External Validation of the Nelson Equation for Kidney Function Decline in Patients with Acute Ischemic Stroke or Transient Ischemic Attack

Background: There is a close brain-kidney interaction following ischemic cerebrovascular disease. The new-onset kidney injury after stroke leads to severe neurological deficits and poor functional outcomes. We aimed to validate the Nelson equation for predicting the new-onset and long-term kidney function decline in patients with acute ischemic stroke (AIS) or transient ischemic attack (TIA).Methods: A total of 3169 patients were enrolled in the Third China National Stroke Registry, whose baseline estimated glomerular filtration rate (eGFR) >= 60 mL/min/1.73 m2. The outcome of interest was the incident eGFR< 60 mL/min/1.73 m2 at 3 months. The prediction equation of participants with or without diabetes was validated respectively. The receiver operating characteristic curve (AUC) evaluated prediction performance. The Delong test compared the Nelson equation performance with the O'Seaghdha equation and the Chien equation. Continuous net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were determined to evaluate the incremental effect.Results: During the 3-mo follow-up period, among 1151 patients with diabetes, there were 31 cases (2.7%) of reduced eGFR. Meanwhile, among 2018 non-diabetic patients, there were 23 cases (1.1%) of reduced eGFR. The Nelson equation showed good discrimination and was well-calibrated in patients with diabetes (AUC 0.82, Hosmer-Lemeshow test p = 0.67) or without diabetes (AUC 0.82, Hosmer-Lemeshow test p = 0.09). The performance of the Nelson equation was superior to other equation, as increased continuous NRI (diabetic, 0.64; non-diabetic, 1.13) and IDI (diabetic, 0.10; non-diabetic, 0.13) to the Chien equation.Conclusion: The Nelson equation reliably predicted the risks of the new-onset and long-term kidney function decline in patients with AIS or TIA, which could help clinicians screen high-risk patients and improve clinical care.