International exchange on the clinical practice and research of rheumatic skin diseases: A report of the 5th International Conference of Cutaneous Lupus Erythematosus.

The 5th International Conference of Cutaneous Lupus Erythematosus was held in Tokyo, Japan on May 9 and 10, 2023. The latest topics on the pathogenesis, diagnosis, assessment, and treatment of cutaneous lupus erythematosus, dermatomyositis, and scleroderma (systemic sclerosis, morphea) were presented by experts in each field and new developments discussed. In these rheumatic skin diseases, many clinical trials of novel therapies targeting cytokines, signaling molecules, plasmacytoid dendritic cells, B cells, and other molecules are currently underway, and standardization of outcome assessment was discussed. In addition, the selection of the therapeutic agents available for the diversity of each case is becoming more important, together with the ongoing pathophysiological analysis of the diseases. The achievements of this conference will further promote the development of clinical practice and research in rheumatic skin diseases through international exchange among researchers. We hope that by reporting a summary of the conference in this manuscript, we can share its contents with readers.

Stroke Lesion Segmentation and Deep Learning: A Comprehensive Review.

Stroke is a medical condition that affects around 15 million people annually. Patients and their families can face severe financial and emotional challenges as it can cause motor, speech, cognitive, and emotional impairments. Stroke lesion segmentation identifies the stroke lesion visually while providing useful anatomical information. Though different computer-aided software are available for manual segmentation, state-of-the-art deep learning makes the job much easier. This review paper explores the different deep-learning-based lesion segmentation models and the impact of different pre-processing techniques on their performance. It aims to provide a comprehensive overview of the state-of-the-art models and aims to guide future research and contribute to the development of more robust and effective stroke lesion segmentation models.

Patients with autoimmune skin diseases are at increased risk of adverse pregnancy outcomes.

BACKGROUND: Increased rates of adverse pregnancy outcomes have been reported in association with rheumatologic diseases such as systemic lupus erythematosus, rheumatoid arthritis, dermatomyositis. However, little is known about pregnancy outcomes in patients with autoimmune skin diseases. OBJECTIVE: This study aimed to determine the frequency of adverse pregnancy outcomes in patients with autoimmune skin diseases. We hypothesized that similar to rheumatic diseases, the rate of adverse pregnancy outcomes in patients with autoimmune skin diseases would be higher than the general population. STUDY DESIGN: This is a case control study using the TriNetX US Collaborative Network, which is a database of electronic medical records of >95 million patients seen at 57 healthcare organizations in the United States. All pregnant women between the ages of 15 and 44 years who were seen at a healthcare organization between January 1, 2016 and December 31, 2021 were included. Participants with autoimmune skin disease were matched to healthy controls and controls with systemic rheumatologic conditions (systemic lupus erythematosus or rheumatoid arthritis). For both the autoimmune skin disease and healthy control groups, those with systemic rheumatologic condition or hidradenitis suppurativa were excluded. The primary outcomes were adverse pregnancy outcomes defined as spontaneous abortion, gestational hypertension, preeclampsia or eclampsia, gestational diabetes mellitus, intrauterine growth restriction, preterm premature rupture of membranes, preterm birth, and stillbirth. Patients with autoimmune skin diseases and controls were 1:1 propensity score-matched by age, race, ethnicity, comorbidities, obesity, and substance use. For each outcome, odds ratio with a 95% confidence interval was calculated. RESULTS: A total of 2788 patients with autoimmune skin diseases were matched to 2788 healthy controls. Patients with autoimmune skin diseases were at a higher risk of spontaneous abortions than controls (odds ratio, 1.54; 95% confidence interval, 1.36-1.75; P<.001). Compared with patients with systemic lupus erythematosus, patients with autoimmune skin diseases were at lower risk of having infants with intrauterine growth restriction (odds ratio, 0.59; 95% confidence interval, 0.4-0.87; P=.01), preterm birth (odds ratio, 0.68; 95% confidence interval, 0.47-0.98; P=.04), and stillbirth (odds ratio, 0.50; 95% confidence interval, 0.25-0.97; P=.04). The differences in adverse pregnancy outcomes between patients with autoimmune skin diseases and those with rheumatoid arthritis were not statistically significant. CONCLUSION: Patients with autoimmune skin diseases are at a higher risk of spontaneous abortions than patients without autoimmune skin diseases. When analyzed by each autoimmune skin disease, patients with cutaneous lupus erythematosus or vitiligo remained at increased risk of spontaneous abortions compared with patients without autoimmune skin diseases. Patients with autoimmune skin diseases have similar risks of adverse pregnancy outcomes as patients with rheumatoid arthritis, but lower risks than patients with systemic lupus erythematosus.

