Prognostic value of geriatric nutritional risk index in patients with stable coronary artery disease undergoing percutaneous coronary intervention.

BACKGROUND: Malnutrition increases the risk of poor prognosis in patients with cardiovascular disease, and our current research was designed to assess the predictive performance of the Geriatric Nutrition Risk Index (GNRI) for the occurrence of poor prognosis after percutaneous coronary intervention (PCI) in patients with stable coronary artery disease (SCAD) and to explore possible thresholds for nutritional intervention. METHODS: This study retrospectively enrolled newly diagnosed SCAD patients treated with elective PCI from 2014 to 2017 at Shinonoi General Hospital, with all-cause death as the main follow-up endpoint. Cox regression analysis and restricted cubic spline (RCS) regression analysis were used to explore the association of GNRI with all-cause death risk and its shape. Receiver operating characteristic curve (ROC) analysis and piecewise linear regression analysis were used to evaluate the predictive performance of GNRI level at admission on all-cause death in SCAD patients after PCI and to explore possible nutritional intervention threshold points. RESULTS: The incidence of all-cause death was 40.47/1000 person-years after a mean follow-up of 2.18 years for 204 subjects. Kaplan-Meier curves revealed that subjects at risk of malnutrition had a higher all-cause death risk. In multivariate Cox regression analysis, each unit increase in GNRI reduced the all-cause death risk by 14% (HR 0.86, 95% CI 0.77, 0.95), and subjects in the GNRI > 98 group had a significantly lower risk of death compared to those in the GNRI < 98 group (HR 0.04, 95% CI 0.00, 0.89). ROC analysis showed that the baseline GNRI had a very high predictive performance for all-cause death (AUC = 0.8844), and the predictive threshold was 98.62; additionally, in the RCS regression analysis and piecewise linear regression analysis we found that the threshold point for the GNRI-related all-cause death risk was 98.28 and the risk will be significantly reduced when the subjects' baseline GNRI was greater than 98.28. CONCLUSIONS: GNRI level at admission was an independent predictor of all-cause death in SCAD patients after PCI, and GNRI equal to 98.28 may be a useful threshold for nutritional intervention in SCAD patients treated with PCI.

A nomogram based on nutritional and inflammatory parameters to predict DMFS and identify beneficiaries of adjuvant chemotherapy in IVA-stage nasopharyngeal carcinoma.

OBJECTIVE: This study aims to develop a nomogram integrating inflammation (NLR), Prognostic Nutritional Index (PNI), and EBV DNA (tumor burden) to achieve personalized treatment and prediction for stage IVA NPC. Furthermore, it endeavors to pinpoint specific subgroups that may derive significant benefits from S-1 adjuvant chemotherapy. METHODS: A total of 834 patients diagnosed with stage IVA NPC were enrolled in this study and randomly allocated into training and validation cohorts. Multivariate Cox analyses were conducted to identify independent prognostic factors for constructing the nomogram. The predictive and clinical utility of the nomogram was assessed through measures including the AUC, calibration curve, DCA, and C-indexes. IPTW was employed to balance baseline characteristics across the population. Kaplan-Meier analysis and log-rank tests were utilized to evaluate the prognostic value. RESULTS: In our study, we examined the clinical features of 557 individuals from the training cohort and 277 from the validation cohort. The median follow-up period was 50.1 and 49.7 months, respectively. For the overall cohort, the median follow-up duration was 53.8 months. The training and validation sets showed 3-year OS rates of 87.7% and 82.5%, respectively. Meanwhile, the 3-year DMFS rates were 95.9% and 84.3%, respectively. We created a nomogram that combined PNI, NRI, and EBV DNA, resulting in high prediction accuracy. Risk stratification demonstrated substantial variations in DMFS and OS between the high and low risk groups. Patients in the high-risk group benefited significantly from the IC + CCRT + S-1 treatment. In contrast, IC + CCRT demonstrated non-inferior 3-year DMFS and OS compared to IC + CCRT + S-1 in the low-risk population, indicating the possibility of reducing treatment intensity. CONCLUSIONS: In conclusion, our nomogram integrating NLR, PNI, and EBV DNA offers precise prognostication for stage IVA NPC. S-1 adjuvant chemotherapy provides notable benefits for high-risk patients, while treatment intensity reduction may be feasible for low-risk individuals.

