Geriatric Nutritional Risk Index as a Predictor of Outcomes After Spinal Deformity Surgery in Elderly Patients

Abstract

Study Design

Retrospective cohort study.

Objectives

The Geriatric Nutritional Risk Index (GNRI) is widely applied to evaluate malnutrition in older adults, yet its relevance in spinal deformity surgery is unclear. This study examined the relationship between nutritional status before surgery, as assessed by GNRI, and postoperative outcomes in geriatric patients undergoing spinal deformity surgery.

Methods

The 2008-2023 ACS-NSQIP database was queried for patients aged ≥65 years who underwent spinal deformity surgery. Patients were stratified by GNRI score: normal (>98), malnourished (92-98), or severely malnourished (<92). The independent association and predictive value of GNRI were assessed in comparison to the 5-item modified Frailty Index (mFI-5) and chronological age for perioperative outcomes, including length of stay, non-home discharge, and 30-day postoperative complications.

Results

A total of 2186 patients were included: 1705 (78%) had normal nutrition, 332 (15.2%) were malnourished, and 149 (6.8%) were severely malnourished. Malnourished status was independently associated with significantly greater odds of wound disruption (OR 3.3, P = .014), prolonged mechanical ventilation (OR 2.2, P = 0.019), postoperative transfusion (OR 1.5, P = .001), increased transfusion volume (coefficient 0.452, P = .044), and non-home discharge (OR 1.6, P < .001) compared to normal patients. In receiver operating characteristic analyses, GNRI demonstrated superior discriminatory ability compared with mFI-5 (P = 0.394, P = .645, P = .179, P = .113, P = .014, P = .233) and age (P = .277, P = .074, P = .039, P = .167, P < .001, P < .001) for predicting wound disruption, superficial surgical site infection, prolonged mechanical ventilation, unplanned intubation, the need for transfusion, and prolonged hospitalization.

Conclusions

Preoperative malnutrition, defined by GNRI, is correlated with a greater risk of adverse outcomes following spinal deformity surgery in older adults, highlighting the importance of incorporating nutritional assessment into preoperative evaluation in this population.

Introduction

Adult spinal deformity (ASD) is an etiologically multifactorial condition whose incidence is rising disproportionately among older adults. Previous studies estimated that spinal deformities affect approximately 32%–68% of the geriatric population.^1,2 The frequency and complexity of surgical corrections for ASD have grown steadily, reflecting both the expanding aging population and the substantial improvements in quality of life and pain relief achieved through operative management.^3-6 Advances in surgical techniques, spinal instrumentation, and alignment strategies have further contributed to better postoperative outcomes in this population.^7,8 Despite these improvements, ASD surgery continues to carry a high risk of postoperative morbidity, including perioperative complications, prolonged hospitalization, and discharge to rehabilitation or nursing facilities, all of which negatively affect outcomes and substantially elevate healthcare costs.^1,4,9-12 As the number of elderly patients undergoing deformity correction increases, there is a critical need for refined risk stratification tools to identify predictors of adverse outcomes. Such predictors can inform preoperative optimization, guide patient selection, and reduce both morbidity and resource utilization.

Among potential patient-specific risk factors, age, comorbidity burden, and nutritional status are particularly important determinants of surgical outcomes.^5,9,10 However, unlike the former two predictors, the impact of preoperative malnutrition on postoperative morbidity in geriatric patients undergoing deformity correction remains insufficiently characterized. Malnutrition, a modifiable and prevalent condition affecting roughly 22% of hospitalized elderly patients,^13-16 has been linked to impaired physical function, delayed recovery, and increased healthcare expenditures.^14,17 The Geriatric Nutritional Risk Index (GNRI) is a validated tool for assessing the risk of malnutrition in older adults.^13,15,16 In spine surgery, lower GNRI values have been associated with increased rates of perioperative complications, extended hospital stay, and mortality.^13,16,18 Despite evidence suggesting GNRI’s favorable performance, its use for prognostic evaluation in elderly patients undergoing ASD surgery remains limited.^13,19

Accordingly, this study aimed to evaluate the role and prognostic value of GNRI, in comparison with the 5-item modified frailty index (mFI-5) and chronological age, in predicting postoperative outcomes, including complications, hospital length of stay, and non-home discharge, among geriatric patients undergoing surgery for ASD.

Methods

Data Source

The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) is a large, multi-institutional registry that prospectively collects standardized data on de-identified surgical patients from more than 700 participating hospitals nationwide, in compliance with the Health Insurance Portability and Accountability Act requirements. The database contains comprehensive information on patient demographics, operative characteristics, and 30-day perioperative outcomes, including complications and mortality. Trained Surgical Clinical Reviewers perform patient sampling and data collection, and data quality is ensured through routine Inter-Rater Reliability evaluations.^20,21 Previous reports have demonstrated a high degree of accuracy, with inter-rater disagreement rates consistently below 2%. ²²

Study Design

This retrospective cohort study was conducted using data from the ACS-NSQIP registry between 2008 and 2023. Patients aged 65 years and older who underwent spinal deformity surgery were identified through relevant Current Procedural Terminology (CPT) codes. Additionally, individuals who had spine procedures without deformity-specific CPT codes were included if they had a diagnosis of spinal deformity based on International Classification of Diseases (ICD) codes (Supplemental Table 1). Since the dataset is fully de-identified, institutional review board approval was not required. Data supporting this work are available from the authors upon reasonable request.

