The prognostic impact of inflammation in patients with decompensated acute heart failure, as assessed using the pan-immune inflammation value (PIV)

İnan, Duygu; Erdoğan, Aslan; Pay, Levent; Genç, Duygu; Demirtola, Ayşe İrem; Yıldız, Ufuk; Güler, Ahmet; Tekkeşin, Ahmet İlker; Karagöz, Ali

doi:10.1080/00365513.2023.2233890

Cited by 9 publications

(2 citation statements)

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“…retrospectively analyzed the association between increased PIV and adverse outcomes, including worse overall survival (HR: 4.46, 95%CI: 2.22-8.99) and progression-free survival (HR: 2.03, 95% CI: 1.08-3.80), besides, resistance to platinum-based chemotherapy in patients with advanced triple-negative breast cancer ( 20 ). Furthermore, PIV has also been discovered as a novel biomarker in reflecting the association between inflammation and noncancer diseases, such as in hypertension, heart failure, myocardial infarction, kidney disease, frailty, and hepatic steatosis ( 13 , 24 – 28 ). Similarly, elevated PIV level correlated with the presence and severity of these noncancerous conditions.…”

Section: Discussionmentioning

confidence: 99%

“…Recent years, the focus of PIV-related research has mainly centered on its implications for the prognosis and therapeutic outcomes in oncological patients (11,12,(18)(19)(20)(21)(22)(23) (20). Furthermore, PIV has also been discovered as a novel biomarker in reflecting the association between inflammation and noncancer diseases, such as in hypertension, heart failure, myocardial infarction, kidney disease, frailty, and hepatic steatosis (13,(24)(25)(26)(27)(28). Similarly, elevated PIV level correlated with the presence and severity of these noncancerous conditions.…”

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confidence: 99%

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Associations between pan-immune-inflammation value and abdominal aortic calcification: a cross-sectional study

Jin,

Li,

Luo

et al. 2024

Front. Immunol.

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BackgroundAbdominal aortic calcification (AAC) pathogenesis is intricately linked with inflammation. The pan-immune-inflammation value (PIV) emerges as a potential biomarker, offering reflection into systemic inflammatory states and assisting in the prognosis of diverse diseases. This research aimed to explore the association between PIV and AAC.MethodsEmploying data from the National Health and Nutrition Examination Survey (NHANES), this cross-sectional analysis harnessed weighted multivariable regression models to ascertain the relationship between PIV and AAC. Trend tests probed the evolving relationship among PIV quartiles and AAC. The study also incorporated subgroup analysis and interaction tests to determine associations within specific subpopulations. Additionally, the least absolute shrinkage and selection operator (LASSO) regression and multivariable logistic regression were used for characteristics selection to construct prediction model. Nomograms were used for visualization. The receiver operator characteristic (ROC) curve, calibration plot and decision curve analysis were applied for evaluate the predictive performance.ResultsFrom the cohort of 3,047 participants, a distinct positive correlation was observed between PIV and AAC. Subsequent to full adjustments, a 100-unit increment in PIV linked to an elevation of 0.055 points in the AAC score (β=0.055, 95% CI: 0.014-0.095). Categorizing PIV into quartiles revealed an ascending trend: as PIV quartiles increased, AAC scores surged (β values in Quartile 2, Quartile 3, and Quartile 4: 0.122, 0.437, and 0.658 respectively; P for trend <0.001). Concurrently, a marked rise in SAAC prevalence was noted (OR values for Quartile 2, Quartile 3, and Quartile 4: 1.635, 1.842, and 2.572 respectively; P for trend <0.01). Individuals aged 60 or above and those with a history of diabetes exhibited a heightened association. After characteristic selection, models for predicting AAC and SAAC were constructed respectively. The AUC of AAC model was 0.74 (95%CI=0.71-0.77) and the AUC of SAAC model was 0.84 (95%CI=0.80-0.87). According to the results of calibration plots and DCA, two models showed high accuracy and clinical benefit.ConclusionThe research findings illuminate the potential correlation between elevated PIV and AAC presence. Our models indicate the potential utility of PIV combined with other simple predictors in the assessment and management of individuals with AAC.

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