Systemic Immune-Inflammation Index as a Predictor of Microvascular Dysfunction in Patients With Cardiac Syndrome X

Association of systemic immune-inflammation index with body mass index, waist circumference and prevalence of obesity in US adults

This study aims to investigate the potential relationships between the systemic immune-inflammation index (SII) and body mass index (BMI), waist circumference, and the prevalence of obesity. A cross-sectional analysis was conducted on 7,645 individuals aged 20 and above from the NHANES 2017-2020. Multivariate linear regression analyses were conducted to evaluate the association of the logarithmically transformed SII (lgSII) with BMI and waist circumference. Additionally, multivariable logistic regression was utilized to explore the relationship between lgSII and the prevalence of obesity. Fitted smoothing curves and threshold-effect analysis were applied to elucidate nonlinear relationships. In the fully adjusted model, a positive relationship was observed between lgSII and BMI, waist circumference, and obesity prevalence (β = 3.13, 95% CI 2.10-4.16; β = 7.81, 95% CI 5.50-10.13; OR = 1.44, 95% CI 1.12-1.86). The variables of gender, age, race, education, marital status, poverty income ratio (PIR), energy intake, sleep disorder, smoking status, and alcohol use did not significantly modify the positive association between lgSII and obesity. However, physical activity appeared to influence the positive correlation between lgSII and obesity. Using a two-segment linear regression model, an inverted U-shaped relationship was observed between lgSII and both BMI and waist circumference. Furthermore, lgSII demonstrated a linear positive correlation with obesity prevalence. When stratified by physical activity, lgSII showed a non-significant negative correlation with obesity in the physically active group. Our findings underscore a robust association between the logarithmically transformed SII and BMI, waist circumference, and the prevalence of obesity.

Systemic immunity-inflammation index is associated with body fat distribution among U.S. adults: evidence from national health and nutrition examination survey 2011-2018

OBJECTIVE

The systemic immunity-inflammation index (SII) is a newly developed biomarker that provides an integrated measure of inflammation in the body. We aim to evaluate the relationship between SII and body fat distribution.

METHODS

Adults from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 were included. The SII was computed using lymphocyte (LC), neutrophil (NC), and platelet (PC) counts as its components. Body fat distribution was assessed by (total, android, gynoid) percentage fat, total abdominal fat area, subcutaneous adipose tissue area, visceral adipose tissue area, and the ratio of visceral to subcutaneous adipose tissue area (V/S ratio). Multivariable weighted linear regression and subgroup analysis were use to examine the relationships between fat distribution and SII. Restricted cubic splines (RCS) and threshold effect analysis were used to examine analyze nonlinear associations.

RESULTS

After exclusions, a total of 11,192 adults with a weighted mean age of 38.46 ± 0.26 years were studied. In multivariable weighted linear regression, each level increase in log2SII was associated with increased of 0.23 SDs total percentage fat (95% CI = 0.03, 0.43) and 0.26 SDs android percentage fat (95% CI = 0.06, 0.47). Besides, the subgroup analysis showed that the positive association between SII and android percentage fat was mainly among obese individuals (BMI > 30 kg/m2) and non-obese individuals without DM or hypertension. Meanwhile, the relationship between SII and the V/S ratio was found to be significant in the female subgroup, the obese subgroup, individuals with non-alcoholic fatty liver disease (NAFLD), and those without diabetes mellitus. Finally, SII exhibited an inverted U-shaped relationship with total percentage fat, android percent fat and total abdominal fat. Accordingly, threshold effect analysis indicated a positive association between lower SII levels and total percentage fat, android percentage fat and total abdominal fat area.

CONCLUSIONS

In the nationwide study, it was observed that the SII exhibited a significant correlation with higher levels of body fat, specifically android fat. This association was particularly noticeable within specific subgroups of the population.

