Prognostic Nutritional Index Predicts Contrast-Associated Acute Kidney Injury in Patients with ST-Segment Elevation Myocardial Infarction

The Impact of Insulin Resistance on the Development of Post-PCI Contrast-Induced Nephropathy in Non-Diabetic STEMI

Aims

Contrast-induced nephropathy (CIN) is a condition characterized by rapidly decreasing renal funciton following by the application of contrast material. Precutaneous coronary intervention (PCI) is a life-saving treatment method that should be applied under emergent conditions. Unfortunately, the incidence of CIN after PCI is common. Patients with insulin resistance or diabetes have a greater risk of developing CIN than most of the population. Therefore, studies on the predictive effects of insulin resistance indicators on CIN are gaining momentum. One of the most popular indicators is triglyceride/glucose-body mass index (TyG-BMI). In this study we aimed to evaluate the effect of TyG-BMI index on CIN.

Materials and Methods

A total of 960 patinets who underwent emergency PCI due to ST elevation myocardial infarction (STEMI) between 2020 and 2023 were included in the study. Laboratory and demographic parameters were compared between the patients who did and did not develop CIN.

Results

While CIN developed in 120 of the 980 patients included in the study, it did not develop in 860 patients. There were significant differences between the groups in terms of age (p < 0.001), gender (p = 0.005), presence of hypertension (p = 0.021), heart rate (p = 0.049), amount of contrast material (p < 0.001), left ventricular ejection fraction (p < 0.001), stent length (p = 0.022), SYNTAX score (p < 0.001), fasting plasma glucose (p < 0.001), baseline creatinine (p < 0.001), glomerular filtration rate (p < 0.001), uric acid (p < 0.001), C reactive protein (CRP) (p < 0.001), baseline creatin kinase myocard band (CKMB) (p = 0.019), CKMB peak (p = 0.030), triglyceride (p = 0.017), and TyG-BMI (p < 0.001). CRP, creatinine, uric asid, amount of contrast material, and TyG-BMI were independent predictors for the development of CIN.

Conclusions

TyG-BMI was a predictor of CIN in STEMI patient who underwent PCI under emergency conditions. In addition, the predicitive power of TyG-BMI was stronger than triglyceride-glucose index.

Predictors of Length of Stay after Transcatheter Aortic Valve Implantation: Impact of Prognostic Nutritional Index

Background

Pre-transcatheter aortic valve replacement (TAVR) nutritional status can potentially affect the length of hospital stay (LoS) after TAVR. The Prognostic Nutritional Index (PNI) is a widely recognised nutritional index. We aimed to determine the effect of PNI on LoS in patients undergoing TAVR.

Methods

The study population (158 patients) was divided into two groups: early discharge (LoS ≤ 3 days) and late discharge (LoS > 3 days). PNI was calculated before TAVR.

Results

In the LoS > 3 days group, the median age, creatinine level, rate of surgical access site closure and rate of major complications were higher, whereas estimated glomerular filtration rate, albumin, haemoglobin, lymphocyte count and PNI were significantly lower. Receiver operating characteristic curve analysis revealed a PNI cutoff of 39 (area under the curve = 0.778, p < 0.001) with 86.8% sensitivity and 55.2% specificity for predicting extended LoS. The 30-day endpoint analysis revealed significantly higher rates of death and hospitalisation with LoS > 3 days and PNI ≤ 39. Multivariate binary logistic regression analysis identified several independent predictors of extended LoS: severe renal insufficiency [odds ratio: 3.951 (95% confidence interval: 1.281-12.191); p = 0.017], surgical access site closure [4.353 (1.701-11.141); p = 0.002), complications [7.448 (1.305-42.518); p = 0.024] and PNI < 39 [5.906 (2.375-14.684); p < 0.005].

Conclusions

Decreased PNI may be associated with LoS > 3 days after TAVR. Nutritional status assessed using PNI may be a useful independent predictor of LoS after TAVR.

