Treating the host, not just the spine: A novel clinical algorithm for spondylodiscitis based on a prospective 14-Year cohort analysis

Treating the host, not just the spine: A novel clinical algorithm for spondylodiscitis based on a prospective 14-Year cohort analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Treating the host, not just the spine: A novel clinical algorithm for spondylodiscitis based on a prospective 14-Year cohort analysis Stavros Oikonomidis, Peer Eysel, Dorothee Hornik, Norma Jung, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9613598/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Purpose This study introduces a novel Clinical Risk Stratification Algorithm for spondylodiscitis, shifting the management focus from purely radiological criteria to clinical risk factors. Methods The study presents a novel clinical risk stratification algorithm for spondylodiscitis, developed through a systematic synthesis of data from a 14-year prospective monocentric cohort. Developed from a prospective 14-year cohort (2008–2022) at a tertiary center, the algorithm synthesizes data from ten sub-analyses using multivariate regression to identify key drivers of mortality and treatment failure. Results Significant risk factors for adverse outcomes include Chronic Kidney Disease (CKD), malignancy, age ≥ 65, and bacteremia. For patients with Spinal Epidural Abscess (SEA), diabetes and CRP levels ≥ 150 mg/l are critical predictors of neurologic deficit. The algorithm categorizes patients into three pathways: Path A (High Mortality) prioritizes aggressive surgical source control, challenging the traditional view that multimorbid patients are "too sick for surgery". Path B addresses failure risks like S. aureus using a "2-week CRP Checkpoint" to guide potential revision surgery. Path C focuses on quality-of-life-driven palliative care for oncology patients. Conclusion This clinical tool enables personalized management by integrating systemic status into surgical decision-making. It emphasizes that surgery is a vital tool for sepsis control in frail patients and pain management in palliative care. Spondylodiscitis vertebral osteomyelitis clinical algorithm prospective cohort study spinal infection Figures Figure 1 Introduction Spondylodiscitis and spinal epidural abscesses represent severe and increasingly common infectious diseases of the spine( 1 ). The clinical presentation of spondylodiscitis is highly heterogeneous and ranges from indolent back pain to fulminant sepsis with neurological compromise( 2 ). In addition to survival and control of infectious diseases, preservation of spinal stability and neurological function is the primary objective of orthopedic management. Despite medical treatment, spondylodiscitis can lead to poor quality of life and poor functional outcomes. Even after "successful" biological cure, many survivors suffer from chronic pain and significant disability ( 3 ). Identifying patients at risk of adverse outcomes is crucial for managing surgical interventions. Recent evidence indicates that patients with spondylodiscitis benefit significantly from surgical intervention compared to conservative therapy, particularly in terms of improved survival rates and a reduced risk of disease recurrence( 4 ). Furthermore, surgical debridement and stabilization have been shown to lead to superior long-term functional outcomes and quality of life by effectively addressing spinal instability and the infectious burden( 1 )( 5 ). Current guidelines for spondylodiscitis provide robust recommendations for antibiotic stewardship and indications for emergency surgery (e.g., in cases of neurological deficits) ( 6 ). However, these recommendations are predominantly based on the radiological criteria derived from advanced imaging modalities. Specifically, decision-making algorithms heavily prioritize morphological findings such as the extent of vertebral bone destruction and the presence of abscesses visible on MRI (magnetic resonance imaging) or CT (computed tomography) scans( 7 ). Consequently, the indication for surgical intervention is frequently dictated by the structural integrity of the spine rather than by clinical variables. This study aimed to propose a novel evidence-based Clinical Risk Stratification Algorithm. This algorithm was designed to guide clinicians through methodological assessment. Baseline Risk Stratification : Identifying patients at high risk of mortality and treatment failure due to critical comorbidities. Structural Assessment : Predicting the likelihood of severe vertebral destruction based on a 7-point risk score. Functional Prognosis : Estimation of long-term Quality of Life outcomes based on preoperative symptom severity. The application of this algorithm can help physicians to assess the risk of treatment failure, mortality, and adverse clinical outcomes based on clinical variables. In this sense, the algorithm could identify patients who need urgent surgical intervention and closer follow-up observation to minimize the risk of unfavorable clinical outcomes. Methods Study Design and Data Source The clinical algorithm presented in this study was developed through systematic synthesis of data derived from a prospective, monocentric cohort study conducted at a tertiary referral center. The study was approved by the institutional review board (number 09-182. The underlying data were sourced from a prospective registry integrated with the Spine Tango Registry of EuroSpine and German Spine Society (DWG) Registry. Data acquisition spans from 2008 to 2022, in total 355 patients were included. The registry included adult patients (aged > 18 years) diagnosed with pyogenic or granulomatous spondylodiscitis. Diagnosis was confirmed based on clinical presentation, elevated inflammatory markers (C-reactive protein [CRP] and leukocytes), and radiological evidence (Magnetic Resonance Imaging [MRI] or Computed Tomography [CT]) demonstrating typical signs of spondylodiscitis (e.g., vertebral bone edema, endplate destruction, fluid intensity in the intervertebral disc, or abscess formation). Microbiological confirmation was sought via blood cultures or tissue samples, but was not mandatory for inclusion if the clinical-radiological diagnosis was definitive. Synthesis of Evidence and Study Selection To construct the risk stratification flowchart, ten specific sub-analyses published by the study group between 2021 and 2025 were evaluated( 8 ) ( 9 ) ( 10 ) ( 11 ) ( 3 ) ( 12 ) ( 13 ) ( 14 ) ( 1 ) ( 15 ). These studies utilized the same patient cohort, but focused on distinct clinical variables and outcomes. The methodology for the current algorithm involved extracting statistically significant independent risk factors identified in the multivariate regression analyses across these studies. The synthesis was categorized into four clinical domains: ( 1 ) Baseline Comorbidities and Mortality, ( 2 ) Morphological Destruction, ( 3 ) Symptomatic Prognosis (Quality of Life), and ( 4 ) management of complications. Variable Definitions and Risk Stratification 1. Baseline Comorbidities and Mortality Risk Based on the analysis by Jochimsen et al. (2024) ( 13 ) and Jung et al. (2021) ( 8 ), specific comorbidities were isolated as primary drivers of adverse outcomes. 2. Assessment of Vertebral Destruction To predict the mechanical stability of the spine, the algorithm utilizes a prediction model for "Severe Vertebral Destruction" as established by Hockmann et al. (2025) ( 15 ). Severe destruction was defined radiologically as extensive osteolysis resulting in significant deformity or instability requiring instrumentation. 3. Quality of Life (QoL) and Symptom Assessment Post-treatment functional outcome was assessed using the Oswestry Disability Index (ODI). Based on Yagdiran et al. (2022) ( 14 ) and Sircar et al. (2024) ( 3 ), QoL outcomes were dichotomized into "Favorable" (ODI < 12) and "Poor" (ODI ≥ 35). 4. Complications and Mortality Timing The algorithm distinguishes between early and late mortality based on the temporal analysis by Kernich et al. (2025) ( 12 ). Algorithm development A flowchart is constructed using a hierarchical logic model. Step 1 serves as a "Red Flag" screen for systemic survival, filtering patients with critical comorbidities (chronic kidney disease, malignancy, and infectious endocarditis). Step 2 evaluated the local morphology (Bone Destruction) to guide surgical decision-making regarding stability. Step 3 addresses patient-reported outcome measures (PROMs) to predict their long-term functionality. Finally, Step 4 addresses specific complications that require immediate surveillance. This stepwise approach transforms complex multivariate statistical data—specifically Odds Ratios (OR) and Hazard Ratios (HR)–from source studiesinto a binary decision tree feasible for bedside clinical use. The cutoff values (e.g., CRP ≥ 10 mg/L, age ≥ 65 years) were adopted directly from the statistically optimal thresholds identified in the respective Receiver Operating Characteristic (ROC) analyses of the source publications. Statistical Validation of Source Data All underlying studies used robust statistical methods to validate the risk factors included in this algorithm. Categorical variables were compared using Pearson’s chi-square test or Fisher’s exact test, while continuous