The Predictive Role of Hematological Parameters in Hypertension

Hypertension (HT) is a common chronic disease that often causes target-organ damage and severe complications, contributing to cardiovascular morbidity and mortality worldwide. Accumulating evidence suggests that inflammation plays a prominent role in the initiation and progression of HT. Multiple inflammatory biomarkers have been proposed to predict HT. Several new hematological parameters can reflect the inflammatory response and platelet activation. The major advantage of hematological parameters over conventional inflammatory markers is that they are relatively inexpensive and easily obtained from routine blood tests. Numerous studies have investigated several hematological parameters for their utility as predictive biomarkers for the diagnosis and prognosis of HT. Among them, the neutrophil to lymphocyte ratio (NLR), monocyte to high density lipoprotein cholesterol ratio (MHR), red cell distribution width (RDW), platelet to lymphocyte ratio (PLR), mean platelet volume (MPV), platelet distribution width (PDW), and systemic immune-inflammation index (SII) have recently received attention. We searched PubMed and Embase databases (up to September 18, 2022) to assess the relationships between hematological parameters and HT. This review discusses the diagnostic and prognostic value of these hematological parameters in HT, providing an important basis for early screening, risk stratification, and optimal management of hypertensive patients.

Association between systemic immune-inflammation index and serum neurofilament light chain: a population-based study from the NHANES (2013-2014)

Background

The systemic immune-inflammation index (SII) is a novel inflammatory marker used to assess the immune-inflammatory status of the human body. The systemic immune inflammation has an interplay and mutual relationship with neurological disorders. Serum neurofilament light chain (sNfL) is widely regarded as a potential biomarker for various neurological diseases. The study aimed to examine the association between SII and sNfL.

Methods

This cross-sectional investigation was conducted in a population with complete data on SII and sNfL from the 2013-2014 National Health and Nutrition Examination Survey (NHANES). The SII was calculated by dividing the product of platelet count and neutrophil count by the lymphocyte count. Multivariate linear regression models and smooth curves were used to explore the linear connection between SII and sNfL. Sensitivity analyses, interaction tests, and diabetes subgroup smoothing curve fitting were also performed.

Results

A total of 2,025 participants were included in our present research. SII showed a significant positive association with the natural logarithm-transformed sNfL (ln-sNfL) in crude model [0.17 (0.07, 0.28)], partially adjusted model [0.13 (0.03, 0.22)], and fully adjusted model [0.12 (0.02, 0.22)]. In all participants, the positive association between SII and ln-sNfL served as a linear relationship, as indicated by a smooth curve. Interaction tests showed that age, gender, BMI, hypertension, and diabetes did not have a significant impact on this positive association (p for interaction >0.05). The subgroup analysis of diabetes was conducted using smooth curve fitting. It was found that compared to the group without diabetes and the group in a pre-diabetic state, the effect was more pronounced in the group with diabetes.

Conclusion

Our findings suggest that there is a positive association between SII and sNfL. Furthermore, in comparison to individuals without diabetes and those in a pre-diabetic state, the positive association between SII and sNfL was more pronounced in individuals with diabetes. Further large-scale prospective studies are needed to confirm the association between SII and sNfL.

RNAseq of INOCA patients identifies innate, invariant, and acquired immune changes: potential autoimmune microvascular dysfunction

Background

Ischemia with non-obstructive coronary arteries (INOCA) is a major clinical entity that involves potentially 20%-30% of patients with chest pain. INOCA is typically attributed either to coronary microvascular disease and/or vasospasm, but is likely distinct from classical coronary artery disease (CAD).

Objectives

To gain insights into the etiology of INOCA and CAD, RNA sequencing of whole blood from patients undergoing both stress testing and elective invasive coronary angiography (ICA) was conducted.

Methods

Stress testing and ICA of 177 patients identified 40 patients (23%) with INOCA compared to 39 controls (stress-, ICA-). ICA+ patients divided into 38 stress- and 60 stress+. RNAseq was performed by Illumina with ribosomal RNA depletion. Transcriptome changes were analyzed by DeSeq2 and curated by manual and automated methods.

Results

Differentially expressed genes for INOCA were associated with elevated levels of transcripts related to mucosal-associated invariant T (MAIT) cells, plasmacytoid dendritic cells (pcDC), and memory B cells, and were associated with autoimmune diseases such as rheumatoid arthritis. Decreased transcripts were associated with neutrophils, but neutrophil transcripts, per se, were not less abundant in INOCA. CAD transcripts were more related to T cell functions.

Conclusions

Elevated transcripts related to pcDC, MAIT, and memory B cells suggest an autoimmune component to INOCA. Reduced neutrophil transcripts are likely attributed to chronic activation leading to increased translation and degradation. Thus, INOCA could result from stimulation of B cell, pcDC, invariant T cell, and neutrophil activation that compromises cardiac microvascular function.

