Unveiling the Aggressiveness of Cholesteatoma: Associating MERI with miRNA-21 & IL-6 Expression.

BACKGROUND: Cholesteatoma, a destructive middle ear condition, poses challenges due to its variable clinical presentation and propensity for recurrence. Understanding its molecular underpinnings could enhance prognostication and guide therapeutic interventions. This study investigates the association between cholesteatoma aggressiveness, as assessed by the Middle Ear Risk Index (MERI), and the expression of miRNA-21 and IL-6 genes. METHODS: A cross-sectional observational study involving 30 patients with cholesteatoma undergoing tympanomastoid exploration was conducted. MERI scores were calculated preoperatively, and cholesteatoma tissue was analyzed for miRNA-21 and IL-6 gene expression using RT-PCR. Statistical analysis was performed to correlate MERI scores with gene expression levels. RESULTS: The majority (80%) of patients exhibited severe MERI scores, correlating with extensive middle ear pathology and necessitating canal wall-down (CWD) mastoidectomy. Higher miRNA-21 and IL-6 gene expression levels were observed in cholesteatoma tissues, indicating local aggressiveness and inflammatory activity. Significant moderate correlations were found between MERI scores and miRNA-21 (Pearson correlation = 0.579, p = 0.001) and IL-6 gene expression (Pearson correlation = 0.388, p = 0.034). Patients with severe MERI scores had elevated miRNA-21 and IL-6 levels, suggesting a more aggressive disease phenotype. CONCLUSION: MERI scores demonstrated utility in predicting cholesteatoma aggressiveness, with higher scores correlating with elevated miRNA-21 and IL-6 expression. These findings suggest a potential role for MERI in guiding surgical decision-making and prognostication. Future research on targeted therapies based on molecular mechanisms holds promise for improving cholesteatoma management. LEVEL OF EVIDENCE: 3 Laryngoscope, 2024.

Evaluating the Impact of Nutritional Risk on Stress-Induced Hyperglycemia and Trauma Patient Outcomes.

INTRODUCTION: Stress-induced hyperglycemia (SIH) and malnutrition are common in trauma patients and are linked to worse outcomes. This study examined the influence of nutritional status, determined by the Geriatric Nutritional Risk Index (GNRI), on the incidence of SIH in trauma patients. METHODS: A retrospective analysis was conducted on adult trauma patients admitted to a Level I trauma center from 1 January 2009 to December 31, 2021. Patients were categorized into four groups: SIH, diabetic hyperglycemia (DH), diabetic normoglycemia (DN), and non-diabetic normoglycemia (NDN). Nutritional status was assessed using GNRI: high risk (GNRI < 82), moderate risk (82 ≤ GNRI < 92), low risk (92 ≤ GNRI ≤ 98), and no risk (GNRI > 98). Incidence of SIH and outcomes were analyzed across GNRI groups. RESULTS: SIH was associated with higher mortality across all GNRI groups compared to NDN, with the highest rate (45.7%) in the high-risk group. Mortality decreased as GNRI increased in all glucose groups. NDN patients had the lowest mortality rates across GNRI groups. There was no correlation between GNRI and SIH incidence (p = 0.259). CONCLUSION: SIH significantly influenced mortality across all nutritional status groups, with the highest impact in malnourished patients. Although malnutrition did not affect SIH incidence, both SIH and poor nutritional status independently contributed to worse trauma outcomes. Targeted management of hyperglycemia and nutritional deficiencies is crucial for improving survival.

Geriatric nutritional risk index predicts postoperative delirium in elderly: A meta-analysis.

OBJECTIVES: To review current evidence on using the geriatric nutritional risk index (GNRI) in predicting postoperative delirium (POD) in elderly patients. METHODS: The literature search was performed in core databases to include all the cohort studies on the association between GNRI and risk of POD for further meta-analysis. RESULTS: A total of 6 studies with 4242 patients underwent this meta-analysis, which showed that the risk of POD was higher in patients with moderate and high GNRI than the ones with low GNRI (odds ratio [OR]=2.04, 95% confidence interval [CI] [1.58, 2.64], p<0.001), and moderate and high GNRI significantly increased the risk of POD in patients of 60 to 75 years or above [OR=1.98, 95%CI (1.49, 2.62), p<0.001; OR=2.79, 95%CI (1.38, 5.64), p=0.004, respectively]. CONCLUSION: Therefore, moderate and high GNRI increased the risk of POD in elderly patients.

