Subperiosteal Abscess of the Orbit: Long-term Trends in Bacteriology and Clinical Outcomes and Current Management Recommendations.

Purpose: To evaluate the impact over time of evolving upper respiratory pathogens, modified microbial terminology, and improved laboratory isolation on the bacteriology and management of sinusitis-related subperiosteal abscess of the orbit.

Methods: Comparative case series of pediatric patients with bacterial sinusitis-related subperiosteal abscess from 2012 to 2022. Outcomes, culture results, age-specific findings, and antibiotic duration were compared with those in 1977 to 1992, 1988 to 1998, 1999 to 2008, and 2002 to 2012 cohorts at the same institution.

Applications and potential of machine learning augmented chest X-ray interpretation in cardiology.

The chest X-ray (CXR) has a wide range of clinical indications in the field of cardiology, from the assessment of acute pathology to disease surveillance and screening. Despite many technological advancements, CXR interpretation error rates have remained constant for decades. The application of machine learning has the potential to substantially improve clinical workflow efficiency, pathology detection accuracy, error rates and clinical decision making in cardiology.

Herpes Simplex Virus Dacryoadenitis Preceding Skin Vesicles.

Herpes simplex virus involvement of the orbit is rare. We report the case of an immunocompetent patient who presented with preseptal edema, erythema, decreased vision, and dacryoadenitis prior to the appearance of vesicular skin lesions and in the absence of corneal dendrites. The patient's clinical picture failed to improve on empiric therapy with intravenous antibiotics.

Isolated Ophthalmoplegia After Periorbital Hyaluronic Acid Filler Injection.

Facial filler injections are the second most commonly performed in-office cosmetic procedure. Vision loss is the most feared complication of hyaluronic acid (HA) filler injection, but isolated ophthalmoplegia can also occur. We report the case of a 45-year-old woman who developed nausea and diplopia following HA filler injection to the bilateral periorbital region.

Opportunities for developing neural stem cell treatments for acute ischemic stroke: A systematic review and gap analysis.

Ischemic stroke is a leading cause of disability and death. Current treatments are limited. Stem cell therapy has been highlighted as a potentially effective treatment to mitigate damage and restore function, but efficacy results are mixed.

Effects of a comprehensive brain computed tomography deep learning model on radiologist detection accuracy.

Objectives: Non-contrast computed tomography of the brain (NCCTB) is commonly used to detect intracranial pathology but is subject to interpretation errors. Machine learning can augment clinical decision-making and improve NCCTB scan interpretation. This retrospective detection accuracy study assessed the performance of radiologists assisted by a deep learning model and compared the standalone performance of the model with that of unassisted radiologists.

Analysis of Line and Tube Detection Performance of a Chest X-ray Deep Learning Model to Evaluate Hidden Stratification.

This retrospective case-control study evaluated the diagnostic performance of a commercially available chest radiography deep convolutional neural network (DCNN) in identifying the presence and position of central venous catheters, enteric tubes, and endotracheal tubes, in addition to a subgroup analysis of different types of lines/tubes. A held-out test dataset of 2568 studies was sourced from community radiology clinics and hospitals in Australia and the USA, and was then ground-truth labelled for the presence, position, and type of line or tube from the consensus of a thoracic specialist radiologist and an intensive care clinician. DCNN model performance for identifying and assessing the positioning of central venous catheters, enteric tubes, and endotracheal tubes over the entire dataset, as well as within each subgroup, was evaluated.

Periocular Infection With Nocardia nova Following Dacryocystorhinostomy With Silicone Stent Intubation.

Nocardia species are aerobic, rod-shaped, Gram-positive bacteria that are ubiquitous throughout the environment. Nocardia nova has been reported as the second most prevalent Nocardia species. However, reports of ocular and periocular infection caused by this organism are rare.

Predicting Acoustic Hearing Preservation Following Cochlear Implant Surgery Using Machine Learning.

Objectives: The aim of the study was to train and test supervised machine-learning classifiers to predict acoustic hearing preservation after CI using preoperative clinical data.

Study Design: Retrospective predictive modeling study of prospectively collected single-institution CI dataset.

Methods: One hundred and seventy-five patients from a REDCap database including 761 patients >18 years who underwent CI and had audiometric testing preoperatively and one month after surgery were included.

Association of Human Endogenous Retrovirus-W (HERV-W) Copies with Pemphigus Vulgaris.

Background: Pemphigus is classified as a group of chronic, recurrent, and potentially fatal bullous autoimmune diseases that leads to blisters and skin lesions resulting from IgG antibodies and the loss of cellular connections in the epidermis. Human endogenous retrovirus (HERV) sequences and their products (RNA, cytosolic DNA, and proteins) can modulate the immune system and contribute to autoimmunity. The extent to which, HERV-W env copies may be involved in the pathogenesis of pemphigus remains to be elucidated.

Machine Learning Augmented Interpretation of Chest X-rays: A Systematic Review.

Limitations of the chest X-ray (CXR) have resulted in attempts to create machine learning systems to assist clinicians and improve interpretation accuracy. An understanding of the capabilities and limitations of modern machine learning systems is necessary for clinicians as these tools begin to permeate practice. This systematic review aimed to provide an overview of machine learning applications designed to facilitate CXR interpretation.

A Case of Fabry Disease With Lacrimal Gland Involvement.

