An evidence-based approach to diagnosing patients presenting with orbital inflammatory syndromes (An American Ophthalmological Society Thesis).

PURPOSE: The initial management of patients presenting with orbital inflammatory syndromes (OIS) varies - with some pursuing a diagnostic workup while others treat without any testing. The evidence behind this rationale is limited. A review of patients with orbital inflammation is performed with analysis of diagnostic testing to develop a workflow for such patients. DESIGN: A retrospective review of patients presenting with acute orbital inflammation at a single institution from 2011 - 2020 was conducted. METHODS: Orbital imaging was required for inclusion. Patients with high suspicion of neoplasm, bacterial infection, vascular malformation, or thyroid eye disease were excluded. Review of presenting clinical findings, laboratory workup, orbital imaging, and biopsy were performed. Statistical analysis was performed identifying statistically significant diagnostic and treatment maneuvers. RESULTS: In total, 172 patients met inclusion criteria (66% female, mean age 46 years). The primary clinical presentation was myositis, dacryoadenitis, and infiltrative in 67, 73, and 32 patients (39.0, 43.0, 18.6%, respectively). Laboratory studies were conducted in 145 (84%) while biopsy was performed in 55 (32%). Specific orbital inflammation (SOI) was diagnosed in 29 (16.9%) with most frequent diagnoses being sarcoidosis, IgG4-related disease, inflammatory bowel disease, and systemic lupus erythematosus. The majority (147, 85.5%) was initially treated with steroids, but steroid-sparing agent use was statistically higher in patients with SOI. CONCLUSIONS: In patients presenting with OIS, distinguishing myositis, dacryoadenitis, and infiltrative disease has workup and differential diagnosis impacts. Because SOI is relatively common, sequelae of SOI, and potential steroid-sparing therapy needs, diagnosis via an evidence-based systemic approach is critical.

SPECTRA Phase 2b Study: Impact of Sotatercept on Exercise Tolerance and Right Ventricular Function in Pulmonary Arterial Hypertension.

BACKGROUND: This study aims to assess the impact of sotatercept on exercise tolerance, exercise capacity, and right ventricular function in pulmonary arterial hypertension. METHODS: SPECTRA (Sotatercept Phase 2 Exploratory Clinical Trial in PAH) was a phase 2a, single-arm, open-label, multicenter exploratory study that evaluated the effects of sotatercept by invasive cardiopulmonary exercise testing in participants with pulmonary arterial hypertension and World Health Organization functional class III on combination background therapy. The primary end point was the change in peak oxygen uptake from baseline to week 24. Cardiac magnetic resonance imaging was performed to assess right ventricular function. RESULTS: Among the 21 participants completing 24 weeks of treatment, there was a significant improvement from baseline in peak oxygen uptake, with a mean change of 102.74 mL/min ([95% CIs, 27.72-177.76]; P=0.0097). Sotatercept demonstrated improvements in secondary end points, including resting and peak exercise hemodynamics, and 6-minute walk distance versus baseline measures. Cardiac magnetic resonance imaging showed improvements from baseline at week 24 in right ventricular function. CONCLUSIONS: The clinical efficacy and safety of sotatercept demonstrated in the SPECTRA study emphasize the potential of this therapy as a new treatment option for patients with pulmonary arterial hypertension. Improvements in right ventricular structure and function underscore the potential for sotatercept as a disease-modifying agent with reverse-remodeling capabilities. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03738150.

Epidemiology of Orbital Inflammatory Disease: An AAO IRIS Registry Study.

