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. 2024 Apr 26;12(1):16.
doi: 10.1186/s40560-024-00729-z.

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

Jia-Jin Chen  1 , Tao-Han Lee  2 , Pei-Chun Lai  3 , Chih-Hsiang Chang  1 , Che-Hsiung Wu  4   5 , Yen-Ta Huang  6
Affiliations

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

Jia-Jin Chen et al. J Intensive Care. .

Abstract

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.

Keywords: Acute kidney injury; Meta-analysis; Prognostic nutritional index; Risk.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Forest plot of prognostic nutritional index diagnostic accuracy: A sensitivity, B specificity, C positive likelihood ratio, and D negative likelihood ratio for acute kidney injury
Fig. 2
Fig. 2
Pooled diagnostic odds ratio (A) and SROC curves (B) of prognostic nutritional index for prediction of AKI. AKI: acute kidney injury; SROC: summary receiver operating characteristic
Fig. 3
Fig. 3
Fagan’s nomogram for prognostic nutritional index as acute kidney injury prediction marker with pre-test probabilities of 15% (A), 25% (B), and 40% (C)
See this image and copyright information in PMC

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