variables were analyzed using the Mann-Whitney U test or Student’s t-test. The identification of independent predictors, which form the nodes of this flowchart, was performed using multivariate logistic regression models and Cox proportional hazards models for mortality, ensuring adjustment for confounding variables, such as age and ASA score. Significance was set at p < 0.05 across all source studies. Results Based on these studies, patients at a higher risk for worse outcomes, such as mortality, treatment failure, neurologic deficits, and poor quality of life, typically share specific demographic and clinical characteristics. Risk factors are categorized by the type of "worse outcomes " identified in the research: 1. Mortality and Treatment Failure Patients with pre-existing severe comorbidities face the highest risk of death or treatment failure (defined as death or recurrence within one year). Chronic Kidney Disease (CKD) : This group had a significantly higher risk of early mortality and treatment failure (45%) than patients without comorbidities ( 13 ) ( 12 ) Malignancy (Cancer) : Patients with underlying malignant diseases are at higher risk of treatment failure and late mortality ( 13 ) Higher ASA Classification : Patients with a higher American Society of Anesthesiologists (ASA) physical status classification (typically > 2) are at increased risk of mortality ( 15 ) Age ≥ 65 Years : Older age is consistently associated with higher rates of early and late mortality. ( 12 ) Bacteremia ( 8 ) ( 4 ): Patients with bacteremia have a higher risk of mortality and treatment failure 2. Neurologic Deficits (Specifically in Spinal Epidural Abscess) Specific factors increase the likelihood of developing neurological impairments in patients with Spinal Epidural Abscess (SEA). Age ≥ 65 years ( 15 ) Diabetes mellitus ( 10 ) Multiple Comorbidities : Having more than two comorbid conditions ( 15 ) High Inflammatory Markers : C-reactive protein (CRP) level ≥ 150 mg/l ( 10 ) Abscess Location : Abscesses located dorsally (on the back side of the spinal cord) ( 10 ) 3. Poor Quality of Life (QoL) After Surgery Even after successful surgical treatment for spondylodiscitis, certain patients are less likely to achieve a favorable quality of life (defined by higher disability scores). Presence of Malignant Disease : This independent risk factor for poor QoL outcomes one year after surgery. ( 3 ) Higher Preoperative Leg Pain : Patients who experience intense leg pain before surgery are at a higher risk for poor QoL outcomes. Specifically, severe preoperative leg pain (measured using the visual analog scale [VAS] ) was identified as a decisive independent risk factor. This allows for early patient expectation management, as the presence of this symptom significantly increases the likelihood of long-term disability, regardless of surgical success. ( 3 ) 4. Severe Bone Destruction Severe osseous destruction is an absolute indication for surgery and is more likely to occur in patients with ( 15 ) Obesity: A Body Mass Index (BMI) ≥ 25 kg/m 2 Bacteremia: The presence of bacteria in the bloodstream Older Age (≥ 65) and High CRP (≥ 10 mg/l) Multiple Comorbidities and higher ASA scores 5. Infective Endocarditis (IE) Co-infection Patients with infective endocarditis and spondylodiscitis face complex risks. Research suggests that the sequence of surgical therapy can affect survival and recurrence rates, although specific risk profiles often depend on which condition is treated first and the patient's overall stability ( 12 ). Clinical Algorithm for spondylodiscitis Based on the Cologne Study Group Data 1. Initial Assessment & Risk Stratification Upon admission and confirmation of spondylodiscitis, the patients underwent immediate risk stratification. The primary risk factors determining the treatment path include Sepsis, Chronic Kidney Disease (CKD), malignancy, and Spinal Epidural Abscess (SEA). 2. Emergency Triage The presence of a Spinal Epidural Abscess requires critical evaluation: Emergency Surgery: Indicated immediately if the patient presented with SEA combined with neurological deficits. Early Surgery Consideration: Strongly recommended for patients with SEA who also have Diabetes Mellitus and high CRP levels to prevent rapid deterioration. Standard Path Selection: If critical SEA signs are present, the patient enters one of three risk-based treatment pathways. 3. Risk-Based Treatment Pathways (see Fig. ) Path A: High Mortality Risk (Sepsis, CKD, Elderly) Profile: Patients with high SOFA scores, renal impairment, or advanced age (> 70 years). Strategy: Prioritize aggressive surgical debridement and stabilization to control septic focus, as conservative management carries a higher mortality risk in this group. Path B: High Failure Risk ( S. aureus , Implants) Profile: Patients infected with Staphylococcus aureus or those with existing spinal implants. Strategy: targeted IV antibiotic therapy combined with radical debridement. The "2-Week Checkpoint": Re-evaluate CRP levels after 14 days of therapy. Drop > 50%: Therapy is effective; continue current management. Drop < 50%: indicates treatment failure. Action: Urgent re-imaging (MRI) and reoperation. Path C: Oncology & Palliative Care Profile: Patients with active malignancy. The primary goals are the Quality of Life (QoL) and pain reduction. Strategy: Decision depends on life expectancy. 6 Months: Standard surgical decompression and stabilization to improve sustainable QoL. 4. Long-Term Surveillance Follow-up is divided into two critical mortality zones: Zone 1: Early Mortality (0–30 days): Focus on monitoring renal function (preventing acute-on-chronic failure) and sepsis management. Most deaths in this phase are due to failure of the organism. Zone 2: Late Mortality (31–365 days): Focus on tumor progression (in oncology patients) and infection recurrence (especially in CKD patients). Red Flag: Any recurrent back pain or a slight rise in CRP level warrants urgent MRI to rule out recurrence. Figure 1 Initial Assessment & Triage: Upon admission, patients are evaluated for severe risk factors (sepsis, chronic kidney disease, malignancy) and the presence of a spinal epidural abscess (SEA). The presence of critical signs dictates immediate surgical intervention: emergency surgery for neurological deficits, or early surgery for patients with diabetes and significantly elevated C-reactive protein (CRP). Risk-Stratified Pathways: In the absence of critical SEA signs, management is divided into three distinct tracks: Path A (High Mortality) : Patients with advanced age, sepsis, or CKD are directed toward aggressive surgical intervention. Path B (High Failure): Patients with risks for medical failure (e.g., S. aureus infection, existing implants) begin with IV antibiotic therapy and debridement. Treatment efficacy is evaluated via CRP levels at two weeks; a CRP drop of less than 50% prompts re-imaging and re-operation, whereas a drop greater than 50% indicates continuation of current therapy. Path C (Oncology): Management for patients with underlying malignancies is dictated by life expectancy. Those with a prognosis of less than 6 months receive less invasive care, while those with a prognosis greater than 6 months are candidates for Quality of Life (QoL) surgery. Post-Treatment Surveillance: All pathways converge into a standardized follow-up protocol. Short-term surveillance (0–30 days) monitors for sepsis and renal function, while long-term surveillance (31–365 days) monitors for oncological progression and infection recurrence. Any recurrent pain or subsequent rise in CRP triggers an urgent MRI. Abbreviations: CKD, Chronic Kidney Disease; CRP, C-Reactive Protein; IV, Intravenous; Mo, Months; MRI, Magnetic Resonance Imaging; QoL, Quality of Life; SEA, Spinal Epidural Abscess; VO, Vertebral Osteomyelitis. Discussion Spondylodiscitis is a complex spinal infection characterized by rising incidence rates, particularly in elderly and multimorbid populations(16) (17) (18). The generated flowchart represents a shift from a generalized treatment approach to a risk-stratified personalized model. While current algorithms for the treatment of spondylodiscitis primarily focus on radiological criteria, the presented flowchart is based on the clinical criteria for treatment recommendations (7). MRI is the gold standard for diagnosis in the management of spondylodiscitis. It offers sensitivity for detecting edema, abscess formation, and bone destruction. Radiological imaging provides useful criteria for treatment recommendations (surgical versus nonsurgical) for the current algorithms(7). However, recent studies have highlighted the importance of clinical features for treatment and outcomes in patients with spondylodiscitis(3). Therefore, a comprehensive clinical algorithm is of major relevance as it integrates the patient’s systemic status, neurological function, and response to therapy into the decision-making process. Analysis of the Cologne Study Group data revealed that comorbidities such as diabetes mellitus, chronic kidney disease, and malignancy are as critical as the infection itself(13) (3). The flowchart visualizes a decision-making process that integrates mortality risk, recurrence probability, and quality of life (QoL) into the surgical indication. The flowchart focuses