Eligibility Criteria

To focus exclusively on routine geriatric patients undergoing spinal deformity surgery, patients were excluded according to the following criteria: (1) spine procedures irrelevant to deformity correction; (2) non-elective surgeries; (3) concomitant unrelated procedures during the same anesthesia session; (4) treatment for infections, fractures, or tumors; (5) age <65 years; (6) preoperative ventilator dependence; (7) disseminated malignancy; (8) systemic sepsis prior to surgery; (9) hospital stay >365 days; (10) preoperative acute kidney injury; (11) being on dialysis preoperatively; (12) presence of ascites prior to surgery; (13) incomplete data on age, gender, weight, height, or preoperative albumin preventing GNRI calculation; (14) procedures not performed by neurosurgical or orthopedic teams; or (15) surgeries not conducted under general anesthesia.

Baseline Variables

Baseline variables collected included: (1) patient age, (2) gender, (3) height, (4) weight, (5) race, (6) preoperative functional health status, (7) serum albumin and hematocrit levels prior to surgery, (8) American Society of Anesthesiologists (ASA) physical status classification, (9) smoking history within 12 months, and (10) presence of comorbidities. Recorded comorbid conditions included: (1) bleeding disorders, (2) congestive heart failure within 30 days preoperatively, (3) diabetes mellitus requiring oral agents or insulin, (4) history of severe chronic obstructive pulmonary disease, (5) hypertension requiring medication, (6) use of immunosuppressive therapy, (7) preoperative systemic inflammatory response syndrome (SIRS), and (8) transfusion of one or more units of whole blood or packed red blood cells within 72 hours before surgery.

The GNRI has been used to assess nutritional status and estimate the risk of morbidity and mortality among hospitalized elderly patients.^13,16 It is calculated using the formula proposed by Bouillanne et al: GNRI = [14.89 × serum albumin (g/dL)] + [41.7 × (actual body weight/ideal body weight)]. ²³ Ideal body weight (WLo) is determined using the Lorentz formula according to sex and height (cm): WLo (males) = height − 100 − [(height − 150)/4] and WLo (females) = height − 100 − [(height − 150)/2.5]. ¹³ To prevent underestimation of malnourishment in overweight or obese individuals, the weight/WLo ratio was capped at 1, consistent with prior studies.^13,16 Patients were stratified into three nutritional risk groups based on GNRI values: normal (GNRI > 98), malnourished (GNRI 92-98), and severely malnourished (GNRI < 92).

Body mass index (BMI) was calculated utilizing the patients’ height and weight based on the Quetelet index. ²⁴ Frailty was evaluated using the mFI-5, as defined in previous literature.^25-27 One point was assigned for the presence of each of the following variables recorded in the ACS-NSQIP dataset: preoperative functional dependence, diabetes mellitus requiring oral agents or insulin, history of severe chronic obstructive pulmonary disease, hypertension requiring medication, and congestive heart failure within 30 days before surgery. The cumulative mFI-5 score ranged from 0 to 5. Anemia was defined as a hematocrit level <41% for males and <36% for females.

Outcomes

The primary outcome was the occurrence of any postoperative complication, excluding blood transfusions, within 30 days after surgery. Secondary outcome variables included: (1) major complications, (2) minor complications, (3) medical complications, (4) surgical complications, (5) specific perioperative complications, (6) hospital readmission, (7) unplanned reoperations, (8) length of total hospital stay, (9) total operative time, (10) volume of postoperative blood transfusions, (11) discharge disposition, and (12) 30-day perioperative mortality. The classification of postoperative complications is summarized in Figure 1.^28,29 Hospital length of stay was dichotomized as standard or prolonged, with prolonged stays defined as those exceeding the 80th percentile of the cohort distribution (i.e., greater than 9 days).

Figure 1.

Classification of perioperative complications. CPR, cardiopulmonary resuscitation. CVA, cerebrovascular accident. SSI, surgical site infection

Statistical Analysis

Descriptive statistics were presented as means with standard deviations for continuous variables and as frequencies with percentages for categorical variables. For univariate analyses, categorical variables were compared using the χ² test or Fisher’s exact test, and continuous variables were analyzed using independent-sample t tests. Variables with >20% missing values were excluded from multivariable analysis, whereas those with ≤20% missing data were imputed using multiple imputation by chained equations. ³⁰ Baseline variables exhibiting a univariate correlation with P < .2 were included in multivariable regression models. To evaluate the independent correlation between GNRI category and categorical outcome variables, multivariable logistic regression was used, adjusting for relevant baseline covariates. For continuous outcome variables, multivariable linear regression was applied. Model selection was performed using a backward stepwise method based on the Akaike Information Criterion. Patients classified as having normal GNRI scores were designated as the reference group in all analyses. Albumin and BMI, as intrinsic components of the GNRI calculation, were included for descriptive purposes only and were intentionally excluded from all multivariable analyses to avoid collinearity. As a sensitivity analysis, GNRI was additionally modeled as a continuous variable in multivariable regression analyses. Results were presented as odds ratios (ORs) or coefficients with corresponding 95% confidence intervals (CIs). Receiver operating characteristic (ROC) curve analyses were used to assess the discriminatory performance of GNRI, mFI-5, and age for predicting postoperative outcomes. All statistical analyses were conducted in RStudio version 4.4.2 (R Foundation for Statistical Computing, Vienna, Austria). ³¹ All tests were two-tailed, and P < 0.05 was considered statistically significant.

