Association of the prognostic nutritional index and geriatric nutritional risk index with clinical outcomes in patients undergoing coronary artery bypass surgery: a systematic review and meta-analysis

Abstract

Background

The association between preoperative prognostic nutritional index (PNI) and geriatric nutritional risk index (GNRI) and clinical outcomes in patients receiving coronary artery bypass surgery (CABG) remains unclear now. This study aimed to clarify the associations of the PNI and the GNRI with clinical outcomes among patients who underwent CABG.

Methods

The PubMed, Embase, and Web of Science databases were searched up to July 11, 2025. Studies that investigated the relationships between the PNI and GNRI and clinical outcomes, such as long-term and short-term mortality and postoperative complications, were included. Odds ratios (ORs) with 95% confidence intervals (CIs) were combined.

Results

Twenty-one observational cohort studies involving 14,523 patients undergoing CABG were included in this meta-analysis. Most studies were retrospective in design, and follow-up periods ranged from in-hospital outcomes to long-term mortality. For PNI, the pooled results demonstrated that a lower PNI was related to an increased risk of long-term mortality (OR =0.91, P<0.001), short-term mortality (OR =0.88, P=0.01), acute kidney injury (AKI) (OR =0.73, P=0.009), major adverse cardiac and cerebrovascular events (OR =0.774, P<0.001), atrial fibrillation (OR =0.92, P=0.02), neurologic complications (OR =0.61, P=0.041), hemorrhage (OR =0.123, P=0.025), hospital-acquired infection (OR =0.472, P<0.001), and intra-aortic balloon pump use (OR =0.372, P<0.001), but the PNI was not associated with the risk of postoperative overall complications (P=0.13) or pulmonary complications (P=0.663). Only three studies evaluated GNRI. The GNRI was only associated with the risk of short-term mortality (OR =0.91; P=0.03), and no significant relationship between the GNRI and AKI (P=0.42) or major adverse cardiac or cerebrovascular events (OR =0.195) was observed.

Conclusions

Based on the current evidence, the PNI was associated with clinical outcomes in patients who underwent CABG, and lower PNI indicated increased risk of postoperative mortality and complications.

Highlight box.

Key findings

• This meta-analysis of 21 observational cohort studies involving 14,523 patients showed that a lower preoperative prognostic nutritional index (PNI) was significantly associated with increased risks of long-term and short-term mortality, acute kidney injury, major adverse cardiac and cerebrovascular events, atrial fibrillation, neurologic complications, hemorrhage, hospital-acquired infection, and intra-aortic balloon pump use after coronary artery bypass grafting (CABG).

• Limited evidence from three studies suggested that a lower geriatric nutritional risk index (GNRI) was associated with increased short-term mortality only.

What is known and what is new?

• Nutritional and immune status are increasingly recognized as important determinants of outcomes after cardiac surgery, and PNI and GNRI have been proposed as simple prognostic markers. However, their specific prognostic value in patients undergoing CABG has not been comprehensively synthesized.

• This study provides focused evidence that lower preoperative PNI is consistently associated with multiple adverse postoperative outcomes in CABG, whereas current evidence for GNRI remains limited.

What is the implication, and what should change now?

• Preoperative PNI may be a practical and noninvasive tool for perioperative risk stratification in CABG patients.

• Greater attention to nutritional assessment before CABG is warranted, and large prospective studies are needed to validate the clinical utility of PNI and GNRI and to determine whether nutritional interventions can improve outcomes.

Introduction

Nutritional status has been increasingly recognized as an important determinant of clinical outcomes in surgical populations, including cardiac surgery patients. The prognostic nutritional index (PNI) and the geriatric nutritional risk index (GNRI) were initially developed as objective tools for assessing systemic nutrition and immune status based on serum albumin, lymphocyte count, and body weight parameters. Both indices have demonstrated prognostic value in various clinical settings, such as oncologic resections and general surgery. Recent evidence has also indicated that these nutritional indices are independent predictors of postoperative outcomes in cardiac surgery patients. For example, a large retrospective study involving patients undergoing coronary artery bypass grafting (CABG) found that a lower preoperative PNI was independently associated with higher short-term and long-term mortality after surgery (n=2,889; PNI independently predicted mortality in multivariate analysis) (1). Moreover, an aggregate systematic review and meta-analysis of cardiac surgery cohorts demonstrated that low preoperative GNRI was significantly associated with increased short- and long-term mortality and postoperative complications such as acute kidney injury (AKI) and infection (2).