not only on the spine, but also on the systemic status of the patient. The separation of risk factors into sepsis/chronic kidney disease (mortality drivers) and S. aureus/implants (failure drivers) is a fundamental innovation of this algorithm. The results indicate that "Early Mortality" ( 2) and renal impairment, whereas "Late Mortality" is driven by malignancy. This distinction allows clinicians to tailor immediate surveillance: acute care for patients with sepsis versus oncological staging for patients with cancer. The flowchart highlights the Spinal Epidural Abscess (SEA) as the most volatile variable. Neurological deficits remain an absolute indication for emergency decompression (ED). The flowchart introduces a "Consider Early Surgery" node for patients with diabetes mellitus and high CRP. The study data suggest that patients with diabetes and SEA have a significantly higher rate of deterioration(3) (10). Therefore, the algorithm advises against "watchful waiting" in this specific subgroup, favoring early decompression surgery to avoid permanent neurological damage. Path A represents the most vulnerable cohort: elderly patients (>70 years), those with sepsis, or those with chronic kidney disease (CKD)(8) (13). Surprisingly, the data support an aggressive surgical strategy (debridement and stabilization) for this group(8) (4). While intuitively, one might prefer conservative therapy for frail patients, the results suggest that conservative management in septic/CKD patients leads to higher mortality owing to persistent infectious foci (4). CKD was identified as an independent predictor of failure (a 45% failure rate) (13). The flowchart reflects this by funneling these patients toward source control rather than prolonged, potentially ineffective antibiotic suppression alone. Crucially, our findings challenge the traditional reluctance to perform extensive surgery on multimorbid patients, particularly those with chronic kidney disease or geriatric patients. While the prevailing clinical trend often considers these patients 'too sick for surgery' due to elevated perioperative risks, our analysis suggests a paradigm shift: these patients are effectively 'too sick not to be operated on.' Our data demonstrate that, in this vulnerable cohort, the physiological burden of uncontrolled infection far outweighs the stress of surgical intervention. Consequently, rather than serving as a contraindication, the presence of severe comorbidities and sepsis should trigger expedited aggressive surgical source control to prevent mortality. Path B addresses the technical difficulty of eradicating infection. Staphylococcus aureus is notorious for biofilm formation, especially in implants (19). A crucial decision node in the flowchart is the re-evaluation of C-Reactive Protein (CRP) level after 14 days. The study data correlate a failure of CRP to drop by >50% within two weeks with a high probability of treatment failure/recurrence (8). The flowchart dictates that "staying in the course’ is insufficient if this target is missed. It mandates re-imaging (MRI) and revision surgery to prevent months of futile antibiotic therapy. For patients with malignancy, the flowchart shifts the goal from "cure" to "Quality of Life" (QoL). The binary decision node ( 6 months) dictates the invasiveness of the procedure. The results showed that while surgery improves QoL by reducing mechanical instability pain, the recovery burden must not outweigh the remaining lifespan. Therefore, minimally invasive stabilization (e.g., percutaneous screws) is preferred for patients with a short life expectancy (13). The bottom section of the flowchart ("Surveillance") addresses the chronic nature of spondylodiscitis. The distinction between the 0–30 day zone and the 31–365 day zone is clinically vital. In the early phase, the algorithm emphasized renal monitoring. These results highlight that acute-on-chronic kidney failure is the leading cause of death in the first month (4). In the late phase, the focus shifted to recurrence. The flowchart provides a "low threshold for MRI" if the back pain returns. This is based on the finding that recurrence is often subtle in the early stages, but is devastating if missed. The study data on rehabilitation is sobering. Only ~45% of the patients who were working prior to the infection returned to full-time employment (14). This result underscores the need for early counseling, as mentioned in the file snippets. The flowchart implies that "success" is not just a biological cure but must account for significant functional impairment. Limitations Although the flowchart provides a structured approach, it relies heavily on the specific demographics of the present cohort. The clinical algorithm proposed herein was derived from the synthesis of prospectively collected data from a single institutional cohort. Although this approach ensures high data consistency in treatment protocols, it inherently limits the external validity of the model. The algorithm reflects the specific patient demographics and referral patterns of tertiary care centers. Consequently, this flowchart should currently be viewed as a locally validated protocol with strong evidence support rather than a universally applicable guideline. The logical next step and a necessary prerequisite for broad implementation is the validation of this algorithm in a multicenter, prospective study setting. Furthermore, the aggressive surgical stance in Path A (High Mortality) requires a surgical team capable of handling high-risk geriatric anesthesia. Furthermore, the "2-Week CRP Rule" requires strict adherence to timing, which may be difficult in outpatient settings. Conclusion The generated flowchart successfully translated the complex multivariate data into a linear clinical algorithm. By moving away from a purely distinct anatomical classification and radiological criteria (e.g., bone destruction levels) toward a clinical algorithm, it addresses the root causes of mortality (sepsis and chronic kidney disease) and failure (biofilm and recurrence). Furthermore, our findings challenge the traditional view that multimorbid patients are unfit for intervention, demonstrating instead that they are effectively 'too sick not to be operated on,' as the mortality risk of uncontrolled infection far outweighs the physiological stress of surgery. The algorithm proposes that surgery in spondylodiscitis is not just for preserving neurological function, but also as a tool for sepsis control in the frail and pain control in the palliative setting, fundamentally changing the indication spectrum for spine surgeons. Declarations Author Contributions Study conception and design were performed by Ayla Yagdiran and Peer Eysel. Material preparation and data collection were led by Dorothee Hornik with assistance from Ayla Yagdiran. Statistical analysis and interpretation of results were conducted by Stavros Oikonomidis and Norma Jung. The first draft of the manuscript was written by Stavros Oikonomidis, and all authors contributed to subsequent revisions and critical editing. Ayla Yagdiran and Norma Jung provided overall supervision for the project. All authors have read and approved the final manuscript for submission. Declaration of conflicting interest The authors declare that there are no conflicts of interest regarding the publication of this paper. Funding Statement This research received no specific grant from any funding agency in the public, commercial, or other sectors. IRB approval/Research Ethics Committee University Clinic Cologne Germany: The study was approved by the institutional review board: number 09-182. The underlying data were sourced from a prospective registry integrated with the Spine Tango Registry of EuroSpine and German Spine Society (DWG) Registry. References Yagdiran A, Otto-Lambertz C, Lingscheid KM, Sircar K, Samel C, Scheyerer MJ, Zarghooni K, Eysel P, Sobottke R, Jung N, Siewe J. 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PMID: 37980371; PMCID: PMC10657388, 2023. Thavarajasingam SG, Subbiah Ponniah H, Philipps R, Neuhoff J, Kramer A, Demetriades AK, Shiban E, Ringel F, Davies B. Increasing incidence of spondylodiscitis in England: An analysis of the national health service (NHS) hospital episode statistics from 2012 to 2021. Brain Spine May 4;3:101733. doi: 10.1016/j.bas.2023.101733. PMID: 37383429; PMCID: PMC10293225, 2023. Zacher AT, Mirza K, Thieme L, Nietzsche S, Senft C, Schwarz F. Biofilm formation of Staphylococcus aureus on various implants used for surgical treatment of destructive spondylodiscitis. Sci Rep. Aug 21;14(1):19364. 10.1038/s41598-024-70244-6 . PMID: 39169088; PMCID: PMC11339328, 2024. