Pan-Immune-Inflammation Value (PIV) has recently received more attention as a novel indicator of inflammation. We aimed to evaluate the association between PIV and prognosis in septic patients. Data were extracted from the Medical Information Mart for Intensive Care IV database. The primary and secondary outcomes were 28-day and 90-day mortality. The association between PIV and outcomes was assessed by Kaplan-Meier curves, Cox regression analysis, restricted cubic spline curves and subgroup analysis. A total of 11,331 septic patients were included. Kaplan-Meier curves showed that septic patients with higher PIV had lower 28-day survival rate. In multivariable Cox regression analysis, log2-PIV was positively associated with the risk of 28-day mortality [HR (95% CI) 1.06 (1.03, 1.09), P < 0.001]. The relationship between log2-PIV and 28-day mortality was non-linear with a predicted inflection point at 8. To the right of the inflection point, high log2-PIV was associated with an increased 28-day mortality risk [HR (95% CI) 1.13 (1.09, 1.18), P < 0.001]. However, to the left of this point, this association was non-significant [HR (95% CI) 1.01 (0.94, 1.08), P = 0.791]. Similar results were found for 90-day mortality. Our study showed a non-linear relationship between PIV and 28-day and 90-day mortality risk in septic patients.

OBJECTIVE: Using the preoperative pan-immune-inflammation value (PIV) and the monocyte to high-density lipoprotein ratio (MHR) to reflect inflammation, immunity, and cholesterol metabolism, we aim to develop and visualize a novel nomogram model for predicting the survival outcomes in patients with colorectal cancer (CRC).
METHODS: A total of 172 patients with CRC who underwent radical resection were retrospectively analyzed. Survival analysis was conducted after patients were grouped according to the optimal cut-off values of PIV and MHR. Univariate and multivariate analyses were performed using Cox proportional hazards regression to screen the independent prognostic factors. Based on these factors, a nomogram was constructed and validated.
RESULTS: The PIV was significantly associated with tumor location (P < 0.001), tumor maximum diameter (P = 0.008), and T stage (P = 0.019). The MHR was closely related to gender (P = 0.016), tumor maximum diameter (P = 0.002), and T stage (P = 0.038). Multivariate analysis results showed that PIV (Hazard Ratio (HR) = 2.476, 95% Confidence Interval (CI) = 1.410-4.348, P = 0.002), MHR (HR = 3.803, 95%CI = 1.609-8.989, P = 0.002), CEA (HR = 1.977, 95%CI = 1.121-3.485, P = 0.019), and TNM stage (HR = 1.759, 95%CI = 1.010-3.063, P = 0.046) were independent prognostic indicators for overall survival (OS). A nomogram incorporating these variables was developed, demonstrating robust predictive accuracy for OS. The area under the curve (AUC) values of the predictive model for 1-, 2-, and 3- year are 0.791,0.768,0.811, respectively. The calibration curves for the probability of survival at 1-, 2-, and 3- year presented a high degree of credibility. Furthermore, Decision curve analysis (DCA) for the probability of survival at 1-, 2-, and 3- year demonstrate the significant clinical utility in predicting survival outcomes.
CONCLUSIONS: Preoperative PIV and MHR are independent risk factors for CRC prognosis. The novel developed nomogram demonstrates a robust predictive ability, offering substantial utility in facilitating the clinical decision-making process.

We evaluated the value of pan-immune-inflammation value (PIV) in predicting the risk for postcontrast acute kidney injury (PCAKI), an important complication following percutaneous coronary intervention (PCI) in acute coronary syndrome (ACS) patients. Medical records of 839 ACS patients underwent PCI between June 2019 and December 2022 were retrospectively analyzed. Patients were divided into two groups: PCAKI (-) and PCAKI (+). PCAKI was defined as a ≥ 0.5 mg/dL and/or a ≥ 25% increase in serum creatinine within 72 h after PCI. The PIV was computed as [neutrophils × platelets × monocytes]÷lymphocytes. The mean age was 60.7 ± 12.9 years. PCAKI was detected in 105 (12.51%) patients. PIV was higher in the PCAKI (+) group compared to PCAKI (-) group (median 1150, interquartile range [IQR] 663-2021 vs median 366, IQR 238-527, p < 0.001). Receiver operating characteristic curve analysis showed that the best cutoff of PIV for predicting PCAKI was 576 with 81% sensitivity and 80% specificity. PIV was superior to neutrophil-lymphocyte ratio and platelet-lymphocyte ratio for the prediction of PCAKI (area under curve:0.894, 0.849 and 0.817, respectively, p < 0.001 for all). A high PIV was independently correlated with PCAKI (≤576 vs. >576, odds ratio [OR] 12.484, 95%confidence interval [CI] 4.853-32.118, p < 0.001) together with older age (OR 1.058, p = 0.009), female gender (OR 4.374, p = 0.005), active smoking (OR 0.193, p = 0.012), left ventricular ejection fraction (OR 0.954, p = 0.021), creatinine (OR 10.120, p < 0.001), hemoglobin (OR 0.759, p = 0.019) and c-reactive protein (OR 1.121, p = 0.002). In conclusion, a high PIV seems to be an easily assessable tool that can be used in clinical practice for predicting the risk of PCAKI in ACS patients implanted drug-eluting stents.

UNASSIGNED: Direct antihypertensive therapy in hypertensive patients with a high CVD risk can reduce the incidence of cardiovascular death but increase adverse cardiovascular events, so additional ways to identify hypertensive patients at high risk may be needed. Studies have shown that immunity and inflammation affect the prognoses of patients with hypertension and that the pan-immune-inflammation value (PIV) is an index to assess immunity and inflammation, but few studies have applied the PIV index to patients with hypertension.
UNASSIGNED: To explore the relationship between the PIV and long-term all-cause and cardiovascular mortality in patients with hypertension.
UNASSIGNED: Data from the National Health and Nutrition Examination Survey (NHANES) 1999-2018 with a mortality follow-up through December 31, 2019, were analyzed. A total of 26,781 participants were evaluated. The patients were grouped based on PIV levels as follows: T1 group (n = 8,938), T2 group (n = 8,893), and T3 group (n = 8,950). The relationship between the PIV and long-term all-cause and cardiovascular death was assessed by survival curves and Cox regression analysis based on the NHANES recommended weights.
UNASSIGNED: The PIV was significantly associated with long-term all-cause and cardiovascular mortality in patients with hypertension. After full adjustment, patients with higher PIV have a higher risk of all-cause [Group 3: HR: 1.37, 95% CI: 1.20-1.55, p < 0.001] and cardiovascular [Group 3: HR: 1.62, 95% CI: 1.22-2.15, p < 0.001] mortality.
UNASSIGNED: Elevated PIV was associated with increased all-cause mortality and cardiovascular mortality in hypertensive patients.