Inflammatory biomarkers in cardiac syndrome X: a systematic review and meta-analysis

INTRODUCTION

In the current systematic review and meta-analysis, we aim to analyze the existing literature to evaluate the role of inflammatory biomarkers, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), C-reactive protein (CRP), tumor necrosis factor-a (TNF-a), and interleukin-6 (IL-6) among individuals with cardiac syndrome X (CSX) compared to healthy controls.

METHODS

We used PubMed, Web of Science, Scopus, Science Direct, and Embase to systematically search relevant publications published before April 2, 2023. We performed the meta-analysis using Stata 11.2 software (Stata Corp, College Station, TX). So, we used standardized mean difference (SMD) with a 95% confidence interval (CI) to compare the biomarker level between patients and healthy controls. The I2 and Cochran's Q tests were adopted to determine the heterogeneity of the included studies.

RESULTS

Overall, 29 articles with 3480 participants (1855 with CSX and 1625 healthy controls) were included in the analysis. There was a significantly higher level of NLR (SMD = 0.85, 95%CI = 0.55-1.15, I2 = 89.0 %), CRP (SMD = 0.69, 95%CI = 0.38 to 1.02, p < 0.0001), IL-6 (SMD = 5.70, 95%CI = 1.91 to 9.50, p = 0.003), TNF-a (SMD = 3.78, 95%CI = 0.63 to 6.92, p = 0.019), and PLR (SMD = 1.38, 95%CI = 0.50 to 2.28, p = 0.02) in the CSX group in comparison with healthy controls.

CONCLUSION

The results of this study showed that CSX leads to a significant increase in inflammatory biomarkers, including NLR, CRP, IL-6, TNF-a, and PLR.

Association of systemic immune-inflammation index with diabetic kidney disease in patients with type 2 diabetes: a cross-sectional study in Chinese population

Objective

Systemic immune-inflammation index (SII), a novel inflammatory marker, has been reported to be associated with diabetic kidney disease (DKD) in the U.S., however, such a close relationship with DKD in other countries, including China, has not been never determined. We aimed to explore the association between SII and DKD in Chinese population.

Methods

A total of 1922 hospitalized patients with type 2 diabetes mellitus (T2DM) included in this cross-sectional study were divided into three groups based on estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (ACR): non-DKD group, DKD stages 1-2 Alb group, and DKD-non-Alb+DKD stage 3 Alb group. The possible association of SII with DKD was investigated by correlation and multivariate logistic regression analysis, and receiver-operating characteristic (ROC) curves analysis.

Results

Moving from the non-DKD group to the DKD-non-Alb+DKD stage 3 Alb group, SII level was gradually increased (P for trend <0.01). Partial correlation analysis revealed that SII was positively associated with urinary ACR and prevalence of DKD, and negatively with eGFR (all P<0.01). Multivariate logistic regression analysis showed that SII remained independently significantly associated with the presence of DKD after adjustment for all confounding factors [(odds ratio (OR), 2.735; 95% confidence interval (CI), 1.840-4.063; P < 0.01)]. Moreover, compared with subjects in the lowest quartile of SII (Q1), the fully adjusted OR for presence of DKD was 1.060 (95% CI 0.773-1.455) in Q2, 1.167 (95% CI 0.995-1.368) in Q3, 1.266 (95% CI 1.129-1.420) in the highest quartile (Q4) (P for trend <0.01). Similar results were observed in presence of DKD stages 1-2 Alb or presence of DKD-non- Alb+DKD stage 3 Alb among SII quartiles. Last, the analysis of ROC curves revealed that the best cutoff values for SII to predict DKD, Alb DKD stages 1- 2, and DKD-non-Alb+ DKD stage 3 Alb were 609.85 (sensitivity: 48.3%; specificity: 72.8%), 601.71 (sensitivity: 43.9%; specificity: 72.3%), and 589.27 (sensitivity: 61.1%; specificity: 71.1%), respectively.

Conclusion

Higher SII is independently associated with an increased risk of the presence and severity of DKD, and SII might be a promising biomarker for DKD and its distinct phenotypes in Chinese population.

