The prognostic nutritional index is an early predictive marker for surgical site infection after spinal fusion surgery: a nested case-control study

Abstract

Objective

This study aimed to evaluate the predictive value of the preoperative prognostic nutritional index (PNI) for surgical site infection (SSI) following spinal fusion surgery and validate its clinical utility as a simple screening tool.

Methods

A retrospective nested case-control study was conducted on consecutive patients who underwent spinal fusion surgery between October 2014 and October 2024. A total of 220 patients with SSI (cases) were matched with 440 SSI-free patients (controls) by age, sex, and calendar year. Preoperative PNI was calculated based on serum albumin concentration and total peripheral blood lymphocyte count. Conditional logistic regression models were used to assess the independent association between PNI and SSI, with subgroup analyses stratified by disease category (degenerative diseases or spinal deformity).

Results

The proportion of patients with PNI < 50 was significantly higher in cases than in controls (34.5% vs. 22.7%, P = 0.001). Univariate analysis showed that PNI < 50 was associated with an increased SSI risk (OR = 1.794, 95%CI = 1.257–2.562, P = 0.001). After adjusting for confounding factors including diabetes status, estimated blood loss, duration of surgery, drain length, number of surgical levels, surgical region, body mass index, age-adjusted Charlson comorbidity index, and American Society of Anesthesiologists physical status classification, PNI < 50 remained an independent predictor of SSI (OR = 1.568, 95%CI = 1.070–2.298, P = 0.021). Subgroup analysis revealed that the predictive value of PNI was significant in patients with degenerative spinal diseases (OR = 1.814, 95%CI = 1.042–3.156, P = 0.035) but not in those with spinal deformity (P > 0.05).

Conclusion

Preoperative PNI < 50 is an independent early predictive marker for SSI after spinal fusion surgery, particularly in patients with degenerative spinal diseases. Routine PNI assessment can facilitate preoperative risk stratification and individualized infection prevention strategies, improving surgical outcomes.

Introduction

In recent years, spinal fusion surgery has become one of the standard surgical approaches for the treatment of spinal degenerative diseases, scoliosis, and spinal trauma. Despite continuous advancements in surgical techniques, aseptic protocols, and perioperative management strategies, surgical site infection (SSI) remains one of the most challenging complications faced by spine surgeons [1, 2]. SSI not only leads to prolonged hospital stays and substantially increased healthcare costs but, in severe cases, may also result in internal fixation failure, pseudoarthrosis, or even neurological impairment [3]. Such complications often necessitate additional surgical debridement or revision procedures, imposing a considerable burden on both patients and society. Therefore, accurate preoperative identification of patients at high risk for SSI is of critical clinical importance for the development of individualized preventive strategies, optimization of perioperative management, and improvement of postoperative outcomes.

Previous studies have demonstrated that preoperative nutritional status is one of the key determinants influencing outcomes following surgery [4]. Malnutrition not only compromises tissue repair capacity but also impairs immune function, thereby increasing the risk of postoperative infections. Serum albumin, the most traditional nutritional assessment marker, has been widely used to predict postoperative complications [5]. However, albumin levels alone are often affected by factors such as hydration status and hepatic function and primarily reflect nutritional reserves, making them insufficient to comprehensively evaluate the host immune response to surgical stress. Lymphocytes play a crucial mediating role in wound healing, tissue regeneration, and infection defense, and a reduced lymphocyte count often indicates an immunosuppressed state with impaired healing capacity [6]. Consequently, identifying a composite biomarker that simultaneously reflects both nutritional reserves and immune status has become a major focus of surgical risk assessment in recent years.