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 17 May, 2026 Reviewers agreed at journal 08 May, 2026 Reviewers invited by journal 06 May, 2026 Editor assigned by journal 05 May, 2026 Submission checks completed at journal 05 May, 2026 First submitted to journal 05 May, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9613598","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":636601641,"identity":"3f570d74-96b4-4639-b7d7-98a6b24970fb","order_by":0,"name":"Stavros Oikonomidis","email":"data:image/png;base64,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","orcid":"","institution":"University of Cologne, University Hospital Cologne","correspondingAuthor":true,"prefix":"","firstName":"Stavros","middleName":"","lastName":"Oikonomidis","suffix":""},{"id":636601644,"identity":"5f173eb6-2b89-4de3-af2b-ad9aefb934b4","order_by":1,"name":"Peer Eysel","email":"","orcid":"","institution":"University of Cologne, University Hospital Cologne","correspondingAuthor":false,"prefix":"","firstName":"Peer","middleName":"","lastName":"Eysel","suffix":""},{"id":636601646,"identity":"9ea88e21-b10a-4d2d-967d-df43b94992b3","order_by":2,"name":"Dorothee Hornik","email":"","orcid":"","institution":"University of Cologne, University Hospital Cologne","correspondingAuthor":false,"prefix":"","firstName":"Dorothee","middleName":"","lastName":"Hornik","suffix":""},{"id":636601648,"identity":"8cd660f5-8062-4982-ba4f-0c3141e4a4e6","order_by":3,"name":"Norma Jung","email":"","orcid":"","institution":"University of Cologne, University Hospital Cologne","correspondingAuthor":false,"prefix":"","firstName":"Norma","middleName":"","lastName":"Jung","suffix":""},{"id":636601650,"identity":"ec15ddf6-c5fd-4e6a-8e8e-71a630b39e48","order_by":4,"name":"Ayla Yagdiran","email":"","orcid":"","institution":"University of Cologne, University Hospital Cologne","correspondingAuthor":false,"prefix":"","firstName":"Ayla","middleName":"","lastName":"Yagdiran","suffix":""}],"badges":[],"createdAt":"2026-05-05 04:09:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9613598/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9613598/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109278962,"identity":"753144e6-130d-457d-9326-58dbe795f6c1","added_by":"auto","created_at":"2026-05-14 16:14:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":242256,"visible":true,"origin":"","legend":"\u003cp\u003eClinical Management and Decision-Making Algorithm for Spondylodiscitis. This flowchart outlines the risk-stratified treatment pathway for patients admitted with a diagnosis of spondylodiscitis.\u003c/p\u003e\n\u003cp\u003eInitial Assessment \u0026amp; Triage: Upon admission, patients are evaluated for severe risk factors (sepsis, chronic kidney disease, malignancy) and the presence of a spinal epidural abscess (SEA). The presence of critical signs dictates immediate surgical intervention: emergency surgery for neurological deficits, or early surgery for patients with diabetes and significantly elevated C-reactive protein (CRP).\u003c/p\u003e\n\u003cp\u003eRisk-Stratified Pathways: In the absence of critical SEA signs, management is divided into three distinct tracks:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePath A (High Mortality)\u003c/strong\u003e: Patients with advanced age, sepsis, or CKD are directed toward aggressive surgical intervention.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePath B (High Failure):\u003c/strong\u003e Patients with risks for medical failure (e.g., S. aureus infection, existing implants) begin with IV antibiotic therapy and debridement. Treatment efficacy is evaluated via CRP levels at two weeks; a CRP drop of less than 50% prompts re-imaging and re-operation, whereas a drop greater than 50% indicates continuation of current therapy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePath C (Oncology):\u003c/strong\u003e Management for patients with underlying malignancies is dictated by life expectancy. Those with a prognosis of less than 6 months receive less invasive care, while those with a prognosis greater than 6 months are candidates for Quality of Life (QoL) surgery.\u003c/p\u003e\n\u003cp\u003ePost-Treatment Surveillance: All pathways converge into a standardized follow-up protocol. Short-term surveillance (0–30 days) monitors for sepsis and renal function, while long-term surveillance (31–365 days) monitors for oncological progression and infection recurrence. Any recurrent pain or subsequent rise in CRP triggers an urgent MRI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003eCKD, Chronic Kidney Disease; CRP, C-Reactive Protein; IV, Intravenous; Mo, Months; MRI, Magnetic Resonance Imaging; QoL, Quality of Life; SEA, Spinal Epidural Abscess; VO, Vertebral Osteomyelitis.\u003c/p\u003e","description":"","filename":"FlowchartSpondylodiszitis.png","url":"https://assets-eu.researchsquare.com/files/rs-9613598/v1/dc692312af5249c2b07376cc.png"},{"id":109296610,"identity":"6f1ca8ce-dd34-4959-bce4-d94025e101a2","added_by":"auto","created_at":"2026-05-15 08:48:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":772391,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9613598/v1/d1cdd8a6-b1c6-4a78-bfa2-344fad70c05b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Treating the host, not just the spine: A novel clinical algorithm for spondylodiscitis based on a prospective 14-Year cohort analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSpondylodiscitis and spinal epidural abscesses represent severe and increasingly common infectious diseases of the spine(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The clinical presentation of spondylodiscitis is highly heterogeneous and ranges from indolent back pain to fulminant sepsis with neurological compromise(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). In addition to survival and control of infectious diseases, preservation of spinal stability and neurological function is the primary objective of orthopedic management. Despite medical treatment, spondylodiscitis can lead to poor quality of life and poor functional outcomes. Even after \"successful\" biological cure, many survivors suffer from chronic pain and significant disability (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Identifying patients at risk of adverse outcomes is crucial for managing surgical interventions. Recent evidence indicates that patients with spondylodiscitis benefit significantly from surgical intervention compared to conservative therapy, particularly in terms of improved survival rates and a reduced risk of disease recurrence(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Furthermore, surgical debridement and stabilization have been shown to lead to superior long-term functional outcomes and quality of life by effectively addressing spinal instability and the infectious burden(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Current guidelines for spondylodiscitis provide robust recommendations for antibiotic stewardship and indications for emergency surgery (e.g., in cases of neurological deficits) (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). However, these recommendations are predominantly based on the radiological criteria derived from advanced imaging modalities. Specifically, decision-making algorithms heavily prioritize morphological findings such as the extent of vertebral bone destruction and the presence of abscesses visible on MRI (magnetic resonance imaging) or CT (computed tomography) scans(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Consequently, the indication for surgical intervention is frequently dictated by the structural integrity of the spine rather than by clinical variables.\u003c/p\u003e \u003cp\u003eThis study aimed to propose a novel evidence-based Clinical Risk Stratification Algorithm. This algorithm was designed to guide clinicians through methodological assessment.\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eBaseline Risk Stratification\u003c/b\u003e: Identifying patients at high risk of mortality and treatment failure due to critical comorbidities.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eStructural Assessment\u003c/b\u003e: Predicting the likelihood of severe vertebral destruction based on a 7-point risk score.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eFunctional Prognosis\u003c/b\u003e: Estimation of long-term Quality of Life outcomes based on preoperative symptom severity.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThe application of this algorithm can help physicians to assess the risk of treatment failure, mortality, and adverse clinical outcomes based on clinical variables. In this sense, the algorithm could identify patients who need urgent surgical intervention and closer follow-up observation to minimize the risk of unfavorable clinical outcomes.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e \u003cem\u003eStudy Design and Data Source\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe clinical algorithm presented in this study was developed through systematic synthesis of data derived from a prospective, monocentric cohort study conducted at a tertiary referral center. The study was approved by the institutional review board (number 09-182. The underlying data were sourced from a prospective registry integrated with the Spine Tango Registry of EuroSpine and German Spine Society (DWG) Registry.\u003c/p\u003e \u003cp\u003eData acquisition spans from 2008 to 2022, in total 355 patients were included. The registry included adult patients (aged\u0026thinsp;\u0026gt;\u0026thinsp;18 years) diagnosed with pyogenic or granulomatous spondylodiscitis. Diagnosis was confirmed based on clinical presentation, elevated inflammatory markers (C-reactive protein [CRP] and leukocytes), and radiological evidence (Magnetic Resonance Imaging [MRI] or Computed Tomography [CT]) demonstrating typical signs of spondylodiscitis (e.g., vertebral bone edema, endplate destruction, fluid intensity in the intervertebral disc, or abscess formation). Microbiological confirmation was sought via blood cultures or tissue samples, but was not mandatory for inclusion if the clinical-radiological diagnosis was definitive.