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Catestatin (CST) is a pleiotropic peptide involved in cardiovascular protection with its antihypertensive and angiogenic effects. Considering that patients with end-stage renal disease (ESRD) who are undergoing hemodialysis (HD) are associated with higher cardiovascular risk, the aim of this study was to investigate plasma CST levels in HD patients, compare them to healthy controls and evaluate possible CST associations with advanced glycation end products (AGEs) and laboratory, anthropometric and clinical parameters. The study included 91 patients on HD and 70 healthy controls. Plasma CST levels were determined by an enzyme-linked immunosorbent assay in a commercially available diagnostic kit, while AGEs were determined using skin autofluorescence. Plasma CST levels were significantly higher in the HD group compared to the controls (32.85 ± 20.18 vs. 5.39 ± 1.24 ng/mL, p < 0.001) and there was a significant positive correlation between CST and AGEs (r = 0.492, p < 0.001). Furthermore, there was a significant positive correlation between plasma CST levels with both the Dialysis Malnutrition Score (r = 0.295, p = 0.004) and Malnutrition-Inflammation Score (r = 0.290, p = 0.005). These results suggest that CST could be playing a role in the complex pathophysiology of ESRD/HD and that it could affect the higher cardiovascular risk of patients on HD.

To evaluate whether the systemic inflammation score (SIS) could predict postoperative outcomes for patients undergoing video-assisted thoracoscopic surgery (VATS) lobectomy for early-stage non-small-cell lung cancer (NSCLC). This retrospective study was conducted on the prospectively maintained database in our institution between January 2016 and December 2017. Preoperative SIS comprising serum albumin (sALB) and lymphocyte-to-monocyte ratio (LMR) was graded into 0, 1 and 2, and then utilized to distinguish patients at high surgical risks. Multivariable logistic-regression analysis was conducted to determine independent risk factors for postoperative outcomes. There were 1,025 patients with TNM-stage I-II NSCLC included, with an overall morbidity rate of 31.1% and mortality rate of 0.3%. We applied the sALB at 40 g/L and the median LMR of our series at 4.42 as dichotomized cutoffs for modified SIS scoring criteria. Both minor and major morbidity rates in patients with SIS=2 were significantly higher than those in patients with SIS=0 and with SIS=1 ( <0.001). No difference was found in overall morbidity rate between patients with SIS=1 and with SIS=0 ( =0.20). No significant difference was found in the mortality rate between these 3 groups. Patients with SIS=2 had the highest probability to experience most of individual complications. Finally, multivariable logistic-regression analysis suggested that preoperative SIS=2 could independently predict the morbidity risks following VATS lobectomy (OR=1.73; 95% CI=1.11-2.71; =0.016). The SIS scoring system can be employed as a simplified, effective and routinely operated risk stratification tool in patients undergoing VATS lobectomy.

While patient care, kidney replacement therapy, and transplantation techniques for chronic kidney disease (CKD) have continued to progress, the incidence of malnutrition disorders in CKD appears to have remained unchanged over time. However, there is now a better understanding of the underlying pathophysiology according to the disease background, disease stage, and the treatment received. In CKD patients, the increased production of proinflammatory cytokines and oxidative stress lead to a proinflammatory milieu that is at least partially responsible for the increased morbidity and mortality in this patient population. New insights into the pathogenic role of innate immunity and the proinflammatory cytokine profile, characterized, for instance, by higher levels of IL-6 and TNF-α, explain some of the clinical and laboratory abnormalities observed in these patients. In this article, we will explore currently available nutritional–inflammatory biomarkers in distinct CKD populations (hemodialysis, peritoneal dialysis, transplantation) with a view to evaluating their efficacy as predictors of malnutrition and their involvement in the common proinflammatory process. Although there is a direct relationship between inflammatory-nutritional status, signs and symptoms [e.g., protein-energy wasting (PEW), anorexia], and comorbidities (e.g., atheromatosis, atherosclerosis), we are in need of clearly standardized markers for nutritional-inflammatory assessment to improve their performance and design appropriate bidirectional interventions.