Multi-model transfer function approach tuned by PSO for predicting stock market implied volatility explained by uncertainty indexes.

This paper studies the forecasting power of uncertainty emanating from the commodities market, energy market, economic policy, and geopolitical threats to the CBOE Volatility Index (VIX). In this study, the relationship between the various uncertainty metrics throughout the period 2012-2022, using a multi-model transfer function technique optimized by particle swarm optimization (PSO) is estimated. Furthermore, we utilize PSO for parameter optimization within the multi-model framework, improving model performance and convergence speed. According to empirical findings, the CBOE Volatility Index reacts nonlinearly to the uncertainty indices. Specifically, the conclusions of the performance metrics show that the OVX index (MAPE: 4.1559%; RMSE: 1.0476% and W: 96.74%) outperforms the geopolitical risk index, the Bloomberg energy index, and the economic policy uncertainty index in predicting the volatility of the US equities market. Although individual models have generated respectful performance, results from the aggregate simulation show that when all predictors are combined, they simultaneously provide better performance indicators (MAVE: 2.7511 %; RMSE: 0.7361%; R2: 98.93%) than when they are estimated separately. In addition, results provide evidence that, when considering non-linear patterns in the data, the multi-model transfer function technique calibrated using PSO demonstrates its outperformance over autoregressive baseline models, traditional econometric models, and deep learning techniques. The effectiveness and accuracy of the multi-model transfer function method tuned by PSO as a forecasting tool are confirmed by the convergence analysis of the cost function. Our methodology innovates by employing a multi-model transfer function technique, which captures the complex and nonlinear relationships between uncertainty indicators and the VIX more comprehensively than traditional single-model approaches. These results are important for traders in terms of hedging as well as portfolio diversification by investing in defensive equities and for policymakers in terms of reliability and preciseness of volatility forecasts.

Microplastics abundance and potential ecological risk assessment in sediment, water and fish of Deepor Beel-a Ramsar Wetland of the Brahmaputra plain, India.

Microplastics (MPs) are increasingly recognized as environmental contaminants with complex impacts on fish and other aquatic organisms. This study determined the microplastics abundance and the induced-ecological risks of microplastics in water, sediment, and commonly harvested fishes of a Ramsar site, Deepor Beel of Assam, India. Six samples of water and sediment were collected with nine individuals of two commonly harvested fish species Puntius sophore (Pool Barb) and Gudusia chapra (Indian River Shad). The abundance of microplastics in water and sediments were analyzed through organic matter digestion using hydrogen peroxide (H2O2, 30%) and sodium chloride (NaCl) for density separation. Potassium hydroxide (KOH, 10%) was used for digestion of fish gut. The microplastics were identified visually and chemically characterized through micro-Raman spectroscopy. Total 467 microplastic particles in water and sediment, and 62 particles in fish were identified. An average concentration of 0.55 ± 0.06 particles/L in water, 4.03 ± 0.41 particles/100 g in sediment samples, 3.83 ± 2.26 particles/individual in Puntius sophore, and 6.5 ± 3.40 particles/individual in Gudusia chapra were detected. Fibers accounted to the major shape of microplastic in water (54%) and sediment (50%), whereas fragments (65%) were the major shapes detected in both fishes. The color composition includes blue, black, red, green, brown, yellow, and transparent. Fiber particles size ranged between 150 and 1782 µm, fragments within 85-325 µm, and sphere within 85-220 µm. Chemical characterization of microplastics revealed polymer types including polypropylene (PP = 27%), polyvinyl chloride (PVC = 25%), acrylonitrile-butadiene-styrene (ABS = 18%), polycarbonate (PC = 13%), polyethylene (12%), and polystyrene (PS = 5%). PHI levels were at hazard level III and V for water and sediment samples and at level IV for both fish species. The PLI at hazard level I indicated low pollution levels, whereas the PERI were within danger and extreme danger levels. This study is the first report in abundances of microplastics and the ecological risk assessment of microplastics in surface waters, sediments and fishes of Deepor Beel wetland.

Machine learning-driven assessment of heavy metal contamination in the impounded lakes of China's South-to-North Water Diversion Project: Identifying spatiotemporal patterns and ecological risks.