The prognostic nutritional index (PNI) is a composite parameter calculated based on serum albumin concentration and total peripheral blood lymphocyte count [7, 8]. Originally developed to assess surgical risk and prognosis in patients with gastrointestinal malignancies, the application of PNI has expanded in recent years to include prognostic evaluation in various solid tumors and certain surgical conditions. Compared with albumin or lymphocyte count alone, PNI incorporates both protein reserve and cellular immune function, theoretically providing a more sensitive reflection of an ability to withstand surgical stress and resist postoperative infections. Previous studies have reported that lower preoperative PNI levels are significantly associated with increased postoperative mortality and poor outcomes in patients with hip fractures [9]. Furthermore, in the field of arthroplasty, reduced PNI has been shown to be closely associated with postoperative wound complications and the development of periprosthetic joint infection [10].

Despite the emerging evidence supporting the predictive value of PNI in arthroplasty and fracture populations, studies examining its association with SSI in patients undergoing spinal fusion surgery remain limited. Owing to the unique anatomical characteristics of the spine, the frequent use of internal implants, and relatively prolonged operative times, the risk factors for SSI in spinal surgery differ from those in joint procedures [11, 12]. At present, whether PNI can serve as an independent predictor of SSI following spinal fusion surgery requires further clinical validation. Therefore, the present study aimed to retrospectively analyze the clinical data of patients undergoing spinal fusion surgery, investigate the relationship between preoperative PNI and postoperative SSI, and evaluate its clinical utility as a simple and cost-effective preoperative screening tool. This study seeks to provide scientific evidence to facilitate early identification of high-risk patients and guide timely clinical interventions.

Materials and methods

Study design

This study was designed as a retrospective nested case-control study to evaluate the predictive value of the PNI for SSI following spinal fusion surgery. The study protocol was approved by the Institutional Ethics Committee of our hospital. All procedures were conducted in strict accordance with the principles of the Declaration of Helsinki, and the study was reported in compliance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.

According to the study protocol, all consecutive patients who underwent spinal fusion surgery at our institution between October 2014 and October 2024 were enrolled to form a retrospective cohort. The cohort included patients treated for spinal degenerative diseases and spinal deformities, with a minimum follow-up duration of 1 year. To ensure the relative homogeneity of the study population, patients who underwent revision procedures, tumor-related surgery, spinal trauma surgery, or revision surgery were excluded from the cohort.

The date of SSI diagnosis was defined as the index date. For each patient who developed SSI, two control patients who had not experienced SSI by the corresponding index date were selected from the same cohort. Controls were matched to cases by age, sex, and calendar year. Both cases and controls were restricted to the same surgical calendar year to minimize the potential influence of temporal changes in perioperative care protocols and surgical strategies on the study outcomes.

Perioperative management

Perioperative management constitutes a critical component of the overall effectiveness of spinal surgery and encompasses standardized infection prevention strategies and patient safety protocols. All surgical procedures in this study were performed by a dedicated team of board-certified spine surgeons with extensive clinical experience. This consistent team composition ensured uniformity in surgical techniques, intraoperative decision-making, and postoperative care pathways, thereby minimizing outcome variability attributable to differences in individual surgeon practice patterns.

Perioperative infection prevention measures were strictly implemented in accordance with the standardized protocols of our institution. Prophylactic intravenous antibiotics were administered in strict adherence to the 30-minute rule, defined as delivery of a full therapeutic dose within 30 min prior to skin incision. Cefazolin was selected as the first-line agent because of its broad-spectrum activity against Gram-positive organisms and its favorable pharmacokinetic properties in both soft tissue and bone. In patients with a documented cephalosporin allergy, clindamycin was administered as an alternative.

Intraoperatively, surgical site preparation followed a two-step antiseptic protocol. The operative field was first cleansed with sterile normal saline to remove surface debris, followed by application of povidone-iodine solution with a minimum contact time of 3 min. Draping was performed only after complete air-drying of the antiseptic solution to maximize its antimicrobial efficacy. Sterile adhesive incise drapes were applied, extending at least 15 cm beyond the planned incision margins to establish a broad sterile field. Throughout the procedure, strict aseptic techniques were maintained, including the use of double gloving, sterile surgical gowns, and masks. Intraoperative normothermia was also incorporated into infection prevention strategies, with forced-air warming systems used to maintain core body temperature above 36 °C, thereby reducing the risk of hypothermia-induced immune suppression.