Background Serum inflammation-based scores can predict clinical outcome in several cancer types, including adrenocortical carcinoma (ACC). It is unclear whether the extent of inflammation-based scores alterations in ACC reflects malignancy, steroid excess, or both. Methods We investigated a large retrospective cohort of adrenocortical adenomas (ACA, n  = 429) and ACC ( n  = 61) with available baseline full blood count and hormonal evaluation. We examined the relationship between different inflammation-based scores [neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic immune-inflammation index (SII), and prognostic nutrition index (PNI)] and both malignancy and steroid secretion patterns. Results All inflammation-based scores differed between ACC and ACA: patients with ACC had higher NLR, PLR, SII and lower LMR and PNI levels compared to ACA (all p values < 0.001). NLR showed a positive correlation with cortisol levels after overnight 1 mg-dexamethasone suppression test (1 mg-DST), both in ACC and ACA ( p  < 0.01). The ROC curve analysis determined NLR > 2.6 as the best cut-off to discriminate ACC from ACA [AUC = 0.846, p  < 0.01]. At multivariable analysis, NLR > 2.6 was independently associated with ACC, 1 mg-DST cortisol levels and age, but not with tumour size. Considering the ACC, NLR and SII were higher and PNI was lower in patients with cortisol excess compared to those without cortisol excess ( p  = 0.002, p  = 0.007, and p  = 0.044 respectively). Finally, LMR and NLR differed between inactive-ACC ( n  = 10) and inactive-ACA ( n  = 215) ( p  = 0.040 and p  = 0.031, respectively). Conclusion Inflammation-based scores are related to steroid secretion both in ACC and ACA. ACCs present a higher grade of inflammation regardless of their hormonal secretion, likely as a feature of malignancy itself.

This cross-sectional study evaluated the association between sleep health and the Lifestyle Inflammation Score (LIS), which has not been sufficiently examined in previous research. We further assessed whether inadequate sleep duration and poor sleep quality are associated with a higher LIS. Moreover, we explored the effects of age, sex, and income. A generalized ordered logit model was used to evaluate the association between sleep health and the LIS, incorporating independent variables and control variables. Separate models predicted the LIS quintile probability for each combination of sleep quality and sleep duration. Inadequate sleep duration (odds ratio [OR]: 1.108, P  < 0.001) and poor sleep quality (OR: 1.090, P  < 0.001) were significantly associated with higher LIS across quintiles. The probability of belonging to the highest LIS quintile (Q5) did not increase proportionally with age. Crucially, predictive margins analysis showed that poor sleep health was associated with a higher predicted probability of being in the highest LIS quintile (20.7%) compared with good sleep health (18.4%). This large-scale nationwide study identified consistent associations between poor sleep health and higher inflammation burden within the study population, highlighting the need for comprehensive management strategies addressing sleep alongside other lifestyle factors.

Background Inflammation scores based on general inflammation markers as leucocyte count or C-reactive protein have been evaluated as prognostic markers of inferior survival in several cancers. In small cell lung cancer (SCLC), however, inflammation scores are less studied. In the present study, we set out to perform a systematic review and meta-analysis investigating reported associations between inflammation scores and overall survival (OS) in SCLC. Methods A literature search was performed in PubMed, Embase, Scopus, and Web of Science following the Preferred Reporting Items for Systematic and Meta-Analyses (PRISMA) guidelines. Of the identified publications, only studies in English containing original data evaluating inflammation scores as a prognostic factor in SCLC patients were included. Hazard ratios (HRs) for OS were pooled in a random-effects model . Results In total, 33 articles were included evaluating eight different inflammation scores in 7762 SCLC patients. Seven of the identified scores were based on leucocyte count. Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte (PLR) ratio were the most frequently evaluated scores (NLR: n = 23; PLR: n = 22). For NLR, a meta-analysis including 16 studies demonstrated that patients with a high NLR had a significantly shorter OS compared to patients with a low NLR (pooled HR = 1.39 (95% CI, 1.23–1.56)). For PLR, an association with survival could not be confirmed in a meta-analysis performed based on eight studies (pooled HR = 1.20 (95% CI, 0.96–1.51)). Conclusions This review identifies that inflammation scores based on general inflammation markers have some potential as prognostic biomarkers in SCLC. The meta-analyses indicated that NLR is associated with inferior OS, whereas an association between PLR and OS could not be confirmed. Thus, NLR could be a useful biomarker of OS in SCLC patients. Systematic review registration The protocol for the study was submitted to the PROSPERO database (registration number CRD42020188553 ).

Background and Objectives: Studies have shown that inflammation markers can be used as prognostic tools in predicting acute ischemic stroke. In this study, we conducted a comparison of several inflammation scores in predicting left atrial thrombosis (LAT) in patients with ischemic stroke without AF. Materials and Methods: In this single-center, retrospective study, we included 303 consecutive patients with ischemic stroke. Each patient underwent a transesophageal echocardiography (TEE) examination within 10 days of admission to detect the presence of LAT. To identify independent predictors of LAT, we conducted a multivariate logistic regression analysis. Results: In total, 303 patients who had ischemic stroke were included in the analysis. LAT was detached in 34 patients at the time of the TEE examination. The patients were categorized into two groups based on their LAT status. The Prognostic Nutritional Index (PNI), HALP score, and C-reactive Protein–Albumin Ratio (CAR) were identified as statistically significant predictors of LAT. Based on the results of the multivariate regression analysis, the CAR emerged as the only independent predictor of LAT. Conclusions: Among several inflammation scores, the PNI, HALP, and CAR were statistically significant predictors of LAT in ischemic stroke patients without AF. CAR was identified as the optimal score for the prediction of LAT in patients with stroke and without AF.