Results

Participants

A total of 204 480 patient records were initially retrieved from the ACS-NSQIP dataset. Following application of the exclusion criteria, 202 294 patients were excluded for the following reasons: age <65 years (n = 127 907), missing data on age, gender, weight, height, or preoperative albumin (n = 37 842), non–spinal deformity pathologies (n = 36 252), non-elective procedures (n = 203), preoperative dialysis (n = 12), disseminated cancer (n = 47), preoperative acute kidney injury (n = 2), preoperative dependence on a ventilator (n = 6), preoperative systemic sepsis (n = 6), presence of ascites preoperatively (n = 2), procedures not performed under general anesthesia (n = 7), and surgeries conducted by non-orthopedic or non-neurosurgical teams (n = 8). No patients had hospitalizations exceeding 365 days. After exclusions, 2186 patients satisfied all inclusion criteria and were included in the analysis (Figure 2). Among these, 1705 (78.0%) had a normal nutritional status, 332 (15.2%) were classified as malnourished, and 149 (6.8%) were severely malnourished.

Figure 2.

Flowchart depicting the patient selection process for study inclusion. ACS-NSQIP, American College of Surgeons National Surgical Quality Improvement Program

Baseline Variables

Patients with normal nutritional status had a higher BMI (29.7 ± 5.9 kg/m²) compared with both malnourished (28.7 ± 6.3 kg/m²) and severely malnourished (28.0 ± 6.5 kg/m²) groups. Similarly, preoperative serum albumin levels were highest among normal patients (4.2 ± 0.3 g/dL) and lower among malnourished (3.6 ± 0.2 g/dL) and severely malnourished (3 ± 0.4 g/dL) patients. The proportion of racial minority patients was greater in the severely malnourished group compared with the normal group (14.4% vs 9.4%; P = .039). Preoperative functional dependence was significantly more common among malnourished (6%; P = .006) and severely malnourished (10.8%; P < .001) patients compared with normal patients (3.7%). Patients with normal nutritional status had a significantly higher proportion of patients with ASA Class I–II designation (29.4%) than those who were malnourished (23.5%; P = .001) or severely malnourished (14.2%; P < .001). Frailty or severe frailty was also significantly more prevalent among severely malnourished patients (32.4%) than among normal patients (21.5%; P = .006). With respect to comorbidities, preoperative anemia was significantly more frequent among malnourished (40.1%; P < .001) and severely malnourished (68.5%; P < .001) patients compared with those who were normal (27.2%). Severely malnourished patients also demonstrated significantly higher rates of preoperative SIRS (3.4% vs 0.9%; P = .022) and preoperative transfusion (2.7% vs 0.7%; P = .034) compared to normal patients. Regarding procedural characteristics, severely malnourished patients underwent osteotomy significantly less frequently than normal patients (32.8% vs 43.4%; P = .005; Table 1).

Table 1.

Baseline Variables of the Patients

	Normal (n = 1705)	Malnourished (n = 332)		Severely malnourished (n = 149)		Total (n = 2186)
	N (%)	N (%)	P	N (%)	P	N (%)
Age group, years
65-74	1200 (70.4)	230 (69.3)	0.4	96 (64.4)	0.137	1526 (69.8)
75-84	476 (27.9)	97 (29.2)		48 (32.2)		621 (28.4)
+85	29 (1.7)	5 (1.5)		5 (3.4)		39 (1.8)
Gender
Female	1037 (60.8)	209 (63)	0.505	90 (60.4)	0.99	1336 (61.1)
Male	668 (39.2)	123 (37)		59 (39.6)		850 (38.9)
Body mass index (kg/m2, mean ± SD)	29.7 ± 5.9	28.7 ± 6.3		28 ± 6.5		29.4 ± 6
Serum albumin (g/dL, mean ± SD)	4.2 ± 0.3	3.6 ± 0.2		3 ± 0.4		4.1 ± 0.5
Race*
White	1460 (90.6)	293 (90.4)	0.296	118 (85.6)	0.039	1871 (90.3)
Black or African American	91 (5.7)	19 (5.9)		10 (7.2)		120 (5.8)
Asian	38 (2.4)	8 (2.5)		5 (3.6)		51 (2.5)
American Indian or Alaska Native	6 (0.4)	4 (1.2)		0		10 (0.5)
Native Hawaiian or Pacific Islander	3 (0.2)	0		2 (1.4)		5 (0.2)
Other	11 (0.7)	0		3 (2.2)		14 (0.7)
Functional health status prior to surgery**
Independent	1638 (96.3)	310 (94)	0.006	132 (89.2)	<0.001	2080 (95.4)
Partially dependent	62 (3.6)	16 (4.8)		14 (9.5)		92 (4.2)
Totally Dependent	2 (0.1)	4 (1.2)		2 (1.4)		8 (0.4)
ASA classification***
1	8 (0.5)	2 (0.6)	0.001	2 (1.4)	<0.001	12 (0.5)
2	493 (28.9)	76 (22.9)		19 (12.8)		588 (26.9)
3	1163 (68.2)	234 (70.5)		112 (75.7)		1509 (69.1)
4	41 (2.4)	20 (6)		15 (10.1)		76 (3.5)
Frailty severity**
Not frail	422 (24.8)	79 (23.9)	0.106	33 (22.3)	0.006	534 (24.5)
Prefrail	914 (53.7)	160 (48.5)		67 (45.3)		1141 (52.3)
Frail	333 (19.6)	83 (25.2)		40 (27)		456 (20.9)
Severely frail	33 (1.9)	8 (2.4)		8 (5.4)		49 (2.2)
History of smoking within one year	142 (8.3)	29 (8.7)	0.892	13 (8.7)	0.989	184 (8.4)
Comorbidities
Anemia^	459 (27.2)	132 (40.1)	<0.001	102 (68.5)	<0.001	693 (32)
Bleeding disorders	48 (2.8)	6 (1.8)	0.354	7 (4.7)	0.203	61 (2.8)
DM treated with medication	301 (17.7)	65 (19.6)	0.449	32 (21.5)	0.292	398 (18.2)
Hypertension treated with medication	1197 (70.2)	234 (70.5)	0.972	106 (71.1)	0.884	1537 (70.3)
CHF within 30 days preoperatively	33 (1.9)	7 (2.1)	0.829	5 (3.4)	0.225	45 (2.1)
Preoperative SIRS^^	16 (0.9)	3 (0.9)	>0.999	5 (3.4)	0.022	24 (1.1)
History of severe COPD	90 (5.3)	25 (7.5)	0.135	13 (8.7)	0.115	128 (5.9)
Preoperative transfusion	12 (0.7)	3 (0.9)	0.723	4 (2.7)	0.034	19 (0.9)
Immunosuppressive therapy	127 (7.4)	29 (8.7)	0.488	14 (9.4)	0.485	170 (7.8)
Surgical approach^^^
Posterior only	1336 (83.5)	268 (84.5)	0.763	126 (88.7)	0.309	1730 (84)
Anterior only	180 (11.3)	36 (11.4)		12 (8.5)		228 (11.1)
Combined	83 (5.2)	13 (4.1)		4 (2.8)		100 (4.9)
Length of spinal construct^^^
Long-segment	862 (53.9)	189 (59.6)	0.071	74 (52.1)	0.746	1125 (54.7)
Short-segment	737 (46.1)	128 (40.4)		68 (47.9)		933 (45.3)
Osteotomy utilization
Smith-Peterson osteotomy	574 (33.7)	95 (28.6)	0.146	37 (24.8)	0.005	706 (32.3)
Three-column osteotomy	158 (9.3)	40 (12)		9 (6)		207 (9.5)
Vertebral column resection	7 (0.4)	2 (0.6)		3 (2)		12 (0.5)
None	966 (56.6)	195 (58.8)		100 (67.2)		1261 (57.7)
Extent of osteotomy
Single-level	322 (43.6)	67 (48.9)	0.289	17 (34.7)	0.286	406 (43.9)
Multi-level	417 (56.4)	70 (51.1)		32 (65.3)		519 (56.1)

