ArticleExperimental and therapeutic medicine2019
Predictive value of procalcitonin in chronic allograft dysfunction in kidney transplant recipients.
Article in Experimental and therapeutic medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed, 2 citations in OpenAlex.
- Liquid biopsy for non-invasive monitoring of patients with kidney transplants.Frontiers in transplantation · 2023Review
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The present study was designed to determine the potential role of circulating procalcitonin (PCT) in predicting chronic allograft dysfunction (CAD) in kidney transplant recipients (KTRs). A total of 87 KTRs were retrospectively analyzed and divided into a CAD and a non-CAD (normal renal function) group. Clinical features and inflammatory markers were compared between the groups, including PCT, white blood cell count, C-reactive protein, neutrophil percentage (N%) and lipoprotein(a) [Lp(a)], and the receiver operating characteristic (ROC) curve for CAD prediction was plotted. Univariate and multivariate logistic regression analyses were used to analyze the relevant risk factors for CAD. The results indicated that i) the values of these indicators in the CAD group, including the male ratio, years after transplantation, PCT, N% and Lp(a), were significantly higher than those in the non-CAD group, while the body mass index, aspartate aminotransferase, high-density lipoprotein and low-density lipoprotein were significantly lower; ii) PCT and Lp(a) were able to predict CAD with an area under the ROC curve of 0.893 and 0.770, respectively; iii) multivariate logistic regression analysis of factors influencing CAD in KTRs suggested that elevated PCT was an independent risk factor. In KTRs, PCT was identified as a potential biomarker for predicting CAD.
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