Predictive value of serum chitinase 3-like 1 for dysfunctional autogenous arteriovenous fistulas in patients with chronic kidney disease stage G5

TL;DR

This study shows that high levels of a protein called CHI3L1 in the blood can predict if an artery-vein connection used for kidney dialysis will not work properly.

Contribution

The study introduces a new predictive model combining clinical factors and CHI3L1 levels to identify high-risk patients for dysfunctional arteriovenous fistulas.

Findings

Serum CHI3L1 levels were significantly higher in patients with dysfunctional AVFs.

CHI3L1 was identified as an independent risk factor for AVF dysfunction.

A prediction model including CHI3L1 showed higher clinical utility for early risk identification.

Abstract

•Uterine carcinosarcoma is treated with no histology-based management.•Heterologous sarcomatous component has a negative impact on overall survival.•First study to report a negative prognostic impact in FIGO I-IVA in Latin America.•There is a need to reconsider the role of the sarcomatous component to tailor treatment.

Uterine carcinosarcoma is treated with no histology-based management.

Heterologous sarcomatous component has a negative impact on overall survival.

First study to report a negative prognostic impact in FIGO I-IVA in Latin America.

There is a need to reconsider the role of the sarcomatous component to tailor treatment.

Arteriovenous Fistula (AVF) is the preferred vascular access for patients with Chronic Kidney Disease Stage G5 (CKDG5). Normal AVF function is an important prerequisite for hemodialysis, and there are few reports of studies predicting the factors affecting dysfunctional AVF. The aim of this study was to investigate the expression of Chitosanase-3-Like protein-1 (CHI3L1) in AVFs from patients with end-stage renal disease and to analyze the potential mechanism of its role in AVF dysfunction.

CKDG5 patients who underwent AVF surgery at our institution from January 2020 to September 2023 were prospectively collected. The general clinical data and laboratory data were collected in detail, and the occurrence of postoperative dysfunctional AVF was recorded. Then, the optimal diagnostic threshold of serum CHI3L1 was observed by the Receiver Operating Characteristic (ROC) curve. Kaplan-Meier survival curve and Log-rank test were used for survival analysis. Multi-factor backward logic analysis was used to screen baseline clinical factors and construct prediction Model 1. Subsequently, serum CHI3L1 was combined with baseline clinical factors to construct Prediction Model 2. The predictive value of the two models was evaluated by the ROC curve and the Area Under the Curve (AUC).

A total of 152 CKDG5 patients who underwent AVF surgery were continuously included. They were divided into a normal AVF group (n = 64) and a dysfunctional AVF group (n = 88). Gender, age, body mass index, primary disease, diameter of cephalic vein, diameter of radial artery, follow-up time, and levels of Ca, K, total cholesterol, triglycerides, high-density lipoprotein, low-density lipoprotein, white blood cell count, platelets, fasting blood glucose, and hemoglobin in both groups were not statistically significant between the two groups (p > 0.05). Systolic blood pressure, diastolic blood pressure, parathyroid hormone, serum albumin, and CHI3L1 were increased, whereas serum phosphorus level was decreased in CKDG5 patients with dysfunctional AVF (p < 0.05). The AUC of serum CHI3L1 was 0.797 (95% CI 0.728‒0.866, p < 0.001), the optimal cut-off value was 148.0 ng/mL, the sensitivity was 62.5%, and the specificity was 84.38%. The primary fluency rate in the high serum CHI3L1 level group was significantly lower than that in the low serum CHI3L1 level group (p < 0.001). Multifactorial logistic regression analysis showed that elevated serum CHI3L1 was an independent risk factor for postoperative dysfunctional AVF. The predictive value of the CHI3L1-containing predictive Model 2 was higher, with a net benefit at threshold probabilities of 0.2‒0.9 for its clinical decision curve.

This study proposes a risk prediction model of serum CHI3L1 combined with clinical risk factors, which can be utilized to make a preliminary prediction of the risk of dysfunctional AVF more easily, and thereafter to identify and intervene in high-risk patients early.

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