The Predictive Value of Geriatric Nutritional Risk Index Combined with the GRACE Score in Predicting the Risk of One Year Poor Prognosis in Elderly Patients with Non-ST Segment Elevation Myocardial Infarction After PCI.

Background: As a nutritional indicator, a lower level of geriatric nutritional risk index (GNRI) has been suggested as a predictor for poor prognosis in acute coronary syndrome (ACS). However, whether GNRI could improve the predictive value of the Global Registry of Acute Coronary Events (GRACE) score for the prognosis in elderly patients with non-ST segment elevation myocardial infarction (NSTEMI) after PCI remains unclear. Methods: A total of 446 elderly patients with NSTEMI after percutaneous coronary intervention (PCI) were consecutively enrolled. Patients were divided into major adverse cardiovascular and cerebrovascular events (MACCE) group and control group according to the occurrence of MACCE during one year follow up. The clinical parameters including GNRI were compared to investigate the predictors for MACCE. The performance after the addition of GNRI to the GRACE score for predicting MACCE was determined. Results: A total of 68 patients developed MACCE. In unadjusted analyses, the rate of MACCE was significantly higher in the 93.8

Standard Nutritional Assessment Tools Are Unable to Predict Loss of Muscle Mass in Patients Due to Undergo Pancreatico-Duodenectomy: Highlighting the Need for Detailed Nutritional Assessment.

BACKGROUND AND METHODS: Pancreatico-duodenectomy (PD) carries significant morbidity and mortality, with very few modifiable risk factors. Radiological evidence of sarcopenia is associated with poor outcomes. This retrospective study aimed to analyse the relationship between easy-to-use bedside nutritional assessment techniques and radiological markers of muscle loss to identify those patients most likely to benefit from prehabilitation. RESULTS: Data were available in 184 consecutive patients undergoing PD. Malnutrition was present in 33-71%, and 48% had a high visceral fat-to-skeletal muscle ratio, suggestive of sarcopenic obesity (SO). Surgical risk was higher in patients with obesity (OR 1.07, 95%CI 1.01-1.14, p = 0.031), and length of stay was 5 days longer in those with SO (p = 0.006). There was no correlation between skeletal muscle and malnutrition using percentage weight loss or the malnutrition universal screening tool (MUST), but a weak correlation between the highest hand grip strength (HGS; 0.468, p < 0.001) and the Global Leadership in Malnutrition (GLIM) criteria (-0.379, p < 0.001). CONCLUSIONS: Nutritional assessment tools give widely variable results. Further research is needed to identify patients at significant nutritional risk prior to PD. In the meantime, those with malnutrition (according to the GLIM criteria), obesity or low HGS should be referred to prehabilitation.

Managing Undernutrition in Pediatric Oncology: A Consensus Statement Developed Using the Delphi Method by the Polish Society for Clinical Nutrition of Children and the Polish Society of Pediatric Oncology and Hematology.

"Managing Undernutrition in Pediatric Oncology" is a collaborative consensus statement of the Polish Society for Clinical Nutrition of Children and the Polish Society of Pediatric Oncology and Hematology. The early identification and accurate management of malnutrition in children receiving anticancer treatment are crucial components to integrate into comprehensive medical care. Given the scarcity of high-quality literature on this topic, a consensus statement process was chosen over other approaches, such as guidelines, to provide comprehensive recommendations. Nevertheless, an extensive literature review using the PubMed database was conducted. The following terms, namely pediatric, childhood, cancer, pediatric oncology, malnutrition, undernutrition, refeeding syndrome, nutritional support, and nutrition, were used. The consensus was reached through the Delphi method. Comprehensive recommendations aim to identify malnutrition early in children with cancer and optimize nutritional interventions in this group. The statement underscores the importance of baseline and ongoing assessments of nutritional status and the identification of the risk factors for malnutrition development, and it presents tools that can be used to achieve these goals. This consensus statement establishes a standardized approach to nutritional support, aiming to optimize outcomes in pediatric cancer patients.