Fabry disease is an X-linked lysosomal storage disease resulting from an error in the glycosphingolipid metabolic pathway, which leads to accumulation of globotriaosylceramide in lysosomes of the skin, kidneys, heart, brain, and other organs. There are no existing reports of histologically proven lacrimal gland involvement in Fabry disease. The authors report the case of a 26-year-old male with Fabry disease who presented with bilateral upper eyelid dermatochalasis, steatoblepharon, and prolapsed lacrimal glands.

Assault-related Orbital Trauma at an Urban Level I Trauma Center: Racial Segregation and Other Neighborhood-level Social Determinants.

Purpose: To report the demographics of assault-related orbital fractures over a 7-year period treated at a level I urban trauma center, as well as describe and analyze the variation in assault rates across different racial/ethnic neighborhoods for patients residing in Milwaukee County.

Methods: A retrospective chart review was conducted for patients who sustained assault-related orbital fractures from January 1, 2013, through December 31, 2019, at the Froedtert & Medical College of Wisconsin, in Milwaukee, Wisconsin. A series of negative binomial regression models evaluating the association of neighborhood (i.

Predictors of improvement in quality of life at 12-month follow-up in patients undergoing anterior endoscopic skull base surgery.

Background: Patients with pituitary lesions experience decrements in quality of life (QoL) and treatment aims to arrest or improve QoL decline.

Objective: To detect associations with QoL in trans-nasal endoscopic skull base surgery patients and train supervised learning classifiers to predict QoL improvement at 12 months.

Methods: A supervised learning analysis of a prospective multi-institutional dataset (451 patients) was conducted.

Charting the potential of brain computed tomography deep learning systems.

Brain computed tomography (CTB) scans are widely used to evaluate intracranial pathology. The implementation and adoption of CTB has led to clinical improvements. However, interpretation errors occur and may have substantial morbidity and mortality implications for patients.

Association between human leukocyte antigens and cutaneous adverse drug reactions to antiepileptics and antibiotics in the Iranian population.

In this case-control study, class І and ІІ human leukocyte antigen (HLA) alleles in Iranian patients with benign and severe cutaneous adverse drug reactions (CADRs) due to aromatic anticonvulsants and antibiotics were evaluated. Patients diagnosed with CADRs (based on clinical and laboratory findings) with a Naranjo score of ≥ 4 underwent blood sampling and HLA-DNA typing. The control group comprised 90 healthy Iranian adults.

Punctate Pattern and Pemphigus: Is There Any Evidence of Punctate Pattern Among Iranian Patients?

Aim: To examine the prevalence of this novel pattern among Iranian patients with pemphigus and peruse the relationship between the presence of a punctate pattern with clinical severity of disease and histopathological findings.

Methods: One hundred recently diagnosed patients with pemphigus were enrolled. DIF evaluation and routine light microscopy were performed on their biopsy specimens.

Assessment of the effect of a comprehensive chest radiograph deep learning model on radiologist reports and patient outcomes: a real-world observational study.

Objectives: Artificial intelligence (AI) algorithms have been developed to detect imaging features on chest X-ray (CXR) with a comprehensive AI model capable of detecting 124 CXR findings being recently developed. The aim of this study was to evaluate the real-world usefulness of the model as a diagnostic assistance device for radiologists.

Design: This prospective real-world multicentre study involved a group of radiologists using the model in their daily reporting workflow to report consecutive CXRs and recording their feedback on level of agreement with the model findings and whether this significantly affected their reporting.

Do comprehensive deep learning algorithms suffer from hidden stratification? A retrospective study on pneumothorax detection in chest radiography.

Objectives: To evaluate the ability of a commercially available comprehensive chest radiography deep convolutional neural network (DCNN) to detect simple and tension pneumothorax, as stratified by the following subgroups: the presence of an intercostal drain; rib, clavicular, scapular or humeral fractures or rib resections; subcutaneous emphysema and erect versus non-erect positioning. The hypothesis was that performance would not differ significantly in each of these subgroups when compared with the overall test dataset.

Design: A retrospective case-control study was undertaken.

Natural Language Processing Applications in the Clinical Neurosciences: A Machine Learning Augmented Systematic Review.

Natural language processing (NLP), a domain of artificial intelligence (AI) that models human language, has been used in medicine to automate diagnostics, detect adverse events, support decision making and predict clinical outcomes. However, applications to the clinical neurosciences appear to be limited. NLP has matured with the implementation of deep transformer models (e.

Effect of a comprehensive deep-learning model on the accuracy of chest x-ray interpretation by radiologists: a retrospective, multireader multicase study.

Background: Chest x-rays are widely used in clinical practice; however, interpretation can be hindered by human error and a lack of experienced thoracic radiologists. Deep learning has the potential to improve the accuracy of chest x-ray interpretation. We therefore aimed to assess the accuracy of radiologists with and without the assistance of a deep-learning model.

Clinical outcomes associated with robotic and computer-navigated total knee arthroplasty: a machine learning-augmented systematic review.

Background: Robotic (RTKA) and computer-navigated total knee arthroplasty (CNTKA) are increasingly replacing manual techniques in orthopaedic surgery. This systematic review compared clinical outcomes associated with RTKA and CNTKA and investigated the utility of natural language processing (NLP) for the literature synthesis.

Methods: A comprehensive search strategy was implemented.

Chest radiographs and machine learning - Past, present and future.

Despite its simple acquisition technique, the chest X-ray remains the most common first-line imaging tool for chest assessment globally. Recent evidence for image analysis using modern machine learning points to possible improvements in both the efficiency and the accuracy of chest X-ray interpretation. While promising, these machine learning algorithms have not provided comprehensive assessment of findings in an image and do not account for clinical history or other relevant clinical information.