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Background The objective was to assess the association of mental health disorders with in‐hospital complication and mortality rates in patients undergoing head and neck cancer surgery. Methods In this exploratory retrospective study, the Nationwide Inpatient Sample was queried from 2003 to 2014 for all patients with a diagnosis of head and neck cancer who underwent surgery. Univariate cross‐tabulation, logistic regression, and propensity score matching (PSM) were used to compare demographics, procedure‐related variables, and in‐hospital postoperative complications and mortality between patients with and without selected comorbid mental health disorders. Results Of 39 600 included patients, 3390 (8.6%) had a selected comorbid mental health disorder diagnosis. After PSM, patients with selected mental health disorders had increased risk of overall medical complications on multivariable analysis (OR 1.28 [CI 1.12–1.46], P < 0.001) but not overall surgical complications or mortality. Conclusions Patients with a mental health disorder diagnosis have increased risk of in‐hospital medical, certain surgical, and total complications.

Objectives: Accurate diagnosis of cholesteatomas is crucial. However, cholesteatomas can easily be missed in routine otoscopic exams. Convolutional neural networks (CNNs) have performed well in medical image classification, so we evaluated their use for detecting cholesteatomas in otoscopic images.Study Design: Design and evaluation of artificial intelligence driven workflow for cholesteatoma diagnosis.Methods: Otoscopic images collected from the faculty practice of the senior author were deidentified and labeled by the senior author as cholesteatoma, abnormal noncholesteatoma, or normal. An image classification workflow was developed to automatically differentiate cholesteatomas from other possible tympanic membrane appearances. Eight pretrained CNNs were trained on our otoscopic images, then tested on a withheld subset of images to evaluate their final performance. CNN intermediate activations were also extracted to visualize important image features.Results: A total of 834 otoscopic images were collected, further categorized into 197 cholesteatoma, 457 abnormal non-cholesteatoma, and 180 normal. Final trained CNNs demonstrated strong performance, achieving accuracies of 83.8%-98.5% for differentiating cholesteatoma from normal, 75.6%-90.1% for differentiating cholesteatoma from abnormal non-cholesteatoma, and 87.0%-90.4% for differentiating cholesteatoma from non-cholesteatoma (abnormal non-cholesteatoma + normal). DenseNet201 (100% sensitivity, 97.1% specificity), NASNetLarge (100% sensitivity, 88.2% specificity), and MobileNetV2 (94.1% sensitivity, 100% specificity) were among the best performing CNNs in distinguishing cholesteatoma versus normal. Visualization of intermediate activations showed robust detection of relevant image features by the CNNs. Conclusion:While further refinement and more training images are needed to improve performance, artificial intelligence-driven analysis of otoscopic images shows great promise as a diagnostic tool for detecting cholesteatomas.

Background As patient satisfaction is a significant qualitative consideration in measuring aesthetic surgery outcome, it is important to characterize the individual factors which shape the patient perspective about blepharoplasty. Objectives This study analyzed patient reviews following blepharoplasty on the aesthetic surgery social media platform Realself.com to determine which aspects of the surgical process have the most significant impact on patient satisfaction. Methods Blepharoplasty reviews were gathered from Realself.com using an automated web crawler. These reviews were characterized as positive or negative, then given a specific category that more specifically defined the theme of the review. Additional variables including the specialty of the reviewed physician and any patient self-reported ratings were documented. Results A total of 1991 reviews pertaining to blepharoplasty were collected. Among reviews with self-reported “worth it” ratings, 93.5% were positive. Following categorization of all reviews, 1865 (93.7%) were positive and 126 (6.3%) were negative. Of the positive reviews, the most common overall themes were bedside manner (n=899, 48.2%), aesthetic result (n=859, 46.1%), and overall comfort (n=58, 3.1%). Among negative reviews, most pertained to aesthetic result (n=100, 79.4%), and bedside manner (n=14, 11.1%). The most frequently encountered physician specialties performing blepharoplasty were plastic surgery (n=1101, 55.3%), ophthalmology (n=634, 31.8%), and otolaryngology (n=69, 3.5%). Conclusions The majority of patient blepharoplasty reviews were positive. The most prominent factor driving positive reviews was bedside manner, followed by aesthetic results. Negative reviews were most frequently attributed to sub-optimal aesthetic results. Most blepharoplasties in our study cohort were performed by plastic and oculoplastic surgeons.

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