Postoperatively, surgical incisions were covered with sterile absorbable dressings, which were routinely changed every 48 h. Patients were closely monitored for clinical signs of SSI during hospitalization and follow-up, including fever, purulent wound discharge, localized warmth, or elevated inflammatory markers. In cases of suspected SSI, prompt diagnostic evaluations were initiated, including wound cultures, blood cultures, and appropriate imaging studies to assess for deep tissue infection or abscess formation. Targeted antimicrobial therapy was subsequently initiated based on microbiological culture results.

Data collection

Demographic characteristics and perioperative data were collected through the electronic medical record system, including age, sex, American Society of Anesthesiologists (ASA) physical status classification, body mass index (BMI), smoking status, diabetes mellitus, age-adjusted Charlson Comorbidity Index (aCCI) score, preoperative length of hospital stay, intraoperative blood loss, operative time, surgical approach, wound drainage, duration of drainage, number of surgical levels, postoperative antimicrobial prophylaxis, and spinal region.

Attention was paid to laboratory parameters obtained at hospital admission (preoperatively), including serum albumin concentration (albumin, g/L) and total peripheral blood lymphocyte count (total lymphocyte count, TLC, cells/mm³). The PNI was calculated according to previously published formulas and patients were stratified into groups based on established cutoff values [13]. To minimize potential bias, all data were independently extracted and verified by research assistants who were not involved in patient care or study design.

Outcomes

In the present study, the primary outcome was SSI. SSI was classified as superficial incisional, deep incisional, or organ/space infection. The diagnosis of SSI was established in accordance with the criteria defined by the Centers for Disease Control and Prevention (CDC) [14]. All cases with ambiguous or borderline diagnostic features were independently reviewed and adjudicated by senior authors to ensure accurate identification and classification.

Statistical analysis

To minimize the influence of confounding factors on the study findings, a nested case-control design was adopted, in which selected confounders were partially balanced through matching. To further account for the effects of unmatched covariates, conditional logistic regression models were applied. Multivariable regression results are presented as an unadjusted (crude) model, a minimally adjusted model, and a fully adjusted model. Variables with a P value < 0.05 in univariable analyses were entered into the adjusted model.

Given the clinical and procedural differences between spinal deformity and degenerative spinal diseases, subgroup analyses were additionally performed beyond the primary analysis. Patients were stratified according to disease category, and the association between PNI and SSI was examined separately within each subgroup.

All statistical analyses were conducted using the SPSS 27. Odds ratio (OR) and corresponding 95% confidence interval (CI) were calculated to estimate the strength of the association between the PNI and SSI. All statistical tests were two-sided, and a P value < 0.05 was considered statistically significant.

Results

Baseline information

A total of 220 patients with SSI (cases) and 440 SSI-free patients (controls) matched by age and sex were included in this nested case-control study. The baseline characteristics of the two groups are summarized in Table 1. No statistically significant differences were observed between cases and controls in terms of age (54.3 ± 9.6 years vs. 55.2 ± 12.1 years, P = 0.336), sex distribution (female: 54.5% vs. 53.6%; male: 45.5% vs. 46.4%, P = 0.825), smoking status (smokers: 21.8% vs. 20.9%, P = 0.788), preoperative hospital stay (3.1 ± 1.3 days vs. 2.9 ± 1.7 days, P = 0.125), drain placement (91.4% vs. 95.0%, P = 0.068), surgical approaches (anterior: 5.0% vs. 8.2%; posterior: 86.4% vs. 86.8%; combined: 8.6% vs. 5.0%, P = 0.074), and postoperative antimicrobial prophylaxis (93.6% vs. 94.1%, P = 0.818).

Table 1.

