Predictive value of peripheral blood piR-hsa-2700592 for prognosis of atrial fibrillation patients

‍Objectives‍ ‍To explore the association of peripheral blood PIWI-interacting RNA, piR-hsa-2700592, with all-cause mortality and stroke outcomes in patients with atrial fibrillation (AF), and to determine whether piR-hsa-2700592 has the potential to be an AF biomarker. Methods‍ ‍A total of 127 patients with non-valvular AF were enrolled, and the relative expression level of plasma piR-hsa-2700592 was detected. Cox proportional hazard regression was used to analyze the correlation between the expression of piR-hsa-2700592 and all-cause death as well as stroke outcome in the patients. Then the molecule expression level was combined with CHA2DS2-VASc score and ABC stroke (or death ) score to establish 2 new prediction models, the improvement of the predictive performance was compared and analyzed. Receiver operating characteristic (ROC) curve analysis (area under the curve, AUC), net reclassification index (NRI), and comprehensive discriminant improvement index (IDI) were used to evaluate the predictive performance, and decision curve analysis (DCA) was employed to assess the clinical benefit. Results‍ ‍Multivariate Cox regression analysis showed that the patients with higher expression level of piR-hsa-2700592 in peripheral blood had a higher risk of stroke (HR: 2.203, 95%CI: 1.120~4.332; P=0.022). In the stroke outcome, combination of plasma piR-hsa-2700592 expression level with CHA2DS2-VASc score and ABC stroke score obtained an AUC of 0.70 (95%CI: 0.55~0.85, P<0.001) and 0.84 (95%CI: 0.73~0.96, P=0.02), respectively. But, no significant association was observed between high plasma piR-hsa-2700592 level and all-cause mortality in the AF patients (HR: 1.997; 95%CI: 0.884~4.509; P=0.096). Combination of plasma piR-hsa-2700592 level improved the discriminative capability than the single CHA2DS2-VASc score and ABC stroke score models, with an NRI and IDI value of 44.20% (95%CI: 3.40~59.90, P<0.001) and 8.20% (95%CI: 0.60~15.40, P<0.001), respectively for the new CHA2DS2-VASc score model, and an NRI and IDI value of 44.20% (95%CI: 9.80~58.90, P<0.001) and 10.40% (95%CI: 0.70~21.40, P<0.001), respectively for the new ABC stroke score model. The DCA curve showed that both new prediction models obtained better net clinical benefits. Conclusion‍ ‍High peripheral blood expression of piR-hsa-2700592 is an independent risk factor for stroke in the AF patients, and the indicator has a good predictive value for prognosis of the patients. piR-hsa-2700592 might be used as a potential biomarker in the diagnosis and prevention of cardiovascular diseases.

Institutions

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-03-01
DOI
https://doi.org/10.16016/j.2097-0927.202409107
Primary Topic
Endoplasmic Reticulum Stress and Disease
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predictive value of peripheral blood piR-hsa-2700592 for prognosis of atrial fibrillation patients

SHILAP Revista de lepidopterología
Endoplasmic Reticulum Stress and Disease
article

Predictive value of peripheral blood piR-hsa-2700592 for prognosis of atrial fibrillation patients

article en

Abstract

‍Objectives‍ ‍To explore the association of peripheral blood PIWI-interacting RNA, piR-hsa-2700592, with all-cause mortality and stroke outcomes in patients with atrial fibrillation (AF), and to determine whether piR-hsa-2700592 has the potential to be an AF biomarker. Methods‍ ‍A total of 127 patients with non-valvular AF were enrolled, and the relative expression level of plasma piR-hsa-2700592 was detected. Cox proportional hazard regression was used to analyze the correlation between the expression of piR-hsa-2700592 and all-cause death as well as stroke outcome in the patients. Then the molecule expression level was combined with CHA2DS2-VASc score and ABC stroke (or death ) score to establish 2 new prediction models, the improvement of the predictive performance was compared and analyzed. Receiver operating characteristic (ROC) curve analysis (area under the curve, AUC), net reclassification index (NRI), and comprehensive discriminant improvement index (IDI) were used to evaluate the predictive performance, and decision curve analysis (DCA) was employed to assess the clinical benefit. Results‍ ‍Multivariate Cox regression analysis showed that the patients with higher expression level of piR-hsa-2700592 in peripheral blood had a higher risk of stroke (HR: 2.203, 95%CI: 1.120~4.332; P=0.022). In the stroke outcome, combination of plasma piR-hsa-2700592 expression level with CHA2DS2-VASc score and ABC stroke score obtained an AUC of 0.70 (95%CI: 0.55~0.85, P<0.001) and 0.84 (95%CI: 0.73~0.96, P=0.02), respectively. But, no significant association was observed between high plasma piR-hsa-2700592 level and all-cause mortality in the AF patients (HR: 1.997; 95%CI: 0.884~4.509; P=0.096). Combination of plasma piR-hsa-2700592 level improved the discriminative capability than the single CHA2DS2-VASc score and ABC stroke score models, with an NRI and IDI value of 44.20% (95%CI: 3.40~59.90, P<0.001) and 8.20% (95%CI: 0.60~15.40, P<0.001), respectively for the new CHA2DS2-VASc score model, and an NRI and IDI value of 44.20% (95%CI: 9.80~58.90, P<0.001) and 10.40% (95%CI: 0.70~21.40, P<0.001), respectively for the new ABC stroke score model. The DCA curve showed that both new prediction models obtained better net clinical benefits. Conclusion‍ ‍High peripheral blood expression of piR-hsa-2700592 is an independent risk factor for stroke in the AF patients, and the indicator has a good predictive value for prognosis of the patients. piR-hsa-2700592 might be used as a potential biomarker in the diagnosis and prevention of cardiovascular diseases.

SHILAP Revista de lepidopterología
Guiyang Medical University (CN), Army Medical University (CN), Affiliated Hospital of Guizhou Medical University (CN)
Reduced inequalities
Openalex Percentile: Top 47%
Endoplasmic Reticulum Stress and Disease
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.