What question did this study set out to answer?

This research aims to investigate the relationship between blood pressure variability and acute kidney injury in patients with traumatic intracranial hemorrhage.

February 28, 2026Open Access

Blood Pressure Variability and Acute Kidney Injury in Traumatic Intracranial Hemorrhage : A Retrospective Cohort Study Using the MIMIC-IV Database

Key Points

This research aims to investigate the relationship between blood pressure variability and acute kidney injury in patients with traumatic intracranial hemorrhage.
Retrospective cohort study using the MIMIC-IV database
Included tICH patients with ≥24 blood pressure measurements within 24 hours of ICU admission
Calculated BPV indices for both systolic and diastolic blood pressures
Applied univariate and multivariate logistic regression models for AKI estimation
Analyzed data separately for hypertensive patients.
385 out of 551 patients developed acute kidney injury (69.9%)
Higher systolic BPV indices (SBP_ARV and SBP_SD) predicted AKI, with significant odds ratios
In hypertensive patients, associations of BPV with AKI were stronger, indicating an increased risk based on BPV indices.

Abstract

Objective: Acute kidney injury (AKI) is a common and serious complication in traumatic intracranial hemorrhage (tICH), leading to worse outcomes. Blood pressure variability (BPV), beyond mean blood pressure levels, may impair end-organ perfusion and predispose to AKI. However, the relationship between BPV and AKI in tICH patients remains poorly defined. We investigated the association between BPV and AKI in patients with tICH. Methods: We conducted a retrospective cohort study of tICH patients from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Inclusion required ≥24 systolic and diastolic blood pressure measurements within the first 24 hours of intensive care unit admission. BPV indices, average real variability (ARV), standard deviation (SD), and coefficient of variation (CV), were calculated for both systolic (SBP) and diastolic pressures. Univariate and multivariate logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for AKI. Two adjustment schemes were applied: group 1 (age, congestive heart failure, diabetes) and group 2 (group 1 covariates + vasoactive agents, mannitol, angiotensin-converting enzyme inhibitors and angiotensin receptor blockers, hypertonic saline). Analyses were performed in the hypertensive subgroup (mean SBP ≥140 mmHg), using the same covariate adjustment schemes. Results: Among 551 patients, AKI developed in 385 (69. 9%). In multivariate analysis with adjusted for all confounders, higher SBPARV (OR, 1. 046; 95% CI, 1. 004–1. 095; p=0. 048) and SBPSD (OR, 1. 052; 95% CI, 1. 010–1. 099; p=0. 018) were independent predictors of AKI. In hypertensive subgroups, after adjustment for all confounders, associations were even stronger: SBPARV (OR, 1. 285; 95% CI, 1. 064–1. 553; p=0. 009), SBPSD (OR, 1. 203; 95% CI, 1. 022–1. 417; p=0. 027) and SBPCV (OR, 1. 273; 95% CI, 1. 012–1. 601; p=0. 039). Conclusion: Elevated systolic BPV independently predicts AKI in tICH patients. Incorporating BPV monitoring into neurocritical care protocols may help identify high-risk patients and guide interventions to stabilize blood pressure fluctuations, potentially minimizing AKI risk.

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Cite This Study

Han et al. (Thu,) studied this question.

synapsesocial.com/papers/69a286c90a974eb0d3c020ba https://doi.org/https://doi.org/10.3340/jkns.2025.0186

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