# Association between D-dimer and in-hospital mortality risk in Acute Kidney Injury based on latent class dynamic trajectory

## TL;DR

This study finds that AKI patients with a specific D-dimer trajectory pattern have higher in-hospital mortality risk.

## Contribution

The novel use of latent class trajectory modeling to identify D-dimer patterns linked to mortality in AKI patients.

## Key findings

- Two D-dimer trajectories identified: high-peak decline and sustained low-level.
- High-peak decline group had 2.27 times higher in-hospital mortality risk.
- Mortality risk remained significant across various patient subgroups.

## Abstract

To investigate the longitudinal D-dimer trajectories in hospitalized acute kidney injury (AKI) patients and analyze their association with in-hospital mortality risk.

A retrospective study was conducted using data from AKI patients admitted to Tongji Hospital (July 2012–April 2024). General information, laboratory results, and outcomes were extracted from the medical record system. Patients with at least three D-dimer measurements within 30 days after AKI onset were included. Several latent class trajectory models (LCTMs) were constructed to identify distinct longitudinal dynamic trajectories of D-dimer. Model fit was assessed using Akaike Information Criterion, Bayesian information criterion, entropy, category probability and the optimal model was selected. Logistic regression and Kaplan-Meier survival analysis were employed to evaluate the relationship between D-dimer trajectories and in-hospital mortality. Subgroup analyses were performed to explore potential interactions between D-dimer trajectories and other variables.

Based on LCTMs evaluation, the model fitting indices were comprehensively analyzed, and a two-class model was identified as the optimal LCTM. The dynamic trajectories revealed two distinct patterns: an early peak followed by a gradual decline and a low-level continuous stability after AKI onset. Accordingly, patients were categorized into the high-peak decline group and the sustained low-level group. Logistic regression analysis demonstrated that AKI patients in the high-peak decline group had a significantly increased risk of in-hospital mortality (OR 2.27, 95% CI: 1.94–2.65). Kaplan-Meier survival curves indicated a reduced in-hospital survival rate in the high-peak decline group (p < 0.05). Subgroup analyses showed that, across age, gender, chronic kidney disease, cancer, surgery, myocardial infarction, and cerebral infarction subgroups, the high-peak decline group exhibited a significantly elevated risk of in-hospital mortality (p < 0.05), with no significant interaction effects observed among subgroups (p > 0.05).

Using LCTM analysis, it was determined that D-dimer exhibits two characteristic longitudinal dynamic trajectories following AKI onset: an early peak followed by a gradual decline and a continuous low-level stability. Among these, the trajectory characterized by an early peak followed by a decline in AKI patients was associated with an increased risk of in-hospital mortality and reduced in-hospital survival, independent of age, gender, chronic kidney disease, cancer, surgery, myocardial infarction, or cerebral infarction.