PURPOSE: The current study queries the American Academy of Ophthalmology (AAO) Intelligent Research in Sight (IRIS) registry for data on the epidemiology, work-up, and management patterns of autoimmune orbital inflammation. METHODS: Analysis and description of patient data from the IRIS registry between 2013 and 2019 reviewing patients with autoimmune or idiopathic orbital inflammation with filters based on International Classification of Disease (ICD) and Current Procedural Terminology (CPT) codes. Patients with thyroid eye disease, orbital cellulitis, and orbital abscess were excluded. MAIN OUTCOME MEASURES: Demographic descriptions included gender, age, geographic region, and treatment. Sub-analysis was performed by assessing rates of imaging, biopsy, lab work-up, and diagnostic categories. RESULTS: In a final cohort of 20,584 patients, the mean age of onset of orbital inflammation was 51.7 years; 67% female; and 63% Caucasian, 21% unknown, 12% Black, 2.6% Asian, and 1.5% other. Only 49 had imaging, 78 had laboratory work-up, and 1,411 had biopsy codes. Treatment results showed 166 patients receiving antibiotics, 224 patients receiving steroids, and 35 patients receiving both. CONCLUSIONS: This study assessed the epidemiology, diagnostic patterns, and treatment patterns for orbital inflammation through the AAO IRIS registry. Practise patterns suggest a relatively low overall rate of imaging and laboratory studies compared to biopsies, although this certainly under-represents the actual number of imaging and laboratory studies and exemplifies the inherent imprecision of using a large database. However, the methodology of this study provides a framework of approaching the IRIS registry for oculoplastic research.

Perceived change in age after functional upper blepharoplasty.

PURPOSE: To evaluate the perceived age of patients before and after functional upper blepharoplasty. METHODS: Retrospective chart review of patients who underwent upper blepharoplasty by a single surgeon at an academic center. The inclusion criterion was having external photographs before and after blepharoplasty. Exclusion criteria included any other concurrent eyelid or facial surgery. Primary endpoint: perceived change in age after surgery as judged by the American Society of Ophthalmic Plastic & Reconstructive Surgery (ASOPRS) surgeons. RESULTS: Sixty-seven patients (14 men, 53 women) were included. Mean pre-operative age was 66.9 years (range 37.8-89.4) and mean post-operative age was 67.4 years (range 38.6-89). The mean perceived age pre-operatively was 68.9 years, and the mean perceived age post-operatively was 67.1 years, a change of 1.8 years (p = 0.0001 by two-tailed paired T-test). Inter-rater reliability of the observers was measured by intraclass correlation coefficient of 0.77 for pre-operative and 0.75 for post-operative photos. The decreased perceived age was 1.9 years for women, 1.4 years for men, 0.3 years for Asians, 1.2 years for Hispanics, and 2.1 years for whites. DISCUSSION: Functional upper blepharoplasty by an experienced ASOPRS surgeon was shown to reduce the perceived age of a patient by an average of 1.8 years.

Stargardt macular dystrophy and therapeutic approaches.

Stargardt macular dystrophy (Stargardt disease; STGD1; OMIM 248200) is the most prevalent inherited macular dystrophy. STGD1 is an autosomal recessive disorder caused by multiple pathogenic sequence variants in the large ABCA4 gene (OMIM 601691). Major advances in understanding both the clinical and molecular features, as well as the underlying pathophysiology, have culminated in many completed, ongoing and planned human clinical trials of novel therapies.The aims of this concise review are to describe (1) the detailed phenotypic and genotypic characteristics of the disease, multimodal imaging findings, natural history of the disease, and pathogenesis, (2) the multiple avenues of research and therapeutic intervention, including pharmacological, cellular therapies and diverse types of genetic therapies that have either been investigated or are under investigation and (3) the exciting novel therapeutic approaches on the translational horizon that aim to treat STGD1 by replacing the entire 6.8 kb ABCA4 open reading frame.

Association of Somatic TET2 Mutations With Giant Cell Arteritis.

OBJECTIVE: Giant cell arteritis (GCA) is an age-related vasculitis. Prior studies have identified an association between GCA and hematologic malignancies (HMs). How the presence of somatic mutations that drive the development of HMs, or clonal hematopoiesis (CH), may influence clinical outcomes in GCA is not well understood. METHODS: To examine an association between CH and GCA, we analyzed sequenced exomes of 470,960 UK Biobank (UKB) participants for the presence of CH and used multivariable Cox regression. To examine the clinical phenotype of GCA in patients with and without somatic mutations across the spectrum of CH to HM, we performed targeted sequencing of blood samples and electronic health record review on 114 patients with GCA seen at our institution. We then examined associations between specific clonal mutations and GCA disease manifestations. RESULTS: UKB participants with CH had a 1.48-fold increased risk of incident GCA compared to UKB participants without CH. GCA risk was highest among individuals with cytopenia (hazard ratio [HR] 2.98, P = 0.00178) and with TET2 mutation (HR 2.02, P = 0.00116). Mutations were detected in 27.2% of our institutional GCA cohort, three of whom had HM at GCA diagnosis. TET2 mutations were associated with vision loss in patients with GCA (odds ratio 4.33, P = 0.047). CONCLUSIONS: CH increases risk for development of GCA in a genotype-specific manner, with the greatest risk being conferred by the presence of mutations in TET2. Somatic TET2 mutations likewise increase the risk of GCA-associated vision loss. Integration of somatic genetic testing in GCA diagnostics may be warranted in the future.

