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PURPOSE: Otoacoustic emissions (OAE) are a common screening tool to evaluate cochlear function. Middle ear dysfunction has been shown to impact results of otoacoustic emission testing, but there are limited data on the effect of tympanostomy tubes on OAE. The purpose of this study was to determine whether tympanostomy tube placement significantly improved OAE. METHODS: A retrospective review of charts was completed for patients younger than 18 years old who underwent tympanostomy tube placement from January 1, 2018 to September 1, 2023 and had preoperative and postoperative OAE testing within 6 months of surgery. The primary variable was presence of OAE preoperatively and postoperatively. Chi-square analysis and t test were used for statistical analysis. RESULTS: A total of 212 ears were examined from 111 pediatric patients who underwent tympanostomy tube placement during the study period. Presence of OAE at 3000, 4000, and 5000 Hz were all noted to significantly increase following tympanostomy tube placement, with OAE presence increasing from approximately 27.8% of the sample preoperatively to 95.3% postoperatively at 3000 and 4000 Hz. Patients who noted improvement had a significantly higher proportion of type B tympanogram preoperatively, compared to a higher proportion of type A tympanogram noted in patients who did not note improvement. CONCLUSION: Tympanostomy tubes can significantly improve otoacoustic emissions in patients with middle ear dysfunction.
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OBJECTIVE: Diagnosis of otosclerosis on temporal bone CT images is often difficult because the imaging findings are frequently subtle. Our aim was to assess the utility of deep learning analysis in diagnosing otosclerosis on temporal bone CT images. METHODS: A total of 198 temporal bone CT images were divided into the training set (n = 140) and the test set (n = 58). The final diagnosis (otosclerosis-positive or otosclerosis-negative) was determined by an experienced senior radiologist who carefully reviewed all 198 temporal bone CT images while correlating with clinical and intraoperative findings. In deep learning analysis, a rectangular target region that includes the area of the fissula ante fenestram was extracted and fed into the deep learning training sessions to create a diagnostic model. Transfer learning was used with the deep learning model architectures of AlexNet, VGGNet, GoogLeNet, and ResNet. The test data set was subsequently analyzed using these models and by another radiologist with 3 years of experience in neuroradiology following completion of a neuroradiology fellowship. The performance of the radiologist and the deep learning models was determined using the senior radiologist's diagnosis as the gold standard. RESULTS: The diagnostic accuracies were 0.89, 0.72, 0.81, 0.86, and 0.86 for the subspecialty trained radiologist, AlexNet, VGGNet, GoogLeNet, and ResNet, respectively. The performances of VGGNet, GoogLeNet, and ResNet were not significantly different compared to the radiologist. In addition, GoogLeNet and ResNet demonstrated non-inferiority compared to the radiologist. CONCLUSIONS: Deep learning technique may be a useful supportive tool in diagnosing otosclerosis on temporal bone CT. KEY POINTS: ⢠Deep learning can be a helpful tool for the diagnosis of otosclerosis on temporal bone CT. ⢠Deep learning analyses with GoogLeNet and ResNet demonstrate non-inferiority when compared to the subspecialty trained radiologist. ⢠Deep learning may be particularly useful in medical institutions without experienced radiologists.
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Aprendizado Profundo , Otosclerose , Humanos , Otosclerose/diagnóstico por imagem , Radiologistas , Osso Temporal/diagnóstico por imagem , Tomografia Computadorizada por Raios XRESUMO
INTRODUCTION: Inpatient and outpatient evaluation is important for management of temporal bone trauma due to the possible otologic complications that can result. However, there is limited literature on follow up rates following temporal bone fracture. This study aimed to determine the proportion of patients lost to follow up after sustaining temporal bone fractures and identify factors associated with loss to follow up. METHODS: Retrospective review of adult patients who sustained temporal bone fractures at a level I trauma center from January 1, 2019 to January 1, 2024 was completed (IRB H-44161). The primary outcome included prevalence of patient loss to follow up. Secondary variables included initial radiographic and exam findings, otologic complications, and demographic characteristics. Patients who were seen in follow up and lost to follow up were compared, and odds of loss to follow up was calculated. RESULTS: Sixty-nine patients met inclusion criteria for this study, of which 30 patients (43.5%) were lost to follow up. Patients who were White had a significantly lower odds of loss to follow up than those who were not White (OR = 0.2506 (95% CI: 0.0706, 0.8067, P = .0024). While need for acute management was not significantly different between the groups, a significantly lower proportion of patients who were intubated on presentation (P = .0091), had abnormal otoscopic exam (P = .0211), and had otologic complications (P = .0056) were lost to follow up. CONCLUSION: Almost half of patients who sustained temporal bone fractures, including a significantly higher odds of minority race/ethnicity patients, were lost to follow up.
