Association of Preoperative Prognostic Nutritional Index with Risk of Postoperative Acute Kidney Injury: A Meta-Analysis of Observational Studies

Relationship between nutritional-inflammatory markers and postoperative outcomes in ovarian cancer: a retrospective study

Background

Elevated inflammatory markers are commonly linked to poor prognoses in cancer patients, while optimal nutritional status correlates with improved survival outcomes. This study aimed to explore the interplay between nutritional and inflammatory markers and their impact on postoperative outcomes in ovarian cancer patients through a retrospective analysis.

Methods

Data were retrospectively retrieved from patients diagnosed with ovarian cancer who required surgical intervention at the Department of Obstetrics and Gynecology. Overall survival (OS) and cancer-specific survival (CSS) were monitored during follow-up. Kaplan-Meier survival curves were employed to assess OS and CSS across different patient cohorts, evaluating the prognostic significance of nutritional and inflammatory markers. Nomograms for predicting OS and CSS at one, three, and five years postoperatively were constructed, followed by external validation.

Results

The prognostic nutritional index (PNI) and Naples prognostic score (NPS) exhibited a significant correlation with OS and CSS in postoperative ovarian cancer patients (p < 0.05). Analysis indicated that patients with a PNI > 51.2 demonstrated the most favorable survival outcomes. Furthermore, those with a low-NPS (L-NPS) had notably better survival rates compared to their high-NPS (H-NPS) counterparts. Independent OS predictors included age, PNI, NPS, histological type, tumor size, targeted therapy, and diabetes. Similarly, the CSS prediction model incorporated age, NPS, tumor size, targeted therapy, and diabetes. The nomograms demonstrated robust predictive accuracy for three- and five-year survival, though one-year calibration curves showed limited agreement. Despite slightly reduced external validation performance compared to the initial sample, the model maintained strong predictive capability.

Conclusions

The nutritional inflammatory index serves as a key independent prognostic marker for OS and CSS in ovarian cancer patients. Nomograms based on PNI and NPS provide valuable prognostic insights for postoperative management. Incorporating these indices into clinical practice could improve patient stratification and guide personalized treatment plans.

Development and validation of a clinical prediction model for dialysis-requiring acute kidney injury following heart transplantation: a single-center study from China

OBJECTIVES

This study seeks to construct and internally validate a clinical prediction model for predicting new-onset dialysis-requiring acute kidney injury (AKI) following heart transplantation (HT).

METHODS

The Kaplan-Meier survival analysis and log-rank test were utilized for conducting the survival analysis. A clinical prediction model was developed to predict postoperative dialysis-requiring AKI, based on a logistic regression model and likelihood ratio test with Akaike Information Criterion. The performance of the prediction model was assessed using C-index, receiver operating characteristic curves, calibration curves, Brier score, and the Spiegelhalter Z-test. Clinical utility was evaluated using decision curve analysis and clinical impact curves.

RESULTS

This study included a total of 525 patients who underwent orthotopic HT in the single center located in Wuhan, China between January 2015 and December 2021, with 16.57% developing postoperative dialysis-requiring AKI. Patients who experienced postoperative dialysis-requiring AKI exhibited a lower overall survival rate. All enrolled participants were randomly allocated into derivation (n = 350) and validation (n = 175) cohorts at a ratio of 2:1. The final prediction model comprised six indicators: diabetes, stroke, gout, prognostic nutritional index, estimated glomerular filtration rate, and cardiopulmonary bypass duration. The prediction model demonstrated outstanding discrimination (C-index of 0.792 in the derivation cohort and 0.834 in the validation cohort) as well as calibration performance, indicating strong concordance between observed and nomogram-predicted probabilities. Subgroup analysis based on age, preoperative serum creatine levels, and year of surgery also exhibited robust discrimination and calibration capabilities.

CONCLUSIONS

Dialysis-requiring AKI following HT is associated with poor clinical prognosis. The prediction model, comprising six indicators, is capable of predicting dialysis-requiring AKI following HT. This prediction model holds promise in assisting both patients and clinicians in forecasting postoperative renal failure, thereby improving clinical management.

CLINICAL TRIAL NUMBER

Not applicable.

Association between prognostic nutritional index and stroke: A nationally representative cross-sectional study from NHANES

BACKGROUND

The correlation between the prognostic nutritional index (PNI) and the risk of stroke has become a hot spot within the medical research community. The available evidence from a large sample regarding the correlation between PNI and stroke is inadequate. There is also a need for more research analysis from national surveys.

OBJECTIVE

The principal goal of this research is to improve our understanding of the relationship between PNI and the risk of stroke. This study also intends to investigate the potential synergistic influence of PNI on stroke in combination with other interacting variables.

METHODS

A cross-sectional study was conducted with 35,549 participants selected from the National Health and Nutrition Examination Survey (NHANES) 2005-2018 cycle. Information was gathered from all participants regarding the following: lymphocyte count, albumin levels, stroke occurrence, age, sex, race/ethnicity, education level, poverty income ratio (PIR), marital status, body mass index (BMI), smoking habits, drinking status, physical activity measured in total metabolic equivalents (PA_total_MET), diabetes status, glycohemoglobin levels, total cholesterol, direct high-density lipoprotein cholesterol(direct HDL-cholesterol), hypertension, and coronary heart disease. Curve fitting, subgroup analysis, and multifactor weighted logistic regression analysis were used to examine the relationship between PNI and stroke.