In addition, a recent multicenter cohort with over 79,000 surgical patients reported that poorer nutritional status defined by both GNRI and PNI was associated with significantly higher postoperative mortality, and that adding these indices improved predictive accuracy of mortality models beyond traditional risk scores (3). Taken together, these findings support the emerging role of PNI and GNRI as simple, reproducible prognostic markers in cardiac surgical risk stratification, yet their specific associations with CABG outcomes have not been comprehensively elucidated.

In this context, nutritional and inflammatory biomarkers, such as the PNI and the GNRI, have emerged as independent predictors of clinical outcomes in various surgical populations. PNI, calculated as [10 × serum albumin (g/dL)] + [0.005 × total lymphocyte count (/mm³)], and the GNRI, calculated as [1.489 × albumin (g/L)] + [41.7 × (actual body weight/ideal body weight)], have been shown to correlate with postoperative complications, length of hospitalization, and overall survival in gastrointestinal, oncologic, and orthopedic surgeries (4-6). For instance, studies have demonstrated that a low PNI is associated with a two- to three-fold increase in postoperative infection and mortality rates (4-6). Similarly, the GNRI has been validated as a robust tool for predicting adverse outcomes in elderly surgical patients (7,8). Despite their growing clinical use, the predictive value of the PNI and GNRI in patients undergoing CABG remains poorly understood and underexplored.

Therefore, we aimed to investigate association between preoperative PNI and GNRI and clinical outcomes in patients undergoing CABG to establish their utility as simple, noninvasive tools for risk assessment, and postoperative management. We present this article in accordance with the PRISMA reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-1-0033/rc) (9).

Methods

Literature search

PubMed, Embase, and Web of Science databases were searched up to July 11, 2025, with the following terms: geriatric nutritional risk index, GNRI, prognostic nutritional index, PNI, coronary artery bypass grafting, and CABG. The specific search strategy used in PubMed is shown in Figure S1. MeSH terms and free texts were used.

Criteria for inclusion and exclusion

We included studies that met the following criteria: (I) patients who received CABG; (II) the PNI or (and) GNRI was calculated before the surgery with the following formulas: PNI =10 × serum albumin level (g/dL) + 0.005 × total lymphocyte count (cells/mm³) and GNRI =14.89 × albumin level (g/dL) + 41.7 × [current body weight (kg)/ideal body weight (kg)]; (III) the association of the PNI or (and) the GNRI with at least one of the clinical outcomes, including the long-term mortality, short-term mortality, AKI, postoperative complications, major adverse cardiac and cerebrovascular events (MACCEs), atrial fibrillation (AF), neurologic complications, pulmonary complications, hemorrhage, hospital-acquired infection (HAI), and intra-aortic balloon pump (IABP) use, was explored; (IV) odds ratios (ORs) with 95% confidence intervals (CIs) were reported, or enough data were provided for their calculation; and (V) the articles were published in English.

We excluded studies that met the following criteria: (I) a type of letter, editorial, case report, review, or animal trial; and (II) duplicated or overlapping data.

Data extraction

Following information was collected: first author, country, year, sample size, observational indicator, threshold of observational indicator, endpoint, source of OR, OR, and 95% CI.

Endpoints in this meta-analysis included long-term mortality, short-term mortality, AKI, postoperative complications, MACCEs, AF, neurologic complications, pulmonary complications, hemorrhage, HAI, and IABP use.

In this meta-analysis, in-hospital mortality and 30-day mortality were regarded as short-term mortality. One-year mortality was regarded as long-term mortality.

Quality assessment

Quality of included studies was assessed by Newcastle-Ottawa Scale (NOS) score, and studies with an NOS score >5 were defined as high-quality studies (10).

Two investigators independently performed the literature search, selection, data collection, and quality assessment, and all disagreements were resolved by team discussion.

Statistical analysis

Statistical analyses were performed with STATA (version 17.0) software. Heterogeneity between included studies was assessed by the I² statistics. If significant heterogeneity was detected (I²>50%), the random-effects model was applied; otherwise, the fixed-effects model was applied. ORs and 95% CIs were combined to evaluate the associations of the PNI and GNRI with clinical outcomes. Sensitivity analysis was conducted to detect the sources of heterogeneity and assess the stability of the overall results. Moreover, Begg’s funnel plot and Egger’s test were conducted to detect publication bias (11,12). If significant publication bias was detected, the trim-and-fill method was further applied (10).

Results

Literature selection

In total, 145 publications were identified through database searches, and 21 studies meeting the inclusion criteria were included in this meta-analysis (1,13-32). The detailed selection process is shown in Figure 1.

Figure 1.

PRISMA flow diagram of this meta-analysis.