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Perda de Seguimento , Fraturas Cranianas , Osso Temporal , Humanos , Masculino , Feminino , Osso Temporal/lesões , Osso Temporal/diagnóstico por imagem , Estudos Retrospectivos , Fraturas Cranianas/complicações , Fraturas Cranianas/epidemiologia , Fraturas Cranianas/diagnóstico por imagem , Adulto , Pessoa de Meia-Idade , Idoso , Fatores de RiscoRESUMO
OBJECTIVE: To determine the impact of comorbid depression on readmission after vestibular schwannoma resection. STUDY DESIGN: Retrospective database analysis. SETTING: National database of readmitted patients. PATIENTS: The Nationwide Readmission Database (NRD) was retrospectively reviewed for patients with history of vestibular schwannoma, identified by International Classification of Disease, Ninth Revision (ICD-9) code 225.1 and ICD-10 code D33.3, who underwent surgical resection (ICD-9 04.01, ICD-10-PCS 00BN0ZZ) in 2020. INTERVENTIONS: Therapeutic. MAIN OUTCOME MEASURES: Need for rehabilitation, need for procedures, length of stay, cost of readmission, and insurance status. RESULTS: A total of 1997 patients were readmitted after resection of vestibular schwannoma in 2020. Of these patients, 290 had history of a comorbid depressive disorder.A significantly higher proportion of patients with history of comorbid depression were transferred to a rehabilitation facility after readmission (11.30% versus 4.30%, p < 0.001). Length of stay (p = 0.227) and total readmission cost (p = 0.723) did not differ significantly, but a significantly lower proportion had private insurance (55.40% versus 64.40%, p = 0.027). CONCLUSION: Depression is associated with higher utilization of postoperative rehabilitation services and higher rates of medical comorbidities, and should be considered during preoperative evaluation.
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Comorbidade , Neuroma Acústico , Readmissão do Paciente , Humanos , Neuroma Acústico/cirurgia , Readmissão do Paciente/estatística & dados numéricos , Feminino , Masculino , Pessoa de Meia-Idade , Estudos Retrospectivos , Adulto , Complicações Pós-Operatórias/epidemiologia , Complicações Pós-Operatórias/psicologia , Idoso , Tempo de Internação/estatística & dados numéricos , Depressão/epidemiologia , Bases de Dados Factuais , Transtorno Depressivo/epidemiologiaRESUMO
OBJECTIVE: To examine the types of pediatric middle ear tumors and review the demographics, management, and survival of pediatric patients with rhabdomyosarcoma (RMS) of the middle ear. METHODS: Pediatric patients in the Surveillance, Epidemiology, and End Results (SEER) database were included from 1973 to 2014 based on a diagnosis of middle ear tumors using the ICD O-3 code: C30.1: Middle ear primary site. Patients were included from ages 0-18 years. RESULTS: Forty pediatric middle ear tumor cases were identified. Twenty patients were female (50%). Twenty-seven (67.5%) cases were rhabdomyosarcomas (RMS). Pediatric RMS patients tended to be diagnosed in early childhood (mean age 5.30 years, standard deviation 2.9, range 1.00-13.00, 59.3% of patients were ages 5 or below). Most pediatric RMS patients received chemotherapy and radiation therapy as part of the treatment regimen (88.8%). Finally, the 5-year overall and disease-specific survival rates were 59% and 63% respectively. CONCLUSIONS: Pediatric middle ear tumors are rare. Females and male pediatric patients are both at risk for middle ear tumors. RMS is the most common malignant middle ear tumor affecting pediatric patients. Despite the use of multimodality therapies, survival rates for pediatric patients with RMS of the middle ear are low. Physicians may consider including middle ear tumors on the differential diagnosis for pediatric patients with symptoms presenting similarly to non-resolving otitis media.