ASA, American Society of Anesthesiologists. CHF, congestive heart failure. COPD, chronic obstructive pulmonary disease. DM, diabetes mellitus. SD, standard deviations. SIRS, systemic inflammatory response syndrome.

^* Data was not available for 115 patients, including 96 normal, 8 malnourished, and 11 severely malnourished patients.

^** Data was not available for 6 patients, including 3 normal, 2 malnourished, and 1 severely malnourished patient.

^*** Data was not available for 1 severely malnourished patient.

^{^} Data was not available for 21 patients, including 18 normal and 3 malnourished patients.

^{^^} Data was not available for 1 normal patient.

^{^^^} Data was not available for 128 patients, including 106 normal, 15 malnourished, and 7 severely malnourished patients.

Outcomes

Univariate Analysis

Malnourished patients had significantly higher rates of postoperative complications compared to normal patients (20.2% vs 15.1%, P = 0.027). In particular, the rates of minor complications (12.3% vs 8.3%, P = 0.023) and medical complications (17.5% vs 13.2%, P = 0.048) were significantly greater among malnourished patients compared to normal patients. Regarding individual complications, malnourished patients experienced prolonged mechanical ventilation (4.8% vs 1.8%, P = .002), postoperative transfusion (59% vs 46.7%, P < 0.001), and wound disruption (2.1% vs 0.6%, P = .018) significantly more frequently than normal patients. Severely malnourished patients demonstrated significantly higher rates of prolonged mechanical ventilation (5.4% vs 1.8%, P = .01), superficial surgical site infection (SSI; 4% vs 1.3%, P = .025), and unplanned intubation (4.7% vs 1.5%, P = .011). Additionally, a significantly greater proportion of malnourished patients required ≥5 units of transfused blood compared to normal patients (18.4% vs 8.5%, P = .028). Hospital length of stay was significantly longer among malnourished (7.6 ± 5.4 days, P < .001) and severely malnourished patients (9.7 ± 8.4 days, P < .001) compared to normal patients (6.4 ± 4.5 days). Extended hospitalization occurred significantly more frequently among malnourished (21.3%, P = .004) and severely malnourished patients (32.9%, P < .001) relative to normal patients (14.9%). Similarly, non-home discharge was significantly more common among malnourished (59.9%, P = 0.007) and severely malnourished patients (60.4%, P < .001) compared to those with normal nutritional status (47.3%; Table 2).

Table 2.