\u003c/p\u003e \u003cp\u003e \u003cem\u003eSynthesis of Evidence and Study Selection\u003c/em\u003e \u003c/p\u003e \u003cp\u003eTo construct the risk stratification flowchart, ten specific sub-analyses published by the study group between 2021 and 2025 were evaluated(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). These studies utilized the same patient cohort, but focused on distinct clinical variables and outcomes. The methodology for the current algorithm involved extracting statistically significant independent risk factors identified in the multivariate regression analyses across these studies. The synthesis was categorized into four clinical domains: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Baseline Comorbidities and Mortality, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Morphological Destruction, (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) Symptomatic Prognosis (Quality of Life), and (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) management of complications.\u003c/p\u003e \u003cp\u003e \u003cem\u003eVariable Definitions and Risk Stratification\u003c/em\u003e \u003c/p\u003e\n\u003ch3\u003e1. Baseline Comorbidities and Mortality Risk\u003c/h3\u003e\n\u003cp\u003eBased on the analysis by Jochimsen et al. (2024) (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) and Jung et al. (2021) (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), specific comorbidities were isolated as primary drivers of adverse outcomes.\u003c/p\u003e\n\u003ch3\u003e2. Assessment of Vertebral Destruction\u003c/h3\u003e\n\u003cp\u003eTo predict the mechanical stability of the spine, the algorithm utilizes a prediction model for \"Severe Vertebral Destruction\" as established by Hockmann et al. (2025) (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Severe destruction was defined radiologically as extensive osteolysis resulting in significant deformity or instability requiring instrumentation.\u003c/p\u003e\n\u003ch3\u003e3. Quality of Life (QoL) and Symptom Assessment\u003c/h3\u003e\n\u003cp\u003ePost-treatment functional outcome was assessed using the Oswestry Disability Index (ODI). Based on Yagdiran et al. (2022) (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) and Sircar et al. (2024) (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e), QoL outcomes were dichotomized into \"Favorable\" (ODI\u0026thinsp;\u0026lt;\u0026thinsp;12) and \"Poor\" (ODI\u0026thinsp;\u0026ge;\u0026thinsp;35).\u003c/p\u003e\n\u003ch3\u003e4. Complications and Mortality Timing\u003c/h3\u003e\n\u003cp\u003eThe algorithm distinguishes between early and late mortality based on the temporal analysis by Kernich et al. (2025) (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eAlgorithm development\u003c/em\u003e \u003c/p\u003e \u003cp\u003eA flowchart is constructed using a hierarchical logic model. \u003cb\u003eStep 1\u003c/b\u003e serves as a \"Red Flag\" screen for systemic survival, filtering patients with critical comorbidities (chronic kidney disease, malignancy, and infectious endocarditis). \u003cb\u003eStep 2\u003c/b\u003e evaluated the local morphology (Bone Destruction) to guide surgical decision-making regarding stability. \u003cb\u003eStep 3\u003c/b\u003e addresses patient-reported outcome measures (PROMs) to predict their long-term functionality. Finally, \u003cb\u003eStep 4\u003c/b\u003e addresses specific complications that require immediate surveillance.\u003c/p\u003e \u003cp\u003eThis stepwise approach transforms complex multivariate statistical data\u0026mdash;specifically Odds Ratios (OR) and Hazard Ratios (HR)\u0026ndash;from source studiesinto a binary decision tree feasible for bedside clinical use. The cutoff values (e.g., CRP\u0026thinsp;\u0026ge;\u0026thinsp;10 mg/L, age\u0026thinsp;\u0026ge;\u0026thinsp;65 years) were adopted directly from the statistically optimal thresholds identified in the respective Receiver Operating Characteristic (ROC) analyses of the source publications.\u003c/p\u003e \u003cp\u003e \u003cem\u003eStatistical Validation of Source Data\u003c/em\u003e \u003c/p\u003e \u003cp\u003eAll underlying studies used robust statistical methods to validate the risk factors included in this algorithm. Categorical variables were compared using Pearson\u0026rsquo;s chi-square test or Fisher\u0026rsquo;s exact test, while continuous variables were analyzed using the Mann-Whitney U test or Student\u0026rsquo;s t-test. The identification of independent predictors, which form the nodes of this flowchart, was performed using multivariate logistic regression models and Cox proportional hazards models for mortality, ensuring adjustment for confounding variables, such as age and ASA score. Significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 across all source studies.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eBased on these studies, patients at a higher risk for worse outcomes, such as mortality, treatment failure, neurologic deficits, and poor quality of life, typically share specific demographic and clinical characteristics.\u003c/p\u003e \u003cp\u003eRisk factors are categorized by the type of \"worse outcomes \" identified in the research:\u003c/p\u003e\n\u003ch3\u003e1. Mortality and Treatment Failure\u003c/h3\u003e\n\u003cp\u003ePatients with pre-existing severe comorbidities face the highest risk of death or treatment failure (defined as death or recurrence within one year).\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eChronic Kidney Disease (CKD)\u003c/em\u003e: This group had a significantly higher risk of early mortality and treatment failure (45%) than patients without comorbidities (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eMalignancy (Cancer)\u003c/em\u003e: Patients with underlying malignant diseases are at higher risk of treatment failure and late mortality (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eHigher ASA Classification\u003c/em\u003e: Patients with a higher American Society of Anesthesiologists (ASA) physical status classification (typically\u0026thinsp;\u0026gt;\u0026thinsp;2) are at increased risk of mortality (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eAge\u0026thinsp;\u0026ge;\u0026thinsp;65 Years\u003c/em\u003e: Older age is consistently associated with higher rates of early and late mortality. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eBacteremia\u003c/em\u003e (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e): Patients with bacteremia have a higher risk of mortality and treatment failure\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e\n\u003ch3\u003e2. Neurologic Deficits (Specifically in Spinal Epidural Abscess)\u003c/h3\u003e\n\u003cp\u003eSpecific factors increase the likelihood of developing neurological impairments in patients with Spinal Epidural Abscess (SEA).\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eAge\u0026thinsp;\u0026ge;\u0026thinsp;65 years\u003c/em\u003e (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eDiabetes mellitus\u003c/em\u003e (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eMultiple Comorbidities\u003c/em\u003e: Having more than two comorbid conditions (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eHigh Inflammatory Markers\u003c/em\u003e: C-reactive protein (CRP) level\u0026thinsp;\u0026ge;\u0026thinsp;150 mg/l (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eAbscess Location\u003c/em\u003e: Abscesses located dorsally (on the back side of the spinal cord) (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e\n\u003ch3\u003e3. Poor Quality of Life (QoL) After Surgery\u003c/h3\u003e\n\u003cp\u003eEven after successful surgical treatment for spondylodiscitis, certain patients are less likely to achieve a favorable quality of life (defined by higher disability scores).\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003ePresence of Malignant Disease\u003c/em\u003e: This independent risk factor for poor QoL outcomes one year after surgery. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eHigher Preoperative Leg Pain\u003c/em\u003e: Patients who experience intense leg pain before surgery are at a higher risk for poor QoL outcomes. Specifically, severe preoperative leg pain (measured using the visual analog scale [VAS] ) was identified as a decisive independent risk factor. This allows for early patient expectation management, as the presence of this symptom significantly increases the likelihood of long-term disability, regardless of surgical success. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e\n\u003ch3\u003e4. Severe Bone Destruction\u003c/h3\u003e\n\u003cp\u003eSevere osseous destruction is an absolute indication for surgery and is more likely to occur in patients with (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eObesity: A Body Mass Index (BMI)\u0026thinsp;\u0026ge;\u0026thinsp;25 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eBacteremia: The presence of bacteria in the bloodstream\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eOlder Age (\u0026ge;\u0026thinsp;65) and High CRP (\u0026ge;\u0026thinsp;10 mg/l)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eMultiple Comorbidities and higher ASA scores\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e\n\u003ch3\u003e5. Infective Endocarditis (IE) Co-infection\u003c/h3\u003e\n\u003cp\u003ePatients with infective endocarditis and spondylodiscitis face complex risks. Research suggests that the sequence of surgical therapy can affect survival and recurrence rates, although specific risk profiles often depend on which condition is treated first and the patient's overall stability (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eClinical Algorithm for spondylodiscitis Based on the Cologne Study Group Data\u003c/b\u003e \u003c/p\u003e\n\u003ch3\u003e1. Initial Assessment \u0026 Risk Stratification\u003c/h3\u003e\n\u003cp\u003eUpon admission and confirmation of spondylodiscitis, the patients underwent immediate risk stratification. The primary risk factors determining the treatment path include Sepsis, Chronic Kidney Disease (CKD), malignancy, and Spinal Epidural Abscess (SEA).\u003c/p\u003e\n\u003ch3\u003e2. Emergency Triage\u003c/h3\u003e\n\u003cp\u003eThe presence of a Spinal Epidural Abscess requires critical evaluation:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eEmergency Surgery: Indicated immediately if the patient presented with SEA combined with neurological deficits.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eEarly Surgery Consideration: Strongly recommended for patients with SEA who also have Diabetes Mellitus and high CRP levels to prevent rapid deterioration.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStandard Path Selection: If critical SEA signs are present, the patient enters one of three risk-based treatment pathways.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e\n\u003ch3\u003e3. Risk-Based Treatment Pathways (see Fig. )\u003c/h3\u003e\n\u003cp\u003e \u003c/p\u003e \u003cp\u003ePath A: High Mortality Risk (Sepsis, CKD, Elderly)\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eProfile: Patients with high SOFA scores, renal impairment, or advanced age (\u0026gt;\u0026thinsp;70 years).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStrategy: Prioritize aggressive surgical debridement and stabilization to control septic focus, as conservative management carries a higher mortality risk in this group.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003ePath B: High Failure Risk (\u003cem\u003eS. aureus\u003c/em\u003e, Implants)\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eProfile: Patients infected with \u003cem\u003eStaphylococcus aureus\u003c/em\u003e or those with existing spinal implants.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStrategy: targeted IV antibiotic therapy combined with radical debridement.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eThe \"2-Week Checkpoint\": Re-evaluate CRP levels after 14 days of therapy.\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eDrop\u0026thinsp;\u0026gt;\u0026thinsp;50%: Therapy is effective; continue current management.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eDrop\u0026thinsp;\u0026lt;\u0026thinsp;50%: indicates treatment failure. Action: Urgent re-imaging (MRI) and reoperation.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003ePath C: Oncology \u0026amp; Palliative Care\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eProfile: Patients with active malignancy. The primary goals are the Quality of Life (QoL) and pain reduction.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStrategy: Decision depends on life expectancy.\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e\u0026lt;\u0026thinsp;6 Months: Minimally invasive stabilization to reduce the surgical burden.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e\u0026gt;\u0026thinsp;6 Months: Standard surgical decompression and stabilization to improve sustainable QoL.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e\n\u003ch3\u003e4. Long-Term Surveillance\u003c/h3\u003e\n\u003cp\u003eFollow-up is divided into two critical mortality zones:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eZone 1: Early Mortality (0\u0026ndash;30 days): Focus on monitoring renal function (preventing acute-on-chronic failure) and sepsis management. Most deaths in this phase are due to failure of the organism.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eZone 2: Late Mortality (31\u0026ndash;365 days): Focus on tumor progression (in oncology patients) and infection recurrence (especially in CKD patients).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eRed Flag: Any recurrent back pain or a slight rise in CRP level warrants urgent MRI to rule out recurrence.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eInitial Assessment \u0026amp; Triage: Upon admission, patients are evaluated for severe risk factors (sepsis, chronic kidney disease, malignancy) and the presence of a spinal epidural abscess (SEA). The presence of critical signs dictates immediate surgical intervention: emergency surgery for neurological deficits, or early surgery for patients with diabetes and significantly elevated C-reactive protein (CRP).\u003c/p\u003e\n\u003cp\u003eRisk-Stratified Pathways: In the absence of critical SEA signs, management is divided into three distinct tracks:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePath A (High Mortality)\u003c/strong\u003e: Patients with advanced age, sepsis, or CKD are directed toward aggressive surgical intervention.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePath B (High Failure):\u003c/strong\u003e Patients with risks for medical failure (e.g., S. aureus infection, existing implants) begin with IV antibiotic therapy and debridement. Treatment efficacy is evaluated via CRP levels at two weeks; a CRP drop of less than 50% prompts re-imaging and re-operation, whereas a drop greater than 50% indicates continuation of current therapy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePath C (Oncology):\u003c/strong\u003e Management for patients with underlying malignancies is dictated by life expectancy. Those with a prognosis of less than 6 months receive less invasive care, while those with a prognosis greater than 6 months are candidates for Quality of Life (QoL) surgery.\u003c/p\u003e\n\u003cp\u003ePost-Treatment Surveillance: All pathways converge into a standardized follow-up protocol. Short-term surveillance (0–30 days) monitors for sepsis and renal function, while long-term surveillance (31–365 days) monitors for oncological progression and infection recurrence. Any recurrent pain or subsequent rise in CRP triggers an urgent MRI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e CKD, Chronic Kidney Disease; CRP, C-Reactive Protein; IV, Intravenous; Mo, Months; MRI, Magnetic Resonance Imaging; QoL, Quality of Life; SEA, Spinal Epidural Abscess; VO, Vertebral Osteomyelitis.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eSpondylodiscitis is a complex spinal infection characterized by rising incidence rates, particularly in elderly and multimorbid populations(16)\u0026nbsp;(17)\u0026nbsp;(18). The generated flowchart represents a shift from a generalized treatment approach to a risk-stratified personalized model. While current algorithms for the treatment of spondylodiscitis primarily focus on radiological criteria, the presented flowchart is based on the clinical criteria for treatment recommendations\u0026nbsp;(7). MRI is the gold standard for diagnosis in the management of spondylodiscitis. It offers sensitivity for detecting edema, abscess formation, and bone destruction. Radiological imaging provides useful criteria for treatment recommendations (surgical versus nonsurgical) for the current algorithms(7). However, recent studies have highlighted the importance of clinical features for treatment and outcomes in patients with spondylodiscitis(3). Therefore, a comprehensive clinical algorithm is of major relevance as it integrates the patient\u0026rsquo;s systemic status, neurological function, and response to therapy into the decision-making process. Analysis of the Cologne Study Group data revealed that comorbidities such as diabetes mellitus, chronic kidney disease, and malignancy are as critical as the infection itself(13) (3). The flowchart visualizes a decision-making process that integrates mortality risk, recurrence probability, and quality of life (QoL) into the surgical indication. The flowchart focuses not only on the spine, but also on the systemic status of the patient. The separation of risk factors into sepsis/chronic kidney disease (mortality drivers) and S. aureus/implants (failure drivers) is a fundamental innovation of this algorithm. The results indicate that \u0026quot;Early Mortality\u0026quot; (\u0026lt;30 days) is driven by organ failure (SOFA \u0026gt; 2) and renal impairment, whereas \u0026quot;Late Mortality\u0026quot; is driven by malignancy. This distinction allows clinicians to tailor immediate surveillance: acute care for patients with sepsis versus oncological staging for patients with cancer.