Machine Learning for Medical Image Translation: A Systematic Review.

BACKGROUND: CT scans are often the first and only form of brain imaging that is performed to inform treatment plans for neurological patients due to its time- and cost-effective nature. However, MR images give a more detailed picture of tissue structure and characteristics and are more likely to pick up abnormalities and lesions. The purpose of this paper is to review studies which use deep learning methods to generate synthetic medical images of modalities such as MRI and CT. METHODS: A literature search was performed in March 2023, and relevant articles were selected and analyzed. The year of publication, dataset size, input modality, synthesized modality, deep learning architecture, motivations, and evaluation methods were analyzed. RESULTS: A total of 103 studies were included in this review, all of which were published since 2017. Of these, 74% of studies investigated MRI to CT synthesis, and the remaining studies investigated CT to MRI, Cross MRI, PET to CT, and MRI to PET. Additionally, 58% of studies were motivated by synthesizing CT scans from MRI to perform MRI-only radiation therapy. Other motivations included synthesizing scans to aid diagnosis and completing datasets by synthesizing missing scans. CONCLUSIONS: Considerably more research has been carried out on MRI to CT synthesis, despite CT to MRI synthesis yielding specific benefits. A limitation on medical image synthesis is that medical datasets, especially paired datasets of different modalities, are lacking in size and availability; it is therefore recommended that a global consortium be developed to obtain and make available more datasets for use. Finally, it is recommended that work be carried out to establish all uses of the synthesis of medical scans in clinical practice and discover which evaluation methods are suitable for assessing the synthesized images for these needs.

Implementation and evaluation of a store-and-forward teledermatology workflow in a United States safety-net hospital urgent care emergency center: A retrospective cohort study.

Background: Teledermatology (TD) is an important method for increasing access to care in outpatient settings. However, less is known regarding its use in emergency/urgent care centers. Objective: To evaluate the effect of TD on urgent care emergency center (UCEC) dwell time and postencounter utilization. Study type and methods: This retrospective cohort study evaluated patients in a safety-net hospital (Parkland Health, Dallas, Texas, USA) UCEC, who (1) received a TD consult in 2018, (2) were referred to dermatology clinic in 2017, or (3) were referred to dermatology clinic in 2018 without a TD consult. Results: We evaluated 2024 patients from 2017 to 2018. Of the 973 referred to dermatology clinic in 2018, 332 (34%) received TD consultations. Mean dwell time for patients receiving TD was longer versus the 2017 cohort (303 vs 204 minutes, respectively). Patients receiving TD consultation with inflammatory skin conditions had lower odds of dermatology clinic visits compared with those that did not (odds ratio, 0.5; 95% CI, 0.3-0.8). Teledermatology was not associated with differences in repeat UCEC utilization. Limitations: Single institution study and inability to account for differences in patient complexity. Conclusion: TD increases dwell time in a safety-net hospital's UCEC but can reduce dermatology clinic utilization for patients with inflammatory skin conditions.

Proportional Recovery After Stroke: Addressing Concerns Regarding Mathematical Coupling and Ceiling Effects.