Subject characteristics for cases and matched controls

Variables	Cases (N = 220)	Controls (N = 440)	P value
Age, years	54.3 ± 9.6	55.2 ± 12.1	0.336
Sex			0.825
Female	120 (54.5%)	236 (53.6%)
Male	100 (45.5%)	204 (46.4%)
Smoking status			0.788
Yes	48 (21.8%)	92 (20.9%)
No	172 (78.2%)	348 (79.1%)
Diabetes status			< 0.001*
Yes	69 (31.4%)	78 (17.7%)
No	151 (68.6%)	362 (82.3%)
BMI, kg/m2	27.3 ± 3.1	25.1 ± 4.1	< 0.001*
aCCI	2.3 ± 1.0	1.7 ± 0.6	< 0.001*
Preoperative hospital stay, days	3.1 ± 1.3	2.9 ± 1.7	0.125
Estimated blood loss, ml	323.3 ± 108.1	305.1 ± 110.2	0.045*
Duration of surgery, min	225.5 ± 99.7	201.0 ± 79.3	0.001*
ASA score	1.8 ± 0.7	1.4 ± 0.6	< 0.001*
Drain placement			0.068
Yes	201 (91.4%)	418 (95.0%)
No	19 (8.6%)	22 (5.0%)
Drain length, days	4.7 ± 1.2	3.9 ± 1.1	< 0.001*
Surgical approaches			0.074
Anterior	11 (5.0%)	36 (8.2%)
Posterior	190 (86.4%)	382 (86.8%)
Combined	19 (8.6%)	22 (5.0%)
Spinal region			0.037*
Cervical	9 (4.1%)	23 (5.2%)
Thoracic	19 (8.6%)	52 (11.8%)
Lumbar	115 (52.3%)	257 (58.4%)
Multiple	77 (35.0%)	108 (24.5%)
Number of surgical levels	5.7 ± 1.6	3.9 ± 1.2	< 0.001*
Postoperative antimicrobial prophylaxis			0.818
Yes	206 (93.6%)	414 (94.1%)
No	14 (6.4%)	26 (5.9%)
Nutritional status			0.001*
PNI < 50	76 (34.5%)	100 (22.7%)
PNI ≥ 50	144 (65.5%)	340 (77.3%)

BMI body mass index, aCCI age-adjusted Charlson comorbidity index, ASA American Society of Anesthesiologists, PNI prognostic nutritional index

*P<0.05

In contrast, several clinical and surgical variables showed significant differences between the two groups. Cases had a significantly higher proportion of diabetes mellitus compared with controls (31.4% vs. 17.7%, P < 0.001). The BMI was notably higher in cases (27.3 ± 3.1 kg/m²) than in controls (25.1 ± 4.1 kg/m², P < 0.001). The aCCI was also elevated in the case group (2.3 ± 1.0 vs. 1.7 ± 0.6, P < 0.001). Regarding surgical-related parameters, cases experienced greater estimated blood loss (323.3 ± 108.1 ml vs. 305.1 ± 110.2 ml, P = 0.045), longer duration of surgery (225.5 ± 99.7 min vs. 201.0 ± 79.3 min, P = 0.001), and higher ASA scores (1.8 ± 0.7 vs. 1.4 ± 0.6, P < 0.001). The drain length was significantly prolonged in cases (4.7 ± 1.2 days vs. 3.9 ± 1.1 days, P < 0.001). For the spinal region, cases had a higher proportion of multiple spinal segments involvement (35.0% vs. 24.5%) compared with controls (P = 0.037). Additionally, the number of surgical levels was significantly greater in cases (5.7 ± 1.6 vs. 3.9 ± 1.2, P < 0.001). Importantly, nutritional status differed significantly between the two groups: the proportion of patients with PNI < 50 was higher in cases (34.5%) than in controls (22.7%, P = 0.001).