\u003c/p\u003e\n\u003cp\u003eThe flowchart highlights the Spinal Epidural Abscess (SEA) as the most volatile variable. Neurological deficits remain an absolute indication for emergency decompression (ED). The flowchart introduces a \u0026quot;Consider Early Surgery\u0026quot; node for patients with diabetes mellitus and high CRP. The study data suggest that patients with diabetes and SEA have a significantly higher rate of deterioration(3)\u0026nbsp;(10). Therefore, the algorithm advises against \u0026quot;watchful waiting\u0026quot; in this specific subgroup, favoring early decompression surgery to avoid permanent neurological damage. \u003cstrong\u003ePath A\u003c/strong\u003e represents the most vulnerable cohort: elderly patients (\u0026gt;70 years), those with sepsis, or those with chronic kidney disease (CKD)(8) (13).\u003c/p\u003e\n\u003cp\u003eSurprisingly, the data support an aggressive surgical strategy (debridement and stabilization) for this group(8)\u0026nbsp;(4). While intuitively, one might prefer conservative therapy for frail patients, the results suggest that conservative management in septic/CKD patients leads to higher mortality owing to persistent infectious foci\u0026nbsp;(4). CKD was identified as an independent predictor of failure (a 45% failure rate)\u0026nbsp;(13). The flowchart reflects this by funneling these patients toward source control rather than prolonged, potentially ineffective antibiotic suppression alone. Crucially, our findings challenge the traditional reluctance to perform extensive surgery on multimorbid patients, particularly those with chronic kidney disease or geriatric patients. While the prevailing clinical trend often considers these patients \u0026apos;too sick for surgery\u0026apos; due to elevated perioperative risks, our analysis suggests a paradigm shift: these patients are effectively \u0026apos;too sick not to be operated on.\u0026apos; Our data demonstrate that, in this vulnerable cohort, the physiological burden of uncontrolled infection far outweighs the stress of surgical intervention. Consequently, rather than serving as a contraindication, the presence of severe comorbidities and sepsis should trigger expedited aggressive surgical source control to prevent mortality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePath B\u003c/strong\u003e addresses the technical difficulty of eradicating infection. \u003cem\u003eStaphylococcus aureus\u003c/em\u003e is notorious for biofilm formation, especially in implants (19). A crucial decision node in the flowchart is the re-evaluation of C-Reactive Protein (CRP) level after 14 days. The study data correlate a failure of CRP to drop by \u0026gt;50% within two weeks with a high probability of treatment failure/recurrence (8). The flowchart dictates that \u0026quot;staying in the course\u0026rsquo; is insufficient if this target is missed. It mandates re-imaging (MRI) and revision surgery to prevent months of futile antibiotic therapy.\u003c/p\u003e\n\u003cp\u003eFor patients with malignancy, the flowchart shifts the goal from \u0026quot;cure\u0026quot; to \u0026quot;Quality of Life\u0026quot; (QoL). The binary decision node (\u0026lt; 6 vs. \u0026gt; 6 months) dictates the invasiveness of the procedure. The results showed that while surgery improves QoL by reducing mechanical instability pain, the recovery burden must not outweigh the remaining lifespan. Therefore, minimally invasive stabilization (e.g., percutaneous screws) is preferred for patients with a short life expectancy\u0026nbsp;(13).\u003c/p\u003e\n\u003cp\u003eThe bottom section of the flowchart (\u0026quot;Surveillance\u0026quot;) addresses the chronic nature of spondylodiscitis. The distinction between the 0\u0026ndash;30 day zone and the 31\u0026ndash;365 day zone is clinically vital. In the early phase, the algorithm emphasized renal monitoring. These results highlight that acute-on-chronic kidney failure is the leading cause of death in the first month\u0026nbsp;(4). In the late phase, the focus shifted to recurrence. The flowchart provides a \u0026quot;low threshold for MRI\u0026quot; if the back pain returns. This is based on the finding that recurrence is often subtle in the early stages, but is devastating if missed. The study data on rehabilitation is sobering. Only ~45% of the patients who were working prior to the infection returned to full-time employment\u0026nbsp;(14). This result underscores the need for early counseling, as mentioned in the file snippets. The flowchart implies that \u0026quot;success\u0026quot; is not just a biological cure but must account for significant functional impairment.\u003c/p\u003e\n\u003cp\u003eLimitations\u003c/p\u003e\n\u003cp\u003eAlthough the flowchart provides a structured approach, it relies heavily on the specific demographics of the present cohort. The clinical algorithm proposed herein was derived from the synthesis of prospectively collected data from a single institutional cohort. Although this approach ensures high data consistency in treatment protocols, it inherently limits the external validity of the model. The algorithm reflects the specific patient demographics and referral patterns of tertiary care centers. Consequently, this flowchart should currently be viewed as a locally validated protocol with strong evidence support rather than a universally applicable guideline. The logical next step and a necessary prerequisite for broad implementation is the validation of this algorithm in a multicenter, prospective study setting. \u0026nbsp;Furthermore, the aggressive surgical stance in Path A (High Mortality) requires a surgical team capable of handling high-risk geriatric anesthesia. Furthermore, the \u0026quot;2-Week CRP Rule\u0026quot; requires strict adherence to timing, which may be difficult in outpatient settings.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe generated flowchart successfully translated the complex multivariate data into a linear clinical algorithm. By moving away from a purely distinct anatomical classification and radiological criteria (e.g., bone destruction levels) toward a clinical algorithm, it addresses the root causes of mortality (sepsis and chronic kidney disease) and failure (biofilm and recurrence). Furthermore, our findings challenge the traditional view that multimorbid patients are unfit for intervention, demonstrating instead that they are effectively \u0026apos;too sick not to be operated on,\u0026apos; as the mortality risk of uncontrolled infection far outweighs the physiological stress of surgery.\u003c/p\u003e\n\u003cp\u003eThe algorithm proposes that surgery in spondylodiscitis is not just for preserving neurological function, but also as a tool for sepsis control in the frail and pain control in the palliative setting, fundamentally changing the indication spectrum for spine surgeons.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy conception and design were performed by Ayla Yagdiran \u0026nbsp;and Peer Eysel. Material preparation and data collection were led by Dorothee Hornik with assistance from Ayla Yagdiran. Statistical analysis and interpretation of results were conducted by Stavros Oikonomidis and Norma Jung. The first draft of the manuscript was written by Stavros Oikonomidis, and all authors contributed to subsequent revisions and critical editing. Ayla Yagdiran and Norma Jung provided overall supervision for the project. All authors have read and approved the final manuscript for submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of conflicting interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no conflicts of interest regarding the publication of this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or other sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIRB approval/Research Ethics Committee University Clinic Cologne Germany:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the institutional review board: number 09-182. The underlying data were sourced from a prospective registry integrated with the Spine Tango Registry of EuroSpine and German Spine Society (DWG) Registry.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eYagdiran A, Otto-Lambertz C, Lingscheid KM, Sircar K, Samel C, Scheyerer MJ, Zarghooni K, Eysel P, Sobottke R, Jung N, Siewe J. Quality of life and mortality after surgical treatment for vertebral osteomyelitis (VO): a prospective study. Eur Spine J Jun;30(6):1721\u0026ndash;31. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00586-020-06519-z\u003c/span\u003e\u003cspan address=\"10.1007/s00586-020-06519-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2020 Jul 1. PMID: 32613398, 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavis DP, Wold RM, Patel RJ, Tran AJ, Tokhi RN, Chan TC, Vilke GM. 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Can we predict favourable quality of life after surgically treated vertebral osteomyelitis? Analysis of a prospective study. Arch Orthop Trauma Surg May;143(5):2317\u0026ndash;24. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00402-022-04431-3\u003c/span\u003e\u003cspan address=\"10.1007/s00402-022-04431-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2022 Mar 31. PMID: 35359162; PMCID: PMC10110645, 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSircar K, Jung N, Kernich N, Zarghooni K, Eysel P, Yagdiran A, Herren C. Risk Factors for Neurologic Deficits in Patients With Spinal Epidural Abscess: An Analysis of One-Hundred-Forty Cases. Global Spine J Mar;15(2):474\u0026ndash;81. doi: 10.1177/21925682231194467. Epub 2023 Aug 7. PMID: 37548223; PMCID: PMC11881126, 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeber C, Misfeld M, Diab M, Saha S, Elderia A, Marin-Cuartas M, Luehr M, Yagdiran A, Eysel P, Jung N, Hagl C, Doenst T, Borger MA, Kernich N, Wahlers T. Infective endocarditis and spondylodiscitis-impact of sequence of surgical therapy on survival and recurrence rate. \u003cem\u003eEur J Cardiothorac Surg.