Basic characteristics

Among the included studies, a total of 14,523 patients undergoing CABG were analyzed. Most studies were retrospective cohort designs, with patient ages ranging approximately from 50 to 75 years and varying proportions of males and females across studies. Twenty studies reported associations of the PNI with clinical outcomes, and three studies reported associations of the GNRI with outcomes. All included studies were of high methodological quality (NOS score >5). Detailed study characteristics, including sample size, follow-up duration, and reported outcomes, are summarized in Table 1.

Table 1. Basic characteristics of included studies.

Author	Year	Country	Sample size	Observational indicator	Cutoff value of observational indicator	Endpoint	Source of OR	NOS
Keskin (13)	2018	Turkey	644	PNI	NR	In-hospital mortality, long-term mortality	M	7
Dolapoglu (14)	2019	Turkey	336	PNI	46.5	AKI	M	7
Teker Açıkel (15)	2019	Turkey	149	PNI	46.7	Overall complication, AKI, neurologic complication, hemorrhage, pulmonary complication, short-term mortality	U	6
Engin (16)	2021	Turkey	199	PNI	43.7	AF	M	7
Gucu (17)	2021	Turkey	742	PNI	45.85	Long-term mortality, HCI, stroke, IABP use	M/U	8
Gucu (18)	2021	Turkey	254	PNI	42.9	AKI	M	7
Tasbulak (19)	2021	Turkey	586	PNI	48.8	MACCE	M	8
Aykut (20)	2022	Turkey	455	PNI/GNRI	48/91	AKI	U/M	7
Kwon (21)	2022	Korea	2149	PNI	NR	1-year mortality, overall complication	M	8
Cui (22)	2023	China	879	PNI	48.1	In-hospital mortality	M	8
Ozcan (23)	2023	Turkey	314	PNI	53.13	AF	M	7
Bao (24)	2024	China	1007	PNI/GNRI	48/continuous	AKI	M	8
Demirci (25)	2024	Turkey	131	PNI	44.9	Long-term mortality	M	6
Koyuncu (26)	2024	Turkey	239	PNI	39.1	Long-term mortality	M	7
Kwon (27)	2024	Korea	229	PNI	NR	Overall complication	U	7
Takagi (28)	2024	Japan	632	GNRI	98	30-day mortality, MACCE	M	8
Yilmaz (29)	2024	Turkey	93	PNI	51.76	AF	U	6
Bae (30)	2025	Republic of Korea	983	PNI	NR	1-year mortality, overall mortality	M	8
Liu (31)	2025	China	1173	PNI	44.425	30-day mortality, long-term mortality	M	8
Sun (1)	2025	China	2889	PNI	44.025	30-day mortality, long-term mortality	M	8
Toprak (32)	2025	Turkey	440	PNI	Continuous	Long-term mortality	M	7

AF, atrial fibrillation; AKI, acute kidney injury; ARF, acute renal failure; GNRI, geriatric nutritional risk index; HCI, hospital-acquired infection; IABP, intra-aortic balloon pump; M, multivariate analysis; MACCE, major adverse cardiac and cerebrovascular event; NOS, Newcastle-Ottawa Scale; NR, not reported; OR, odds ratio; PNI, prognostic nutritional index; U, univariate analysis.

Associations between PNI and clinical outcomes in patients who underwent CABG

Based on the pooled results, lower preoperative PNI was associated with increased risk of long-term mortality (OR =0.91; 95% CI: 0.87–0.95; P<0.001; I²=79.4%; P<0.001) (Figure 2). In addition, lower PNI was significantly associated with short-term mortality (OR =0.88; 95% CI: 0.80–0.97; P=0.01; I²=78.0%; P=0.001) (Figure 3A), AKI (OR =0.73; 95% CI: 0.57–0.92; P=0.009; I²=59.4%; P=0.043) (Figure 3B), MACCE (OR =0.774; 95% CI: 0.730–0.819; P<0.001), AF (OR =0.92; 95% CI: 0.85–0.99; P=0.02; I²=0.0%; P=0.727) (Figure S2), neurologic complications (OR =0.61; 95% CI: 0.38–0.98; P=0.041; I²=0.0%; P=0.76) (Figure S3), hemorrhage (OR =0.123; 95% CI: 0.016–0.977; P=0.02), HAI (OR =0.472; 95% CI: 0.343–0.651; P<0.001), and IABP use (OR =0.372; 95% CI: 0.221–0.624; P<0.001) (Table 2).

Figure 2.

Association between prognostic nutritional index and risk of postoperative long-term mortality in patients undergoing coronary artery bypass surgery. CI, confidence interval; OR, odds ratio.