Development of the VEGANScreener, a Tool for a Quick Diet Quality Assessment among Vegans in Europe.

BACKGROUND: Plant-based diets are not inherently healthy. Similar to omnivorous diets, they may contain excessive amounts of sugar, sodium, and saturated fats, or lack diversity. Moreover, vegans might be at risk of inadequate intake of certain vitamins and minerals commonly found in foods that they avoid. We developed the VEGANScreener, a tool designed to assess the diet quality of vegans in Europe. METHODS: Our approach combined best practices in developing diet quality metrics with scale development approaches and involved the following: (a) narrative literature synthesis, (b) evidence evaluation by an international panel of experts, and (c) translation of evidence into a diet screener. We employed a modified Delphi technique to gather opinions from an international expert panel. RESULTS: Twenty-five experts in the fields of nutrition, epidemiology, preventive medicine, and diet assessment participated in the first round, and nineteen participated in the subsequent round. Initially, these experts provided feedback on a pool of 38 proposed items from the literature review. Consequently, 35 revised items, with 17 having multiple versions, were suggested for further consideration. In the second round, 29 items were retained, and any residual issues were addressed in the final consensus meeting. The ultimate screener draft encompassed 29 questions, with 17 focusing on foods and nutrients to promote, and 12 addressing foods and nutrients to limit. The screener contained 24 food-based and 5 nutrient-based questions. CONCLUSIONS: We elucidated the development process of the VEGANScreener, a novel diet quality screener for vegans. Future endeavors involve contrasting the VEGANScreener against benchmark diet assessment methodologies and nutritional biomarkers and testing its acceptance. Once validated, this instrument holds potential for deployment as a self-assessment application for vegans and as a preliminary dietary screening and counseling tool in healthcare settings.

Prognostic Nutritional Index and Instant Nutritional Assessement Are Associated with Clinical Outcomes in a Geriatric Cohort of Acutely Inpatients.

BACKGROUND: Among elderly inpatients, malnutrition is one of the most important predictive factors affecting length of stay (LOS), mortality, and risk of re-hospitalization. METHODS: We conducted an observational, retrospective study on a cohort of 2206 acutely inpatients. Serum albumin and lymphocytes were evaluated. Instant Nutritional Assessment (INA) and the Prognostic Nutritional Index (PNI) were calculated to predict in-hospital mortality, LOS, and risk of rehospitalization. RESULTS: An inverse relationship between LOS, serum albumin, and PNI were found. Deceased patients had lower albumin levels, lower PNI values, and third- and fourth-degree INA scores. An accurate predictor of mortality was PNI (AUC = 0.785) after ROC curve analysis; both lower PNI values (HR = 3.56) and third- and fourth-degree INA scores (HR = 3.12) could be independent risk factors for mortality during hospitalization after Cox regression analysis. Moreover, among 309 subjects with a lower PNI value or third- and fourth-class INA, hospitalization was re-hospitalization. CONCLUSIONS: PNI and INA are two simple and quick-to-calculate tools that can help in classifying the condition of hospitalized elderly patients also based on their nutritional status, or in assessing their mortality risk. A poor nutritional status at the time of discharge may represent an important risk factor for rehospitalization in the following thirty days. This study confirms the importance of evaluating nutritional status at the time of hospitalization, especially in older patients. This study also confirms the importance for adequate training of doctors and nurses regarding the importance of maintaining a good nutritional status as an integral part of the therapeutic process of hospitalization in acute departments.

Nutritional Prognosis of Patients Submitted to Radiotherapy and Its Implications in Treatment.