Comparison of Systemic Immune-Inflammation Index and Naples Prognostic Score for Prediction Coronary Artery Severity Patients Undergoing Coronary Computed Tomographic Angiography

This study compared the predictive power of the systemic immune-inflammation index (SII) and Naples prognostic score (NPS) in determining the severity of coronary artery disease (CAD). The study included 1138 patients who underwent coronary computed tomographic angiography (CCTA). The primary outcome was the evaluation of CAD severity, determined by the Coronary Artery Disease-Reporting and Data System (CAD-RADS) obtained from the CCTA scans. A basic statistical model including age, gender, chest pain, diabetes mellitus, hypertension, hyperlipidemia, and smoking was built, and categorical variables, NPS (Naples 3,4 vs 0,1,2) and SII, were added to the basic statistical model. The net benefits of the predictive parameters were determined by a decision curve analysis, and the association between CAD-RADS and NPS, SII was quantified by odds ratios (OR) and 95% confidence intervals (CI). The decision curve analysis showed that adding SII to the statistical model had a better full range of probability of clinical net benefit compared with the baseline model (OR: 5.77, 95% CI 4.15-8.02, P < .001). However, adding the NPS (P = .11) to the model did not outperform the basic statistical model. In conclusion, the SII may have a net predictive effect on top of traditional risk factors.

Increased Systemic Immune-Inflammation Index Was Associated with Type 2 Diabetic Peripheral Neuropathy: A Cross-Sectional Study in the Chinese Population

Background

Systemic immune-inflammation index (SII), a novel inflammatory marker, has been demonstrated to be associated with type 2 diabetes mellitus (T2DM) and its vascular complications, however, the relation between SII and diabetic peripheral neuropathy (DPN) has been never reported. We aimed to explore whether SII is associated with DPN in Chinese population.

Methods

A cross-sectional study was conducted among 1460 hospitalized patients with T2DM. SII was calculated as the platelet count × neutrophil count/lymphocyte count, and its possible association with DPN was investigated by correlation and multivariate logistic regression analysis, and subgroup analyses.

Results

Patients with higher SII quartiles had higher vibration perception threshold and prevalence of DPN (all P<0.01), and SII was independently positively associated with the prevalence of DPN (P<0.01). Multivariate logistic regression analysis showed that the risk of prevalence of DPN increased progressively across SII quartiles (P for trend <0.01), and participants in the highest quartile of SII was at a significantly increased risk of prevalent DPN compared to those in the lowest quartile after adjustment for potential confounding factors (odds rate: 1.211, 95% confidence intervals 1.045-1.404, P<0.05). Stratified analysis revealed positive associations of SII quartiles with risk of prevalent DPN only in men, people less than 65 years old, with body mass index <24 kg/m2, duration of diabetes >5 years, hypertension, dyslipidaemia, poor glycaemic control, and estimated glomerular filtration rate <90 mL/min/1.73 m2 (P for trend <0.01 or P for trend <0.05). The receiver operating characteristic curve analysis revealed that the optimal cut-off point of SII for predicting DPN was 617.67 in patients with T2DM, with a sensitivity of 45.3% and a specificity of 73%.

Conclusion

The present study showed that higher SII is independently associated with increased risk of DPN, and SII might serve as a new risk biomarker for DPN in Chinese population.

Association between pan-immune-inflammation value and no-reflow in patients with ST elevation myocardial infarction undergoing percutaneous coronary intervention

Noreflow is a condition associated with a poor prognosis in ST segment elevation myocardial infarction patients. It has been shown that many inflammatory markers and index such as procalcitonin, C-reactive protein, neutrophil to lymphocyte ratio, systemic immune inflammatory index (SII), are associated with noreflow. We used a brand-new index pan-immune-inflammation value (PIV) to retrospectively evaluate the relationship between PIV and noreflow. A total of 1212 patients were included for analysis. Noreflow was observed in 145 patients. In multivariate analysis, PIV (odds ratio (OR): 1.025; [1.002-1.115], p < 0.001), baseline ejection fraction (OR: 0.963; [0.934-0.993], p = 0.015), stent length (OR: 1.032; [1.010-1.054], p = 0.004), age (OR: 1.034; [1.014-1.053], p = 0.001) and pain to PCI time (OR: 1.003 [1.002-1.005], p < 0.001) were observed to be the independent predictors of noreflow. ROC curve analysis showed that the best cut off value of PIV for predicting noreflow was ≥889 with 77.2% sensitivity and 77.5% specificity (AUC, 0.828; 95% CI [0.806-0.849]). A ROC curve comparison analysis was performed to compare PIV and SII. The predictive power of PIV was higher than SII (differences between areas: 0.154; p < 0.001). According to our findings, an increase in PIV is an independent predictor of noreflow in patients with STEMI.