The Eastern Route of China's South-to-North Water Diversion Project (SNWDP-ER) traverses through impounded lakes that are potentially vulnerable to heavy metals (HMs) contamination although the understanding remains elusive. This study employed machine learning approaches, including super-clustering of Self-Organizing Map (SOM) and Robust Principal Component Analysis (RPCA), to elucidate the spatiotemporal patterns and assess ecological risks associated with HMs in the surface sediments of Gao-Bao-Shaobo Lake (GBSL) and Dongping Lake (DPL). We collected 184 surface sediments from 47 stations across the two important impounded lakes over four seasons. The results revealed higher HMs concentrations in the south-central GBSL and west-central DPL, with a notable increase in contamination in autumn. The comprehensive risk assessment, utilizing various indicators such as the Sediment Quality Guidelines (SQGs), Improved Potential Ecological Risk Index (IPERI), Geo-accumulation Index (Igeo), Contamination Factor (CF), and Enrichment Factor (EF), identified arsenic (As), cadmium (Cd), nickel (Ni), and chromium (Cr) as primary contaminants of concern. Positive Matrix Factorization (PMF) model, coupled with Spearman analysis, attributed over 70 % of HMs pollution to anthropogenic activities. This research provides a nuanced understanding of HMs pollution in the context of large-scale water diversion projects and offers a scientific basis for targeted pollution mitigation strategies.

Prognostic value of the geriatric nutritional risk index in patients with non-metastatic clear cell renal cell carcinoma: a propensity score matching analysis.

BACKGROUND: This study aimed to investigate the prognostic value of the geriatric nutritional risk index (GNRI) in patients with non-metastatic clear cell renal cell carcinoma (ccRCC) who underwent nephrectomy. METHODS: Patients with non-metastatic ccRCC who underwent nephrectomy between 2013 and 2021 were analyzed retrospectively. The GNRI was calculated within one week before surgery. The optimal cut-off value of GNRI was determined using X-tile software, and the patients were divided into a low GNRI group and a high GNRI group. The Kaplan-Meier method was used to compare the overall survival (OS), cancer-specific survival (CSS) and recurrence-free survival (RFS) between the two groups. Univariate and multivariate Cox proportional hazard models were used to determine prognostic factors. In addition, propensity score matching (PSM) was performed with a matching ratio of 1:3 to minimize the influence of confounding factors. Variables entered into the PSM model were as follows: sex, age, history of hypertension, history of diabetes, smoking history, BMI, tumor sidedness, pT stage, Fuhrman grade, surgical method, surgical approach, and tumor size. RESULTS: A total of 645 patients were included in the final analysis, with a median follow-up period of 37 months (range: 1-112 months). The optimal cut-off value of GNRI was 98, based on which patients were divided into two groups: a low GNRI group (≤ 98) and a high GNRI group (> 98). Kaplan-Meier analysis showed that OS (P < 0.001), CSS (P < 0.001) and RFS (P < 0.001) in the low GNRI group were significantly worse than those in the high GNRI group. Univariate and multivariate Cox analysis showed that GNRI was an independent prognostic factor of OS, CSS and RFS. Even after PSM, OS (P < 0.05), CSS (P < 0.05) and RFS (P < 0.05) in the low GNRI group were still worse than those in the high GNRI group. In addition, we observed that a low GNRI was associated with poor clinical outcomes in elderly subgroup (> 65) and young subgroup (≤ 65), as well as in patients with early (pT1-T2) and low-grade (Fuhrman I-II) ccRCC. CONCLUSION: As a simple and practical tool for nutrition screening, the preoperative GNRI can be used as an independent prognostic indicator for postoperative patients with non-metastatic ccRCC. However, larger prospective studies are necessary to validate these findings.

Management Architecture With Multi-modal Ensemble AI Models for Worker Safety.

Introduction: Following the Republic of Korea electric power industry site-specific safety management system, this paper proposes a novel safety autonomous platform (SAP) architecture that can automatically and precisely manage on-site safety through ensemble artificial intelligence (AI) models. The ensemble AI model was generated from video information and worker's biometric information as learning data and the estimation results of this model are based on standard operating procedures of the workplace and safety rules. Methods: The ensemble AI model is designed and implemented by the Hadoop ecosystem with Kafka/NiFi, Spark/Hive, HUE, and ELK (Elasticsearch, Logstash, Kibana). Results: The functional evaluation shows that the main function of this SAP architecture was operated successfully. Discussion: The proposed model is confirmed to work well with safety mobility gateways to provide some safety applications.

