UNASSIGNED: Enterostomy is important for radical resection of colorectal cancer (CRC). Nevertheless, the notable occurrence of complications linked to enterostomy results in a reduction in patients\' quality of life and impedes adjuvant therapy. This study sought to forecast early stoma-related complications (ESRCs) by leveraging easily accessible nutrition-inflammation markers in CRC patients.
UNASSIGNED: This study involved 470 individuals with colorectal cancer who underwent intestinal ostomy at Changhai Hospital Affiliated with Naval Medical University as the internal cohort. Between January 2016 and December 2018, the patients were enrolled and randomly allocated into a primary training group and a secondary validation group, with a ratio of 2:1 being upheld. The research encompassed collecting data on each patient\'s clinical and pathological status, along with preoperative laboratory results. Independent risk factors were identified through Lasso regression and multivariate analysis, leading to the development of clinical models represented by a nomogram. The model\'s utility was assessed using decision curve analysis, calibration curve, and ROC curve. The final model was validated using an external validation set of 179 individuals from January 2015 to December 2021.
UNASSIGNED: Among the internal cohort, stoma complications were observed in 93 cases. Multivariate regression analysis confirmed that age, stoma site, and elevated markers (Mon, NAR, and GLR) in conjunction with diminished markers (GLB and LMR) independently contributed to an increased risk of ESRCs. The clinical model was established based on these seven factors. The training, internal, and external validation groups exhibited ROC curve areas of 0.839, 0.812, and 0.793, respectively. The calibration curve showed good concordance among the forecasted model with real incidence of ostomy complications. The model displayed outstanding predictive capability and is deemed applicable in clinical settings, as evidenced by Decision Curve Analysis.
UNASSIGNED: This study identified nutrition-inflammation markers (GLB, NAR, and GLR) in combination with demographic data as crucial predictors for forecasting ESRCs in colorectal cancer patients. A novel prognostic model was formulated and validated utilizing these markers.

BACKGROUND: Tuberculosis (TB) remains a global health challenge, with India bearing a significant burden. Despite advancements in TB diagnosis and treatment, monitoring TB treatment is challenging, particularly in resource-limited settings. This study aimed to explore the mean platelet volume (MPV) as a potential surrogate marker for monitoring TB treatment and assessing if the neutrophil-to-albumin ratio (NAR) enhances treatment monitoring.
METHODS: Patients diagnosed with TB following NTEP guidelines were recruited. Participants underwent routine blood tests during the six-month Anti-Tubercular therapy course at the start, end of the intensive phase, and end of the continuous phase. Statistical analyses included Spearman correlation, Friedman test, linear mixed effects (LME) models, and multiple linear regression.
RESULTS: 150 individuals were included for analysis. Deviations from normality were noted. Significant associations were found between CRP and sputum grade. MPV mediated between CRP and sputum grade. Significant differences were observed across the three-time points. LME models showed changes in MPV and CRP levels over time. Including NAR enhanced predictive capability.
CONCLUSIONS: MPV may serve as a promising surrogate marker for monitoring ATT. Personalized approaches are crucial in TB treatment monitoring. LME models revealed MPV and CRP level trends. Future research should explore MPV\'s treatment response mechanisms and cost-effectiveness.

BACKGROUND: Stroke is a leading cause of disability and mortality globally. This study aimed to develop a prognostic nomogram based on neutrophil-to-albumin ratio (NAR) and collateral status in acute ischemic stroke (AIS) patients with anterior large vessel occlusion (LVO).
METHODS: 590 AIS patients with LVO assessed for regional leptomeningeal collateral (rLMC) were retrospectively enrolled, and randomly divided into a training set (n = 414) and a testing set (n = 176). Unfavorable functional outcome was defined as a modified Rankin scale (mRS) score of 3 to 6 at 3 months. We assessed the accuracy and clinical utility of the nomogram using calibration plots, area under the curve (AUC), decision curve analysis (DCA), net reclassification index (NRI), and integrated discrimination improvement (IDI).
RESULTS: Both NAR and rLMC were independently associated with unfavorable outcome at 3 months (OR=8.96, p=0.0341; OR=0.89, p=0.0002, respectively). The developed nomogram (akaike information criterion (AIC)=398.77), which included NAR, rLMC and other factors, showed good performance (the AUC for the development and validation cohorts was 0.848 and 0.840 respectively) and improved the predictive value compared to a model without NAR and rLMC, according to an overall NRI of 3.27% (p=0.2401), overall IDI of 3.27% (p=0.2414), and a higher AUC (0.848 vs 0.831).
CONCLUSIONS: NAR can serve as an independent predictor in AIS patients with anterior LVO, and the nomogram incorporating NAR and rLMC is reliable in predicting unfavorable outcome. Further studies with larger sample sizes are needed to validate and extend these findings.