Figure 3.

Association between prognostic nutritional index and risk of postoperative short-term mortality (A) and acute kidney injury (B) in patients undergoing coronary artery bypass surgery. CI, confidence interval; OR, odds ratio.

Table 2. Results of meta-analysis for prognostic nutritional index.

Items	Number of studies	Odds ratio	95% confidence interval	P value	I2 (%)	P value for heterogeneity
Long-term mortality	9	0.91	0.87–0.95	<0.001	79.4	<0.001
Short-term mortality	5	0.88	0.80–0.97	0.01	78.0	0.001
Acute kidney injury	5	0.73	0.57–0.92	0.009	59.4	0.043
Overall complication	3	0.87	0.73–1.05	0.13	90.2	<0.001
Major adverse cardiac and cerebrovascular event	1	0.774	0.730–0.819	<0.001	–	–
Atrial fibrillation	3	0.92	0.85–0.99	0.02	0.0	0.72
Neurologic complication	2	0.61	0.38–0.98	0.041	0.0	0.76
Pulmonary complication	1	0.575	0.099–3.342	0.66	–	–
Hemorrhage	1	0.123	0.016–0.977	0.02	–	–
Hospital-acquired infection	1	0.472	0.343–0.651	<0.001	–	–
Intra-aortic balloon pump use	1	0.372	0.221–0.624	<0.001	–	–

However, PNI was not significantly associated with the incidence of overall complications (OR =0.87; 95% CI: 0.73–1.05; P=0.13; I²=90.2%; P<0.001) (Figure S4) or pulmonary complications (OR =0.575; 95% CI: 0.099–3.342; P=0.66) (Table 2).

Associations between the GNRI and clinical outcomes in patients who underwent CABG

Only three studies investigated the relationship of preoperative GNRI with postoperative outcomes. According to the available evidence, lower GNRI was associated with increased short-term mortality (OR =0.91; 95% CI: 0.83–0.99; P=0.03). No significant associations were observed between GNRI and AKI (OR =0.52; 95% CI: 0.11–2.57; P=0.424; I²=81.9%; P=0.01) (Figure S5) or MACCE (OR =1.44; 95% CI: 0.83–2.50; P=0.19) (Table 3).

Table 3. Results of meta-analysis for geriatric nutritional risk index.

Items	Number of studies	Odds ratio	95% confidence interval	P value	I2 (%)	P value for heterogeneity
Short-term mortality	1	0.91	0.83-0.99	0.03	–	–
Acute kidney injury	2	0.52	0.11-2.57	0.42	81.9	0.019
Major adverse cardiac and cerebrovascular event	1	1.44	0.83-2.50	0.19	–	–

Sensitivity analysis

Sensitivity analysis for long-term mortality was performed by excluding each included study, one at a time, which indicated that our pooled results were stable and that none of the included studies had a significant effect on the overall conclusion (Figure 4).

Figure 4.

Sensitivity analysis about the association between prognostic nutritional index and risk of postoperative long-term mortality in patients undergoing coronary artery bypass surgery. CI, confidence interval.

Publication bias

According to the asymmetric Begg’s funnel plot (Figure 5A) and Egger’s test (P=0.001), significant publication bias was detected. The trim-and-fill method was subsequently used, but no potentially unpublished studies were detected (Figure 5B), which indicated that our results were reliable.

Figure 5.

Begg’s (A) and filled (B) funnel plots about the association between prognostic nutritional index and risk of postoperative long-term mortality in patients undergoing coronary artery bypass surgery. s.e., standard error.

Discussion

This study revealed that preoperative PNI was significantly related to risk of multiple clinical outcomes, such as long-term mortality, short-term mortality, and AKI, among patients who underwent CABG. However, the preoperative GNRI was only associated with short-term mortality according to evidence from one relevant study. Therefore, based on the current evidence, the preoperative PNI is believed to serve as a novel and reliable prognostic indicator for patients undergoing CABG and lower PNI predicts increased risk of worse clinical outcomes.

The significant association between a lower PNI and poorer postoperative outcomes in CABG patients may be explained by the interplay among malnutrition, systemic inflammation, and immune dysfunction. PNI incorporates both serum albumin levels and peripheral lymphocyte counts, two key markers reflecting a patient’s nutritional and immunological status. Hypoalbuminemia is not only indicative of inadequate protein reserves but also serves as a marker of chronic systemic inflammation, which can impair wound healing, delay recovery, and increase susceptibility to postoperative infections (33). Additionally, lymphopenia reflects a suppressed immune response, which is associated with a heightened risk of sepsis and poor tolerance to surgical stress (34). These factors collectively contribute to increased rates of adverse outcomes, such as longer hospital stays, higher incidence of complications (e.g., pneumonia and wound infection), and reduced long-term survival after CABG (31). Previous studies have also shown that malnourished patients undergoing major surgeries often experience impaired cardiac remodeling and compromised myocardial recovery, further exacerbating surgical risk (35).