Serum Albumin as a Prognostic Biomarker for Febrile Neutropenia Outcome and Complications: A Prospective Observational Trial.

Background: Febrile neutropenia (FN) poses a significant challenge in cancer treatment, with a high incidence among patients undergoing standard therapies. Predicting FN complications and outcomes remains crucial for improving patient management strategies. Biomarkers, including procalcitonin and albumin, have garnered attention for their potential prognostic value in FN. Methods: We conducted a prospective observational study at a tertiary hospital, enrolling 185 adult cancer patients experiencing FN episodes. We assessed serum albumin levels and incorporated them into the Multinational Association for Supportive Care in Cancer (MASCC) risk index to enhance risk stratification. Results: Serum albumin levels displayed promising prognostic utility in febrile neutropenia (FN). They exhibited moderate specificity and sensitivity in predicting mortality during FN and 28-day mortality. Serum albumin levels were significantly associated with gastrointestinal infections, serving as an independent predictor. Integrating serum albumin into the MASCC risk index improved predictive accuracy for FN mortality by 50%, 28-day mortality by 66.67%, and respiratory tract infections by 62.50%, enhancing in this way risk stratification for FN-related complications. Conclusion: Serum albumin emerges as a promising biomarker for prognostication in FN, complementing existing risk assessment frameworks. Its incorporation into the MASCC risk index enhances predictive capabilities, aiding clinicians in identifying high-risk patients promptly. While albumin shows potential in predicting mortality and complications, further research is warranted to optimize sensitivity and specificity, ensuring its clinical utility.

Association between geriatric nutritional risk index and cognitive function in older adults with/without chronic kidney disease.

BACKGROUND: Cognitive impairment is highly prevalent among patients with chronic kidney disease, who face an increased risk of cognitive decline. The aim of this study was to investigate the relationship between the Geriatric Nutritional Risk Index (GNRI) and cognitive function in older individuals, both with and without chronic kidney disease (CKD). METHODS: In this study, we analyzed data from 2728 participants in the 2011-2014 National Health and Nutrition Examination Survey (NHANES). Cognitive function was measured using the Consortium to Establish a Registry for the Alzheimer's Disease Word Learning subtest (CERAD W-L), the animal fluency test (AFT), the digit symbol substitution test (DSST), and the global cognitive z-score. The GNRI, representing whole-body nutritional status, was calculated based on serum albumin, body weight, and ideal body weight. We employed weighted multiple linear regression analyses and subgroup analyses to assess the independent association of GNRI with cognitive function in CKD and non-CKD populations. Smoothing techniques were used to fit curves, and interaction tests were used to assess the robustness and specificity of the findings. RESULTS: Our analyses revealed a significant positive association between higher GNRI levels and cognitive function in the older US population (for global z-score: ß = 0.01; 95% confidence interval [CI] = 0.00, 0.01). This association remained consistent across various subgroup analyses, including those for different gender groups, age groups, smoking statuses, diabetes statuses, hypertension statuses, individuals with a BMI below 25, individuals who consumed alcohol, and non-Hispanic white individuals. Smoothed curve-fitting analyses indicated that the GNRI was linearly related to cognitive function. No statistically significant interactions were detected among these variables. CONCLUSION: Our findings emphasize the positive association between GNRI and cognitive health in individuals with or without CKD, especially when combined with other risk factors. Consequently, enhancing the nutritional status of the elderly may serve as a viable strategy to thwart the onset of cognitive decline.

Evaluating ecological risks and metal bioavailability in post-dredging sediments of a wetland affected by artisanal gold mining.