Baseline scores after stroke have long been known as a good predictor of post-stroke outcomes. Similarly, the extent of baseline impairment has been shown to strongly correlate with spontaneous recovery in the first 3 to 6 months after stroke, a principle known as proportional recovery. However, recent critiques have proposed that proportional recovery is confounded, most notably by mathematical coupling and ceiling effects, and that it may not be a valid model for post-stroke recovery. This article reviews the current understanding of proportional recovery after stroke, discusses its supposed confounds of mathematical coupling and ceiling effects, and comments on the validity and usefulness of proportional recovery as a model for post-stroke recovery. We demonstrate that mathematical coupling of the true measurement value is not a real statistical confound, but rather a notational construct that has no effect on the correlation itself. On the other hand, mathematical coupling does apply to the measurement error and can spuriously amplify correlation effect sizes, but should be negligible in most cases. We also explain that compression toward ceiling and the corresponding proportional recovery relationship are consistent with our understanding of post-stroke recovery dynamics, rather than being unwanted confounds. However, while proportional recovery is valid, it is not particularly groundbreaking or meaningful as previously thought, just like how correlations between baseline scores and outcomes are relatively common in stroke research. Whether through proportional recovery or baseline-outcome regression, baseline scores are a starting point for investigating factors that determine recovery and outcomes after stroke.

Predicting Motor Outcomes Using Atlas-Based Voxel Features of Post-Stroke Neuroimaging: A Scoping Review.

BACKGROUND: Atlas-based voxel features have the potential to aid motor outcome prognostication after stroke, but are seldom used in clinically feasible prediction models. This could be because neuroimaging feature development is a non-standardized, complex, multistep process. This is a barrier to entry for researchers and poses issues for reproducibility and validation in a field of research where sample sizes are typically small. OBJECTIVES: The primary aim of this review is to describe the methodologies currently used in motor outcome prediction studies using atlas-based voxel neuroimaging features. Another aim is to identify neuroanatomical regions commonly used for motor outcome prediction. METHODS: A Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol was constructed and OVID Medline and Scopus databases were searched for relevant studies. The studies were then screened and details about imaging modality, image acquisition, image normalization, lesion segmentation, region of interest determination, and imaging measures were extracted. RESULTS: Seventeen studies were included and examined. Common limitations were a lack of detailed reporting on image acquisition and the specific brain templates used for normalization and a lack of clear reasoning behind the atlas or imaging measure selection. A wide variety of sensorimotor regions relate to motor outcomes and there is no consensus use of one single sensorimotor atlas for motor outcome prediction. CONCLUSION: There is an ongoing need to validate imaging predictors and further improve methodological techniques and reporting standards in neuroimaging feature development for motor outcome prediction post-stroke.

Non-adherence of surgical treatment in patients with non-melanoma skin cancer: a retrospective cohort pilot study.

There is limited data on non-adherence for surgical treatment in non-melanoma skin cancer (NMSC) patients. The objective of this single-center, retrospective cohort study is to compare rates of non-adherence of surgical treatment options, determine factors associated with non-adherence, and identify barriers for non-adherence. All adult patients with NMSC (> 18 years) seen between 2015 and 2017 recommended surgical treatment (surgical excision and electrodessication and curettage (ED&C) or Mohs surgery) were eligible. Non-adherence was defined as not completing recommended treatment and reasons for non-adherence were collected. Out of 427 patients that met inclusion criteria, patients recommended surgical excision and ED&C had a lower non-adherence rate of 3.4% compared to those recommended Mohs (11.4%) (p = 0.006). Factors associated with non-adherence included self-pay patients (19.07% adherent vs. 43.24% non-adherent, p = 0.004). Multivariate logistic regression analysis confirmed that Mohs patients were more likely to be non-adherent (odds ratio (OR) = 3.839, 95% confidence interval (CI) (1.435-10.270), p = 0.007) compared to surgical excision and ED&C patients. Males were more likely to be non-adherent (OR = 2.474, 95% CI (1.105-5.542), p = 0.028) to females, and self-pay patients were more likely to be non-adherent than those with other payers (OR = 3.050, 95% CI (1.437-6.475), p = 0.004). Of the 37 patients who were non-adherent, the most common reasons were loss to follow-up (46%), social reasons (41%), medical reasons (38%), and financial reasons (22%). There was a significant difference in non-adherence rates between surgical treatments for NMSCs in our cohort. Our study suggests the need for future interventional studies that implement strategies and patient education to decrease non-adherence rates.

