Effectiveness evaluation for a digital health intervention in proteinuria screening
Abstract Objective: Persistent proteinuria is a hallmark of glomerulonephritis and serves as an important diagnostic and prognostic marker. This study proposes a novel digital approach––the quantitative urine protein-to-creatinine ratio (UPCR) home-testing kit (UTK)––for proteinuria screening based on advanced computer-vision algorithms, and evaluates its effectiveness. Methods: Randomly selected spot urine samples were collected from 199 participants recruited from a tertiary hospital in Beijing, China. The UTK method utilized contour detection and image segmentation algorithms to extract the topological information of the urinalysis strip for color calibration, and employed a three-dimensional color space interpolation algorithm to obtain quantitative UPCR readings. Using the laboratory results as a benchmark, we evaluated the diagnostic performance of UTK in proteinuria screening in terms of validity, reliability, predictive values, and area under the receiver operating characteristic curve (AUC). Results: The mean age of the 199 participants was 51.6 ± 16.2 years and 88 (44.2%) of them were male. The median UPCR was 222.5 mg/g (interquartile range: 106.5–844.6), and 20 (10.1%) participants were identified as having proteinuria. The UTK method performed well in proteinuria screening, with a high accuracy rate of 91.0%, 85.0% sensitivity, a 91.6% specificity, and an AUC of 0.966. The Bland-Altman plot showed a high level of agreement of the quantitative UPCR results between the UTK and laboratory methods. Conclusions: The proposed digital solution for quantitative UPCR analysis based on advanced computer-vision technologies showed good performance in proteinuria screening. This user-friendly and cost-effective UPCR measure method presents a promising new strategy for enhancing the efficiency of the primary monitoring and management of glomerulonephritis.
Authors
- Cheng Zhou (ORCID: https://orcid.org/0000-0002-4091-4777)
- Jingyi Wu (ORCID: https://orcid.org/0000-0002-3519-3952)
- Luxia Zhang (ORCID: https://orcid.org/0000-0003-2349-2936)
- Qing Li (ORCID: https://orcid.org/0000-0003-0251-9159)
- Yuewen Zheng
- Pengfei Li (ORCID: https://orcid.org/0009-0003-1899-3709)
- Fei Wang (ORCID: https://orcid.org/0000-0001-9961-0543)
Institutions
- Peking University (CN)
- Peking University First Hospital (CN)
Publication Details
- Journal
- Interdisciplinary Nursing Research
- Published
- 2025-04-29
- DOI
- https://doi.org/10.1097/nr9.0000000000000090
- Primary Topic
- Chronic Kidney Disease and Diabetes
- Type
- article
- Field-Weighted Citation Impact
- 0.00