Oncological patients show intense catabolic activity, as well as a susceptibility to higher nutritional risk and clinical complications. Thus, tools are used for monitoring prognosis. Our objective was to analyze the nutrition prognosis of patients who underwent radiotherapy, correlating it with outcomes and complications. We performed a retrospective transversal study based on secondary data from hospital records of patients who started radiotherapy between July 2022 and July 2023. We established Prognostic Scores through a combination of Prognostic Nutritional Index (PNI) and a Subjective Global Assessment (SGA), assessed at the beginning and end of treatment. Score 3 patients, with PNI ≤ 45.56 and an SGA outcome of malnutrition, initially presented a higher occurrence of odynophagia, later also being indicative of reduced diet volume, treatment interruption, and dysphagia. SGA alone showed sensitivity to altered diet volume, dysphagia, and xerostomia in the second assessment. Besides this, PNI ≤ 45.56 also indicated the use of alternative feeding routes, treatment interruption, and hospital discharge with more complications. We conclude that the scores could be used to indicate complications; however, further studies on combined biomarkers are necessary.

Low prognostic nutrition index as a prognostic biomarker in elderly patients with early gastric cancer after gastrectomy.

Purpose Non-invasive biomarkers including systemic inflammatory or nutrition-based index including neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR) lymphocyte to monocyte ratio (LMR), and prognostic nutritional index (PNI) can be useful in determining treatment strategies for elderly patients with early gastric cancer (EGC). The aim of this study was to investigate the significance of these index for predicting the long-term survival of EGC patients aged 80 years over. Methods This study included 80 elderly EGC patients with pStageIA after gastrectomy. Optimal cutoff value for PNI, NLR, PLR and LMR were set by using receiver operating curve analysis. The long-term outcomes after gastrectomy were analyzed by univariate and multivariate Cox regression analyses. Results Cut-off value for PNI, NLR, PLR and LMR was set at 46.5, 2.8, 210 and 4.6, respectively. By univariate analyses, low PNI, high NLR, high PLR and low LMR were significantly associated with worse prognosis. By multivariate analysis, low PNI was confirmed as an independent prognostic factor after gastrectomy (HR 0.17 ; 95% CI 0.03-0.91 ; P = 0.04). 5-year overall survival rate of patients with low PNI (≤ 46.5) were 52.4%. Conclusion Low PNI might be useful biomarker to predict worse prognosis of elderly EGC patients after gastrectomy. J. Med. Invest. 71 : 113-120, February, 2024.

Investigation of the predictive value of systemic immune inflammation index (SII) and prognostic nutritional index (PNI) on mortality in patients with endoprosthesis after hip fracture.

In this research, we aimed to investigate the predictive value of the systemic immune inflammation index and prognostic nutritional index on mortality among patients with an endoprosthesis after a hip fracture. In this retrospective, cross-sectional study, a total of 915 patient files applied to our hospital between 2020 and 2023 with an endoprosthesis after a hip fracture were subjected to the study. The patients were divided into 2 groups: alive (n = 396; 43.3%) and deceased (n = 519; 56.7%). The eosinophil-to-lymphocyte ratio, hemoglobin-to-red cell distribution width ratio (HRR), mean platelet volume-to-platelet ratio (MPVPR), neutrophil-to-lymphocyte ratio, monocyte/lymphocyte ratio, platelet-to-lymphocyte ratio, MPV-to-lymphocyte ratio, monocyte-to-eosinophil ratio (MER), neutrophile-to-monocyte ratio, systemic inflammation index (SII), and prognostic nutritional index (PNI) parameters of the patients were evaluated. The mortality rate was higher among male patients, with a statistically significant difference (P < .05). The follow-up duration, albumin, HGB, eosinophil, lymphocyte, eosinophil %, eosinophil-to-lymphocyte ratio, HRR, and PNI means were significantly higher in the living group (P < .05). Age, MPV, MPVPR, neutrophil-to-lymphocyte ratio, monocyte/lymphocyte ratio, platelet-to-lymphocyte ratio, MPV-to-lymphocyte ratio, MER, and systemic inflammation index were significantly higher in the deceased group (P < .05). The predictive value of gender (B = -0.362; P < .01), age (B = 0.036; P < .01), HRR (B = -1.100; P < .01), MPVPR (B = 8.209; P < .01), MER (B = 0.006; P < .01), and PNI (B = -0.078; P < .01) were statistically significant at the multivariate level. The time of death was significantly predicted by gender (B = 0.10; P < .05), age (B = -0.02; P < 0 = 1), HRR (B = 0.61; P < .01), MPVPR (r = -4.16; P < .01), MER (B = -0.01; P < .05), and PNI (B = 0.03; P < .01). The predictive value of PNI for the 30-day mortality rate was statistically significant (AUC: 0.643; P < .01). For a PNI cutoff value of 34.475, sensitivity was 69.7%, and specificity was 51.1%. The PNI has predictive value both in estimating overall mortality and in predicting the 30-day mortality rates among patients undergoing endoprosthesis after a hip fracture.