Steroid-responsive unilateral keratouveitis following systemic treatment in a patient with human immunodeficiency virus and leishmaniasis.

Ocular leishmaniasis, a rare form of vector-borne parasitic infection, can affect the adnexa, retina, uvea, and cornea. Coinfection with human immunodeficiency virus (HIV) and Leishmania may be a distinct clinical entity as the pathogens act synergistically, enhancing each other's pathogenicity, and leading to more severe forms of the disease. Ocular leishmaniasis in the setting of HIV coinfection most commonly causes anterior granulomatous uveitis, for which the etiology can be either active ocular infection or posttreatment inflammatory phenomenon. Keratitis is not considered to be associated with HIV but has rarely been seen from direct parasite invasion or in association with miltefosine. The judicious use of steroids in the treatment of ocular leishmaniasis is critical as steroid use is paramount to the treatment of uveitis associated with posttreatment inflammatory phenomenon but can worsen the prognosis when given in the setting of active, untreated infection. Here, we present a case of unilateral keratouveitis in a leishmaniasis and HIV-coinfected male following completion of systemic antileishmanial therapy. The keratouveitis completely resolved with only the addition of topical steroids. The rapid resolution with steroids suggests that keratitis, not only uveitis, can be an immune-mediated phenomenon in post- or ongoing-treatment individuals.

VLDL receptor gene therapy for reducing atherogenic lipoproteins.

Over the past 40 years, there has been considerable research into the management and treatment of atherogenic lipid disorders. Although the majority of treatments and management strategies for cardiovascular disease (CVD) center around targeting low-density lipoprotein cholesterol (LDL-C), there is mounting evidence for the residual CVD risk attributed to high triglyceride (TG) and lipoprotein(a) (Lp(a)) levels despite the presence of lowered LDL-C levels. Among the biological mechanisms for clearing TG-rich lipoproteins, the VLDL receptor (VLDLR) plays a key role in the trafficking and metabolism of lipoprotein particles in multiple tissues, but it is not ordinarily expressed in the liver. Since VLDLR is capable of binding and internalizing apoE-containing TG-rich lipoproteins as well as Lp(a), hepatic VLDLR expression has the potential for promoting clearance of these atherogenic particles from the circulation and managing the residual CVD risk not addressed by current lipid lowering therapies. This review provides an overview of VLDLR function and the potential for developing a genetic medicine based on liver-targeted VLDLR gene expression.

The Role of Steroids for Pediatric Orbital Cellulitis - Review of the Controversy.

Orbital cellulitis in the pediatric population is treated primarily with antibiotic therapy. This leaves the inflammatory component unchecked. Corticosteroid therapy has been used to accelerate recovery and decrease the long-term morbidity in other infectious conditions. Its use has also been proposed for pediatric orbital cellulitis. The aim of this manuscript is to conduct a literature review to summarize existing evidence and understand ongoing controversies. Overall, prior investigations on corticosteroid therapy for pediatric orbital cellulitis are limited by their study design and sample sizes. One of the most discussed potential benefits is that adjuvant steroid therapy for pediatric orbital cellulitis is associated with shorter hospitalization without major infectious complications. However, decreased hospitalization length is an imperfect metric, especially without standardized criteria for hospital discharge. Future studies are warranted to better guide the use of adjuvant steroid therapy and to optimize its potential in the management of pediatric orbital cellulitis.