Background and Aim The existed staging systems were limited in the accuracy of prediction for overall survival (OS) of hepatocellular carcinoma (HCC) patients. The aim of this study is to establish a novel inflammation‐based prognostic system with nomogram for HCC patients. Methods A prospective cohort of patients was recruited and assigned to the training cohort (n = 659) and validation cohort (n = 320) randomly. Different inflammation‐based score systems were evaluated to select the best one predicting overall survival (OS). The inflammation‐based score system with the highest predicting value and the parameters best reflecting tumor burden identified by multivariate analysis were selected to construct a novel predicting nomogram system. The predictive accuracy and discriminative ability of the nomogram were evaluated by concordance index (C‐index) and calibration curve and compared with conventional staging systems. Results With a highest C‐index and areas under the receiver operating characteristic curve (AUC), C‐reactive protein/albumin ratio (CAR) was selected to construct the novel system, along with tumor number, tumor size, macrovascular invasion and extra‐hepatic metastases. The C‐index of the nomogram was 0.813 (95% CI, 0.789‐0.837) in the training cohort and 0.794 (95% CI, 0.756‐0.832) in the validation cohort. The calibration curve for predicting probability of survival showed that the nomogram had a high consistency with follow‐up data. The C‐index of the novel system was higher than other conventional staging systems (P < 0.001). Conclusions The novel inflammation‐based nomogram, developed from prospectively collected data in the present study, predicted the OS of HCC patients. The inflammation‐based score system with the highest predicting value and the parameters best reflecting tumor burden identified by multivariate analysis were selected to construct a novel predicting nomogram system. C‐reactive protein albumin ratio was selected to construct the novel system, along with tumor number, tumor size, macrovascular invasion, and extra‐hepatic metastases. The novel inflammation‐based nomogram, developed from prospectively collected data, predicted the overall survival of hepatocellular carcinoma patients.

Approximately 20% of the thyroid biopsies render an indeterminate (ID) cytology. We evaluated the diagnostic value of preoperative modified systemic inflammation score (mSIS) in predicting the malignancy of ID thyroid nodules (TNs). Data of 162 patients with indeterminate TNs were examined retrospectively. The mSIS was calculated as follows: mSIS 0 [patients with albumin (ALB) ≥ 4.0 g/dL and lymphocyte-to-monocyte ratio (LMR) ≥ 3.4], mSIS 1 [ALB < 4.0 g/dL or LMR < 3.4], and mSIS 2 [ALB < 4.0 g/dL and LMR < 3.4]. Patients were classified into mSIS 0 (n = 105), mSIS 1 (n = 34) and mSIS 2 (n = 23) groups. The malignancy rates for the mSIS 0, 1 and 2 groups were 34.3%, 64.7% and 100% respectively. Preoperative mSIS was significantly associated with the presence of thyroid malignancy (p < 0.001). If the mSIS of patients with ID cytology is 1 or 2, appropriate surgical treatment should be performed without delay, due to the increased risk of malignancy. •Modified systemic inflammation score (mSIS) is an easy and cost-effective method to assess the risk of malignancy.•mSIS may provide important contributions to clinicians in predicting malignancy risk of indeterminate TNs.•This is the first report that establishes a positive association between preoperative mSIS and thyroid malignancies.

BackgroundThe systemic inflammation score (SIS), based on preoperative serum albumin (Alb) level and lymphocyte-to-monocyte ratio (LMR), has been shown to be a novel prognostic score for some tumors. We investigate the prognostic value of the SIS in patients with resectable gastric cancer (GC).MethodsPatients with GC who underwent curative resection between December 2008 and December 2013 were included. Time-dependent receiver operating characteristics analysis (t-ROC), concordance index (C-index) and AUC were used to compare the prognostic impact.ResultsTotally, 1786 patients with resectable GC were included in the study. By multivariate analysis, the SIS was not an independent prognostic factor. However, the normal Alb level (≥ 40 g/l) and LMR ≥ 3.4 both remained independent protective factors for GC (both P < 0.05). Due to the similar survival of patients with LMR ≥ 3.4 and LMR < 3.4 in the normal Alb group, we combined the two subgroups to establish the modified SIS (mSIS). Multivariate analysis revealed that the mSIS was the only significant independent biomarker (P < 0.05). The t-ROC curve and C-index for the mSIS were superior to those of the SIS throughout the observation period. Furthermore, the AUC of the mSIS was significantly greater than that of the SIS at 3 and 5 years after operation (both P < 0.05).ConclusionThe preoperative mSIS is a novel, simple and useful prognostic factor for postoperative survival in patients with GC and can be used as a part of the preoperative risk stratification process to improve the prediction of clinical outcomes.