Computed Tomography-Assessed Sarcopenia Predicts Mortality in Kidney Transplant Candidates.

OBJECTIVES: Sarcopenia is common in chronic kidney disease and associated with increased mortality. We investigated the prevalence of sarcopenia, defined as low muscle mass by the psoas muscle index, in endstage renal disease patients on waiting lists for kidney transplant and determined its association with prognostic nutritional index, C-reactive protein-toalbumin ratio, cardiovascular events, and mortality. MATERIALS AND METHODS: Our study included 162 patients with end-stage renal disease and 87 agematched healthy controls. We calculated nutritional status as follows: prognostic nutritional index = (10 × albumin [g/dL]) + (0.005 × total lymphocyte count (×103/µL]) and C-reactive protein-to-albumin ratio. We gathered demographic and laboratory data from medical records. RESULTS: Patients with end-stage renal disease had a mean age of 44.7 ± 14.2 years; follow-up time was 3.37 years (range, 0.35-9.60 y). Although patients with endstage renal disease versus controls had higher prevalence of sarcopenia (16.7% vs 3.4%; P = .002) and C-reactive protein-to-albumin ratio (1.47 [range, 0.12-37.10] vs 0.74 [range, 0.21-10.20]; P < .001), prognostic nutritional index was lower (40 [range, 20.4-52.2] vs 44 [range, 36.1-53.0]; P < .001). In patients with end-stage renal disease with and without sarcopenia, prognostic nutritional index (P = .005) was lower and C-reactive protein-to-albumin ratio (P = .041) was higher in those with versus those without sarcopenia. Among 67 patients on waiting lists who received kidney transplants, those without sarcopenia had better 5-year patient survival posttransplant than those with sarcopenia (P = .001). Multivariate regression analysis showed sarcopenia and low prognostic nutritional index were independentrisk factors for mortality among patients with end-stage renal disease. CONCLUSIONS: Sarcopenia was ~5 times more frequent in patients with end-stage renal disease than in healthy controls and was positively correlated with the prognostic nutritional index. Sarcopenia was an independent risk factor for mortality in patients on transplant waiting lists.

Dietary pattern and diversity analysis using DietDiveR in R: a cross-sectional evaluation in the National Health and Nutrition Examination Survey.

