume 107, Issue 4 (2023)
- Year:
- 2023
- Volume:
- 107
- Issue:
- 4
- Issue Sort Value:
- 2023-0107-0004-0000
- Page Start:
- 547
- Page End:
- 554
- Publication Date:
- 2022-01-18
- Subjects:
- telemedicine
Ophthalmology -- Periodicals
617.7 - Journal URLs:
- http://bjo.bmj.com/ ↗
http://bjo.bmjjournals.com/ ↗
http://www.bmj.com/archive ↗ - DOI:
- 10.1136/bjophthalmol-2021-319807 ↗
- Languages:
- English
- ISSNs:
- 0007-1161
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
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