Multivariate logistic regression

To evaluate the independent association between PNI and SSI risk, multivariate logistic regression analyses were conducted with three models (Table 2). In the crude model (model a, without adjusting for any covariates), PNI < 50 was significantly associated with an increased SSI risk (OR = 1.794, 95%CI = 1.257–2.562, P = 0.001). After adjusting for BMI, aCCI, and ASA score (model b, minimally adjusted model), the association remained statistically significant (OR = 1.720, 95%CI = 1.178–2.511, P = 0.005). In the fully adjusted model (model c), which further adjusted for diabetes status, estimated blood loss, duration of surgery, drain length, number of surgical levels, and surgical region, PNI < 50 still independently predicted a higher SSI risk (OR = 1.568, 95%CI = 1.070–2.298, P = 0.021). These results indicate that PNI is an independent predictive marker for SSI after spinal fusion surgery, regardless of other potential confounding factors.

Table 2.

Relationship between nutritional status and SSI

Variable	Crude model a	Minimally adjusted model b	Fully adjusted model c
Nutritional status
PNI < 50	1.794 (1.257–2.562) P = 0.001*	1.720 (1.178–2.511) P = 0.005*	1.568 (1.070–2.298) P = 0.021*
PNI ≥ 50	Ref	Ref	Ref

Values are odds ratio (OR) (95%CI)

BMI body mass index, aCCI age-adjusted Charlson comorbidity index, ASA American Society of Anesthesiologists, PNI prognostic nutritional index

^a Crude model: we did not adjust other covariants

^b Minimally adjusted model: we adjusted BMI, aCCI and ASA score

^c Fully adjusted model: we adjusted diabetes status, estimated blood loss, duration of surgery, drain length, number of surgical levels, surgical region, BMI, aCCI and ASA score

*P<0.05

Subgroup analysis

Subgroup analyses were performed to explore the consistency of the association between PNI and SSI risk across different disease categories (degenerative diseases and deformity), and the results are shown in Table 3. For patients with degenerative diseases, PNI < 50 was significantly associated with an increased SSI risk in all three models. In the crude model, the OR was 2.076 (95%CI = 1.642–2.624, P = 0.001). After minimal adjustment (BMI, aCCI, ASA score), the OR was 1.909 (95%CI = 1.014–3.596, P = 0.045). In the fully adjusted model, the association remained significant (OR = 1.814, 95%CI = 1.042–3.156, P = 0.035).

Table 3.

Relationship between nutritional status and SSI stratified by disease categories

Variable	Crude model a	Minimally adjusted model b	Fully adjusted model c
Nutritional status
Degeneration
PNI < 50	2.076 (1.642–2.624) P = 0.001*	1.909 (1.014–3.596) P = 0.045*	1.814 (1.042–3.156) P = 0.035*
PNI ≥ 50	Ref	Ref	Ref
Deformity
Nutritional status
PNI < 50	1.579 (0.803–3.106) P = 0.186	1.417 (0.858–2.340) P = 0.174	1.318 (0.884–1.964) P = 0.176
PNI ≥ 50	Ref	Ref	Ref

Values are odds ratio (OR) (95%CI)

BMI body mass index, aCCI age-adjusted Charlson comorbidity index, ASA American Society of Anesthesiologists, PNI prognostic nutritional index

^a Crude model: we did not adjust other covariants

^b Minimally adjusted model: we adjusted BMI, aCCI and ASA score

^c Fully adjusted model: we adjusted diabetes status, estimated blood loss, duration of surgery, drain length, number of surgical levels, surgical region, BMI, aCCI and ASA score

*P<0.05

In contrast, for patients with deformity, no statistically significant association was observed between PNI and SSI risk in any of the models. The OR values were 1.579 (95%CI = 0.803–3.106, P = 0.186) in the crude model, 1.417 (95%CI = 0.858–2.340, P = 0.174) in the minimally adjusted model, and 1.318 (95%CI = 0.884–1.964, P = 0.176) in the fully adjusted model. These findings suggest that the predictive value of PNI for SSI risk is more prominent in patients with degenerative spinal diseases than in those with spinal deformity.