Outcome Variables of the Study

	Normal (n = 1705)	Malnourished (n = 332)		Severely malnourished (n = 149)		Total (n = 2186)
	N (%)	N (%)	P	N (%)	P	N (%)
Any deaths	13 (0.8)	2 (0.6)	>0.999	2 (1.3)	0.342	17 (0.8)
Any complications (excluding blood transfusions)	258 (15.1)	67 (20.2)	0.027	28 (18.8)	0.286	353 (16.1)
Any major complications	186 (10.9)	42 (12.7)	0.409	19 (12.8)	0.581	247 (11.3)
Any minor complications	141 (8.3)	41 (12.3)	0.023	14 (9.4)	0.747	196 (9)
Any medical complications	225 (13.2)	58 (17.5)	0.048	21 (14.1)	0.854	304 (13.9)
Any surgical complications	64 (3.8)	18 (5.4)	0.169	10 (6.7)	0.081	92 (4.2)
Postoperative complications
Superficial surgical site infection	23 (1.3)	8 (2.4)	0.146	6 (4)	0.025	37 (1.7)
Deep incisional surgical site infection	17 (1)	7 (2.1)	0.095	1 (0.7)	>0.999	25 (1.1)
Organ/Space surgical site infection	17 (1)	0	0.093	3 (2)	0.213	20 (0.9)
Pneumonia	47 (2.8)	14 (4.2)	0.159	6 (4)	0.313	67 (3.1)
Urinary tract infection	68 (4)	16 (4.8)	0.453	3 (2)	0.368	87 (4)
Sepsis	36 (2.1)	6 (1.8)	0.835	3 (2)	>0.999	45 (2.1)
Septic shock	19 (1.1)	0	0.058	2 (1.3)	0.683	21 (1)
Postoperative renal insufficiency*	25 (1.7)	3 (1)	0.607	0	0.262	28 (1.4)
Postoperative dialysis	3 (0.2)	0	>0.999	0	>0.999	3 (0.1)
Vein thrombosis requiring therapy	30 (1.8)	8 (2.4)	0.381	0	0.166	38 (1.7)
Pulmonary embolism	42 (2.5)	8 (2.4)	>0.999	3 (2)	>0.999	53 (2.4)
Myocardial infarction	23 (1.3)	5 (1.5)	0.797	3 (2)	0.46	31 (1.4)
Cardiac arrest requiring CPR	9 (0.5)	1 (0.3)	>0.999	2 (1.3)	0.219	12 (0.5)
Stroke/CVA with neurological deficit	8 (0.5)	4 (1.2)	0.117	3 (2)	0.052	15 (0.7)
Unplanned intubation	25 (1.5)	8 (2.4)	0.232	7 (4.7)	0.011	40 (1.8)
On a ventilator over 48 hours	31 (1.8)	16 (4.8)	0.002	8 (5.4)	0.01	55 (2.5)
Bleeding requiring transfusion	797 (46.7)	196 (59)	<0.001	77 (51.7)	0.284	1070 (48.9)
Wound disruption	11 (0.6)	7 (2.1)	0.018	1 (0.7)	>0.999	19 (0.9)
Non-home discharge destination**	787 (47.3)	194 (59.9)	0.007	87 (60.4)	<0.001	1068 (50.1)
Any readmissions***	156 (9.4)	36 (11)	0.409	13 (9)	>0.999	205 (9.6)
Return to the operating room	103 (6)	27 (8.1)	0.176	5 (3.4)	0.205	135 (6.2)
Total operative time (minutes, mean ± SD)	337.5 ± 158.5	346.2 ± 154.7	0.357	315.1 ± 160.5	0.098	337.3 ± 158.1
Length of total hospital stay^ (days, mean ± SD)	6.4 ± 4.5	7.6 ± 5.4	<0.001	9.7 ± 8.4	<0.001	6.8 ± 5.1
Extended length of total hospital stay^	252 (14.9)	70 (21.3)	0.004	49 (32.9)	<0.001	371 (17.1)
Total amount of postoperative transfusion^^
0	403 (56.9)	57 (50)	0.028	26 (45.7)	0.446	486 (55.3)
1-2	149 (21)	26 (22.8)		17 (29.8)		192 (21.8)
3-4	96 (13.6)	10 (8.8)		8 (14)		114 (13)
+5	60 (8.5)	21 (18.4)		6 (10.5)		87 (9.9)

CPR, cardiopulmonary resuscitation. CVA, cerebrovascular accident. SD, standard deviations.

^* Data was not available for 234 patients, including 191 normal, 33 malnourished, and 10 severely malnourished patients.

^** Data was not available for 54 patients, including 41 normal, 8 malnourished, and 5 severely malnourished patients.

^*** Data was not available for 47 patients, including 37 normal, 5 malnourished, and 5 severely malnourished patients.

^{^} Data was not available for 14 patients, including 10 normal and 4 malnourished patients.

^{^^} Data was not available for 1,307 patients, including 997 normal, 218 malnourished, and 92 severely malnourished patients.

Multivariate Analysis

After adjusting for baseline covariates, malnourished status was independently associated with higher risks of wound disruption (OR 3.317, 95% CI 1.212-8.486; P = 0.014), prolonged mechanical ventilation (OR 2.19, 95% CI 1.11-4.135; P = .019), postoperative transfusion (OR 1.552, 95% CI 1.195-2.02; P = .001), greater volumes of postoperative transfusions (coefficient 0.452, 95% CI 0.013-0.891; P = .044), longer hospital stay (coefficient 0.856, 95% CI 0.319-1.39; P = .002), and non-home discharge (OR 1.566, 95% CI 1.216-2.021; P < .001). Severely malnourished status was independently associated with longer hospital stays (coefficient 2.4, 95% CI 1.56-3.25; P < .001), as well as higher likelihood of extended hospitalization (OR 2.087, 95% CI 1.386-3.106; P < .001) and non-home discharge (OR 1.563, 95% CI 1.086-2.262; P = .017; Table 3).

Table 3.

