Adjacent segment infection (ASI) following posterior lumbar spinal fusion is an uncommon yet clinically significant postoperative complication that poses substantial diagnostic and therapeutic challenges. Although posterior lumbar fusion is an established intervention for degenerative spinal disorders, postoperative infectious complications extending to adjacent spinal segments can compromise functional recovery, increase healthcare costs, prolong hospitalization, and necessitate revision surgery. Existing literature primarily emphasizes surgical site infection and vertebral osteomyelitis, while comprehensive clinical assessment strategies specifically addressing adjacent segment infection remain insufficiently developed. This review proposes a clinical assessment model integrating patient-related, surgical, microbiological, radiological, and laboratory parameters to facilitate earlier diagnosis and evidence-based management of ASI after posterior lumbar spinal fusion. The model synthesizes evidence from published clinical investigations, systematic reviews, treatment guidelines, and case reports to identify the principal determinants influencing disease onset, progression, diagnosis, and therapeutic decision-making. The proposed framework highlights the importance of multidisciplinary evaluation combining inflammatory biomarkers, advanced imaging, microbiological confirmation, and individualized risk stratification. Furthermore, the study discusses diagnostic uncertainty associated with culture-negative infections, imaging limitations during early disease stages, and the influence of implant-related factors on clinical outcomes. The findings indicate that systematic assessment significantly improves diagnostic accuracy, optimizes treatment selection, reduces neurological deterioration, and supports preservation of spinal stability. The review contributes a structured assessment approach that may assist clinicians in improving postoperative surveillance and patient management while identifying future research priorities for predictive clinical models and standardized diagnostic algorithms.
Clinical Assessment Model of Adjacent Segment Infection After Posterior Lumbar Spinal Fusion
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References
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