Evidence map›Paper›PMID 42611160›Full record

ArticleInfection2026

Treating the host, not just the spine: a position paper proposing a clinical algorithm for spondylodiscitis based on a prospective 14-year cohort analysis.

Stavros Oikonomidis, Peer Eysel, Dorothee Hornik, Norma Jung, Ayla Yagdiran

Abstract read
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Article in Infection, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Stavros OikonomidisDepartment of Orthopaedic Surgery, Traumatology and Plastic-Reconstructive Surgery, University of Cologne, Faculty of Medicine and University Hospital Cologne, Joseph-Stelzmann-Str. 24, 50931, Cologne, Germany. Stavros.oikonomidis@rwth-aachen.de.ORCID http://orcid.org/0000-0002-7637-8611
Peer EyselDepartment of Orthopaedic Surgery, Traumatology and Plastic-Reconstructive Surgery, University of Cologne, Faculty of Medicine and University Hospital Cologne, Joseph-Stelzmann-Str. 24, 50931, Cologne, Germany.
Dorothee HornikDivision of Infectious Diseases, Department I of Internal Medicine, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany.
Norma Jung *Division of Infectious Diseases, Department I of Internal Medicine, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany.
Ayla Yagdiran *Department of Orthopaedic Surgery, Traumatology and Plastic-Reconstructive Surgery, University of Cologne, Faculty of Medicine and University Hospital Cologne, Joseph-Stelzmann-Str. 24, 50931, Cologne, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study introduces a novel Clinical Risk Stratification Algorithm for spondylodiscitis, shifting the management focus from purely radiological criteria to clinical risk factors.

methodsThe 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.

resultsSignificant 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.

conclusionThis 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. While based on robust individual predictors, the proposed integrated decision tree has not yet undergone internal or external validation to confirm its clinical utility.

Indexed as

Clinical algorithmProspective cohort studySpinal infectionSpondylodiscitisVertebral osteomyelitis

Identifiers

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.