SII, PIV, and SIRI are closely linked to depressive symptoms, suggesting that they could serve as accessible inflammatory correlates of depression, and longitudinal research is required to test their prognostic utility and unravel their underlying biology.
Abstract
Inflammation is increasingly being recognized as a central factor in the development of depression, a common and debilitating condition. However, the relationship between depression and systemic inflammation indices – systemic immune-inflammation index (SII), pan-immune-inflammatory value (PIV), and systemic inflammatory response index (SIRI) – is not fully understood. In this cross-sectional study, data from the National Health and Nutrition Examination Survey 2005 to 2018, including 22,936 adults in the United States, were analyzed using multivariate logistic regression, smoothed curve fitting, and threshold and subgroup analyses to examine the associations between SII, PIV, SIRI, and depression, as well as their potential nonlinear characteristics. The analysis revealed that a 1-unit increase in Ln(SII), Ln(PIV), and Ln(SIRI) was associated with 18.2%, 14%, and 9.5% higher odds of prevalent depression, respectively. Nonlinear “J-shaped” relationships were observed for all the 3 indices. The threshold effect analysis identified significantly higher odds for Ln(SII) > 6.187, Ln(PIV) > 5.581, and Ln(SIRI) > 0.95. The subgroup analysis showed that smoking, diabetes, and liver disease significantly modified these associations. SII, PIV, and SIRI are closely linked to depressive symptoms, suggesting that they could serve as accessible inflammatory correlates of depression. Longitudinal research is required to test their prognostic utility and unravel their underlying biology.
Higher SIRI levels were associated with higher odds of clinically relevant depressive symptoms among adults from the National Health and Nutrition Examination Survey 2005 to 2016, with a nonlinear dose-response pattern.
Qiongqiong Zhan, Yu Wu, Jiaojiao Sun et al.· Medicine· 0 citations
Diabetes is a major global health burden, with chronic inflammation playing a central role in its progression and complications. The pan-immune-inflammation value (PIV) is a novel composite biomarker reflecting systemic immune inflammation. However, its prognostic value for mortality in individuals with diabetes remains unclear.
We conducted a retrospective cohort analysis using the nationally representative National Health and Nutrition Examination Survey (NHANES) data, including participants aged ≥ 20 with available PIV data. PIV was calculated using a validated equation and then log-transformed (ln) before analysis. Multivariable Cox regression models were employed to evaluate this association. We further explored the dose-response relationship using restricted cubic splines (RCS) and threshold analysis to identify potential non-linear effects. The robustness of findings was confirmed through subgroup and sensitivity analyses, and the potential mediating role of estimated glomerular filtration rate (eGFR) was investigated.
During a median follow-up of 94.9 months, 2,549 deaths were recorded, including 727 attributable to cardiovascular diseases. Elevated lnPIV levels were strongly associated with increased all-cause and cardiovascular mortality. Critical thresholds were identified at lnPIV values of 5.056 for all-cause mortality and 5.586 for cardiovascular mortality. These core associations were stable across all subgroup and sensitivity analyses. Furthermore, mediation analysis estimated that eGFR accounted for 5.1% and 6.4% of the lnPIV-associated risk for all-cause and cardiovascular mortality, respectively.
Pan-immune-inflammation value was found to be independently associated with increased risks of all-cause and cardiovascular mortality in individuals with diabetes, characterized by a nonlinear association and a distinct threshold effect. These findings suggest that PIV could serve as a practical biomarker for risk stratification, potentially identifying patients who may benefit from more intensive management of both inflammation and renal function.
Chen Fu, Jiaer Gao, Yijie Mao et al.· Archives of Medical Science· 0 citations
The findings highlight a unique susceptibility of the cardiovascular system to low-level inflammation, overshadowing the contribution of sleep disturbances, and identified model-based turning points reflect an inflection in mortality risk, suggesting a potential threshold effect in systemic inflammation.
Depression is associated with greater odds of prevalent diabetes, with systemic inflammation contributing to a small but significant proportion of the observed association.