Late-onset cutaneous lupus erythematosus patients have distinctive clinical features and demographics versus early-onset patients.

BACKGROUND: Cutaneous lupus erythematosus (CLE) can present later in life, but frequency and risk factors of late-onset CLE patients are not well characterized. The study determined frequency of late-onset CLE and compared the demographic and disease characteristics between early-onset and late-onset CLE in a cohort of patients with CLE. OBJECTIVES: To determine the frequency and compare clinical features of early-onset and late-onset CLE. METHODS: This was a cross-sectional study of CLE patients seen in outpatient dermatology clinics at University of Texas Southwestern Medical Center (UTSW) and Parkland Health and Hospital System, Dallas, TX, from April 2009 to May 2019. The primary outcome was the age of CLE onset, stratified by early-onset (<50 years) and late-onset CLE (≥50 years). Predictor variables significantly associated with CLE onset groups were identified by univariate and multivariable logistic regression analyses. RESULTS: Of the 291 CLE patients studied, 79% were early-onset, and 21% were late-onset. Multivariable logistic regression analyses identified that Caucasian race (odds ratio (OR): 2.23, 95% Confidence Interval (CI): 1.19-4.19, p = 0.013), having a CLE subtype other than chronic (OR: 2.18, 95% CI: 1.02-4.65, p = 0.044), and drug-induced cases (OR: 4.65, 95% CI: 1.18-18.24, p = 0.028) were significantly associated with late-onset CLE. Early-onset CLE patients were more likely to have oral ulcers (OR: 3.58, 95% CI: 1.46-8.78, p = 0.005) and renal disorders (OR: 4.02, 95% CI: 1.10-14.71, p = 0.036). LIMITATIONS: This was a single center study. Age of onset was self-reported and late-onset CLE cohort has a small sample size. CONCLUSIONS: Our diverse cohort of CLE patients had about one out of five patients with CLE experiencing disease onset after 50 years old. These patients have distinct demographic and clinical presentations compared to early-onset CLE patients. Providers should remain mindful of CLE in older patients with photosensitive rashes and mild systemic symptoms.

Influence of Socio-Demographic Factors in Patients With Cutaneous Lupus Erythematosus.

Cutaneous lupus erythematosus (CLE) is a chronic autoimmune skin disease with potential for systemic involvement, disfigurement, and significant disease burden. The relationships of demographics and socioeconomic status with patients with CLE are emerging topics with important clinical implications. The primary objective of our study is to perform a literature review of studies that have investigated demographic and socioeconomic factors amongst patients with CLE and determine whether these factors influence diagnosis frequency, disease severity and outcomes or health related quality of life. We searched multiple databases to identify literature addressing CLE and concepts such as race, ethnicity, gender, income, education level and geographic location. Information regarding primary research objective was extracted from all full text articles, and a summary of findings was prepared. We found that race and ethnicity can influence CLE diagnosis frequency and disease outcomes. Chronic cutaneous lupus (CCLE) occurs more frequently in Black patients, often with higher overall disease damage. Differences between genders exist in CLE in terms of health-related quality of life, as female gender was a risk factor for worse quality of life in several studies. Lower income, low educational attainment, and lack of health insurance all contribute to poorer overall outcomes in CLE patients. This review will help inform physicians about populations at risk for potentially worse outcomes to guide treatment decisions for patients with CLE and provide important information to design interventions that address modifiable social determinants of health in this population.

The Genetic Landscape of Cutaneous Lupus Erythematosus.