BACKGROUND: There are few resources available for researchers aiming to conduct 24-h dietary record and recall analysis using R. OBJECTIVES: We aimed to develop DietDiveR, which is a toolkit of functions written in R for the analysis of recall or record data collected with the Automated Self-Administered 24-h Dietary Assessment Tool or 2-d 24-h dietary recall data from the National Health and Nutrition Examination Survey (NHANES). The R functions are intended for food and nutrition researchers who are not computational experts. METHODS: DietDiveR provides users with functions to 1) clean dietary data, 2) analyze 24-h dietary intakes in relation to other study-specific metadata variables, 3) visualize percentages of energy intake from macronutrients, 4) perform principal component analysis or k-means clustering to group participants by similar data-driven dietary patterns, 5) generate foodtrees based on the hierarchical food group information for food items consumed, 6) perform principal coordinate analysis taking food grouping information into account, and 7) calculate diversity metrics for overall diet and specific food groups. DietDiveR includes a self-paced tutorial on a website (https://computational-nutrition-lab.github.io/DietDiveR/). As a demonstration, we applied DietDiveR to a demonstration data set and data from NHANES 2015-2016 to derive a dietary diversity measure of nuts, seeds, and legumes consumption. RESULTS: Adult participants in the NHANES 2015-2016 cycle were grouped depending on the diversity in their mean consumption of nuts, seeds, and legumes. The group with the highest diversity in nuts, seeds, and legumes consumption had 3.8 cm lower waist circumference (95% confidence interval: 1.0, 6.5) than those who did not consume nuts, seeds, and legumes. CONCLUSIONS: DietDiveR enables users to visualize dietary data and conduct data-driven dietary pattern analyses using R to answer research questions regarding diet. As a demonstration of this toolkit, we explored the diversity of nuts, seeds, and legumes consumption to highlight some of the ways DietDiveR can be used for analyses of dietary diversity.

Standardized phase angle: relationship with functionality, muscle mass and postoperative outcomes in surgical cancer patients.

To evaluate the association of standardized phase angle (SPA) with nutritional status, functional parameters, and postoperative outcomes in surgical cancer patients. This prospective study includes 59 cancer patients from Pelotas (Brazil) admitted for elective cancer surgery. We obtained the phase angle through Bioelectrical Impedance Analysis (BIA) and standardized it according to the population's reference values. We estimated the muscle mass using BIA for later calculation of the Skeletal Muscle Index (SMI) and performed handgrip strength (HGS) and gait speed (GS) tests. We used the Patient-Generated Subjective Global Assessment (PG-SGA) to assess the nutritional status. Postoperative complications and duration of hospital stay were evaluated as the outcomes. The prevalence of malnutrition in the sample was 28.8%, according to ASG-PPP. SPA was statistically lower in patients with malnutrition, with lower HGS and reduced GS. For postoperative outcomes, patients with severe complications and those with prolonged hospitalization also had lower SPA values. The greater the number of functional alterations in patients, the lower the SPA value, mainly when associated with reduced muscle mass assessed by BIA, suggesting that muscle mass reduction plays an important role in the association between functional alterations and phase angle in patients with cancer. According to the parameters used in this study, low SPA value was associated with impaired nutritional and functional status and negative outcomes in the analyzed sample.

Do nutritional assessment tools (PNI, CONUT, GNRI) predict adverse events after spinal surgeries? A systematic review and meta-analysis.

BACKGROUND: Nutritional assessment tools are used to predict outcomes in cancer. However, their utility in patients undergoing spinal surgery is unclear. This review examined if prognostic nutritional index (PNI), controlling nutritional status (CONUT), and geriatric nutritional risk index (GNRI) can predict adverse events after spinal surgeries. METHODS: PubMed, CENTRAL, Scopus, and Embase were screened by two reviewers for relevant studies up to 26th January 2024. The primary outcome of interest was total adverse events after spinal surgery. Secondary outcomes were surgical site infections (SSI) and mortality. RESULTS: 14 studies were included. Meta-analysis showed that while reduced PNI was not associated with an increased risk of SSI there was a significant association between PNI and higher risk of adverse events. Meta-analysis showed that high CONUT was not associated with an increased risk of complications after spinal surgeries. Pooled analysis showed that low GNRI was associated with an increased risk of both SSI and adverse events. Data on mortality was scarce. CONCLUSIONS: The PNI and GNRI can predict adverse outcomes after spinal surgeries. Limited data shows that high CONUT is also associated with a non-significant increased risk of adverse outcomes. High GNRI was predictive of an increased risk of SSI. Data on mortality is too scarce for strong conclusions.