Samuel Akyirem, J. Okyere, Jonathan Bayuo et al.· Biological Research for Nurs...· 0 citations
Obesity-associated cardiometabolic risk involves a complex interplay of systemic inflammation and atherogenic dyslipidemia that escalates with increasing adiposity. This study investigated the relationship between obesity severity and established hematological inflammatory indices and lipid-based metabolic markers, and derived a composite score (CORI_Ridge) as a proof of concept for integrating these routine parameters. In this retrospective multicenter cohort study, 1,107 adults with obesity were stratified by BMI into Grade I (
n
= 475), Grade II (
n
= 396), and Grade III (
n
= 236) categories. Inflammatory indices (NLR, PLR, MLR, SII, SIRI, AISI) and metabolic indices (Castelli Risk Index-1 and − 2, AIP) were calculated from routine complete blood count and fasting lipid parameters. CORI_Ridge was derived via Ridge regression with continuous BMI as the dependent variable. Because the score was derived in the same cohort, performance was evaluated not only apparently but with a strict out-of-sample framework: 50 repeated stratified 70:30 holdout splits in which z-score standardization, λ selection and weight derivation were repeated from scratch within each training partition. Progressive and significant increases were observed across obesity grades in neutrophil counts, platelet counts, SII, AISI, Castelli Risk Index-1, Castelli Risk Index-2, and AIP (all
p
< 0.001); metabolic indices showed a true dose-response gradient, whereas inflammatory indices escalated predominantly at Grade III. CORI_Ridge correlated most strongly with obesity severity (Spearman ρ = 0.420,
p
< 0.001) and achieved the highest apparent discrimination of Grade III obesity (AUC 0.796, 95% CI 0.763–0.829), significantly above every individual index (all DeLong
p
< 0.05). Out-of-sample, CORI_Ridge achieved a median AUC of 0.779 (IQR 0.763–0.793). A simple reference model of waist circumference, fasting glucose and triglycerides performed better (median AUC 0.827), and adding CORI_Ridge to it yielded a small increment (median AUC 0.845) that reached statistical significance in only 6 of 50 splits (median DeLong
p
= 0.38). Systemic inflammatory and atherogenic burden escalates progressively with obesity severity. CORI_Ridge — derived from universally available routine laboratory parameters — integrates this signal into a single graded score with moderate out-of-sample discrimination for Grade III obesity; it does not, however, exceed the discriminative performance of a simple three-variable clinical model and should be regarded strictly as a proof of concept. External validation against clinical outcomes is required before any clinical application can be considered.
Berçem Afşar Karatepe, Gülşah Altun, A. Kılıç et al.· Scientific Reports· 0 citations
Depression has been associated with cardiovascular disorders, including stroke. Although, the graded association and the role of antidepressant medication use continue to be uncertain. To examine the link between depression severity (PHQ-9) and stroke, comprising nonlinear effects and interaction with the use of antidepressant. In this study, data was analysed from NHANES 2007–2018 (n = 35,162), of whom 32,040 participants with complete data were incorporated in the final analysis. Severity of depression was evaluated by using PHQ-9. Self-reported prevalent stroke was the outcome. Odds ratios (ORs) were estimated by survey weighted logistic regression models. Nonlinear associations were evaluated by using natural cubic splines. Greater PHQ-9 scores were significantly linked with augmented odds of self-reported stroke (OR 1.07, 95% CI 1.05–1.09, p < 0.001). Use of antidepressant was independently linked with self-reported stroke (OR 1.74, 95% CI 1.27–2.39). No statistically significant interaction was observed between PHQ-9 score and antidepressant use (p = 0.061). Natural cubic spline analysis demonstrated a significant overall association between PHQ-9 score and self-reported stroke, with no statistically significant evidence of nonlinearity. Both hypertension and diabetes were strong independent predictors of self-reported stroke, while higher income (PIR) was protective. Severity of depression was independently associated with higher odds of self-reported stroke. These findings highlight an association between depression severity and self-reported stroke history.
Unknown authors· Discover Public Health· 0 citations
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