Cutaneous lupus erythematosus (CLE) is an autoimmune connective tissue disease that can exist as a disease entity or within the context of systemic lupus erythematosus (SLE). Over the years, efforts to elucidate the genetic underpinnings of CLE and SLE have yielded a wealth of information. This review examines prior studies investigating the genetics of CLE at the DNA and RNA level and identifies future research areas. In this literature review, we examined the English language literature captured within the MEDLINE and Embase databases using pre-defined search terms. First, we surveyed studies investigating various DNA studies of CLE. We identified three predominant areas of focus in HLA profiling, complement deficiencies, and genetic polymorphisms. An increased frequency of HLA-B8 has been strongly linked to CLE. In addition, multiple genes responsible for mediating innate immune response, cell growth, apoptosis, and interferon response confer a higher risk of developing CLE, specifically TREX1 and SAMHD1. There was a strong association between C2 complement deficiency and CLE. Second, we reviewed literature studying aberrations in the transcriptomes of patients with CLE. We reviewed genetic aberrations initiated by environmental insults, and we examined the interplay of dysregulated inflammatory, apoptotic, and fibrotic pathways in the context of the pathomechanism of CLE. These current learnings will serve as the foundation for further advances in integrating personalized medicine into the care of patients with CLE.

A Systematic Review of the Progression of Cutaneous Lupus to Systemic Lupus Erythematosus.

Lupus erythematosus is an autoimmune disease that may manifest in a variety of organs and tissues including the skin, kidney, brain, heart and lung. Many patients present with cutaneous lupus, where disease is often limited to the skin, but are at risk for developing systemic lupus. The objective of our present study is to perform a systematic review of studies that investigated patient cohorts and populations for the occurrence of cutaneous lupus progressing to systemic lupus. Inclusion criteria required that studies present longitudinal data of patients with limited cutaneous lupus erythematosus who were followed for development of systemic lupus erythematosus. Studies were excluded if patients had concurrent diagnosis of SLE, or if they failed to present longitudinal data. Medline and Embase were searched for English language studies using the Ovid platform. A total of 25 adult studies were identified, as well as 8 pediatric studies. The rate of cutaneous to systemic lupus progression ranged between 0% to 42% in the adult studies and 0% to 31% in the pediatric groups. The variability in these rates were due to differences in patient populations, study design, criteria used to diagnose systemic lupus, and follow-up time. Common risk factors associated with systemic lupus erythematosus development including having positive anti-nuclear antibodies, hematologic abnormalities, and higher number of lupus classification criteria at baseline. This study emphasizes the importance for providers to routinely monitor for systemic lupus in patients with cutaneous lupus.

Investigating the structure-function relationship of the corticomotor system early after stroke using machine learning.

BACKGROUND: Motor outcomes after stroke can be predicted using structural and functional biomarkers of the descending corticomotor pathway, typically measured using magnetic resonance imaging and transcranial magnetic stimulation, respectively. However, the precise structural determinants of intact corticomotor function are unknown. Identifying structure-function links in the corticomotor pathway could provide valuable insight into the mechanisms of post-stroke motor impairment. This study used supervised machine learning to classify upper limb motor evoked potential status using MRI metrics obtained early after stroke. METHODS: Retrospective data from 91 patients (49 women, age 35-97 years) with moderate to severe upper limb weakness within a week after stroke were included in this study. Support vector machine classifiers were trained using metrics from T1- and diffusion-weighted MRI to classify motor evoked potential status, empirically measured using transcranial magnetic stimulation. RESULTS: Support vector machine classification of motor evoked potential status was 81% accurate, with false positives more common than false negatives. Important structural MRI metrics included diffusion anisotropy asymmetry in the supplementary and pre-supplementary motor tracts, maximum cross-sectional lesion overlap in the sensorimotor tract and ventral premotor tract, and mean diffusivity asymmetry in the posterior limbs of the internal capsule. INTERPRETATIONS: MRI measures of corticomotor structure are good but imperfect predictors of corticomotor function. Residual corticomotor function after stroke depends on both the extent of cross-sectional macrostructural tract damage and preservation of white-matter microstructural integrity. Analysing the corticomotor pathway using a multivariable MRI approach across multiple tracts may yield more information than univariate biomarker analyses.