Geriatric nutritional risk index is associated with the occurrence of acute kidney injury in critically ill patients with acute heart failure.

Background: During the acute heart failure (AHF), acute kidney injury (AKI) is highly prevalent in critically ill patients. The occurrence of the latter condition increases the risk of mortality in patients with acute heart failure. The current research on the relationship between nutritional risk and the occurrence of acute kidney injury in patients with acute heart failure is very limited. Methods: This retrospective cohort study utilized data from the Medical Information Mart for Intensive Care IV (MIMIC-IV, version 2.1) database. We included adult patients with AHF who were admitted to the intensive care unit in the study. Results: A total of 1310 critically ill patients with acute heart failure were included. The AUC of geriatric nutritional risk index (GNRI) (0.694) is slightly superior to that of controlling nutritional status (CONUT) (0.656) and prognostic nutritional index (PNI) (0.669). The Log-rank test revealed a higher risk of acute kidney injury in patients with high nutritional risk (p < 0.001). Multivariate COX regression analysis indicated that a high GNRI (adjusted HR 0.62, p < 0.001) was associated with a reduced risk of AKI during hospitalization in AHF patients. The final subgroup analysis demonstrated no significant interaction of GNRI in all subgroups except for diabetes subgroup and ventilation subgroup (P for interaction: 0.057-0.785). Conclusion: Our study findings suggest a correlation between GNRI and the occurrence of acute kidney injury in patients hospitalized with acute heart failure.

Association between the geriatric nutritional risk index and clinical outcomes among peritoneal dialysis patients: A meta-analysis.

BACKGROUND: To identify the relationship between the geriatric nutritional risk index (GNRI) and clinical outcomes in patients receiving peritoneal dialysis (PD). METHODS: The PubMed, EBASE, Web of Science and CNKI databases were searched for available studies up to December 25, 2023. The primary outcome was all-cause mortality, and the secondary outcomes included the incidence of PD dropout, major adverse cardiac and cerebrovascular events (MACCEs), technique failure and peritonitis. Hazard ratios (HRs) and 95% confidence intervals (CIs) were combined to evaluate the predictive value of the GNRI for the occurrence of the above endpoints. RESULTS: Ten cohort studies with 3897 patients were included. The pooled results demonstrated that a lower GNRI was significantly associated with a greater incidence of all-cause mortality (HR = 0.71, 95% CI: 0.55-0.91; P = .007). In addition, a decreased GNRI predicted the occurrence of dropout from PD (HR = 0.971, 95% CI: 0.945-0.998, P = .034) and MACCE (HR = 0.95, 95% CI: 0.92-0.98, P = .001). However, no significant associations of the GNRI with technique failure (P = .167) or peritonitis (P = .96) were observed. CONCLUSION: A low GNRI is significantly associated with poor clinical outcomes and might serve as a novel and valuable prognostic indicator among PD patients.

Development and Validation of a Nomogram for Predicting Nutritional Risk Based on Frailty Scores in Older Stroke Patients.