Prognostic nutritional index as a predictive marker for acute kidney injury in adult critical illness population: a systematic review and diagnostic test accuracy meta-analysis

BACKGROUND

The prognostic nutritional index (PNI), integrating nutrition and inflammation markers, has been increasingly recognized as a prognostic predictor in diverse patient cohorts. Recently, its effectiveness as a predictive marker for acute kidney injury (AKI) in various clinical settings has gained attention. This study aims to assess the predictive accuracy of the PNI for AKI in critically ill populations through systematic review and meta-analysis.

METHODS

A systematic review was conducted using the databases MEDLINE, EMBASE, PubMed, and China National Knowledge Infrastructure up to August 2023. The included trials reported the PNI assessment in adult population with critical illness and its predictive capacity for AKI. Data on study characteristics, subgroup covariates, and diagnostic performance of PNI, including sensitivity, specificity, and event rates, were extracted. A diagnostic test accuracy meta-analysis was performed. Subgroup analyses and meta-regression were utilized to investigate the sources of heterogeneity. The GRADE framework evaluated the confidence in the meta-analysis's evidence.

RESULTS

The analysis encompassed 16 studies with 17 separate cohorts, totaling 21,239 patients. The pooled sensitivity and specificity of PNI for AKI prediction were 0.67 (95% CI 0.58-0.74) and 0.74 (95% CI 0.67-0.80), respectively. The pooled positive likelihood ratio was 2.49 (95% CI 1.99-3.11; low certainty), and the negative likelihood ratio was 0.46 (95% CI 0.37-0.56; low certainty). The pooled diagnostic odds ratio was 5.54 (95% CI 3.80-8.07), with an area under curve of summary receiver operating characteristics of 0.76. Subgroup analysis showed that PNI's sensitivity was higher in medical populations than in surgical populations (0.72 vs. 0.55; p < 0.05) and in studies excluding patients with chronic kidney disease (CKD) than in those including them (0.75 vs. 0.56; p < 0.01). Overall, diagnostic performance was superior in the non-chronic kidney disease group.

CONCLUSION

Our study demonstrated that PNI has practical accuracy for predicting the development of AKI in critically ill populations, with superior diagnostic performance observed in medical and non-CKD populations. However, the diagnostic efficacy of the PNI has significant heterogeneity with different cutoff value, indicating the need for further research.

Association between nutritional status scores and the 30-day mortality in patients with acute kidney injury: an analysis of MIMIC-III database

BACKGROUND

Studies have proven that the risk of acute kidney injury (AKI) increased in patients with malnutrition. Prognostic nutritional index (PNI) and geriatric nutritional risk index (GNRI) were general tools to predict the risk of mortality, but the prognostic value of them for in-hospital mortality among patients with AKI have not been validated yet. Herein, this study aims to explore the association between PNI and GNRI and 30-day mortality in patients with AKI.

METHODS

Demographic and clinical data of 863 adult patients with AKI were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database in 2001-2012 in this retrospective cohort study. Univariate and multivariate Cox proportional regression analyses were used to explore the association between PNI and GNRI and 30-day mortality. The evaluation indexes were hazard ratios (HRs) and 95% confidence intervals (CIs). Subgroup analyses of age, Sequential Organ Failure Assessment (SOFA) score and Simplified Acute Physiology (SAPS-II) score were also performed.

RESULTS

Totally, 222 (26.71%) patients died within 30 days. After adjusting for covariates, PNI ≥ 28.5 [HR = 0.71, 95%CI: (0.51-0.98)] and GNRI ≥ 83.25 [HR = 0.63, 95%CI: (0.47-0.86)] were both associated with low risk of 30-day mortality. These relationships were also found in patients who aged ≥ 65 years old. Differently, high PNI level was associated with low risk of 30-day mortality among patients with SOFA score < 6 or SAPS-II score < 43, while high GNRI was associated with low risk of 30-day mortality among those who with SOFA score ≥ 6 or SAPS-II score ≥ 43 (all P < 0.05).

CONCLUSION

PNI and GNRI may be potential predictors of 30-day mortality in patients with AKI. Whether the PNI is more recommended for patients with mild AKI, while GNRI for those with severe AKI is needed further exploration.