Discussion

The present study aimed to evaluate the predictive value of the preoperative PNI for SSI following spinal fusion surgery using a nested case-control design. The principal findings demonstrated that a preoperative PNI < 50 was independently associated with an increased risk of postoperative SSI, even after adjustment for multiple confounding factors, including diabetes mellitus, BMI, operative duration, and overall comorbidity burden. Notably, this predictive effect was particularly pronounced in patients with degenerative spinal diseases, whereas no statistically significant association was observed in patients undergoing surgery for spinal deformities. These findings extend the clinical applicability of PNI in the field of spinal fusion surgery and highlight its potential utility as a simple and cost-effective tool for preoperative risk stratification.

Association between PNI and SSI

Nutritional status and immune competence are closely linked to the risk of postoperative infection. PNI integrates serum albumin concentration (a surrogate marker of nutritional reserve) and total lymphocyte count (which reflects cellular immune function), thereby providing a composite assessment of the ability to tolerate surgical stress and resist infection [15, 16]. Previous studies have established the prognostic value of PNI in predicting postoperative complications in patients undergoing hip fracture surgery, arthroplasty, and gastrointestinal malignancy surgery [17–19]. However, its role in spinal fusion surgery had not been clearly defined prior to this investigation.

Spinal fusion procedures involve unique anatomical complexity, frequent use of internal fixation devices, and relatively prolonged operative times, all of which substantially increase the risk of SSI compared with other orthopedic procedures [20, 21]. In the fully adjusted model, patients with a preoperative PNI < 50 exhibited a 1.5-fold higher risk of developing SSI than those with a PNI ≥ 50 (95% CI = 1.070–2.298, P = 0.021). These findings suggest that PNI effectively captures the combined impact of malnutrition and immunosuppression in this specific surgical population.

The mechanisms underlying the association between low PNI and increased SSI risk are likely multifactorial. Serum albumin plays a critical role in tissue repair and maintenance of vascular integrity; hypoalbuminemia has been shown to impair wound healing and reduce the efficacy of antimicrobial agents at the surgical site [22]. Lymphocytes are essential for pathogen clearance and regulation of inflammatory responses, and a reduced lymphocyte count indicates compromised cellular immunity. These effects may be particularly detrimental in the context of surgical trauma and implanted hardware [23]. By integrating these two components, PNI provides a more comprehensive assessment of host defense capacity than either marker alone, which may explain its superior predictive performance for SSI compared with isolated nutritional or immune indices.

Subgroup differences

One notable finding of the present study is the heterogeneity in the predictive value of PNI across different disease subgroups. Among patients with degenerative spinal diseases, a preoperative PNI < 50 remained a significant predictor of SSI in the fully adjusted model (OR = 1.814, 95% CI = 1.042–3.156, P = 0.035). In contrast, no statistically significant association was observed between PNI and SSI in patients undergoing surgery for spinal deformities. Several factors may account for this discrepancy.

First, spinal deformity surgery is typically more complex, characterized by longer operative times, greater intraoperative blood loss, and more extensive soft tissue dissection [24]. These factors may introduce stronger confounding effects that attenuate or obscure the predictive contribution of PNI. Second, patients with spinal deformities often exhibit distinct physiological characteristics, such as younger age at surgery or different comorbidity profiles, which may modify the relationship between nutritional status and infection risk [25]. Third, the sample size of the deformity subgroup may have been insufficient to detect a statistically significant association, raising the possibility of a type II error. Future large-scale cohort studies focusing specifically on patients with spinal deformities are warranted to validate these findings.