Given these findings, routine assessment of the PNI prior to CABG could offer valuable prognostic insight and guide perioperative clinical decision-making. For instance, identifying patients with low PNI values may help flag those at an elevated risk for complications and mortality, enabling the implementation of tailored interventions, such as preoperative nutritional optimization, enhanced postoperative monitoring, and more cautious hemodynamic management. Furthermore, integrating the PNI into existing cardiac surgery risk scores could improve their predictive accuracy and support multidisciplinary strategies involving nutritionists and critical care teams. Importantly, the PNI is a cost-effective and easily obtainable parameter derived from routine laboratory tests, making it feasible for widespread clinical use. As our findings suggest, PNI-based risk stratification could play a pivotal role in the preoperative evaluation process, ultimately contributing to better outcomes and resource allocation in CABG patients.

Although a nonsignificant association between the PNI and overall complications or pulmonary complications was observed, three studies reporting overall complications (Figure S4) reported positive findings, and only one study explored the role of the PNI in predicting pulmonary complications. Therefore, we still believe that the preoperative PNI may be associated with the risk of overall and pulmonary complications, which should be further investigated. With respect to the association between the GNRI and AKI, the two included studies reported opposite results (Figure S5). Therefore, the association between the GNRI and the risk of AKI in patients undergoing CABG remains unclear.

In addition to the prognostic associations observed, it is important to consider factors that may contribute to a low preoperative PNI. Low PNI reflects not only poor nutritional status, but also systemic inflammation, immune dysfunction, and underlying comorbidities such as chronic kidney disease, heart failure, and advanced age. Conditions like end-stage renal disease (ESRD) are known to be associated with chronic inflammation and proteinenergy wasting, which can contribute to hypoalbuminemia and lymphopenia—key components of PNI—and thereby could influence surgical risk (36). Furthermore, chronic liver disease, malabsorption syndromes, and malignancy can similarly lead to compromised nutritional and immunologic status. For patients with significant comorbidities, preoperative optimization strategies may be considered. These include comprehensive nutritional assessment and intervention (e.g., dietitian‑guided nutritional support, protein supplementation), management of chronic inflammation and metabolic disturbances, and careful perioperative planning to mitigate risks associated with malnutrition and immune compromise. Tailored interventions to improve nutritional and inflammatory status prior to CABG may potentially improve resilience to surgical stress and postoperative recovery, although further studies are needed to confirm the effectiveness of such strategies in this population.

In addition to the outcomes we analyzed, postoperative myocardial infarction (PMI) is a clinically important adverse event after CABG and has been associated with worse short- and long-term prognosis after surgery (37). Although PMI was not separately analyzed in most included studies of this meta-analysis, it is plausible that preoperative nutritional status reflected by PNI or GNRI may also be relevant to the risk of PMI. Poor nutritional status is linked to systemic inflammation, impaired immune response, and endothelial dysfunction, all of which could contribute to myocardial injury in the perioperative period. Therefore, future studies should explore whether PNI or GNRI has predictive value for PMI after CABG to further expand the clinical utility of nutritional risk stratification in cardiac surgery.

There are several limitations in this meta-analysis. First, the number of studies reporting certain outcomes, such as MACCE and hemorrhage, was limited, which may affect the reliability of these pooled results. Second, only a few studies investigated the association between preoperative GNRI and clinical outcomes in patients undergoing CABG, so the prognostic value of GNRI remains uncertain and warrants further research. Third, the cutoff values of PNI and GNRI varied across studies, and we were unable to determine optimal thresholds due to the lack of individual patient data. Fourth, significant heterogeneity was observed for several outcomes, likely due to differences in study populations, surgical techniques, and follow-up durations, which should be considered when interpreting our results.

Conclusions

In summary, based on the available evidence, preoperative PNI appears to be associated with clinical outcomes in patients undergoing CABG, with lower PNI potentially indicating higher risk of postoperative mortality and complications. However, due to the limitations of this meta-analysis, including heterogeneity and limited data for some outcomes, further high-quality studies are needed to confirm these findings and clarify the role of PNI and GNRI in risk stratification.

Supplementary

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Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.