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Machine learning method to derive serum chlorine in acute kidney injury with traumatic brain injury

Year: 2025
Type: article
Study design: Observational Study
Abstract: Background Chloride was prioritized due to its established role in acid-base balance and renal perfusion, which are critical in TBI-AKI pathophysiology. This study aimed to investigate the impact of changes in the trajectory of early blood chlorine levels on the prognosis of patients with traumatic brain injury (TBI)-associated acute kidney injury (AKI). Methods Critical Medicine Database (MIME-IV) and eICU were used to include patients with TBI and AKI. We used a latent class mixed model (LCMM) to determine the AKI class according to the blood chlorine trial of patients in TBI. The primary endpoint was 28 day all-cause mortality, and the secondary endpoints were the development of acute kidney disease and 7 day all-cause mortality. Multivariate regression was performed to assess the effect of classification based on blood chlorine levels, and external validation was performed using the eICU database. Results In 640 patients with TBI-associated AKI, we identified five categories based on blood chlorine trials with different characteristics. Compared with patients with slightly elevated blood chlorine levels late in life, those with rapidly elevated blood chlorine levels early in life had the highest risk of all-cause mortality at 28 days (HR: 2.47 (1.16, 5.65), P = 0.019), a higher risk of death at 7 days (HR: 3.18 (1.21–8.36), P = 0.019), and the highest adjusted risk of developing acute kidney disease (HR: 5.40 (1.44–20.22), P = 0.012). These associations were similar in external validation. Conclusion The stratification of early blood chlorine trajectories can be used as a prognostic indicator for TBI-associated AKI patients, and monitoring chloride trajectories may guide early interventions to mitigate mortality and AKD risk.
Language: English
Subfield: Nephrology
Field: Medicine
Open Access status: gold
Estimated APC paid: $1,400
OpenAlex ID: W4411080746
FWCI:
Cites: 5
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Related to: 10