Risk of Acquired Cholesteatoma and External Auditory Canal Stenosis in Traumatic Brain Injury: A Nationwide Population-Based Cohort Study.
Hung-Che LinCheng-Ping ShihHsin-Chien ChenChun-An ChengYuahn-Sieh HuangChen-Shien LinChi-Hsian ChungBor-Rong HuangJih-Chin LeeWei-Chuan ShangkuanWu-Chien ChienChi-Ming ChuPublished in: International journal of environmental research and public health (2020)
The aim of study is to investigate the risk of developing acquired cholesteatoma and external auditory canal (EAC) stenosis after traumatic brain injury (TBI) from the Taiwan National Health Insurance Research Database (NHIRD). Each subject was individually traced from their index date to identify those who received a diagnosis of acquired cholesteatoma and EAC stenosis. Cox regression analyses were applied to determine the risk of TBI-related acquired cholesteatoma and EAC stenosis. The follow-up data collected over 10 years were obtained from the TBI and comparison cohorts, of 455,834 and 911,668 patients, respectively. Multivariate analysis demonstrated that TBI significantly increased the risk of cholesteatoma (adjusted hazard ratio (HR), 1.777; 95% confidence interval (CI), 1.494-2.114, p < 0.001) and EAC stenosis (adjusted (HR), 3.549; 95% (CI), 2.713-4.644, p < 0.001). In our subgroup injury analysis, falls had the highest associated risk (4.308 times), followed by traffic injuries (66.73%; 3.718 times that of the control group). Otolaryngologists should not neglect the clinical importance and carefully investigate the possibility of subsequent cholesteatoma and EAC stenosis, which leads to hearing impairment in patients with TBI. Our research also shows the important role in preventing TBI, especially as a result of traffic injuries and falls.
Keyphrases
- traumatic brain injury
- health insurance
- severe traumatic brain injury
- mild traumatic brain injury
- end stage renal disease
- chronic kidney disease
- ejection fraction
- emergency department
- newly diagnosed
- randomized controlled trial
- clinical trial
- peritoneal dialysis
- affordable care act
- electronic health record
- deep learning
- finite element