Investigating real-world consequences of biases in commonly used clinical calculators.

OBJECTIVES: To evaluate whether one summary metric of calculator performance sufficiently conveys equity across different demographic subgroups, as well as to evaluate how calculator predictive performance affects downstream health outcomes. STUDY DESIGN: We evaluate 3 commonly used clinical calculators-Model for End-Stage Liver Disease (MELD), CHA2DS2-VASc, and simplified Pulmonary Embolism Severity Index (sPESI)-on the cohort extracted from the Stanford Medicine Research Data Repository, following the cohort selection process as described in respective calculator derivation papers. METHODS: We quantified the predictive performance of the 3 clinical calculators across sex and race. Then, using the clinical guidelines that guide care based on these calculators' output, we quantified potential disparities in subsequent health outcomes. RESULTS: Across the examined subgroups, the MELD calculator exhibited worse performance for female and White populations, CHA2DS2-VASc calculator for the male population, and sPESI for the Black population. The extent to which such performance differences translated into differential health outcomes depended on the distribution of the calculators' scores around the thresholds used to trigger a care action via the corresponding guidelines. In particular, under the old guideline for CHA2DS2-VASc, among those who would not have been offered anticoagulant therapy, the Hispanic subgroup exhibited the highest rate of stroke. CONCLUSIONS: Clinical calculators, even when they do not include variables such as sex and race as inputs, can have very different care consequences across those subgroups. These differences in health care outcomes across subgroups can be explained by examining the distribution of scores and their calibration around the thresholds encoded in the accompanying care guidelines.

An orbital calcific cyst following exenteration.

A 77-year-old Asian female with a history of left orbit exenteration and lid-sparing reconstruction for recurrent sebaceous carcinoma presented with fluid-like sensation of the left orbit. Magnetic resonance imaging (MRI) demonstrated bright T2 signal and a cyst-like cavity within the exenterated orbit. Decision was made to proceed with surgical exploration and excision. A calcified, bone-like cavity was encountered intraoperatively and removed. Histopathology revealed dense fibrous connective tissue with areas of calcification without osseous metaplasia, suggestive of retained blood in the orbit that underwent dystrophic calcification. This case report illustrates a rare occurrence of a bone-like calcific cyst following exenteration.

Considerations in the reliability and fairness audits of predictive models for advance care planning.

Multiple reporting guidelines for artificial intelligence (AI) models in healthcare recommend that models be audited for reliability and fairness. However, there is a gap of operational guidance for performing reliability and fairness audits in practice. Following guideline recommendations, we conducted a reliability audit of two models based on model performance and calibration as well as a fairness audit based on summary statistics, subgroup performance and subgroup calibration. We assessed the Epic End-of-Life (EOL) Index model and an internally developed Stanford Hospital Medicine (HM) Advance Care Planning (ACP) model in 3 practice settings: Primary Care, Inpatient Oncology and Hospital Medicine, using clinicians' answers to the surprise question ("Would you be surprised if [patient X] passed away in [Y years]?") as a surrogate outcome. For performance, the models had positive predictive value (PPV) at or above 0.76 in all settings. In Hospital Medicine and Inpatient Oncology, the Stanford HM ACP model had higher sensitivity (0.69, 0.89 respectively) than the EOL model (0.20, 0.27), and better calibration (O/E 1.5, 1.7) than the EOL model (O/E 2.5, 3.0). The Epic EOL model flagged fewer patients (11%, 21% respectively) than the Stanford HM ACP model (38%, 75%). There were no differences in performance and calibration by sex. Both models had lower sensitivity in Hispanic/Latino male patients with Race listed as "Other." 10 clinicians were surveyed after a presentation summarizing the audit. 10/10 reported that summary statistics, overall performance, and subgroup performance would affect their decision to use the model to guide care; 9/10 said the same for overall and subgroup calibration. The most commonly identified barriers for routinely conducting such reliability and fairness audits were poor demographic data quality and lack of data access. This audit required 115 person-hours across 8-10 months. Our recommendations for performing reliability and fairness audits include verifying data validity, analyzing model performance on intersectional subgroups, and collecting clinician-patient linkages as necessary for label generation by clinicians. Those responsible for AI models should require such audits before model deployment and mediate between model auditors and impacted stakeholders.