Elevated neutrophil counts and decreased albumin levels have been linked to an unfavorable prognosis in acute cerebral infarction (ACI). The objective of this study is to explore the correlation between the neutrophil-to-albumin ratio (NAR) and the early neurological improvement (ENI) of ACI patients following intravenous thrombolysis (IVT). ACI patients who underwent IVT between June 2019 and June 2023 were enrolled. The severity of ACI was assessed using the National Institutes of Health Stroke Scale (NIHSS). ENI was defined as a reduction in NIHSS score of ≥ 4 or complete resolution of neurological deficit within 24 h after IVT. Propensity score match (PSM) and logistic regression analysis were used to explore the correlation between these variables and the early neurological outcomes of patients. A total of 545 ACI patients were included, with 253 (46.4 %) experiencing ENI. Among the 193 pairs of patients after PSM, there was a significant association between NAR and ENI (OR, 0.89; 95 % CI, 0.85-0.94; p < 0.001). The restricted cubic splines analysis revealed a significant nonlinear correlation between NAR and ENI (p for nonlinear = 0.0004; p for overall = 0.0002). The optimal cutoff for predicting ENI was determined as a NAR level of 10.20, with sensitivity and specificity values of 73.6 % and 60.9 %. NAR levels are associated with ENI in ACI patients after IVT. The decreased levels of NAR indicate an increased likelihood of post-thrombolysis ENI in ACI patients.

BACKGROUND: Neutrophil-To-Albumin Ratio (NAR) is a novel inflammatory biomarker. However, the potential prognostic value of NAR in acute ischemic stroke (AIS) remains unclear. This study aimed to evaluate whether NAR levels correlated with the 3-month modified Rankin scale (mRS) in patients with AIS.
METHODS: AIS patients were included in this retrospective study. NAR was calculated as the ratio of absolute neutrophil count to serum albumin level. Logistic regression analyses were used to investigate the effect of NAR on 3-month mRS of AIS. The predictive values of NAR, albumin level, and neutrophil count were compared utilizing receiver operating characteristic (ROC) curves. Moreover, subgroup analyses and interaction tests were conducted to evaluate the consistency of NAR\'s effect on AIS prognosis.
RESULTS: Of the 780 patients included, 403 (51.67%) had a poor clinical outcome (mRS 3-6) at 3 months. NAR was independently correlated to 3-month poor functional outcome after adjusting for confounders (Odds ratios (OR), 9.34; 95% confidence intervals (CI), 1.09 to 80.13; p =0.0417). Subgroup analysis showed a relative effect consistent with the overall population results, and no statistical interactions were found in the subgroups (all p for interaction > 0.05). The ROC curve showed that the prognosis-related cutoff value for NAR was 0.123, with corresponding specificity and sensitivity of 53.55% and 63.94%, respectively. When comparing the predictive power, NAR (0.590; 95%CI 0.549-0.630) exhibited the highest area under the curve (AUC) of ROC compared to neutrophils (0.584; 95%CI 0.543-0.624) and albumin (0.540; 95%CI 0.500-0.581).
CONCLUSIONS: There is a positive relationship between NAR levels and 3-month poor functional outcomes in AIS patients, supporting the potential of NAR as a readily available and economic serum biomarker for the early identification of AIS prognosis. Further studies are required to validate the prognostic value and clinical utility of the NAR.

The C-reactive protein-to-albumin ratio (CAR) and neutrophil-to-albumin ratio (NAR) serve as established markers for inflammatory diseases. However, limited studies have investigated their potential in predicting response and prognosis following infliximab (IFX) treatment. The objective of this paper was to evaluate feasibility of CAR and NAR as biomarkers to assess response to IFX induction therapy. Additionally, we attempted to determine the capacity to predict clinical remission in ulcerative colitis (UC) after 54 weeks of IFX treatment. We enrolled a total of 157 UC patients diagnosed via endoscopic mucosal biopsy at our hospital between October 2018 and June 2023. Additionally, 199 patients presenting with gastrointestinal symptoms, who underwent physical examinations, constituted the control group. Comprehensive clinical data, laboratory indicators, and endoscopic findings were systematically collected. CAR and NAR values were computed before treatment, post-induction, and subsequently at 8-week intervals. Comparisons between two groups were analyzed using the Wilcoxon rank-sum test or the independent samples t-test, and comparisons between multiple groups were analyzed using the one-way ANOVA (analysis of variance) or the Kruskal-Wallis rank sum test. We found CAR and NAR emerged as sensitive biomarkers for assessing disease activity. Notably, our findings indicated their dual predictive capability: foreseeing response post-IFX induction therapy and prognosticating the likelihood of UC patients achieving clinical remission following 54 weeks on IFX therapy.

