# The relationship between platelet count and postoperative acute kidney injury and long-term prognosis in neurosurgical critically ill patients: A retrospective study

## TL;DR

This study found that early platelet levels in neurosurgical ICU patients are linked to kidney injury risk and long-term survival, with a specific range showing better outcomes.

## Contribution

The study identifies a non-linear relationship between platelet count and AKI/mortality in neurosurgical ICU patients, suggesting platelet count could aid in risk stratification.

## Key findings

- Lower platelet counts (<204 × 10⁹/L) are associated with increased AKI risk in neurosurgical ICU patients.
- Both very low and very high platelet counts correlate with higher one-year mortality risk.
- Platelet count between 179–234 × 10⁹/L is linked to lower AKI risk and better prognosis.

## Abstract

This study was designed to investigate the associations among platelet (PLT) count upon admission to the intensive care unit (ICU), postoperative acute kidney injury (AKI), and long-term prognosis (one-year mortality risk) in patients undergoing neurosurgical operations.

This study conducted a retrospective analysis based on the MIMIC-IV database, including patients who underwent neurosurgery and were admitted to the ICU. Platelet count information at admission was collected. The primary endpoint were AKI within 7 days of ICU admission and mortality within one year after surgery. For the primary endpoint, a multivariate logistic regression model combined with restricted cubic spline was used for statistical analysis to explore the potential association between platelet count and AKI, and subgroup analysis was conducted to assess the stability of the results. For the other endpoint, a restricted cubic spline was used to construct a visualization relationship graph, and a Cox multivariate regression model was further established and a cumulative mortality curve was drawn. Sensitivity analyses were performed using both the first recorded platelet count following ICU admission and the 24-hour mean platelet count to assess the robustness of our findings. Additionally, an independent validation cohort was constructed using the MIMIC-III database to conduct external validation.

A total of 1605 patients were included in this study, with a median age of 60 years, among whom 875 were male (54.5%). Among the 1605 patients, 607 (37.82%) developed acute kidney injury within 7 days of hospitalization. Logistic regression analysis showed that compared with patients in the first quartile of platelet count (Q1 ≤ 179), those in the third quartile (Q3 > 234) had a significantly lower risk of developing acute kidney injury within 7 days of hospitalization (Model 1:HR = 0.42, 95% CI: 0.33–0.54; Model 2: HR = 0.67, 95% CI: 0.59–0.76; Model 3: HR = 0.57, 95% CI: 0.43–0.74; Model 4: HR = 0.62, 95%CI: 0.47–082; all P-values < 0.050). Furthermore, when the platelet count is below 204 × 10⁹/L, the risk of AKI occurrence in patients increases significantly. Cox multivariate regression analysis of the secondary endpoint showed that both relatively low platelet count (≤ 179) and relatively high platelet count (> 234) were associated with an increased risk of death within 1 year, with the former association being particularly significant (HR = 1.53, 95% CI: 1.17–2, P = 0.002). Sensitivity analyses yielded directionally consistent results. In the MIMIC-III external validation cohort, the associations between platelet levels and risks of AKI as well as long-term mortality remained generally consistent.

In neurosurgical patients admitted to the ICU, early platelet levels within the first 24 hours were associated with the incidence of AKI within 7 days and long-term outcomes. A lower platelet count during the early ICU period was associated with an increased risk of AKI and poorer prognosis. This association appeared to be non-linear, the range of 179–234 × 10⁹/L corresponded to a lower risk or better prognosis. Platelet count can be a potential tool for risk stratification, but it is not sufficient to support clinical intervention decisions based on causal relationships.