RESUMEN
BACKGROUND: Recent studies have demonstrated that individuals hospitalized due to COVID-19 can be affected by "long-COVID" symptoms for as long as one year after discharge. OBJECTIVES: Our study objective is to identify data-driven clusters of patients using a novel, unsupervised machine learning technique. METHODS: The study uses data from 437 patients hospitalized in New York City between March 3rd and May 15th of 2020. The data used was abstracted from medical records and collected from a follow-up survey for up to one-year post-hospitalization. Hospitalization data included demographics, comorbidities, and in-hospital complications. The survey collected long-COVID symptoms, and information on general health, social isolation, and loneliness. To perform the analysis, we created a graph by projecting the data onto eight principal components (PCs) and running the K-nearest neighbors algorithm. We then used Louvain's algorithm to partition this graph into non-overlapping clusters. RESULTS: The cluster analysis produced four clusters with distinct health and social connectivity patterns. The first cluster (n = 141) consisted of patients with both long-COVID neurological symptoms (74%) and social isolation/loneliness. The second cluster (n = 137) consisted of healthy patients who were also more socially connected and not lonely. The third cluster (n = 96) contained patients with neurological symptoms who were socially connected but lonely, and the fourth cluster (n = 63) consisted entirely of patients who had traumatic COVID hospitalization, were intubated, suffered symptoms, but were socially connected and experienced recovery. CONCLUSION: The cluster analysis identified social isolation and loneliness as important features associated with long-COVID symptoms and recovery after hospitalization. It also confirms that social isolation and loneliness, though connected, are not necessarily the same. Physicians need to be aware of how social characteristics relate to long-COVID and patient's ability to cope with the resulting symptoms.
Asunto(s)
COVID-19 , Hospitalización , Soledad , Aislamiento Social , Humanos , COVID-19/epidemiología , COVID-19/psicología , Ciudad de Nueva York/epidemiología , Masculino , Femenino , Hospitalización/estadística & datos numéricos , Persona de Mediana Edad , Análisis por Conglomerados , Aislamiento Social/psicología , Anciano , Soledad/psicología , Adulto , Síndrome Post Agudo de COVID-19 , Aprendizaje Automático no Supervisado , SARS-CoV-2RESUMEN
The lymphatic vasculature regulates lung homeostasis through drainage of fluid and trafficking of immune cells and plays a key role in the response to lung injury in several disease states. We have previously shown that lymphatic dysfunction occurs early in the pathogenesis of chronic obstructive pulmonary disease (COPD) caused by cigarette smoke (CS) and that this is associated with increased thrombin and fibrin clots in lung lymph. However, the direct effects of CS and thrombin on lymphatic endothelial cells (LECs) in COPD are not entirely clear. Studies of the blood vasculature have shown that COPD is associated with increased thrombin after CS exposure that causes endothelial dysfunction characterized by changes in the expression of coagulation factors and leukocyte adhesion proteins. Here, we determined whether similar changes occur in LECs. We used an in vitro cell culture system and treated human lung microvascular lymphatic endothelial cells with cigarette smoke extract (CSE) and/or thrombin. We found that CSE treatment led to decreased fibrinolytic activity in LECs, which was associated with increased expression of plasminogen activator inhibitor 1 (PAI-1). LECs treated with both CSE and thrombin together had a decreased expression of tissue factor pathway inhibitor (TFPI) and increased expression of adhesion molecules. RNA sequencing of lung LECs isolated from mice exposed to CS also showed upregulation of prothrombotic and inflammatory pathways at both acute and chronic exposure time points. Analysis of publicly available single-cell RNA sequencing of LECs as well as immunohistochemical staining of lung tissue from COPD patients supported these data and showed increased expression of inflammatory markers in LECs from COPD patients compared to those from controls. These studies suggest that in parallel with blood vessels, the lymphatic endothelium undergoes inflammatory changes associated with CS exposure and increased thrombin in COPD. Further research is needed to unravel the mechanisms by which these changes affect lymphatic function and drive tissue injury in COPD.