Clinical implications

Identifying PNI as an independent predictor of SSI carries important clinical implications. Preoperative PNI assessment is simple, noninvasive, and cost-effective, as it relies on routinely obtained laboratory parameters in standard clinical practice. For patients with a PNI < 50, targeted interventions can be implemented, such as preoperative nutritional supplementation (increased protein intake or oral nutritional supplements) and immune optimization, to improve preoperative nutritional and immune status prior to surgery.

Furthermore, high-risk patients may benefit from intensified perioperative infection prevention strategies, including stricter glycemic control, optimized antimicrobial prophylaxis when clinically indicated, and meticulous surgical techniques aimed at minimizing tissue trauma. By incorporating PNI into preoperative risk assessment, clinicians can develop individualized perioperative management strategies, reduce the incidence of SSI, improve patient outcomes, and ultimately decrease healthcare costs associated with prolonged hospitalization and revision surgery.

Beyond preoperative risk stratification and intervention, PNI can also provide valuable guidance for postoperative monitoring and follow-up. Patients with low preoperative PNI who undergo spinal fusion surgery may require more frequent postoperative assessments of wound healing, inflammatory markers, and nutritional status, allowing for early detection of incipient SSI and prompt initiation of treatment. This proactive approach not only improves the likelihood of successful infection management but also reduces the risk of severe complications, such as deep SSI, osteomyelitis, or implant failure, which can significantly impair patient recovery and quality of life. Additionally, the use of PNI can facilitate patient education, as clinicians can use this simple index to inform patients about their infection risk and the importance of preoperative nutritional optimization, thereby enhancing patient compliance with intervention strategies and improving overall perioperative outcomes.

Strengths and limitations

This study has several notable strengths. The nested case-control design, with matching by age, sex, and calendar year, effectively balanced key confounding factors and minimized temporal bias. The relatively large sample size (220 cases and 440 controls), together with a minimum follow-up duration of 1 year, provided adequate statistical power to detect clinically meaningful associations. Comprehensive adjustment for multiple established risk factors, including diabetes mellitus, BMI, ASA, and operative parameters, further strengthened the validity of PNI as an independent predictor of SSI. In addition, subgroup analyses stratified by disease category offered valuable insights into the heterogeneous applicability of PNI across different patient populations.

Nevertheless, several limitations should be acknowledged. First, the retrospective nature of the study may have introduced selection bias, as patients with incomplete laboratory data or follow-up information were excluded. Second, certain potential confounders, such as occult sources of infection, liver dysfunction, and immunosuppressive medications were not available for analysis and may have influenced the observed associations. Third, the single-center study design limits the generalizability of the findings, underscoring the need for multicenter studies to validate the predictive value of PNI in diverse populations. Finally, this study did not assess the dynamic trends of PNI, which limits its effectiveness in assessing long-term or chronic nutritional status. Future research should incorporate this dynamic data.

Conclusions

In conclusion, a preoperative PNI < 50 is an independent predictor of SSI following spinal fusion surgery, particularly among patients with degenerative spinal diseases. Routine preoperative assessment of PNI may facilitate early identification of high-risk patients and guide targeted preventive interventions to mitigate SSI risk. As a simple and cost-effective tool, PNI holds promise for optimizing perioperative management and improving surgical outcomes in patients undergoing spinal fusion.

Authors’ contributions

Bin Wang: Writing-original draft. Haoran Zhang: Writing-original draft. Shibin Shen: Investigation. Haoran Huang: Investigation. Zhenggang Zhou: Investigation. Jianlin Ma: Writing-review & editing. Liang Li: Writing-review & editing.

Funding

This work was supported by the Project (RDEB2025-18) Supported By Peking University People’s Hospital Research And Development Funds.

Data availability

The datasets generated for this study are available on request from the corresponding authors.

Declarations

Ethics approval and consent to participate

This research was performed in accordance with the guidelines as set out by the Declaration of Helsinki. Ethical approval for the project was obtained from the Peking University People’s Hospital Institutional Review Board-2025PHB476-001. Informed consent was obtained from all patients.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.