Regression Analysis

	Malnourished		Severely malnourished
	OR (95% CI)	P	OR (95% CI)	P
Any complications (excluding blood transfusions)	1.342 (0.983-1.812)	0.059
Any minor complications	1.435 (0.977-2.069)	0.058
Any medical complications	1.32 (0.95-1.81)	0.091
Superficial surgical site infection			2.149 (0.752-5.343)	0.12
Wound disruption	3.317 (1.212-8.486)	0.014
Unplanned intubation			2.354 (0.894-5.46)	0.06
On a ventilator over 48 hours	2.19 (1.11-4.135)	0.019	2.05 (0.791-4.769)	0.114
Bleeding requiring transfusion	1.552 (1.195-2.02)	0.001
Non-home discharge destination	1.566 (1.216-2.021)	<0.001	1.563 (1.086-2.262)	0.017
Length of total hospital stay (coefficient [95%CI])	0.856 (0.319-1.39)	0.002	2.4 (1.56-3.25)	<0.001
Prolonged hospital stay	1.324 (0.968-1.792)	0.074	2.087 (1.386-3.106)	<0.001
Total amount of postoperative transfusions (coefficient [95%CI])	0.452 (0.013-0.891)	0.044

CI, confidence intervals. OR, odds ratio.

In sensitivity analyses treating GNRI as a continuous variable, higher GNRI values were independently associated with lower odds of unplanned intubation (OR 0.937, 95% CI 0.901-0.978; P = .002), prolonged mechanical ventilation (OR 0.954, 95% CI 0.918-0.993; P = .018), postoperative transfusion (OR 0.97; 95% CI 0.956-0.984; P < 0.001), lower volumes of postoperative transfusions (coefficient −0.026; 95% CI -0.048 to −0.004; P = .021) shorter hospital length of stay (coefficient −0.07, 95% CI -0.1 to −0.04; P < .001), lower likelihood of extended hospitalization (OR 0.971, 95% CI 0.954-0.988; P < .001), and lower odds of non-home discharge (OR 0.972, 95% CI 0.958-0.985; P < .001; Supplemental Table 2).

ROC Curve Analysis

For superficial SSI, GNRI showed higher discriminative ability (AUC 0.617) compared with mFI-5 (AUC 0.592, P = .645) and age (AUC 0.51, P = 0.074). Similarly, GNRI (AUC 0.61) exhibited superior predictive performance for wound disruption relative to mFI-5 (AUC 0.543, P = 0.394) and age (AUC 0.534, P = .277). For unplanned intubation, the predictive ability of GNRI (AUC 0.635) surpassed that of mFI-5 (AUC 0.541, P = .113) and age (AUC 0.549, P = .167). GNRI also demonstrated greater accuracy in predicting prolonged mechanical ventilation (AUC 0.652) than mFI-5 (AUC 0.576, P = .179) and age (AUC 0.548, P = .039). Similarly, GNRI (AUC 0.565) outperformed mFI-5 (AUC 0.525, P = .014) and age (AUC 0.502, P < .001) in predicting postoperative transfusion. Finally, for extended hospitalization, GNRI (AUC 0.594) provided better discrimination than mFI-5 (AUC 0.568, P = .233) and age (AUC 0.511, P < .001; Figure 3).

Figure 3.

Receiver operating characteristic curve analyses of the Geriatric Nutritional Risk Index, 5-item modified Frailty Index, and patient age for predicting: A. Any postoperative complication excluding blood transfusions. (B) Any minor postoperative complication. (C) Any medical postoperative complication. (D) Superficial surgical site infection. (E) Wound disruption. (F) Unplanned intubation. (G) On a ventilator for greater than 48 hours. (H) The need for postoperative transfusion. (I) Non-Home Discharge. (J) prolonged hospitalization. AUC, area under the curve. GNRI, the Geriatric Nutritional Risk Index. mFI-5, 5-item modified Frailty Index

Discussion

With the growing number of elderly individuals undergoing corrective surgery for ASD, the need for more precise risk assessment tools to highlight predictors of unfavorable postoperative outcomes has become increasingly important.^1-6 Prior studies have indicated that poor nutritional status may be associated with greater susceptibility to postoperative complications after ASD surgery.^13,16,18,19 However, there was a scarcity of large-scale studies that have specifically examined this relationship in geriatric patients with ASD using a validated nutritional index. The present study sought to address this gap by assessing the prognostic utility of the GNRI in predicting perioperative outcomes in elderly patients undergoing ASD surgery. To our knowledge, this study represents the first large, national-level analysis investigating the relationship between the GNRI and postoperative outcomes in elderly patients undergoing deformity-type spine surgery.

Summary of Findings

In this retrospective cohort study of 2186 geriatric patients undergoing surgery for ASD, nutritional status was found to be a significant predictor of postoperative outcomes. After controlling for potential confounders, malnourishment was independently associated with an increased risk of wound disruption, prolonged mechanical ventilation, postoperative transfusion requirements, greater transfusion volumes, longer hospitalization, and discharge to non-home facilities. Severe malnourishment was independently associated with a longer hospital stay, as well as an increased risk of prolonged hospitalization and non-home discharge. When evaluating predictive performance, the GNRI demonstrated superior discriminative ability compared to both the mFI-5 and chronological age in predicting superficial SSI, wound disruptions, unplanned intubations, prolonged mechanical ventilation, the need for postoperative transfusions, and extended hospital stay.

Perioperative Complications

Existing literature indicates that compromised nutritional status is closely linked to an elevated risk of postoperative complications, particularly pulmonary and infectious adverse events.^32-38 Additionally, preoperative malnutrition has been associated with suboptimal radiographic and alignment outcomes following corrective surgery for ASD.^34,39 Consistent with the previous literature, in the present study, preoperative malnutrition independently correlated with higher incidences of wound disruption, prolonged mechanical ventilation, and increased transfusion requirements and volumes in older adults undergoing ASD surgery. Moreover, the GNRI demonstrated greater predictive accuracy for superficial SSI, wound disruption, unplanned intubation, prolonged mechanical ventilation, and postoperative transfusion compared with chronological age or frailty.

