Prediction Model and Decision Analysis for Early Recognition of SDNS/FRNS in Children
PLR, eGFR, the time for urinary protein turned negative, low-density lipoprotein, thrombin time, and neutrophil absolute counts may be effective predictors for identifying SSNS patients at risk of progressing to SDNS/FRNS. These findings offer valuable insights for early detection and support the use of precision medicine strategies in managing SDNS/FRNS.
Authors
- Chun Loo Gan (ORCID: https://orcid.org/0000-0003-2576-9310)
- Xindi Zhou (ORCID: https://orcid.org/0009-0001-7715-6105)
- Qing Yang (ORCID: https://orcid.org/0000-0002-6706-3124)
- Qiu Li (ORCID: https://orcid.org/0000-0002-5299-9050)
- Yaru Jiang
- Mo Wang (ORCID: https://orcid.org/0000-0002-4761-4216)
- Xiao Han (ORCID: https://orcid.org/0000-0001-7525-2067)
- Wei Jiang (ORCID: https://orcid.org/0000-0002-4878-8381)
- Haiping Yang (ORCID: https://orcid.org/0000-0002-0456-9304)
- Xiao Lin (ORCID: https://orcid.org/0009-0005-9592-4736)
- Hui Yin
- Han Chan
- Gaofu Zhang (ORCID: https://orcid.org/0000-0003-4452-3674)
Institutions
- Children's Hospital of Chongqing Medical University (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- Journal of Inflammation Research
- Published
- 2024-12-01
- DOI
- https://doi.org/10.2147/jir.s494530
- Citations
- 1
- Primary Topic
- Pediatric health and respiratory diseases
- Type
- article
- Field-Weighted Citation Impact
- 0.74
Funders
- Chongqing Medical University