1 Introduction

Anterior lumbar interbody fusion (ALIF) has seen a marked rise in utilization, with annual growth rates reaching 24 %, solidifying its role as a standard intervention for various degenerative conditions of the lumbar spine.¹ ALIF provides superior access to the anterior spinal column, facilitating a thorough discectomy and enabling placement of larger interbody cages. These features contribute to the restoration of lumbar lordosis and improvements in both sagittal and coronal alignment.² Among fusion techniques, ALIF is the preferred surgical option for managing discogenic low back pain.³ While this approach is associated with benefits such as reduced operative time and lower intraoperative blood loss, it also introduces unique risks related to its anterior route. In particular, ALIF carries the potential for severe vascular and visceral complications—including injuries to the iliac vessels—that are not typically encountered with posterior techniques, which more commonly threaten neural elements.^4,5 Therefore, patient selection and surgical planning are critical to maximizing outcomes and minimizing adverse events in ALIF.

Advanced age is a well-documented predictor of postoperative complications in spine surgery.⁶ Given projections that the United States (U.S.) population aged 85 and older will surpass 20 million by 2060, tripling its current size, there is an urgent need to evaluate outcomes in this demographic.^7,8 A study by Liu et al. analyzed 202 elderly patients (ages 77–92) undergoing lumbar fusion and found that age emerged as an independent risk factor for major complications; notably, those aged 80–81 had ten times the odds of adverse events compared to patients aged 77.⁹ Despite this elevated risk, elective spine surgery in older adults can be performed safely with appropriate care. Kuo et al. evaluated 7,880 patients who underwent posterior lumbar fusion and found that octogenarians experienced similar rates of mortality, readmission, emergency department visits, and thromboembolic complications compared to younger counterparts.¹⁰ However, they did observe a higher incidence of pneumonia within 30 days, emphasizing the value of thorough preoperative screening. These findings reinforce the importance of tailored perioperative strategies in elderly patients.

With the concurrent rise in ALIF utilization and the aging of the population, it is increasingly important to understand how age influences postoperative outcomes. This study seeks to characterize the impact of patient age on (1) postoperative complications, (2) hospital length of stay, and (3) discharge disposition following ALIF.

2 Methods

3 Results

4 Discussion

ALIF remains a well-established and safe surgical option for managing degenerative lumbar spine conditions in the elderly.¹² The procedure has been associated with high patient satisfaction and marked improvements in both pain and functional status.¹³ Its consistent clinical benefits have made ALIF a preferred choice among both surgeons and patients seeking long-term relief from disabling spinal disorders.¹⁴ While prior studies have identified increased rates of complications such as pneumonia, sepsis, and other major events in individuals aged 65 and older undergoing ALIF, specific risks affecting the octogenarian population remain underexplored.¹⁵ This study addressed this gap by examining postoperative complications, LOS, and discharge disposition in patients aged 50–64, 65–79, and 80+, highlighting the importance of age-informed perioperative planning to improve outcomes in older adults.

Our findings reaffirm that postoperative complications increase with age, with distinct patterns observed across the ALIF population. The 65–79 group had the highest incidence of acute post-hemorrhagic anemia, and older patients were more likely to experience cardiovascular and renal events such as myocardial infarction, stroke, and acute kidney injury. These findings likely reflect both increased baseline comorbidity burden and reduced physiologic reserve in elderly surgical patients. In the 80+ cohort, sepsis and anesthesia-related complications were more prevalent, highlighting the need for age-informed perioperative planning. While our study does not directly evaluate the mechanisms underlying these trends, the data emphasize the relevance of tailoring ALIF care pathways to the physiologic complexity of older adults.

Several prior studies have attempted to characterize postoperative risks in older patients undergoing spine surgery. Kamalapathy et al. evaluated single-level ALIF outcomes by age group and found no significant differences in complications between those aged 65+ and 75–84.¹⁵ Although our analysis identified sepsis as more common in patients aged 80+, their findings suggest this risk may extend to a broader elderly cohort. Additional research is warranted to clarify the relationship between age and infection risk. Kim et al. studied 36 patients aged 85 and older undergoing spinal procedures and identified postoperative delirium as a frequent complication, underscoring the cognitive vulnerability of this population.^16,17 While such cognitive outcomes are clinically important and may be influenced by anesthetic exposure, they were not captured in our dataset and should not be inferred from our analysis. Anesthesia-related complications reported here reflect only the events coded within the NIS. These findings nonetheless emphasize the need for cautious perioperative planning and age-specific optimization protocols in very elderly ALIF patients.

Age also plays a significant role in determining hospital length of stay. Patients over 65 consistently required longer hospitalizations following ALIF, consistent with prior findings in elderly spine surgery populations. McGirt et al. compared outcomes between older and younger adults undergoing surgery for degenerative lumbar disease and found that, despite similar health gains and comparable complication rates, elderly patients had longer hospital stays, likely due to greater postoperative care needs.¹⁸ Hospitals with robust resources and coordinated care teams are often better positioned to manage these complex patients. The observed increase in admission charges with age likely reflects the additive effects of longer hospital stays, higher rates of complications, and increased resource utilization required for perioperative management and discharge planning. These findings underscore the economic burden associated with ALIF in elderly populations and highlight opportunities for targeted care pathways to improve both outcomes and cost-efficiency. A multidisciplinary care approach — combining surgical expertise with geriatric assessment — has been shown to reduce complications, shorten LOS, and enhance functional recovery in older adults across multiple surgical disciplines, including spine surgery.^19,20 Implementing such models for elderly ALIF patients may improve outcomes and optimize healthcare utilization.