\u003c/em\u003e Jul 1;66(1):ezae246. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/ejcts/ezae246\u003c/span\u003e\u003cspan address=\"10.1093/ejcts/ezae246\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 38964339, 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKernich N, Abi-Chokami A, Jung N, Jochimsen D, Sircar K, Hoffmann AM, Meuser S, Eysel P, Weber C, Vinas-Rios JM, Yagdiran A. Interdisciplinary Studygroup of Spondylodiscitis \u0026ndash; Cologne (IST-SPONDYL). Early and late mortality in vertebral osteomyelitis: who dies within the first year after diagnosis. Infection Oct;53(5):2025\u0026ndash;35. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s15010-025-02541-9\u003c/span\u003e\u003cspan address=\"10.1007/s15010-025-02541-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2025 May 9. PMID: 40343568; PMCID: PMC12460364, 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJochimsen D, Yagdiran A, Meyer-Schwickerath C, Sircar K, Kernich N, Eysel P, Weber C, Jung N. Vertebral osteomyelitis in patients with an underlying malignancy or chronic kidney disease - who is at higher risk for adverse outcome? Infection Aug;53(4):1363\u0026ndash;72. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s15010-024-02451-2\u003c/span\u003e\u003cspan address=\"10.1007/s15010-024-02451-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2024 Dec 21. PMID: 39708242; PMCID: PMC12316775, 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYagdiran A, Bredow J, Weber C, Mousa Basha G, Eysel P, Fischer J, Jung N. The Burden of Vertebral Osteomyelitis-An Analysis of the Workforce before and after Treatment. J Clin Med Feb 18;11(4):1095. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/jcm11041095\u003c/span\u003e\u003cspan address=\"10.3390/jcm11041095\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 35207367; PMCID: PMC8875884, 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHockmann JP, Kernich N, Sircar K, Eysel P, Hoffmann A, Jochimsen D, Jung N, Yagdiran A. Severe destruction in vertebral osteomyelitis - risk factors and survival. Infection Nov 24. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s15010-025-02701-x\u003c/span\u003e\u003cspan address=\"10.1007/s15010-025-02701-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub ahead of print. PMID: 41284212, 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHeck VJ, Prasse T, Klug K, Vinas-Rios JM, Oikonomidis S, Klug A, Kernich N, Weber M, von der H\u0026ouml;h N, Lenz M, Walter SG, Himpe B, Eysel P, Scheyerer MJ. The projected increase of vertebral osteomyelitis in Germany implies a demanding challenge for future healthcare management of aging populations. Infection Aug;52(4):1489\u0026ndash;97. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s15010-024-02243-8\u003c/span\u003e\u003cspan address=\"10.1007/s15010-024-02243-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2024 Apr 9. PMID: 38592659; PMCID: PMC11289156, 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKramer A, Thavarajasingam SG, Neuhoff J, Ponniah HS, Ramsay DSC, Demetriades AK, Davies BM, Shiban E, Ringel F. Epidemiological trends of pyogenic spondylodiscitis in Germany: an EANS Spine Section Study. \u003cem\u003eSci Rep.\u003c/em\u003e Nov 18;13(1):20225. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-023-47341-z\u003c/span\u003e\u003cspan address=\"10.1038/s41598-023-47341-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 37980371; PMCID: PMC10657388, 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThavarajasingam SG, Subbiah Ponniah H, Philipps R, Neuhoff J, Kramer A, Demetriades AK, Shiban E, Ringel F, Davies B. Increasing incidence of spondylodiscitis in England: An analysis of the national health service (NHS) hospital episode statistics from 2012 to 2021. Brain Spine May 4;3:101733. doi: 10.1016/j.bas.2023.101733. PMID: 37383429; PMCID: PMC10293225, 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZacher AT, Mirza K, Thieme L, Nietzsche S, Senft C, Schwarz F. Biofilm formation of Staphylococcus aureus on various implants used for surgical treatment of destructive spondylodiscitis. \u003cem\u003eSci Rep.\u003c/em\u003e Aug 21;14(1):19364. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-024-70244-6\u003c/span\u003e\u003cspan address=\"10.1038/s41598-024-70244-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 39169088; PMCID: PMC11339328, 2024.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"infection","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infe","sideBox":"Learn more about [Infection](http://link.springer.com/journal/15010)","snPcode":"15010","submissionUrl":"https://submission.nature.com/new-submission/15010/3","title":"Infection","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Spondylodiscitis, vertebral osteomyelitis, clinical algorithm, prospective cohort study, spinal infection","lastPublishedDoi":"10.21203/rs.3.rs-9613598/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9613598/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eThis study introduces a novel Clinical Risk Stratification Algorithm for spondylodiscitis, shifting the management focus from purely radiological criteria to clinical risk factors.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe study presents a novel clinical risk stratification algorithm for spondylodiscitis, developed through a systematic synthesis of data from a 14-year prospective monocentric cohort. Developed from a prospective 14-year cohort (2008\u0026ndash;2022) at a tertiary center, the algorithm synthesizes data from ten sub-analyses using multivariate regression to identify key drivers of mortality and treatment failure.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSignificant risk factors for adverse outcomes include Chronic Kidney Disease (CKD), malignancy, age\u0026thinsp;\u0026ge;\u0026thinsp;65, and bacteremia. For patients with Spinal Epidural Abscess (SEA), diabetes and CRP levels\u0026thinsp;\u0026ge;\u0026thinsp;150 mg/l are critical predictors of neurologic deficit. The algorithm categorizes patients into three pathways: Path A (High Mortality) prioritizes aggressive surgical source control, challenging the traditional view that multimorbid patients are \"too sick for surgery\". Path B addresses failure risks like \u003cem\u003eS. aureus\u003c/em\u003e using a \"2-week CRP Checkpoint\" to guide potential revision surgery. Path C focuses on quality-of-life-driven palliative care for oncology patients.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis clinical tool enables personalized management by integrating systemic status into surgical decision-making. It emphasizes that surgery is a vital tool for sepsis control in frail patients and pain management in palliative care.\u003c/p\u003e","manuscriptTitle":"Treating the host, not just the spine: A novel clinical algorithm for spondylodiscitis based on a prospective 14-Year cohort analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-14 16:13:56","doi":"10.21203/rs.3.rs-9613598/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"89208763421816849773776744655450666417","date":"2026-05-17T06:21:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"214503146274463985719133346853365764105","date":"2026-05-08T05:36:54+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-05-06T04:20:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-05T11:58:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-05-05T11:45:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"Infection","date":"2026-05-05T04:02:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"infection","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infe","sideBox":"Learn more about [Infection](http://link.springer.com/journal/15010)","snPcode":"15010","submissionUrl":"https://submission.nature.com/new-submission/15010/3","title":"Infection","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"8439e074-f256-45c0-bf71-ec9f7d5d2d32","owner":[],"postedDate":"May 14th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"89208763421816849773776744655450666417","date":"2026-05-17T06:21:33+00:00","index":27,"fulltext":""},{"type":"reviewerAgreed","content":"214503146274463985719133346853365764105","date":"2026-05-08T05:36:54+00:00","index":20,"fulltext":""},{"type":"reviewersInvited","content":"21","date":"2026-05-06T04:20:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-05T11:58:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-05-05T11:45:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"Infection","date":"2026-05-05T04:02:34+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-14T16:13:56+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-14 16:13:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9613598","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9613598","identity":"rs-9613598","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}