RESULTS

The overall prevalence of stroke was found to be 3.9%, PNI quartile 4(Q4) had an increased prevalence of stroke than quartile 1, 2, and 3(Q1,2,3). Our research suggested a negative association between PNI and the risk of stroke, as indicated by the odds ratio (OR=0.98) with a 95% confidence interval (CI=0.97∼0.99) and a p-value <0.05 (P=0.005), even after adjusting for all confounders. Subsequent subgroup analysis indicated a significant difference in the impact of PNI on stroke between individuals with different body mass index(BMI) levels (p for interaction = 0.02).

CONCLUSION

Our findings underscore that lower PNI in US adults is associated with an increased stroke risk, shedding light on a potential interrelationship between nutrition, inflammatory parameters, and stroke.

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.

Value of preoperative prognostic nutritional index combined with NT-proBNP in predicting acute kidney injury of congenital heart disease children

Objective

The study investigates value of preoperative prognostic nutritional index (PNI) combined with N-terminal pro-brain natriuretic peptide (NT-proBNP) in predicting postoperative acute kidney injury (AKI) in congenital heart disease (CHD) children.

Methods

The clinical data of 108 children with congenital heart disease were retrospectively collected. According to whether AKI occurred 48 h after operation, they were divided into AKI group (n = 32) and non-AKI group (n = 76). The clinical data, preoperative PNI and NT-proBNP levels were compared between the two groups. Multivariate logistic regression analysis was used to analyze the influencing factors of AKI, and the receiver operating characteristic (ROC) curve was drawn to evaluate the predictive value of preoperative PNI, NT-proBNP and their combination.

Results

Multivariate logistic regression analysis showed that Scr, PNI and NT-proBNP were independent risk factors for postoperative AKI in children with congenital heart disease (P < 0.001). The results of ROC curve analysis showed that the area under the curve (AUC) of preoperative PNI, NT-proBNP and their combination in predicting postoperative AKI in children with congenital heart disease were 0.839, 0.738 and 0.907, respectively, and the AUC of their combination was the highest.

Conclusion

The combined use of preoperative PNI as well as NT-proBNP holds significant value in predicting postoperative AKI in CHD children. Monitoring preoperative PNI and NT-proBNP levels may aid in clinically identifying the risk of postoperative AKI in CHD children, thereby improving their prognosis.

Clinical implications of four different nutritional indexes in patients with IgA nephropathy

Background

Immunoglobulin A nephropathy (IgAN) is the most prevalent form of chronic kidney disease (CKD), marked by diverse pathological patterns and variable prognostic outcomes. Nutritional indexes are crucial for disease assessment and prognosis prediction. This study investigates associations between nutritional indexes and renal function in patients with IgAN.

Methods

A cohort of 736 adults diagnosed with IgAN, who underwent renal biopsy at the First Hospital of Jilin University between January 2010 and October 2022, was examined. Clinical and laboratory data were reviewed, and four nutritional indexes were calculated: controlling nutritional status (CONUT) score, geriatric nutritional risk index (GNRI), body mass index (BMI), and prognostic nutritional index (PNI). Cox-proportional hazard analysis evaluated factors associated with end-stage renal disease (ESRD).

Results

Patients with ESRD showed significantly lower GNRI (91.84 vs. 98.94, p < 0.001) and median PNI (41.90 vs. 46.30, p < 0.001), with higher median CONUT score (2.00 vs. 1.00, p = 0.001) compared to those without ESRD. PNI, GNRI, and CONUT scores correlated significantly with C2 in MEST-C classification. Kaplan-Meier analysis indicated increased ESRD probability in individuals with specific thresholds of PNI, GNRI, or CONUT scores. Additionally, GNRI emerged as an independent predictor of ESRD (hazard ratio: 0.963, 95% CI: 0.940-0.979, p < 0.001), along with platelet count, serum creatinine, eGFR (CKD-EPI), and triglyceride levels.

Conclusion

GNRI, PNI, and CONUT scores hold potential in reflecting IgAN severity and predicting ESRD risk. GNRI especially may serve as a valuable tool for identifying high-risk individuals for ESRD in IgAN.

Prediction of severe radiation-induced oral mucositis in locally advanced nasopharyngeal carcinoma using the combined systemic immune-inflammatory index and prognostic nutritional index

OBJECTIVE

Severe radiation-induced oral mucositis (sRIOM) can seriously affect patients' quality of life and treatment compliance. This study was to investigate the utility of the systemic immune-inflammatory index (SII) and prognostic nutritional index (PNI) in predicting sRIOM in patients with locally advanced nasopharyngeal carcinoma (LANPC).

METHODS

295 patients with LANPC were retrospectively screened. The pre-radiotherapy SII and PNI were calculated based on peripheral blood samples. A receiver operating characteristic (ROC) curve was used to determine the cut-off value. Logistic regression was used for univariate and multivariate analyses. Patients were classified into three groups based on the SII-PNI score: score of 2, high SII (> cut-off value) and low PNI (≤ cut-off value); score of 1, either high SII or low PNI; score of 0, neither high SII nor low PNI.

RESULTS

The SII-PNI demonstrated significant predictive ability for sRIOM occurrence, as evidenced by an area under the curve (AUC) of 0.738. The incidence rates of sRIOM with SII-PNI score of 2, 1, and 0 were 73.86%, 44.35%, and 18.07%, respectively. Multivariate analysis confirmed that the SII-PNI score was an independent risk factor for sRIOM.

CONCLUSION

The SII-PNI score is a reliable and convenient indicator for predicting sRIOM in patients with LANPC.