BACKGROUND: In older stroke patients with frailty, nutritional deficiencies can amplify their susceptibility, delay recovery, and deteriorate prognosis. A precise predictive model is crucial to assess their nutritional risk, enabling targeted interventions for improved clinical outcomes. OBJECTIVE: To develop and externally validate a nutritional risk prediction model integrating general demographics, physical parameters, psychological indicators, and biochemical markers. The aim is to facilitate the early identification of older stroke patients requiring nutritional intervention. METHODS: This was a multicenter cross-sectional study. A total of 570 stroke patients were included, 434 as the modeling set and 136 as the external validation set. The least absolute shrinkage selection operator (LASSO) regression analysis was used to select the predictor variables. Internal validation was performed using Bootstrap resampling (1000 iterations). The nomogram was constructed based on the results of logistic regression. The performance assessment relied on the receiver operating characteristic curve (ROC), Hosmer--Lemeshow test, calibration curves, Brier score, and decision curve analysis (DCA). RESULTS: The predictive nomogram encompassed seven pivotal variables: Activities of Daily Living (ADL), NIHSS score, diabetes, Body Mass Index (BMI), grip strength, serum albumin levels, and depression. Together, these variables comprehensively evaluate the overall health and nutritional status of elderly stroke patients, facilitating accurate assessment of their nutritional risk. The model exhibited excellent accuracy in both the development and external validation sets, evidenced by AUC values of 0.934 and 0.887, respectively. Such performance highlights its efficacy in pinpointing elderly stroke patients who require nutritional intervention. Moreover, the model showed robust goodness of fit and practical applicability, providing essential clinical insights to improve recovery and prognosis for patients prone to malnutrition. CONCLUSIONS: Elderly individuals recovering from stroke often experience significant nutritional deficiencies. The nomogram we devised accurately assesses this risk by combining physiological, psychological, and biochemical metrics. It equips healthcare providers with the means to actively screen for and manage the nutritional care of these patients. This tool is instrumental in swiftly identifying those in urgent need of targeted nutritional support, which is essential for optimizing their recovery and managing their nutrition more effectively.

Establishment of in-hospital nutrition support program for middle-aged and elderly patients with acute decompendated heart failure.

OBJECTIVE: To construct a nutrition support program for middle-aged and elderly patients with acute decompensated heart failure (ADHF) during hospitalization. METHODS: Based on the JBI Evidence-Based Health Care Model as the theoretical framework, the best evidence was extracted through literature analysis and a preliminary nutrition support plan for middle-aged and elderly ADHF patients during hospitalization was formed. Two rounds of expert opinion consultation were conducted using the Delphi method. The indicators were modified, supplemented and reduced according to the expert's scoring and feedback, and the expert scoring was calculated. RESULTS: The response rates of the experts in the two rounds of consultation were 86.7% and 100%, respectively, and the coefficient of variation (CV) for each round was between 0.00% and 29.67% (all < 0.25). In the first round of expert consultation, 4 items were modified, 3 items were deleted, and 3 items were added. In the second round of the expert consultation, one item was deleted and one item was modified. Through two rounds of expert consultation, expert consensus was reached and a nutrition support plan for ADHF patients was finally formed, including 4 first-level indicators, 7 s-level indicators, and 24 third-level indicators. CONCLUSION: The nutrition support program constructed in this study for middle-aged and elderly ADHF patients during hospitalization is authoritative, scientific and practical, and provides a theoretical basis for clinical development of nutrition support program for middle-aged and elderly ADHF patients during hospitalization.

The prognostic value of prognostic nutritional index and renal function indicators for mortality prediction in severe COVID-19 elderly patients: A retrospective study.

Identifying prognostic factors in elderly patients with severe coronavirus disease 2019 (COVID-19) is crucial for clinical management. Recent evidence suggests malnutrition and renal dysfunction are associated with poor outcome. This study aimed to develop a prognostic model incorporating prognostic nutritional index (PNI), estimated glomerular filtration rate (eGFR), and other parameters to predict mortality risk. This retrospective analysis included 155 elderly patients with severe COVID-19. Clinical data and outcomes were collected. Logistic regression analyzed independent mortality predictors. A joint predictor "L" incorporating PNI, eGFR, D-dimer, and lactate dehydrogenase (LDH) was developed and internally validated using bootstrapping. Decreased PNI (OR = 1.103, 95% CI: 0.78-1.169), decreased eGFR (OR = 0.964, 95% CI: 0.937-0.992), elevated D-dimer (OR = 1.001, 95% CI: 1.000-1.004), and LDH (OR = 1.005, 95% CI: 1.001-1.008) were independent mortality risk factors (all P < .05). The joint predictor "L" showed good discrimination (area under the curve [AUC] = 0.863) and calibration. The bootstrapped area under the curve was 0.858, confirming model stability. A combination of PNI, eGFR, D-dimer, and LDH provides useful prognostic information to identify elderly patients with severe COVID-19 at highest mortality risk for early intervention. Further external validation is warranted.