The evaluation of metal contamination, ecological risk, bioavailability, and the environmental dredging depth in sediments of two Colombian riverine systems impacted by artisanal and small-scale gold mining (ASGM) and agricultural activities, was conducted following dredging processes. Results indicated significant contamination by Cd and Pb before dredging, based on the contamination factor (CF) and the geoaccumulation index (Igeo). Additionally, Cu and Hg were found to cause adverse biological effects according to sediment quality guidelines. Post-dredging, surface sediments exhibited a moderate ecological risk index (RI, 150-300), primarily due to increased contamination by Hg, Pb, and Cd. To mitigate this ecological risk (RI < 150), the environmental dredging depth needed to exceed 20 cm for all metals. On average, the bioavailable fraction increased 2.3 times within two months after dredging. However, the low environmental risk (%F1 = 1-10) calculated using risk assessment codes (RAC) indicates a potential risk due to metals entering the water column and bioaccumulating in organisms. These findings provide insights into the dynamics of metals and the impact of dredging activities on sediments in the Colombian Caribbean coast affected by various anthropogenic activities. The research underscores the importance of integrating sustainable practices in mining and agriculture to protect the ecological integrity of these riverine systems.

Landscape transition-induced ecological risk modeling using GIS and remote sensing techniques: a case of Saint Martin Island, Bangladesh.

Uncontrolled human activity and nature are causing the deterioration of Saint Martin Island, Bangladesh's only tropical island, necessitating sustainable land use strategies and ecological practices. Therefore, the present study measures the land use/cover transition from 1974 to 2021, predicts 2032 and 2042, and constructs the spatiotemporal features of the Landscape Ecological Risk Index based on land use changes. The study utilized Maximum Likelihood Classification (MLC) on Landsat images from 1974, 1988, 2001, 2013, and Sentinel 2B in 2021, achieving ≥ 80% accuracy. The MLP-MC approach was also used to predict 2032 and 2042 LULC change patterns. The eco-risk index was developed using landscape disturbance and vulnerability indices, Bayesian Kriging interpolation, and spatial autocorrelations to indicate spatial clustering. The research found that settlements increased from 2.06 to 28.62 ha between 1974 and 2021 and would cover 41.22 ha in 2042, causing considerable losses in agricultural areas, waterbodies, sand, coral reefs, and vegetation. The area under study showed a more uniform and homogenous environment as Shannon's diversity and evenness scores decreased. The ecological risk of Saint Martin Island increased from 4.31 to 31.05 ha between 1974 and 2042 due to natural and human factors like erosion, tidal bores, population growth, coral mining, habitat destruction, and intensive agricultural practices and tourism, primarily in Nazrul Para, Galachipa, and Western Dakhin Para. The findings will benefit St. Martin Island stakeholders and policymakers by providing insights into current and potential landscape changes and land eco-management.

The relationship between Geriatric Nutritional Risk Index (GNRI) and in-hospital mortality in critically ill patients with Acute Kidney Injury (AKI).

BACKGROUND: The role of the geriatric nutritional risk index (GNRI) as a prognostic factor in intensive care unit (ICU) patients with acute kidney injury (AKI) remains uncertain. OBJECTIVES: The aim of this study was to investigate the impact of the GNRI on mortality outcomes in critically ill patients with AKI. METHODS: For this retrospective study, we included 12,058 patients who were diagnosed with AKI based on ICD-9 codes from the eICU Collaborative Research Database. Based on the values of GNRI, nutrition-related risks were categorized into four groups: major risk (GNRI < 82), moderate risk (82 ≤ GNRI < 92), low risk (92 ≤ GNRI < 98), and no risk (GNRI ≥ 98). Multivariate analysis was used to evaluate the relationship between GNRI and outcomes. RESULTS: Patients with higher nutrition-related risk tended to be older, female, had lower blood pressure, lower body mass index, and more comorbidities. Multivariate analysis showed GNRI scores were associated with in-hospital mortality. (Major risk vs. No risk: OR, 95% CI: 1.90, 1.54-2.33, P < 0.001, P for trend < 0.001). Moreover, increased nutrition-related risk was negatively associated with the length of hospital stay (Coefficient: -0.033; P < 0.001) and the length of ICU stay (Coefficient: -0.108; P < 0.001). The association between GNRI scores and the risks of in-hospital mortality was consistent in all subgroups. CONCLUSIONS: GNRI serves as a significant nutrition assessment tool that is pivotal to predicting the prognosis of critically ill patients with AKI.

Spatiotemporal characterization of heatwave exposure across historically vulnerable communities.