Prognostic Value of Systemic Immune-Inflammation Index in Predicting Premature Saphenous Vein Graft Disease in Patients With Coronary Artery Bypass Grafting

BACKGROUND

Systemic inflammation is a risk factor for premature coronary artery disease (CAD), and systemic immune-inflammation index (SII), a new marker of systemic inflammation, is linked to the severity and prognosis of CAD. However, the prognosis of the SII in bypass patients' venous saphenous grafts has not been adequately evaluated. This study aimed to evaluate the prognostic value of SII in predicting premature saphenous vein graft disease (SVGD) in patients who underwent bypass surgery with venous saphenous grafts.

METHODS

We retrospectively included 422 patients who had saphenous vein grafts (SVG) at least one year after bypass surgery. Of these, 222 patients had SVGD, and 200 had patent SVG.

RESULTS

SII was higher in the SVGD group than in the control group (631.55 ± 397.84, 421.71 ± 351.07, P=0.001). A receiver operating characteristic (ROC) analysis was performed to identify the optimal cutoff point with the highest sensitivity and specificity. The optimal cutoff point for SII was defined as 430. Using a cutoff level of >430, SII predicted SVGD with a sensitivity of 73% and specificity of 56%.

CONCLUSION

Our study demonstrated that SII was substantially higher in patients with SVGD than in those with patent SVG. SII predicted SVGD in bypass surgery patients. SII may be a helpful parameter for identifying patients at high risk of SVGD and guiding preventive treatments.

Diagnostic value of systemic immune-inflammation index and red cell distribution width-lymphocyte ratio in predicting troponin elevation in carbon monoxide poisoning

Purpose: The aim of our study was to assess the significant value of the systemic inflammatory index (SII) and red cell distribution width/lymphocyte ratio (RLR) in patients with carbon monoxide poisoning (COP). Materials and Methods: Based on a retrospective cross-sectional study design, this study was conducted among patients 18 years and older who presented to the hospital's emergency department with COP. The patients were separated into troponin positive and negative groups as an outcome of serial troponin measurements. Receiver operating characteristic (ROC) analysis was used to determine the cut-off value of neutrophil/lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), RLR, and SII to predict troponin positivity. Results: This study included 195 patients with CO exposure, 50 of whom had positive troponin tests. It was discovered that the diagnostic power of NLR, RLR, MLR, and SII was acceptable for identifying troponin positivity (AUC: 0.71-0.77). According to ROC curve comparisons, there was no diagnostic difference between these inflammatory biomarkers. Increased NLR, RLR, MLR, and SII were found to be independent predictors of troponin positivity after CO exposure (Odds ratio respectively: 8.65, 4.31, 7.24, 6.31). Conclusion: SII and RLR, which are simple, inexpensive, and easily accessible parameters, are valuable in predicting troponin positivity in COP cases.

Assessment of the Diagnostic Value of Novel Biomarkers in Adult Patients With Acute Appendicitis: A Cross-Sectional Study

Background Acute appendicitis (AA) is one of the most frequent causes of abdominal pain requiring emergency intervention in adults. Approximately one-third of cases present with atypical clinical symptoms. This study aims to compare the monocyte-to-lymphocyte ratio (MLR), red cell distribution width (RDW) to lymphocyte ratio (RLR), and systemic immune inflammation index (SII) with other biomarkers in distinguishing patients with and without AA. Methodology A total of 347 patients (AA 125, nonspecific abdominal pain 90, and control group 132) were enrolled in the study according to the cross-sectional study design. Receiver operating characteristic (ROC) analysis was used to determine the cutoff in diagnostic value measurements. Statistical significance was determined by the statistics of sensitivity, specificity, positive predictive value, and negative predictive value. Comparison of ROC curves of C-reactive protein (CRP), white blood cell (WBC), neutrophil count (NEU), neutrophil-to-lymphocyte ratio (NLR), MLR, and SII was evaluated with the pairwise comparison of ROC curves and 95% confidence interval. Results In detecting AA, CRP, WBC, NEU, NLR, MLR, and SII have excellent diagnostic power (area under the curve [AUC] 0.80-0.88), while RDW, lymphocyte count, monocyte (MON) count, and RLR had acceptable diagnostic power (AUC 0.70-0.77). When the power in the diagnosis of AA was compared, a significant difference was found between CRP and NEU, CRP and SII, WBC and NEU, and WBC and SII. Conclusions The diagnosis of AA remains dependent on many factors. Inflammatory biomarkers assist this process. MLR and SII may be recommended to use in diagnosing AA in adults, along with other clinical findings. RLR is adequate but not superior.

