Three Distinct Transcriptional Profiles of Monocytes Associate with Disease Activity in Scleroderma Patients.

OBJECTIVE: Patients with diffuse cutaneous systemic sclerosis (dcSSc) display a complex clinical phenotype. Transcriptional profiling of whole blood or tissue from patients are affected by changes in cellular composition that drive gene expression and an inability to detect minority cell populations. We undertook this study to focus on the 2 main subtypes of circulating monocytes, classical monocytes (CMs) and nonclassical monocytes (NCMs) as a biomarker of SSc disease severity. METHODS: SSc patients were recruited from the Prospective Registry for Early Systemic Sclerosis. Clinical data were collected, as well as peripheral blood for isolation of CMs and NCMs. Age-, sex-, and race-matched healthy volunteers were recruited as controls. Bulk macrophages were isolated from the skin in a separate cohort. All samples were assayed by RNA sequencing (RNA-seq). RESULTS: We used an unbiased approach to cluster patients into 3 groups (groups A-C) based on the transcriptional signatures of CMs relative to controls. Each group maintained their characteristic transcriptional signature in NCMs. Genes up-regulated in group C demonstrated the highest expression compared to the other groups in SSc skin macrophages, relative to controls. Patients from groups B and C exhibited worse lung function than group A, although there was no difference in SSc skin disease at baseline, relative to controls. We validated our approach by applying our group classifications to published bulk monocyte RNA-seq data from SSc patients, and we found that patients without skin disease were most likely to be classified as group A. CONCLUSION: We are the first to show that transcriptional signatures of CMs and NCMs can be used to unbiasedly stratify SSc patients and correlate with disease activity outcome measures.

Prominent rash and multisystem inflammatory syndrome in a 29-year-old patient with COVID-19: a case report.

BACKGROUND: Adult patients with coronavirus disease present primarily with respiratory symptoms, but children and some adults may display a more systemic inflammatory syndrome with rash, fever, mucosal changes, and elevated inflammatory biomarkers. CASE PRESENTATION: Here, we report the case of a 29-year-old Hispanic patient presenting with significant rash and multisystem inflammation. We describe his clinical course, review dermatological manifestations of coronavirus disease, and summarize the pathophysiology of coronavirus disease-associated multisystem inflammation. CONCLUSION: This case should alert physicians to the atypical nature of presenting rash with minimal respiratory symptoms in coronavirus disease.

Risk assessment for inpatient survival in the long-term acute care setting after prolonged critical illness.

OBJECTIVE: The past decade has witnessed growth in the long-term acute care (LTAC) hospital industry. There are no reliable risk assessment models that can adjust outcomes across such facilities with different criteria for admitting patients. Variation in reported outcomes makes it difficult to determine whether a patient, or group of patients, may benefit from such care. This study sought to determine the extent to which survival in the LTAC setting is associated with age, race, residual organ system failures (OSFs), or APACHE (acute physiology and chronic health evaluation) III scores at the time of admission to LTAC. DESIGN: Retrospective medical record review. SETTING: Four freestanding facilities of a LTAC hospital. PATIENTS: A sample of 300 hospital admissions weighted to represent the study hospital population. MEASUREMENTS: Inpatient survival modeled as a function of age, APACHE III score calculated within 72 h prior to LTAC admission, and residual OSFs present on admission to LTAC. RESULTS: Logistic regression analysis shows age and OSF were most predictive of inpatient survival (receiver operating characteristic curve area = 0.81). APACHE III score was not predictive of survival in the multivariate model. CONCLUSIONS: Survival in LTAC is primarily associated with age and OSFs, which should be used to adjust for patient populations among LTAC settings when comparing outcomes. Our model identifies a group of patients with the poorest likelihood of survival in the LTAC setting, and may be used to facilitate dialogue with patients and family in cases where continued aggressive care is least effective.