Nurse Brenda Eadie told how she has been left penniless after Long Covid stopped her working
Nurses suffering from Long Covid have told how their lives and careers have been left in ruins after picking up the virus as they cared for others.
“I was in hospital for two days on oxygen and was then sent home with a nebuliser. I spent about a whole month in bed at home. While she moved into other areas of nursing temporarily, with the worsening of her condition she eventually had to admit her career was over. But as Covid Special Leave has ended she is now on standard sick pay which will drop to half pay tomorrow and cease altogether in September.
She continued: “Covid and Long Covid are in the process of robbing me of everything: my job, my career, my home, my income and my beloved cats. I am trying to get my affairs in order but, to be brutally honest, I don’t see the point in continuing anymore. Baillie said: “People are crying out for treatment and there is an economic consequence of this as well because people are being taken out of the labour market.
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Organ and cell-specific biomarkers of Long-COVID identified with targeted proteomics and machine learning - Molecular MedicineBackground Survivors of acute COVID-19 often suffer prolonged, diffuse symptoms post-infection, referred to as “Long-COVID”. A lack of Long-COVID biomarkers and pathophysiological mechanisms limits effective diagnosis, treatment and disease surveillance. We performed targeted proteomics and machine learning analyses to identify novel blood biomarkers of Long-COVID. Methods A case–control study comparing the expression of 2925 unique blood proteins in Long-COVID outpatients versus COVID-19 inpatients and healthy control subjects. Targeted proteomics was accomplished with proximity extension assays, and machine learning was used to identify the most important proteins for identifying Long-COVID patients. Organ system and cell type expression patterns were identified with Natural Language Processing (NLP) of the UniProt Knowledgebase. Results Machine learning analysis identified 119 relevant proteins for differentiating Long-COVID outpatients (Bonferonni corrected P | 0.01). Protein combinations were narrowed down to two optimal models, with nine and five proteins each, and with both having excellent sensitivity and specificity for Long-COVID status (AUC = 1.00, F1 = 1.00). NLP expression analysis highlighted the diffuse organ system involvement in Long-COVID, as well as the involved cell types, including leukocytes and platelets, as key components associated with Long-COVID. Conclusions Proteomic analysis of plasma from Long-COVID patients identified 119 highly relevant proteins and two optimal models with nine and five proteins, respectively. The identified proteins reflected widespread organ and cell type expression. Optimal protein models, as well as individual proteins, hold the potential for accurate diagnosis of Long-COVID and targeted therapeutics.
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