Renal histopathology spectrum in children with kidney diseases in Saudi Arabia, 1998-2017.


Journal

Saudi medical journal
ISSN: 1658-3175
Titre abrégé: Saudi Med J
Pays: Saudi Arabia
ID NLM: 7909441

Informations de publication

Date de publication:
Apr 2020
Historique:
entrez: 16 4 2020
pubmed: 16 4 2020
medline: 13 4 2021
Statut: ppublish

Résumé

To identify the trends in the diagnostic frequency of glomerular disease subtypes by renal biopsy in children in Saudi Arabia over the last 20 years. In this retrospective observational study, we identified all patients aged less than 18 years for whom native kidney biopsy was performed between 1998 and 2017. The period during which biopsy was performed (1998-2004, 2005-2011, and 2012-2017) and the demographic information and their association with the prevalence of various glomerular disease subtypes were our primary outcomes. Results: A total of 326 cases with renal biopsy were analyzed; the mean age of participants being 11 years and 45.4% of them were girls. Unexpectedly, secondary glomerulonephritis accounted for 42.3% of the cases, and lupus nephritis was the most common cause noted in 20.7% of the cases. The minimal change and focal segmental glomerulosclerosis were the most common glomerulonephritis in 59% of the cases. The frequency of membranoproliferative glomerulonephritis and mesangioproliferative glomerulonephritis significantly decreased from 15% and 17% in the period prior to 2004 to 3.3% (p=0.003) and 1.7% in 2012-2017 (p less than 0.001). We found a considerable shift in the frequency of many glomerular disease subtypes in 1998-2017, which make clinical predication of the underlying etiology challenging for clinician. Renal biopsy still remains a critical diagnostic procedure for managing a considerable proportion of renal diseases.

Identifiants

pubmed: 32291423
doi: 10.15537/smj.2020.4.24999
pmc: PMC7841618
doi:

Types de publication

Journal Article Observational Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

369-375

Références

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pubmed: 24821178

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Classifications MeSH