Discharge disposition is another critical outcome influenced by age, with patients aged 65 and older significantly more likely to require non-routine discharge due to elevated postoperative care needs. Prior studies have consistently identified older age as a strong predictor of discharge to skilled nursing or rehabilitation facilities.²¹ Lagman et al. specifically reported increased non-routine discharge rates among patients aged 80 and older, highlighting the added complexity of post-hospital transitions in the very elderly.²² With institutional care facilities increasingly strained, Toh et al. advocate for greater investment in home and community-based services to meet the growing demands of this population.²³ Because non-routine discharges are linked to higher 30-day readmission rates, early and coordinated discharge planning — including risk screening by primary care providers, lab evaluation, and timely involvement of social work and rehabilitation services — can help facilitate safer transitions and reduce downstream complications.^24,25

Recent efforts to enhance individualized care have leveraged national surgical registries to develop risk prediction tools and frailty-based discharge models. For example, Karabacak et al. applied machine learning to the American College of Surgeons’ National Surgical Quality Improvement Program (NSQIP) database to forecast short-term ALIF outcomes, including prolonged length of stay, readmission, and non-home discharge, with strong predictive accuracy.²⁶ Asserson et al. similarly demonstrated that frailty indices, particularly the Revised Risk Analysis Index, are significant predictors of non-home discharge following ALIF procedures.²⁷ These registry-based findings complement the present population-level analysis and underscore the growing utility of predictive modeling and frailty assessment to guide patient selection, optimize perioperative care, and improve outcomes in elderly ALIF patients.

This study has several limitations. The NIS is the largest publicly available all-payer inpatient healthcare database, but it is based on administrative ICD-10 coding and lacks detailed clinical information such as surgical technique (e.g., standalone vs. instrumented ALIF), intraoperative blood loss, operative duration, and long-term outcomes. As such, some observations, such as increased transfusion rates or higher anemia prevalence in older patients, must be interpreted cautiously, as pre-existing anemia or surgical complexity cannot be confirmed. Coding errors and variability in documentation may also introduce misclassification bias. The retrospective design limits causal inference, and residual confounding may persist despite statistical adjustment. Selection bias may be present due to the exclusion of emergent cases and incomplete records, which may systematically differ from the included elective cohort. Additionally, the lack of outpatient follow-up data precludes evaluation of longitudinal outcomes such as readmissions, reoperations, or recovery trajectories. No sensitivity analyses were performed across key subgroups such as comorbidity burden, hospital type, or insurance status; future studies may benefit from these approaches to further validate and extend our findings. While we did not employ multivariate regression modeling due to the study's descriptive design and population-level focus, we acknowledge that such models could adjust for confounding variables and offer additional analytic depth. Surgeon volume, hospital-level factors, and variability in surgical approach — important drivers of outcome — could not be assessed using the available dataset. Broad age groupings (50–64, 65–79, 80+) may mask subtler within-group differences; although finer age stratification (e.g., 5-year intervals) could have revealed additional patterns, this was limited by small sample sizes in the oldest subgroups. Our age categories were selected to balance statistical power with clinical relevance and consistency with prior spine literature. Despite these limitations, this study provides valuable, age-specific insights into ALIF outcomes and serves as a foundation for future research aimed at developing clinical risk tools, optimization strategies, and comparative effectiveness analyses in elderly spine surgery.

5 Conclusions

As the population ages and demand for spinal fusion procedures rises, understanding age-related variation in ALIF outcomes is increasingly important. This large, nationally representative analysis highlights that advancing age is associated with increased postoperative complications, longer hospital stays, and a higher likelihood of non-routine discharge. While ALIF can be safely performed in appropriately selected elderly patients, these findings underscore the need for careful preoperative evaluation, age-specific perioperative planning, and multidisciplinary coordination to mitigate risks and support optimal recovery. Future studies should focus on developing prospective registries, evaluating risk prediction models, and implementing geriatric co-management strategies to further guide evidence-based, patient-centered care in this growing population.

CRediT authorship contribution statement

Paul G. Mastrokostas: Conceptualization, Methodology, Data curation, Software, Formal analysis, Visualization, Writing – original draft, Writing – review & editing. Leonidas E. Mastrokostas: Conceptualization, Methodology, Data curation, Software, Formal analysis, Visualization, Writing – original draft, Writing – review & editing. Aaron B. Lavi: Writing – original draft, Writing – review & editing. Abigail Razi: Writing – original draft, Writing – review & editing. John K. Houten: Conceptualization, Supervision, Writing – review & editing. Ahmed Saleh: Conceptualization, Supervision, Project administration, Writing – review & editing. Jad Bou Monsef: Conceptualization, Supervision, Project administration, Writing – review & editing. Afshin E. Razi: Conceptualization, Supervision, Project administration, Writing – review & editing. Mitchell K. Ng: Conceptualization, Supervision, Project administration, Writing – review & editing.

Guardian/patient's consent

The National Inpatient Sample (NIS) is a publicly available, de-identified database. As such, this study was exempt from institutional review board approval, and the requirement for informed patient or guardian consent was waived.

Ethical statement

The authors affirm that this study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. All methods adhered to relevant guidelines and regulations. As the study utilized publicly available, de-identified data from the National Inpatient Sample, no direct patient involvement occurred, and institutional review board approval was not required.

Funding statement

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.