Among older adults, malnutrition may result from a natural decline in dietary intake and overall caloric consumption.^38,40 This nutritional insufficiency can lead to a negative energy balance, diminishing the physiologic reserve necessary to tolerate surgery-associated metabolic stress. ³⁸ Supporting this mechanism, prior studies have shown that unintentional weight loss related to malnutrition independently heightens the risk of postoperative complications. ⁴¹ Conversely, obesity has also been linked to increased postoperative complications following spine surgery, which may be partly due to a paradoxical coexistence of malnutrition within this population. ⁴² Collectively, these findings underscore that malnutrition is a multifactorial condition, encompassing both inadequate intake and abnormal body composition, which together may contribute to greater surgical morbidity. ³⁸ Unlike many previous studies that used preoperative serum albumin alone to define malnutrition, the GNRI utilized in this study integrates both body weight and serum albumin, providing a more comprehensive assessment of nutritional status specifically tailored for geriatric patients.^13,23 The GNRI reflects not only nutritional reserve but also systemic inflammatory burden through its albumin component, which may explain its stronger association with several postoperative outcomes compared with chronological age alone or comorbidity-based indices such as the mFI-5.^43-45

The association between GNRI and perioperative transfusion observed in this study requires nuanced interpretation. Transfusion in large spine surgery is strongly influenced by operative complexity, including surgical approach, construct length, the use and extent of osteotomy, the utilization of pelvic fixation, and whether the procedure is a revision.^46-48 In the present analysis, we sought to adjust for available proxies of surgical magnitude using CPT-based variables that capture these elements. However, such codes serve only as indirect surrogates and do not fully reflect intraoperative decision-making or technical execution. As a result, transfusion likely represents a composite marker reflecting both the patient’s physiologic vulnerability and the magnitude of the surgical procedure, rather than a nutrition-specific outcome. Accordingly, the observed association between GNRI and transfusion should be interpreted cautiously and not attributed solely to nutritional status.

Postoperative Course

Preoperative malnutrition has been consistently identified as a predictor of prolonged hospitalization and non-routine discharge after ASD surgery.^33,38 In line with previous studies, the present study demonstrated that patients with poor preoperative nutritional status experienced significantly longer hospital stays as well as a higher likelihood of discharge to facilities other than home. Specifically, severe malnourishment was independently associated with a 2.4-day increase in length of stay. Moreover, the GNRI outperformed both the mFI-5 and chronological age in discriminating patients at risk for extended hospitalization.

Several mechanisms may explain these associations. Malnourished geriatric patients typically exhibit diminished physiological reserve and slower postoperative recovery, prompting clinicians to adopt a more conservative postoperative management strategy. As a result, they may intentionally extend the hospital stay duration to ensure adequate monitoring and stabilization before discharge. Furthermore, delayed wound healing and the higher incidence of postoperative complications in malnourished individuals can impede functional recovery, increasing the likelihood of requiring discharge to rehabilitation or skilled nursing facilities rather than home.^13,38 Although the current study did not directly assess healthcare costs, both hospital length of stay and discharge disposition can serve as surrogate indicators of increased resource utilization, suggesting that preoperative malnutrition may indirectly contribute to higher overall surgical expenditures.

Future Directions

Given the observed association between malnutrition and adverse outcomes following ASD surgery in geriatric patients, these findings highlight the potential benefit of preoperative nutritional optimization. Prior studies suggest that integrating nutritional support as part of a comprehensive preoperative optimization strategy may improve postoperative outcomes, including reduced delirium, shorter hospital length of stay, lower transfusion requirements, and fewer other medical complications.^49-53 Screening tools, including the GNRI score, can help identify patients at nutritional risk and guide targeted interventions to address their needs. GNRI is an objective, readily available metric derived from routinely collected laboratory and anthropometric data, making it well-suited for integration into preoperative workflows. For example, a GNRI threshold of <98 could be used to trigger formal preoperative nutritional consultation, enabling targeted optimization prior to surgery. In select elective cases, identification of severe malnutrition may also prompt consideration of deferring surgery when clinically feasible to improve physiological reserve. Nutritional optimization may include tailored guidance and supplementation addressing both micronutrients and macronutrients. However, the most effective strategies and specific recommendations for the geriatric ASD population remain to be established, necessitating future prospective studies for elucidation.^50,53-55

Although GNRI demonstrated statistically superior discrimination compared with chronological age and mFI-5 for several postoperative outcomes in the present study, the modest AUC values highlight the inherent limitations of single-variable prediction models. Combining GNRI with detailed clinical, functional, radiographic, and operative variables may yield more accurate predictive performance and improve individualized risk assessment in elderly patients undergoing complex spine surgery. Prospective, procedure-specific studies incorporating granular perioperative data will be essential to validate such composite models and to clarify the role of preoperative nutritional status by integrating GNRI into multimodal risk stratification frameworks rather than evaluating it as a standalone predictor. Importantly, these applications should be viewed as adjunctive measures to support perioperative risk stratification and optimization rather than as determinants of surgical eligibility.

