Glomerulonephritis associated with systemic sclerosis: a case report.

BACKGROUND: Systemic sclerosis is a multiorgan autoimmune disease that can overlap with other rheumatologic disorders; however, co-occurrence with antineutrophil cytoplasmic antibody-associated vasculitis is rare. CASE PRESENTATION: A 39-year-old Persian female patient with systemic sclerosis according to American College of Rheumatology/European League Against Rheumatism 2013 criteria with a disease duration of 6 years was admitted to the hospital due to a rise in creatinine level in July 2021. She had complaints of nasal speech and feeling of nasal perforation. The first symptoms of antineutrophil cytoplasmic antibody-associated vasculitis had started 5 years earlier with palpable purpura in the lower limbs, hemoptysis, and positive perinuclear (p)-antibody-associated vasculitis level (> 300 AU/mL). Still, the diagnosis was not achieved due to the patient's reluctance to undergo a biopsy. She was treated with azathioprine (150 mg/day) and prednisolone (10 mg/day) during the 5-year follow-up. Her renal biopsy results showed cortical renal tissue with a cellular crescent in more than 50% of the specimen, rupture of the Bowman capsule and the glomerular basement membrane, peri-glomerular inflammation, and mild tubular atrophy in microscopic examinations. The immunofluorescence study resulted in a granular pattern of immune deposits along the glomerular basement membrane, mesangial tissue, and tubular basement membranes. CONCLUSION: We reported a rare case of comorbid systemic sclerosis and antineutrophil cytoplasmic antibody-associated vasculitis with nasal perforation. Her renal biopsy showed immune deposits along the glomerular basement membrane, mesangial tissue, and tubular basement membranes. Overlapping with other collagen vascular diseases can occur in rheumatology patients with uncommon manifestations. In systemic sclerosis, renal involvement in the form of glomerulonephritis is infrequent, and comorbid systemic lupus erythematosus or antineutrophil cytoplasmic antibody-associated vasculitis should be considered.

Cardiopulmonary predictors of mortality in patients with COVID-19: What are the findings?

BACKGROUND: Since 2019, coronavirus disease 2019 (COVID-19) has been the leading cause of mortality worldwide. AIMS: To determine independent predictors of mortality in COVID-19, and identify any associations between pulmonary disease severity and cardiac involvement. METHODS: Clinical, laboratory, electrocardiography and computed tomography (CT) imaging data were collected from 389 consecutive patients with COVID-19. Patients were divided into alive and deceased groups. Independent predictors of mortality were identified. Kaplan-Meier analysis was performed, based on patients having a troponin concentration>99th percentile (cardiac injury) and a CT severity score ≥18. RESULTS: The mortality rate was 29.3%. Cardiac injury (odds ratio [OR] 2.19, 95% confidence interval [CI] 1.14-4.18; P=0.018), CT score ≥18 (OR 2.24, 95% CI 1.15-4.34; P=0.017), localized ST depression (OR 3.77, 95% CI 1.33-10.67; P=0.012), hemiblocks (OR 3.09, 95% CI 1.47-6.48; P=0.003) and history of leukaemia/lymphoma (OR 3.76, 95% CI 1.37-10.29; P=0.010) were identified as independent predictors of mortality. Additionally, patients with cardiac injury and CT score ≥ 18 were identified to have a significantly shorter survival time (mean 14.21 days, 95% CI 10.45-17.98 days) than all other subgroups. There were no associations between CT severity score and electrocardiogram or cardiac injury in our results. CONCLUSIONS: Our findings suggest that using CT imaging and electrocardiogram characteristics together can provide a better means of predicting mortality in patients with COVID-19. We identified cardiac injury, CT score ≥18, presence of left or right hemiblocks on initial electrocardiogram, localized ST depression and history of haematological malignancies as independent predictors of mortality in patients with COVID-19.

Cardiopulmonary predictors of mortality in patients with COVID-19: What are the findings? prédicteurs cardio-pulmonaire de la mortalité chez les patients ayant la COVID-19 : quel éclairage?

Background. – Since 2019, coronavirus disease 2019 (COVID-19) has been the leading cause of mortality worldwide. Aims. – To determine independent predictors of mortality in COVID-19, and identify any associations between pulmonary disease severity and cardiac involvement. Methods. – Clinical, laboratory, electrocardiography and computed tomography (CT) imaging data were collected from 389 consecutive patients with COVID-19. Patients were divided into alive and deceased groups. Independent predictors of mortality were identified. Kaplan-Meier analysis was performed, based on patients having a troponin concentration > 99th percentile (cardiac injury) and a CT severity score ≥ 18. Results. – The mortality rate was 29.3%. Cardiac injury (odds ratio [OR] 2.19, 95% confidence interval [CI] 1.14–4.18;P = 0.018), CT score ≥ 18 (OR 2.24, 95% CI 1.15–4.34;P = 0.017), localized ST depression (OR 3.77, 95% CI 1.33–10.67;P = 0.012), hemiblocks (OR 3.09, 95% CI 1.47–6.48;P = 0.003) and history of leukaemia/lymphoma (OR 3.76, 95% CI 1.37–10.29;P = 0.010) were identified as independent predictors of mortality. Additionally, patients with cardiac injury and CT score ≥ 18 were identified to have a significantly shorter survival time (mean 14.21 days, 95% CI 10.45–17.98 days) than all other subgroups. There were no associations between CT severity score and electrocardiogram or cardiac injury in our results. Conclusions. – Our findings suggest that using CT imaging and electrocardiogram characteristics together can provide a better means of predicting mortality in patients with COVID-19. We identified cardiac injury, CT score ≥ 18, presence of left or right hemiblocks on initial electrocardiogram, localized ST depression and history of haematological malignancies as independent predictors of mortality in patients with COVID-19.