Association between SII and hepatic steatosis and liver fibrosis: A population-based study

Background

The systemic immune-inflammation index (SII) is a novel marker of inflammation, and hepatic steatosis and fibrosis are associated with inflammation. This study aimed to investigate the possible relationship between SII and hepatic steatosis and fibrosis.

Methods

The datasets from the National Health and Nutrition Examination Survey (NHANES) 2017–2020 were used in a cross-sectional investigation. Multivariate linear regression models were used to examine the linear connection between SII and controlled attenuation parameter (CAP) and liver stiffness measurement (LSM). Fitted smoothing curves and threshold effect analysis were used to describe the nonlinear relationship.

Results

This population-based study included a total of 6,792 adults aged 18–80 years. In a multivariate linear regression analysis, a significant positive association between SII and CAP was shown [0.006 (0.001, 0.010)]. This positive association in a subgroup analysis was maintained in men [0.011 (0.004, 0.018)] but not in women. Furthermore, the association between SII and CAP was nonlinear; using a two-segment linear regression model, we found an inverted U-shaped relationship between SII and CAP with an inflection point of 687.059 (1,000 cells/µl). The results of the multiple regression analysis showed that the relationship between SII and LSM was not significant (P = 0.263).

Conclusions

Our findings imply that increased SII levels are linked to hepatic steatosis, but SII is not linked to liver fibrosis. To confirm our findings, more large-scale prospective investigations are needed.

Systemic immune-inflammation index predicts postoperative delirium in elderly patients after surgery: a retrospective cohort study

Background

Postoperative delirium (POD) is a common complication among elderly patients after surgery. It is unclear whether the systemic immune-inflammation index (SII) can be a predictor of POD. We explored the prognostic value of the SII in predicting POD in elderly patients undergoing non-neurosurgery and non-cardiac surgery in a large retrospective cohort.

Methods

We enrolled elderly patients undergoing non-neurosurgery and non-cardiac surgery between January 2014 and August 2019. Univariate and multivariate logistic regression analyses were performed to explore the correlation between POD and the SII value as both a continuous and categorical variable. Then, propensity score matching (PSM) analysis was applied to eliminate the confounding effect of covariates and prove our results. Subgroup analyses were then performed to discover the association between the SII and POD in different subgroups.

Results

A total of 29,608 patients with a median age of 70 years (IQR: 67–74) were enrolled in the retrospective cohort. The cut-off value of the SII was 650, which was determined by the receiver operating characteristic (ROC) curve. The ORs of an SII value > 650 was 2.709 (95% CI:2.373–3.092, P < 0.001), 1.615 (95% CI:1.384–1.882, P < 0.001), 1.855 (95% CI:1.602–2.146, P < 0.001), and 1.302 (95% CI:1.106–1.531, P = 0.001) for prediction of POD in univariate model and three multivariate regression models. After PSM, the OR of an SII value > 650 was 1.301 (95% CI: 1.062–1.598, P = 0.011). The subgroup analysis indicated that the SII indicates a significantly increased risk of POD in patients with Hb < 130 g/L, 4*10⁹/L < WBC ≤ 10*10⁹/L, albumin < 39 g/L, or duration of MAP < 60 mmHg ≥ 5 min. The SII was found to be a useful prognostic predictor of POD for patients of different ages, sexes, and ASA classifications.

Conclusions

The SII had a predictive value for POD in patients undergoing non-neurosurgery and non-cardiac surgery. As an index generated from routine blood tests, the SII has advantages regarding cost and time. After further validation, the SII may provide a new option for POD prediction.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-03418-4.