OBJECTIVE: The practicality and effectiveness of using the prognostic value of the neutrophil-to-albumin ratio (NAR) in evaluating patients with cancer remain unclear, and research is needed to fully understand its potential application in the cancer population.
METHODS: The Kaplan-Meier method was used for survival analysis, and the log-rank test was employed for comparison. Univariate and multivariate Cox proportional hazards models were used to determine the prognostic biomarkers, and Logistic regression analysis was conducted to investigate the relationship between NAR and 90-day outcomes and cachexia.
RESULTS: The study included 14 682 patients with cancer, divided into discovery (6592 patients), internal validation (2820 patients), and external validation groups (5270 patients). Patients with high NAR had higher all-cause mortality than those with low NAR in the discovery (50.15% versus 69.29%, P < 0.001), internal validation (54.18% versus 70.91%, P < 0.001), and external validation cohorts (40.60% versus 66.68%, P < 0.001). In the discovery cohort, high NAR was observed to be independently associated with all-cause mortality in patients (HR 1.16, 95% CI 1.12-1.19; P < 0.001). Moreover, we validated the promising prognostic value of NAR as a predictor of survival in patients with cancer through internal validation (HR 1.21, 95% CI 1.16-1.27, P < 0.001) and external validation cohorts (HR 1.27, 95% CI 1.21-1.34, P < 0.001). Additionally, in the subgroup analysis by tumor type, high NAR was identified as a risk factor for most cancers, except for breast cancer.
CONCLUSIONS: This study showed that NAR is a feasible and promising biomarker for predicting prognosis and cancer cachexia in cancer patients.

We aimed to evaluate the prognostic significance of preoperative neutrophil-to-albumin ratio (NAR) in oral squamous cell carcinoma (OSCC).
A total of 622 patients with surgically treated OSCC were enrolled. NAR was defined as the absolute neutrophil count divided by the serum albumin level in peripheral blood before the radical surgery. Cox proportional hazards model were used to discover survival outcome-associated factors.
The optimal cut-off of NAR to predict overall survival (OS) was determined to be 0.1. In Cox model, high NAR was identified as an independent negative prognosticator of OS, cancer-specific survival, and recurrence-free survival (adjusted hazard ratio: 1.503, 1.958, and 1.727, respectively; all p < 0.05). The NAR-based nomogram accurately predicted OS (concordance index: 0.750).
Our study suggests that preoperative NAR is a convenient and effective prognostic marker for OSCC and NAR-based nomogram can be a promising prognostic tool in clinical setting.

UNASSIGNED: Many peripheral inflammatory markers were reported to be associated with the prognosis of aneurysmal subarachnoid hemorrhage (aSAH). We aimed to identify the most promising inflammatory factor that can improve existing predictive models.
UNASSIGNED: The study was based on data from a 10 year retrospective cohort study at Sichuan University West China Hospital. We selected the well-known SAFIRE and Subarachnoid Hemorrhage International Trialists\' (SAHIT) models as the basic models. We compared the performance of the models after including the inflammatory markers and that of the original models. The developed models were internally and temporally validated.
UNASSIGNED: A total of 3,173 patients were included in this study, divided into the derivation cohort (n = 2,525) and the validation cohort (n = 648). Most inflammatory markers could improve the SAH model for mortality prediction in patients with aSAH, and the neutrophil-to-albumin ratio (NAR) performed best among all the included inflammatory markers. By incorporating NAR, the modified SAFIRE and SAHIT models improved the area under the receiver operator characteristics curve (SAFIRE+NAR vs. SAFIRE: 0.794 vs. 0.778, p = 0.012; SAHIT+NAR vs. SAHIT: 0.831 vs. 0.819, p = 0.016) and categorical net reclassification improvement (SAFIRE+NAR: 0.0727, p = 0.002; SAHIT+NAR: 0.0810, p < 0.001).
UNASSIGNED: This study illustrated that among the inflammatory markers associated with aSAH prognosis, NAR could improve the SAFIRE and SAHIT models for 3 month mortality of aSAH.

UNASSIGNED: Ulcerative colitis (UC) is characterized by refractory and recurrent mucosal inflammation, leading to a substantial healthcare burden. Diagnostic biomarkers predicting disease activity and treatment response remain elusive. To evaluate the application value of a novel neutrophil-based index (the neutrophil-to-albumin ratio, NAR) as a novel diagnostic biomarker in patients with UC and a predictive marker for disease activity and response to infliximab (IFX) therapy.
UNASSIGNED: Clinical characteristics and laboratory parameters of enrolled subjects (patients with UC and healthy controls) were retrieved from the electronic medical record database of our hospital. Serum cytokine and fecal calprotectin levels were measured by enzyme-linked immunosorbent assay (ELISA). Mucosal expression levels of inflammatory agents were measured by quantitative RT-PCR (qRT-PCR).
UNASSIGNED: We found that NAR, which had not yet been explored in UC, was significantly increased in patients with UC (n = 146) compared to that in controls (n = 133) (1.95 ± 0.41 vs. 1.41 ± 0.23, p < 0.0001). NAR showed a positive association with the disease activity and inflammatory load in patients with UC. Pre-treatment NAR was significantly lower in IFX responders than that in non-responders (2.18 ± 0.29 vs. 2.44 ± 0.21, p = 0.0118), showing a significant ability to discriminate initial responders from primary non-responders to IFX induction therapy (AUC = 0.7866, p = 0.0076). Moreover, pre-treatment NAR predicted postinduction serum IFX trough level.
UNASSIGNED: Our study provides evidences to utilize NAR in the diagnosis, activity monitoring, and IFX response prediction in patients with UC.