Enhanced Recovery After Surgery (ERAS) protocols offer a structured, evidence-based framework for optimizing perioperative care through multidisciplinary optimization of mobility, pain control, and nutrition. ⁵⁶ ERAS pathways have only recently been applied in spine surgery, including ASD procedures, and have demonstrated improved restoration of physiological function and reduced rates of unfavorable outcomes in frail patients.^57,58 Within these programs, postoperative nutritional optimization has been a key component driving improved outcomes. ⁵⁷ In this context, GNRI could be incorporated into ERAS or anti-frailty pathways as a complementary tool for identifying vulnerable patients who may benefit from multidisciplinary optimization strategies. The current literature supports the potential value of integrating targeted nutritional interventions into postoperative care for elderly patients undergoing ASD surgery, warranting further prospective studies to define optimal strategies and quantify their impact on postoperative recovery. ⁵⁷

Limitations

This study has several limitations that should be considered when interpreting the results. First, as a retrospective analysis of the ACS-NSQIP database, our findings are inherently subject to coding and reporting biases. Misclassification of ASD and corrective procedures may have occurred due to variability in ICD and CPT coding practices across participating institutions. Although administrative coding is commonly used in large database studies, ICD and CPT codes may not reliably distinguish rigorously defined ASD populations based on radiographic criteria, as demonstrated in prior literature. ⁵⁹ As such, the present cohort may include an elderly population undergoing surgery for degenerative spinal pathology requiring extended or deformity-type constructs. Accordingly, our findings should be interpreted with caution and not extrapolated indiscriminately to all radiographically defined ASD populations. Although we attempted to mitigate this by using well-defined inclusion criteria, selection bias remains possible. Additionally, the ACS-NSQIP database includes only complications captured within 30 days postoperatively, which precludes assessment of long-term outcomes related to malnutrition or delayed complications beyond this period. Furthermore, the ACS-NSQIP lacks spine-specific variables, such as deformity classification, radiographic alignment parameters, patient-reported outcomes, or procedure-specific complications. Furthermore, variables such as pre- and postoperative neurological function, nutritional practices, and physical therapy participation, which may have introduced unmeasured confounding. Another limitation of this study is the lack of procedural granularity inherent to large national databases, including detailed information regarding surgical decision-making, intraoperative technique, and surgeon-specific factors. Such variables may influence the extent of the surgical procedure, thereby affecting postoperative outcomes through differing levels of physiological stress, precluding assessment of their direct contribution to complications such as wound complications or prolonged recovery. Accordingly, GNRI should not be interpreted as predicting outcomes independent of surgical context or as a determinant of whether a patient should undergo deformity correction. The objective of this study was not to evaluate operative execution, but rather to assess whether preoperative nutritional status, as measured by the GNRI, is associated with early postoperative morbidity at a population level. By adjusting for available demographic, comorbidity, and operative factors (e.g., surgical approach, length of construct, osteotomy utilization, and extent of osteotomy), our findings provide risk-stratification insight and generate hypotheses that may inform future procedure-specific or single-institution prospective studies with greater operative detail. Our findings suggest that GNRI functions as a marker of reduced physiological reserve, identifying patients who may be less tolerant of surgical stress and therefore at increased risk for early postoperative morbidity across a spectrum of complex spine procedures. Furthermore, participating hospitals are predominantly large academic centers within the United States, which may limit the generalizability of our results to community or international settings. Differences in albumin assay methods, surgeon experience, and institutional protocols could further contribute to heterogeneity in outcomes. Additionally, while the use of a multicenter national dataset provides statistical power and external validity, it limits the ability to control for subtle clinical nuances or individualized perioperative management strategies. Lastly, as with all retrospective database studies, causal inferences between malnutrition and specific postoperative complications cannot be established. The GNRI, although a validated nutritional index, may not fully capture the complexity of nutritional and metabolic states that influence postoperative recovery. Despite these limitations, the ACS-NSQIP database remains one of the most rigorously curated national surgical datasets, with standardized data collection performed by trained Surgical Clinical Reviewers, including experienced nurses and non-nurses directly mentored by senior healthcare professionals, and supported by systematic sampling and robust quality assurance mechanisms.^20,21,60 These features enhance the accuracy, reliability, and clinical relevance of the captured variables compared with many administrative databases. ²² Accordingly, NSQIP is particularly well-suited for evaluating short-term postoperative outcomes and risk stratification, making it an appropriate platform for examining the association between the GNRI and early postoperative outcomes in this patient population. The present study, therefore, leveraged this validated, large, prospectively collected dataset to provide a representative overview of the relationship between preoperative nutritional status and outcomes in geriatric patients undergoing surgery for ASD.

Conclusion

In this multicenter cohort of 2186 geriatric patients undergoing surgery for ASD, preoperative malnutrition, measured using the GNRI, was identified as an independent predictor of increased 30-day postoperative complications, prolonged hospital stays, and non-home discharge. These findings highlight the critical importance of incorporating objective nutritional assessment into the preoperative evaluation of older adults undergoing ASD surgery. The GNRI, in particular, may serve as a practical and viable tool for identifying patients at elevated perioperative risk. Future studies should aim to validate these findings prospectively and investigate targeted preoperative nutritional optimization strategies that can mitigate postoperative morbidity, reduce hospitalization duration, and improve recovery and quality of life in this vulnerable population.

Appendix.

List of Abbreviations

ACS-NSQIP

American College of Surgeons National Surgical Quality Improvement Program

ASA

American Society of Anesthesiologists

ASD

Adult spinal deformity

AUC

Area under the curve

BMI

Body mass index

CI

Confidence interval

CPT

Current Procedural Terminology

ERAS

Enhanced Recovery After Surgery

GNRI

Geriatric Nutritional Risk Index

ICD

International Classification of Diseases

mFI-5

Five-item Modified Frailty Index

OR

Odds ratio

ROC:

Receiver operating characteristic

SIRS

Systemic inflammatory response syndrome

SSI

Surgical site infection

WLo

Ideal body weight

ORCID iD

Ataollah Shahbandi https://orcid.org/0000-0003-1042-8580

Data Availability Statement

The data supporting the findings of this study are available from the authors upon reasonable request.*