Association of Malnutrition with Risk of Acute Kidney Injury: A Systematic Review and Meta-Analysis

Background

Acute kidney injury (AKI) is a complex clinical syndrome of hospitalization that may be affected by undernutrition and metabolic changes. The aim of this meta-analysis was to systematically assess the association between malnutrition and the risk of prevalent AKI.

Materials and Methods

We searched PubMed, Embase, Ovid MEDLINE, Web of Science, and Chinese databases (WANFANG, VIP, and CKI) from database inception until May 1, 2023, for studies evaluating the association of malnutrition with the risk of AKI. Summary odds ratios (ORs) were estimated using a random-effects model.

Results

We identified 17 observational studies, which included 273,315 individuals. Compared with patients with normal nutritional status, those with malnutrition had a 125% increased risk of prevalent AKI (pooled ORs, 2.25; 95% confidence interval, 1.80-2.82). Malnutrition was also significantly associated with prevalent AKI across all subgroups when subgroup analyses were performed on covariates such as region, study design, age, sample size, malnutrition assessment method, patient characteristics, covariate adjustment degree, and risk of bias. Meta-regression models demonstrated no significant differences in AKI risk between patients with malnutrition and without malnutrition.

Conclusions

Our results suggest that malnutrition may be a potential target for AKI prevention. However, well-designed studies with ethnically or geographically diverse populations are needed to evaluate strategies and interventions to prevent or slow the development and progression of AKI in malnourished individuals.

The prognostic nutritional index predicts all-cause mortality in critically ill patients with acute myocardial infarction

BACKGROUND

Malnutrition is common in patients with acute myocardial infarction (AMI) and is associated with a poor prognosis. The prognostic value of the prognostic nutritional index (PNI) in patients with AMI remains controversial. We aimed to explore the relationship between PNI and all-cause mortality in critically ill patients with AMI and evaluate the incremental prognostic value of PNI to commonly used prognostic assessment tools.

METHODS

The Medical Information Mart for Intensive Care-IV (MIMIC-IV) database was used to conduct a retrospective cohort analysis on 1180 critically ill patients with AMI. The primary endpoints were defined as 6-month and 1-year all-cause mortality. Cox regression analysis was used to investigate the relationship between admission PNI and all-cause mortality. The effect of adding PNI to sequential organ failure assessment (SOFA) score, or charlson comorbidity index (CCI) on its discriminative ability was assessed using C-statistic, net reclassification improvement (NRI), and integrated discrimination improvement (IDI).

RESULTS

Multivariate cox regression analysis demonstrated that the low PNI was regarded as an independent predictor of 1-year all-cause mortality in AMI patients admitted to ICU (adjusted Hazard Ratio: 95% CI = 1.75 (1.22-2.49)). The ROC test showed that admission PNI had a moderate predictive ability to predict all-cause mortality of critically ill patients with AMI. Furthermore, the net reclassification and integrated discrimination of the CCI alone model improved significantly with PNI. [C-statistic increased from 0.669 to 0.752, p < 0.001; NRI = 0.698, p < 0.001; IDI = 0.073, p < 0.001]. When PNI was added to the SOFA score, the C-statistic significantly improved from 0.770 to 0.805 (p < 0.001), and the NRI and IDI were estimated at 0.573 (p < 0.001) and 0.041 (p < 0.001), respectively.

CONCLUSION

PNI could be a novel predictor for identifying patients at high risk of 1-year all-cause mortality in critically ill patients with AMI. The addition of PNI to the SOFA score or CCI may be useful for very early risk stratification.

Repetition of Paclitaxel-Coated Devices for the Treatment of Lower Extremity Artery Disease: Mortality Outcomes and Predictors

Background

A recent meta-analysis reported late excess mortality in patients treated with paclitaxel-coated devices (PCDs) for symptomatic femoropopliteal disease. However, this finding is controversial.

Objectives

To investigate the impact on mortality and predictors of repeat exposure to PCDs in patients with lower extremity peripheral arterial disease (LE-PAD).