Heatwaves pose a serious threat and are projected to amplify with changing climate and social demographics. A comprehensive understanding of heatwave exposure to the communities is imperative for the development of effective strategies and mitigation plans. This study explores spatiotemporal characterization of heatwaves across the historically vulnerable communities in Mississippi, United States. We derive multiple heatwave metrics including frequency, duration, and magnitude based on temperature data for urban-specific daytime, nighttime, and day-night combined conditions. Our analysis depicts a rising heatwave trend across all counties, with the most extreme shifts observed in prolonged day-night events lacking overnight relief. We integrate physical heatwave hazards with a socioeconomic vulnerability index to develop an integrated urban heatwave risk index. Integrated metric identifies the counties in northwest Mississippi as heat-prone areas, exhibiting an urgent need to prioritize heat resilience and adaptive strategies in these regions. The compounding urban heatwave and vulnerability risks in these communities highlights an environmental justice imperative to implement equitable policies that protect disadvantaged populations. Although this study is focused on Mississippi, our framework is scalable and can be employed to urban regions globally. This study provides a solid foundation for developing timely heatwave preparedness and mitigation to avert preventable heat-related tragedies as extremes intensify with climate change.

Microplastics in commercial bivalves from coastal areas of Thailand and health risk associated with microplastics in ingested bivalves.

Microplastics (MPs) contamination in marine organisms is a significant threat to seafood consumers worldwide. This study is the first to investigate the abundance of MPs in the commercial bivalves from six sites along Thailand's coastline, the daily exposure of bivalve consumers to MPs, and potential associated health risks. The microplastic occurrence varied from 69 % to 93 % in four bivalve species while the average abundance of MPs was 1.87 ± 0.86 items/individual or 0.46 ± 0.43 items/g ww. Benthic bivalves (cockles and clams) contained more MPs than their pelagic counterparts (mussels and oysters). Small blue microfibers (<500 µm) were the most abundant. The most common polymers were natural based polymers (cotton and rayon) and polyethylene terephthalate (PET). The daily microplastic exposure for consumers was 0.52 items/person. Although the risk of microplastic contamination is low, we recommend investigation into the transfer of MPs within the food web, notably as it may pose significant human health concerns.

Geriatric nutritional risk index and quality of life among elderly hemodialysis patients: a cross-sectional study.

Background: Nutritional problems are considered one of the main complications of hemodialysis, and the geriatric nutritional risk index (GNRI) is a new instrument for assessing geriatric nutritional status. The present study sought to evaluate the relationship between the GNRI and quality of life (QOL) among elderly hemodialysis patients. Methods: In the present analytical cross-sectional study, 110 hemodialysis individuals were selected by applying a simple random sampling method, among whom 57 and 53 were males and females, respectively (mean: 70.3±6.93 years). Demographic characteristics, GNRI, and QOL status were determined. The data were analyzed using SPSS 20 software and descriptive statistics, Pearson's correlation, ANOVA, independent sample t-tests, and multiple linear regression analysis. Results: The mean GNRI and mean total QOL were respectively obtained 93.903±11.067 and 20.95 ± 4.89. Among females, a significant direct relationship was observed between GNRI and total QOL (P = 0.010, r = 0.352), autonomy (P = 0.004, r = 0.389), and pleasure (P = 0.015, r = 0.333), while GNRI was not directly and significantly related to QOL in males (P = 0.161, r = 0.188). Conclusion: Due to the presence of a significant association between Geriatric GNRI and QOL among elderly hemodialysis patients, particularly among females, highlighting the importance of addressing nutritional status in optimizing well-being.

The Geriatric Nutritional Risk Index as a prognostic factor in patients treated with immune checkpoint inhibitors with non-small-cell lung cancer.