Assessment of Adherence to Reporting Guidelines by Commonly Used Clinical Prediction Models From a Single Vendor: A Systematic Review.

Importance: Various model reporting guidelines have been proposed to ensure clinical prediction models are reliable and fair. However, no consensus exists about which model details are essential to report, and commonalities and differences among reporting guidelines have not been characterized. Furthermore, how well documentation of deployed models adheres to these guidelines has not been studied. Objectives: To assess information requested by model reporting guidelines and whether the documentation for commonly used machine learning models developed by a single vendor provides the information requested. Evidence Review: MEDLINE was queried using machine learning model card and reporting machine learning from November 4 to December 6, 2020. References were reviewed to find additional publications, and publications without specific reporting recommendations were excluded. Similar elements requested for reporting were merged into representative items. Four independent reviewers and 1 adjudicator assessed how often documentation for the most commonly used models developed by a single vendor reported the items. Findings: From 15 model reporting guidelines, 220 unique items were identified that represented the collective reporting requirements. Although 12 items were commonly requested (requested by 10 or more guidelines), 77 items were requested by just 1 guideline. Documentation for 12 commonly used models from a single vendor reported a median of 39% (IQR, 37%-43%; range, 31%-47%) of items from the collective reporting requirements. Many of the commonly requested items had 100% reporting rates, including items concerning outcome definition, area under the receiver operating characteristics curve, internal validation, and intended clinical use. Several items reported half the time or less related to reliability, such as external validation, uncertainty measures, and strategy for handling missing data. Other frequently unreported items related to fairness (summary statistics and subgroup analyses, including for race and ethnicity or sex). Conclusions and Relevance: These findings suggest that consistent reporting recommendations for clinical predictive models are needed for model developers to share necessary information for model deployment. The many published guidelines would, collectively, require reporting more than 200 items. Model documentation from 1 vendor reported the most commonly requested items from model reporting guidelines. However, areas for improvement were identified in reporting items related to model reliability and fairness. This analysis led to feedback to the vendor, which motivated updates to the documentation for future users.

Nursing Workflow Change in a COVID-19 Inpatient Unit Following the Deployment of Inpatient Telehealth: Observational Study Using a Real-Time Locating System.

BACKGROUND: The COVID-19 pandemic prompted widespread implementation of telehealth, including in the inpatient setting, with the goals to reduce potential pathogen exposure events and personal protective equipment (PPE) utilization. Nursing workflow adaptations in these novel environments are of particular interest given the association between nursing time at the bedside and patient safety. Understanding the frequency and duration of nurse-patient encounters following the introduction of a novel telehealth platform in the context of COVID-19 may therefore provide insight into downstream impacts on patient safety, pathogen exposure, and PPE utilization. OBJECTIVE: The aim of this study was to evaluate changes in nursing workflow relative to prepandemic levels using a real-time locating system (RTLS) following the deployment of inpatient telehealth on a COVID-19 unit. METHODS: In March 2020, telehealth was installed in patient rooms in a COVID-19 unit and on movable carts in 3 comparison units. The existing RTLS captured nurse movement during 1 pre- and 5 postpandemic stages (January-December 2020). Change in direct nurse-patient encounters, time spent in patient rooms per encounter, and total time spent with patients per shift relative to baseline were calculated. Generalized linear models assessed difference-in-differences in outcomes between COVID-19 and comparison units. Telehealth adoption was captured and reported at the unit level. RESULTS: Change in frequency of encounters and time spent per encounter from baseline differed between the COVID-19 and comparison units at all stages of the pandemic (all P<.001). Frequency of encounters decreased (difference-in-differences range -6.6 to -14.1 encounters) and duration of encounters increased (difference-in-differences range 1.8 to 6.2 minutes) from baseline to a greater extent in the COVID-19 units relative to the comparison units. At most stages of the pandemic, the change in total time nurses spent in patient rooms per patient per shift from baseline did not differ between the COVID-19 and comparison units (all P>.17). The primary COVID-19 unit quickly adopted telehealth technology during the observation period, initiating 15,088 encounters that averaged 6.6 minutes (SD 13.6) each. CONCLUSIONS: RTLS movement data suggest that total nursing time at the bedside remained unchanged following the deployment of inpatient telehealth in a COVID-19 unit. Compared to other units with shared mobile telehealth units, the frequency of nurse-patient in-person encounters decreased and the duration lengthened on a COVID-19 unit with in-room telehealth availability, indicating "batched" redistribution of work to maintain total time at bedside relative to prepandemic periods. The simultaneous adoption of telehealth suggests that virtual care was a complement to, rather than a replacement for, in-person care. However, study limitations preclude our ability to draw a causal link between nursing workflow change and telehealth adoption. Thus, further evaluation is needed to determine potential downstream implications on disease transmission, PPE utilization, and patient safety.

