Prognostic nutritional index and prognosis of patients with coronary artery disease: A systematic review and meta-analysis

Establishment and evaluation of a nomogram for in-hospital new-onset atrial fibrillation after percutaneous coronary intervention for acute myocardial infarction

Background

New-onset atrial fibrillation (NOAF) is prognostic in acute myocardial infarction (AMI). The timely identification of high-risk patients is essential for clinicians to improve patient prognosis.

Methods

A total of 333 AMI patients were collected who underwent percutaneous coronary intervention (PCI) at Zhejiang Provincial People's Hospital between October 2019 and October 2020. Least absolute shrinkage and selection operator regression (Lasso) and multivariate logistic regression analysis were applied to pick out independent risk factors. Secondly, the variables identified were utilized to establish a predicted model and then internally validated by 10-fold cross-validation. The discrimination, calibration, and clinical usefulness of the prediction model were evaluated using the receiver operating characteristic (ROC) curve, calibration curve, Hosmer-Lemeshow test decision curve analyses, and clinical impact curve.

Result

Overall, 47 patients (14.1%) developed NOAF. Four variables, including left atrial dimension, body mass index (BMI), CHA2DS2-VASc score, and prognostic nutritional index, were selected to construct a nomogram. Its area under the curve is 0.829, and internal validation by 10-fold cross-folding indicated a mean area under the curve is 0.818. The model demonstrated good calibration according to the Hosmer-Lemeshow test (P = 0.199) and the calibration curve. It showed satisfactory clinical practicability in the decision curve analyses and clinical impact curve.

Conclusion

This study established a simple and efficient nomogram prediction model to assess the risk of NOAF in patients with AMI who underwent PCI. This model could assist clinicians in promptly identifying high-risk patients and making better clinical decisions based on risk stratification.

Values of prognostic nutritional index for predicting Kawasaki disease: a systematic review and meta-analysis

Objective

This systematic review and meta-analysis aimed to evaluate the relationship between the prognostic nutritional index (PNI) and intravenous immunoglobulin (IVIG) resistance and coronary artery lesion (CAL) in Kawasaki disease (KD).

Methods

The relevant literature was searched on PubMed, Embase, Cochrane Library, Web of Science, and Google Scholar up to August 5, 2023. A pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under curve (AUC) were calculated to assess the predicted values of PNI in KD patients with IVIG resistance and CAL.

Results

A total of 8 articles containing 10 studies involving 7,047 participants were included. The pooled results revealed a pooled sensitivity of 0.44 (0.25-0.65), a pooled specificity of 0.87 (0.73-0.94), a pooled PLR of 3.4 (2.0-5.9), a pooled NLR of 0.65 (0.48-0.87), a pooled DOR of 5.26 (2.76-10.02), and a pooled AUC of 0.75 (0.71-0.78) in the diagnosis of KD with CAL. The pooled results suggested that a pooled sensitivity was 0.69 (0.60-0.77), specificity was 0.76 (0.69-0.82), PLR was 2.9 (2.1-4.1), NLR was 0.40 (0.29-0.56), DOR was 7.27 (3.89-13.59), and AUC was 0.79 (0.75-0.82) in the diagnosis of KD with IVIG resistance. The combined results revealed the pooled sensitivity was 0.63 (0.58-0.67), specificity was 0.82 (0.80-0.83), PLR was 3.09 (1.06-8.98), NLR was 0.38 (0.07-2.02), DOR was 8.23 (0.81-83.16) in differentiating KD from febrile patients. These findings demonstrated low sensitivity and relatively high specificity of PNI for KD, KD-CAL, and IVIG-resistant KD.

Conclusion

In conclusion, this study was the first systematic review and meta-analysis of the diagnostic value of PNI in KD with IVIG resistance and CAL. The results suggested that PNI could be used as biomarkers for distinguish KD, KD with CAL, and KD with IVIG resistance.

Relationship between immune nutrition index and all-cause and cause-specific mortality in U.S. adults with chronic kidney disease

Objective

The available evidence regarding the association of immune nutrition status with chronic kidney disease (CKD) is limited. Thus, the present study examined whether immunonutrition indices were associated with renal function and mortality among CKD individuals.

Research design and methods

This study enrolled 6,099 U.S. adults with CKD from the NHANES 2005-2018 database. Participants were matched with National Death Index records until 31 December 2019 to determine mortality outcomes. The time-dependent receiver operating characteristic was utilized to identify the most effective index among the prognostic nutritional index (PNI), system inflammation score (SIS), Naples prognostic score (NPS), and controlling nutritional status (CONUT) for predicting mortality. Cox regression models were employed to evaluate the associations of immunonutrition indices with mortality in participants with CKD.

Results

The PNI exhibited the strongest predictive power among the four indices evaluated and the restricted cubic spline analysis revealed a cutoff value of 51 for the PNI in predicting mortality. During a median follow-up of 72 months (39-115 months), a total of 1,762 (weighted 24.26%) CKD participants died from all causes. The Kaplan-Meier curve demonstrated a reduced risk of death for the subjects with a higher PNI compared to those in the lower group. Besides, after adjusting for multiple potential confounders, a higher PNI remained an independent predictor for lower risks of all-cause mortality (HR 0.80, 95%CI: 0.71-0.91, p < 0.001) and cardiovascular disease (CVD) mortality (HR 0.69, 95%CI: 0.55-0.88, p = 0.002) in individuals with CKD.

Conclusion

In CKD, a higher PNI level was significantly associated with lower mortality from all causes and CVD. Thus, the clinical utility of this immunonutrition indicator may facilitate risk stratification and prevent premature death among patients with CKD.

Prognostic Nutritional Index Combined with Triglyceride-Glucose Index to Contrast a Nomogram for Predicting Contrast-Induced Kidney Injury in Type 2 Diabetes Mellitus Patients with Acute Coronary Syndrome After Percutaneous Coronary Intervention

Objective

Our objective was to develop and validate a nomogram model aiming at predicting the risk of contrast-induced acute kidney injury (CI-AKI) following percutaneous coronary intervention (PCI) in patients suffering from type 2 diabetes mellitus (T2DM) and also diagnosed with acute coronary syndrome (ACS).

Methods

The study gathered data from 722 T2DM patients with ACS who received PCI treatment at the Affiliated Hospital of Xuzhou Medical University between February 2019 and December 2022, serving as the training set. Considering the validation set, the study included 217 patients who received PCI at the East Affiliated Hospital of Xuzhou Medical University. The patients were classified into CI-AKI and non-CI-AKI groups. The study employed univariate and multivariate logistic analysis for identifying independent risk factors for CI-AKI, followed by developing a predictive nomogram model for CI-AKI risk using R software. The predictive performance and clinical utility of the nomogram were assessed through internal and external validation, utilizing the areas under the receiver operating characteristic curve (AUC-ROC), the Hosmer-Lemeshow test and calibration correction curve, and decision curve analysis (DCA).

Results

The nomogram comprised four variables: age, estimated glomerular filtration rate (eGFR), triglyceride-glucose (TyG) index, and prognostic nutritional index (PNI). The AUC-ROC were 0.785 (95% confidence interval (CI) 0.729-0.841) and 0.802 (95% CI 0.699-0.905) for the training and validation cohorts, respectively, indicating a high discriminative ability of the nomogram. The calibration assessment and decision curve analysis have substantiated the strong concordance and clinical usefulness of the aforementioned.

Conclusion

The nomogram exhibits favorable discrimination and accuracy, enabling it to visually and individually identify pre-procedure high-risk patients, and possesses a predictive capacity regarding CI-AKI incidence after PCI in patients diagnosed with both T2DM and ACS.