Background: Globally, non-small cell lung cancer (NSCLC) is a leading factor in cancer-related mortality. Additionally, the Geriatric Nutritional Risk Index (GNRI) has been assessed as a predictive and prognostic indicator in various types of carcinomas. Our study aims to assess the prognostic importance of GNRI computed at diagnosis in NSCLC patients receiving immune checkpoint inhibitors (ICIs). Methods: The study evaluated 148 patients who underwent immunotherapy for NSCLC from January 1, 2018, through December 31, 2021, retrospectively. Patients combined with other malignant tumors or severe comorbidities were excluded from the study. The receiver operating characteristic (ROC) curve was employed in regulating the ideal cutoff worth of GNRI. Survival outcomes were evaluated through Kaplan-Meier analysis. Following this, both univariate and multivariate analyses were conducted utilizing Cox regression analysis to identify any potential factors that may influence the survival outcomes. Results: The cutoff point for GNRI was 108.15 [area under the curve (AUC) =0.575, P=0.048]. Further analysis using the Kaplan-Meier method demonstrated that individuals in the high GNRI group had significantly longer progression-free survival (PFS) and overall survival (OS) compared to those in the low GNRI group (P=0.02, P=0.01). The further stratified study showed that GNRI had greater predictive value in tumor node metastasis (TNM) stage II-III and elderly (age ≥65 years) NSCLC patients undergoing ICI therapy. The multivariate Cox regression analysis indicated that GNRI [hazard ratio (HR): 0.536, P=0.03], obesity (HR: 16.283, P<0.001), and surgical history (HR: 0.305, P<0.001) were associated with poorer survival rates. Conclusions: Among patients undergoing ICI therapy for NSCLC, GNRI is an effective independent prognostic indicator, and a high GNRI at diagnosis is substantially related with longer PFS and OS. The incorporation of GNRI in pre-treatment evaluations within clinical settings is beneficial.

Long-term agricultural reuse of treated wastewater and sewage sludge: developing a Time to Critical Content Index for metal species.

This study evaluates the sustainability of spreading wastewater or sewage sludge on agricultural land, balancing benefits with contamination risks. Conventional ecological risk indices often fail to address the long-term accumulation of metals in soils. We investigate the feasibility of spreading based on current knowledge of potentially contaminating metals and their behavior in soil. We analyzed the speciation of metals (Ag, Cd, Co, Cr, Cu, Ni, Pb, Ti, Zn) through sequential extraction in sludge, treated wastewater, and soils after 14 years of application of sewage sludge and treated wastewater issued from an Algerian wastewater treatment plant. We introduce a Time to Critical Content Index (TCCI) that calculates the time required to reach critical levels of potentially mobile metals, considering total metal content and speciation. The TCCI takes into account product knowledge, soil characteristics, metal behavior, ecological/toxicological thresholds, and regulations. Applied to our case study, the TCCI indicates that spreading sewage sludge can continue despite metal contents exceeding regulatory ceiling values. The index serves as a precautionary measure, adaptable to evolving knowledge, providing a comprehensive framework for sustainable agricultural practices.

Geriatric Nutritional Risk Index and 30-Day Postoperative Mortality in Geriatric Burn Patients.

INTRODUCTION: The geriatric nutritional risk index (GNRI) can easily identify malnutrition-associated morbidity and mortality. We investigated the association between preoperative GNRI and 30-d mortality in geriatric burn patients who underwent surgery. METHODS: The study involved geriatric burn patients (aged ≥ 65 y) who underwent burn surgery between 2012 and 2022. The GNRI was computed using the following formula: 1.489 × serum albumin concentration (mg/L) + 41.7 × patient body weight/ideal body weight. Patients were dichotomized into the high GNRI (≥ 82) and low GNRI (< 82) groups. GNRI was evaluated as an independent predictor of 30-d postoperative mortality. The study also evaluated the association between GNRI and sepsis, the need for continuous renal replacement therapy (CRRT), major adverse cardiac events (MACE), and pneumonia. RESULTS: Out of 270 patients, 128 (47.4%) had low GNRI (< 82). Multivariate Cox regression analysis revealed that low GNRI was significantly associated with 30-d postoperative mortality (hazard ratio: 1.874, 95% confidence interval [CI]: 1.146-3.066, P = 0.001). Kaplan-Meier analysis revealed that the 30-day mortality rate differed significantly between the low and high GNRI groups (log-rank test, P < 0.001). The 30-d postoperative mortality (hazard ratio: 2.677, 95% CI: 1.536-4.667, P < 0.001) and the incidence of sepsis (odds ratio [OR]: 2.137, 95% CI: 1.307-3.494, P = 0.004), need for CRRT (OR: 1.919, 95% CI: 1.101-3.344, P = 0.025), MACE (OR: 1.680, 95% CI: 1.018-2.773, P = 0.043), and pneumonia (OR: 1.678, 95% CI: 1.019-2.764, P = 0.044), were significantly higher in the low GNRI group than in the high GNRI group. CONCLUSIONS: Preoperative low GNRI was associated with increased 30-d postoperative mortality, sepsis, need for CRRT, MACE, and pneumonia in geriatric burn patients.