Inflammatory biomarkers serve as components of a diagnostic framework for pyogenic spinal infectionNewer tests may help doctors track spinal infections more accurately

Pyogenic spinal infection (PSI) remains challenging to diagnose at an early stage because symptoms are often nonspecific, imaging findings may overlap with degenerative, neoplastic, or postoperative changes, and microbiological confirmation is frequently delayed or unavailable. Magnetic resonance imaging, microbiological culture, biopsy, and conventional inflammatory markers remain central to diagnosis, but their findings may be discordant, particularly in early infection, postoperative settings, chronic disease, and immunocompromised patients. Inflammatory cytokines and acute-phase markers reflect different aspects of the host response and may therefore provide useful information for clinical assessment, longitudinal follow-up, and the timing of reassessment. In this narrative and conceptual review, we examine the diagnostic value and limitations of conventional markers, including C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), white blood cell count (WBC), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and interleukin-1β (IL-1β), together with emerging candidates such as procalcitonin (PCT), pentraxin 3 (PTX3), and S100A8/A9. Particular attention is paid to the source and directness of the available evidence, distinguishing studies conducted in PSI or native vertebral osteomyelitis from findings derived from postoperative spinal infection, periprosthetic joint infection, sepsis, and other bone and joint infections. We further discuss how longitudinal biomarker trajectories, differences among specimen sources, spatial heterogeneity of inflammatory signals, and circulating biomarker networks may help interpret diagnostically uncertain cases, while recognizing that several emerging biomarkers and integrated approaches still lack direct validation in PSI. The complementary role of metagenomic next-generation sequencing (mNGS) and the potential use of artificial intelligence (AI) for integrating heterogeneous clinical information are also considered, together with their current methodological and clinical limitations. Overall, inflammatory biomarkers are best interpreted as components of an evidence-informed diagnostic and reassessment framework that integrates clinical findings, imaging, microbiology, and changes in the host inflammatory response, rather than as standalone tests for PSI.