Methods

We analyzed registry patient-level data from two centers. A total of 214 patients were enrolled, and stratified based on terciles of cumulative dose of paclitaxel. We treated 134 patients with a single PCD exposure and 80 with multiple PCD exposures. We used the follow-up index (FUI) in Kaplan-Meier survival estimates to minimize potential selection bias. We used Cox proportional hazard and splines models to determine the predictors of mortality and assess their relationships with mortality.

Results

The mean cumulative dose of paclitaxel was significantly different among groups (6.40 mg vs. 15.06 mg vs. 38.57 mg, p < 0.001). The 5-year FUI (0.93 ± 0.19 vs. 0.94 ± 0.18 vs. 0.95 ± 0.15, p = 0.836) and survival rates were not different (65.4% vs. 51.9% vs. 72.0%, p = 0.148). There was no dose-response association between paclitaxel dosage and death (p = 0.297). The predictors of death were congestive heart failure, stroke, dialysis dependence, neutrophil-lymphocyte ratio (NLR) > 3, age > 71 years, and body mass index (BMI) < 20 kg/m². Spline model analysis validated the non-linear associations between mortality, age, BMI, and NLR.

Conclusions

Repeated PCD exposure for LE-PAD did not result in excess late mortality. Predictors of mortality might change over time, and continuous variables had non-linear relationships with death.

Is the prognostic nutritional index a predictor of Covid-19 related hospitalizations and mortality?

Introduction

Prognostic nutritional index (PNI) is a novel inflammation marker that useful in predicting prognosis of certain conditions. We aimed to study PNI of the outpatient and inpatient subjects with established Covid-19 and also aimed to compare PNI of deceased and survived Covid-19 patients.

Methods

The patients with Covid-19 whom presented to outpatient or inpatient clinics of Abant Izzet Baysal University Hospital were enrolled to the study. PNI levels of the inpatients and outpatients, deceased and survived were compared. PNI values of deceased and survived in inpatients were also compared.

Results

Study population was consisted of 4419 subjects (2907 outpatients and 1512 inpatients). PNI of the inpatient (41.55 (36.42-47.1)) group was significantly lower than the PNI of the outpatient (51.95 (47.95-55.75)) subjects (p<0.001). The sensitivity and specificity of PNI (≤46.2 level) in determination of requirement inpatient treatment were 71.2% and 83.5%, respectively. PNI of the deceased patients (37(33.39-40.86)) was lower than the PNI of the survivors (50.45(45.6-54.65)), (p<0.001). The sensitivity and specificity of PNI at ≤44.55 level in determining mortality were 89.22% and 78.87%, respectively.

Conclusion

We suggest that PNI could serve as a reliable prognostic index in covid-19 patients. Reduced level of PNI should alert physicians since it is associated with need for hospitalization and mortality in this population.

Association of prognostic nutritional index with risk of contrast induced nephropathy: A meta-analysis

Background

Although prognostic nutritional index (PNI) has been frequently applied in patients with malignancy or those during postoperative recovery, whether it is also an optimal indicator of the risk of contrast-induced nephropathy (CIN) in patients receiving coronary angiography remains uncertain. This meta-analysis aimed at investigating the clinical association of PNI with the risk of CIN in patients receiving coronary angiography or percutaneous coronary intervention.

Methods

Embase, Medline, Cochrane Library, and Google scholar were searched for studies until January 2023. The relationship between CIN risk and PNI (i.e., low vs. high) (primary outcome) as well as other variables (secondary outcomes) were analyzed using a random-effects model.

