Kidney Week

Abstract: FR-PO944

Geospatial Mapping to Identify Primary Glomerulonephritis Hot Spots in Saskatchewan

Session Information

• Glomerular Diseases: Potpourri
  October 25, 2024 | Location: Exhibit Hall, Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: Glomerular Diseases

• 1402 Glomerular Diseases: Clinical, Outcomes, and Therapeutics

Authors

• Prasad, Bhanu, Regina General Hospital, Regina, Saskatchewan, Canada

Bhanu Prasad, MD

• Sharma, Aditi, University of Regina, Regina, Saskatchewan, Canada

Aditi Sharma, PhD

• Garg, Aarti, University of Regina, Regina, Saskatchewan, Canada

Aarti Garg, PhD

• Raouf, Abdul, Saskatchewan Polytechnic - Regina Campus, Regina, Saskatchewan, Canada

Abdul Raouf, PhD

• Patterson, Matthew, University of Saskatchewan, Saskatoon, Saskatchewan, Canada

Matthew Patterson, MD, MSc

• Dokouhaki, Pouneh Pam, The University of British Columbia, Vancouver, British Columbia, Canada

Pouneh Pam Dokouhaki, MD, PhD

Background

Saskatchewan (SK), a province rich in oil, minerals, and agriculture, with 1.2M population, is principally served by its two urban renal centers in Regina and Saskatoon. There is a lack of comprehensive data on the association of GN subtypes with rural-urban divide, and geographic hotspots like mines and refineries. Utilizing the kidney biopsy, our objective was to identify clusters of GN subtypes, calculate yearly incidence rates, urban/rural comparisons, and distance and travel time to access care.

Methods

A centralized provincial kidney pathology database was used to capture all incident cases of biopsy-proven GN in the adult population from 2002 - 2018. Only patients with primary GN were included (n=1372). Demographic attributes, 3-digit postal codes, lab parameters, definitive GN diagnosis, the date of biopsy, dialysis start, and death were collected and analyzed. To analyze the variation of GN across different regions in SK we used SaTScan v10.1.3 software. The population data from Census 2016 was used as a reference, and age and sex were taken as covariates.

Results

GN incidence increased from 4.6 to 13.6 per 100,000 persons from 2002 to 2018 (p<0.001). GN incidence was higher in rural areas than in urban areas (p<0.001). Significantly higher dialysis progression rates were seen for rural and remote areas (p<0.01). We identified a geospatial cluster of 345.7 km² for lupus nephropathy (Figure 1(f)), with an incident rate ratio of 1.73, a relative risk of 2.7, and a Log likelihood ratio of 13.87. No significant clusters were identified for any other subtypes of GN.

Conclusion

We identified a geographic cluster for lupus nephropathy, encompassing both urban and rural areas. While there was a higher incidence of MN and AGBM in rural areas, we did not identify any geographic clusters for the same. Addressing and understanding the multifaceted factors driving these disparities are essential steps towards easing the burden of GN on impacted communities.