Monitoring Approaches for a Pediatric Chronic Kidney Disease Machine Learning Model.

OBJECTIVE: The purpose of this study is to evaluate the ability of three metrics to monitor for a reduction in performance of a chronic kidney disease (CKD) model deployed at a pediatric hospital. METHODS: The CKD risk model estimates a patient's risk of developing CKD 3 to 12 months following an inpatient admission. The model was developed on a retrospective dataset of 4,879 admissions from 2014 to 2018, then run silently on 1,270 admissions from April to October, 2019. Three metrics were used to monitor its performance during the silent phase: (1) standardized mean differences (SMDs); (2) performance of a "membership model"; and (3) response distribution analysis. Observed patient outcomes for the 1,270 admissions were used to calculate prospective model performance and the ability of the three metrics to detect performance changes. RESULTS: The deployed model had an area under the receiver-operator curve (AUROC) of 0.63 in the prospective evaluation, which was a significant decrease from an AUROC of 0.76 on retrospective data (p = 0.033). Among the three metrics, SMDs were significantly different for 66/75 (88%) of the model's input variables (p <0.05) between retrospective and deployment data. The membership model was able to discriminate between the two settings (AUROC = 0.71, p <0.0001) and the response distributions were significantly different (p <0.0001) for the two settings. CONCLUSION: This study suggests that the three metrics examined could provide early indication of performance deterioration in deployed models' performance.

Aspiration as a Novel Technique to Address Facial and Periocular Myiasis.

Suction aspiration, which has not yet been described in the treatment for myiasis in the periorbital and facial regions, was used to achieve rapid resolution of maggot burden in a 78-year-old patient who presented with a large ulcerated squamous cell carcinoma of the face. This technique also facilitates submission of parasite samples for further analysis. Suction aspiration had no complications, such as significant residual ruptured maggots in the wound or eye injury. Suction aspiration is a safe and efficient technique to reduce maggot burden that has advantages over classic myiasis treatments, especially near the eyes and airway.

Causal network inference from gene transcriptional time-series response to glucocorticoids.

Gene regulatory network inference is essential to uncover complex relationships among gene pathways and inform downstream experiments, ultimately enabling regulatory network re-engineering. Network inference from transcriptional time-series data requires accurate, interpretable, and efficient determination of causal relationships among thousands of genes. Here, we develop Bootstrap Elastic net regression from Time Series (BETS), a statistical framework based on Granger causality for the recovery of a directed gene network from transcriptional time-series data. BETS uses elastic net regression and stability selection from bootstrapped samples to infer causal relationships among genes. BETS is highly parallelized, enabling efficient analysis of large transcriptional data sets. We show competitive accuracy on a community benchmark, the DREAM4 100-gene network inference challenge, where BETS is one of the fastest among methods of similar performance and additionally infers whether causal effects are activating or inhibitory. We apply BETS to transcriptional time-series data of differentially-expressed genes from A549 cells exposed to glucocorticoids over a period of 12 hours. We identify a network of 2768 genes and 31,945 directed edges (FDR ≤ 0.2). We validate inferred causal network edges using two external data sources: Overexpression experiments on the same glucocorticoid system, and genetic variants associated with inferred edges in primary lung tissue in the Genotype-Tissue Expression (GTEx) v6 project. BETS is available as an open source software package at https://github.com/lujonathanh/BETS.