Results

Overall, 10 observational studies with 17,590 patients (pooled incidence of CIN: 18%) were eligible for analysis. There was a higher risk of CIN in patients with a low PNI compared to those with a high PNI [odd ratio (OR) = 3.362, 95% confidence interval (CI): 2.054 to 5.505, p < 0.0001, I ² = 89.6%, seven studies, 12,972 patients, certainty of evidence: very low]. Consistently, a lower PNI was noted in patients with CIN compared to those without (Mean difference = -5.1, 95% CI: -6.87 to -3.33, p < 0.00001, I ² = 96%, eight studies, 15,516 patients, certainty of evidence: very low). Other risks of CIN included diabetes and hypertension, while male gender and the use of statins were associated with a lower risk of CIN. Patients with CIN were older, had a higher creatinine level, and received a higher contrast volume compared to those without. On the other hand, pre-procedural albumin, estimated glomerular filtration rate, ejection fraction, hemoglobin, lymphocyte ratio were found to be lower in patients with CIN than in those without.

Conclusion

This meta-analysis highlighted an inverse association of PNI with the risk of CIN, which required further studies for verification.

Systematic review registration

[https://www.crd.york.ac.uk/prospero/], identifier [CRD42023389185].

Prognostic Nutritional Index and Major Cardiovascular Events in Patients Undergoing Invasive Coronary Angiography: A Clinical Retrospective Study

We aimed to examine whether prognostic nutritional index (PNI) could serve as an auxiliary predictor for major cardiovascular events (MCEs) in patients undergoing invasive coronary angiography (ICA). A total of 485 participants were enrolled, divided into low-PNI (≥47.40) and high-PNI (<47.40) groups. ICA determined the stenotic vessels of coronary artery disease. The primary outcome was incidental MCEs, a composite of all-cause death, non-fatal myocardial infarction, non-fatal stroke, or rehospitalization of in-stent restenosis. There were 47 (9.69%) MCEs during the 3.78-years follow-up. The cumulative incidence of MCEs was significantly higher in the low-PNI patients compared with the high-PNI patients (17.07% vs. 7.18%, p = 0.001). Malnutrition risk (low PNI) was significantly and independently associated with a higher risk of MCEs (hazard ratios: 2.593, 95% confidence intervals [CI]: 1.418−4.742). Combined use of the number of stenotic vessels with malnutrition risk showed a higher capacity to predict the MCEs than the presence of stenotic vessels alone (areas under the receiver operator characteristic curve: 0.696 [95% CI, 0.618−0.775] vs. 0.550 [95% CI, 0.466−0.633], p = 0.013). In conclusion, lower PNI levels may predict a higher risk of cardiovascular events in patients undergoing ICA, which supports the necessity of the risk assessment of nutrition status and guide the clinical treatment on strengthening nutritional support before ICA is performed, as well as nutritional intervention after ICA.

Relationship Between Prognostic Nutrition Index and New York Heart Association Classification in Patients with Coronary Heart Disease: A RCSCD-TCM Study

Aim

This study aimed to elucidate the relationship between the prognostic nutrition index (PNI) of patients with coronary heart disease (CHD) and the New York Heart Association (NYHA) classification and the complex relationship between PNI combined body mass index (BMI) and NYHA classification.

Methods

The PNI was applied to 17,413 consecutive patients with CHD. Patients were divided into three groups according to PNI: normal nutrition (PNI ≥ 38), moderate malnutrition (35 < PNI < 38), and severe malnutrition (PNI ≤ 35). A total of 2,052 CHD patients with BMI were selected and stratified by combined subgroups of nutritional status and BMI. Logistic regression analysis was used to evaluate the relationship between the PNI and NYHA classification and to adjust for confounding factors.

Results

The prevalence of malnutrition among the 17,413participants with CHD was 4.2%. Moderate and severe malnutrition were significantly related to NYHA class III and V, and the strongest relationship was observed in NYHA class V (odd ratio [OR]: 6.564; 95% confidence interval [CI]: 4.043–10.658). Malnourished-underweight patients and malnourished-overweight patients were significantly associated with higher NYHA classification, and malnourished-underweight patients (OR: 8.038; 95% CI: 2.091–30.892) were significantly more than malnourished-overweight patients (OR: 3.580; 95% CI: 1.286–9.966).

Conclusion

There were differences in the NYHA classification of CHD patients with different nutritional statuses. The lower the PNI, the worse the NYHA classification of CHD patients. Malnourished-underweight patients had a worse NYHA classification than malnourished-overweight patients.