The impact of COVID-19 in diabetic kidney disease and chronic kidney disease: A population-based study
Leon-Abarca, J. A.; Memon, R. S.; Rehan, B.; Iftikhar, M.; Chatterjee, A.
Show abstract
BackgroundThe spectrum of pre-existing renal disease is known as a risk factor for severe COVID-19 outcomes. However, little is known about the impact of COVID-19 on patients with diabetic nephropathy in comparison to patients with chronic kidney disease. MethodsWe used the Mexican Open Registry of COVID-19 patients 11 to analyze anonymized records of those who had symptoms related to COVID-19 to analyze the rates of SARS-CoV-2 infection, development of COVID-19 pneumonia, admission, intubation, Intensive Care Unit admission and mortality. Robust Poisson regression was used to relate sex and age to each of the six outcomes and find adjusted prevalences and adjusted prevalence ratios. Also, binomial regression models were performed for those outcomes that had significant results to generate probability plots to perform a fine analysis of the results obtained along age as a continuous variable. ResultsThe adjusted prevalence analysis revealed that that there was a a 87.9% excess probability of developing COVID-19 pneumonia in patients with diabetic nephropathy, a 5% excess probability of being admitted, a 101.7% excess probability of intubation and a 20.8% excess probability of a fatal outcome due to COVID-19 pneumonia in comparison to CKD patients (p< 0.01). ConclusionsPatients with diabetic nephropathy had nearly a twofold rate of COVID-19 pneumonia, a higher probability of admission, a twofold probability of intubation and a higher chance of death once admitted compared to patients with chronic kidney disease alone. Also, both diseases had higher COVID-19 pneumonia rates, intubation rates and case-fatality rates compared to the overall population.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Latin American Registry of renal involvement in COVID-19 disease. The relevance of assessing proteinuria throughout the clinical course 97%
- The Chronic Kidney Disease and Acute Kidney Injury Involvement in COVID-19 Pandemic: A Systematic Review and Meta-analysis 97%
- Incidence and risk factors of kidney impairment on patients with COVID-19: a systematic review and meta-analysis 97%
Similar papers in this journal
- Ramadan and Kidney disease (RaK) risk assessment tool. Potential Risk Calculator for Evaluating the Risk of Ramadan Fasting In Chronic Kidney Disease patients 97%
- Prognostic Imaging Biomarkers for Diabetic Kidney Disease (iBEAt): Study protocol 95%
- Health-related hope and reduced distress associated with fluid and dietary restrictions in advanced chronic kidney disease and dialysis: a cohort study 94%
Similar papers in this journal
- Development and Validation of a Web-based Prediction Model for Acute Kidney Injury after surgery 96%
- Biopsychosocial correlates of somatic symptom burden in chronic kidney disease: results of the Hamburg City Health Study (HCHS) 95%
- Nephron Number and Kidney Outcomes in IgA Nephropathy: A Retrospective Cohort Study 93%
Similar papers in this journal
- Refining the Composition and Significance of Human Renal Intratubular Casts Using Spatial Protein Imaging 93%
- The mediating role of trust in physicians on the association between multidimensional health literacy and medication adherence in hemodialysis: A cross-sectional study 93%
- Preprint server use in kidney disease research: a rapid review 93%
Similar papers in this journal
- Glomerular spatial transcriptomics of IgA nephropathy according to the presence of mesangial proliferation 94%
- Pool walking may temporarily improve renal function by suppressing renin-angiotensin-aldosterone system in pregnant women 94%
- Temporal and sex-dependent gene expression patterns in a renal ischemia-reperfusion injury and recovery pig model 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.