Evidence map›Paper›PMID 42563307›Full record

ArticleNeurospine2026

The MSI-20 Score Provides Reproducible Mortality Risk Stratification in Spinal Infection: A Multicenter Registry Study and External Validation.

Sara Lener, Raphael Gmeiner, Anto Abramovic, Anna Koller, Christoph Orban, Sebastian Hartmann, Alexandra Grob, Victor Staartjes, Ann Kathrin Joerger, Carolin Albrecht and 17 more

Abstract read
In one paragraph

Article in Neurospine, 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

27 authors.

Sara Lener *Department of Neurosurgery, Medical University of Innsbruck, Innsbruck, Austria. sara.lener@i-med.ac.at.
Raphael Gmeiner *Department of Neurosurgery, Medical University of Innsbruck, Innsbruck, Austria.
Anto AbramovicDepartment of Neurosurgery, Medical University of Innsbruck, Innsbruck, Austria.
Anna KollerDepartment of Neurosurgery, Medical University of Innsbruck, Innsbruck, Austria.
Christoph OrbanDepartment of Neurosurgery, Medical University of Innsbruck, Innsbruck, Austria.
Sebastian HartmannDepartment of Neurosurgery and Neurology, Spine Center Innsbruck (WIK), Sanatorium Kettenbrücke, Innsbruck, Austria.
Alexandra GrobMachine Intelligence in Clinical Neuroscience and Microsurgical Neuroanatomy (MICN) Laboratory, Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Victor StaartjesMachine Intelligence in Clinical Neuroscience and Microsurgical Neuroanatomy (MICN) Laboratory, Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Ann Kathrin JoergerDepartment of Neurosurgery, Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Germany.
Carolin AlbrechtDepartment of Neurosurgery, Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Germany.
Bernhard MeyerDepartment of Neurosurgery, Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Germany.
Felipa LangeDepartment of Neurosurgery, Klinikum Dortmund Hospital, Dortmund, Germany.
Andreas KramerDepartment of Neurosurgery, University Medical Center Mainz, Mainz, Germany.
Florian RingelDepartment of Neurosurgery, University Medical Center Mainz, Mainz, Germany.
Christopher Marvin JesseDepartment of Neurosurgery, Inselspital, Bern University Hospital, Bern, Switzerland.
Ralph T SchärDepartment of Neurosurgery, Inselspital, Bern University Hospital, Bern, Switzerland.
Christoph BettagDepartment of Neurosurgery, University Hospital Goettingen, Göttingen, Germany.
Veit RohdeDepartment of Neurosurgery, University Hospital Goettingen, Göttingen, Germany.
Insa K JanssenDepartment of Neurosurgery, Hôpitaux Universitaires de Genève, Geneva, Switzerland.
Karl SchallerDepartment of Neurosurgery, Hôpitaux Universitaires de Genève, Geneva, Switzerland.
Julia OnkenDepartment of Neurosurgery, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Aminaa SanchinDepartment of Neurosurgery, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Peter VajkoczyDepartment of Neurosurgery, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Imran ShahEdinburgh Spinal Surgery Outcome Studies Group, Department of Neurosurgery, Royal Infirmary Edinburgh, Scotland, UK.
Rebecca SutherlandDepartment of Infectious Diseases, Western General Hospital, Edinburgh, Scotland, UK.
Andreas K DemetriadesEdinburgh Spinal Surgery Outcome Studies Group, Department of Neurosurgery, Royal Infirmary Edinburgh, Scotland, UK.
Claudius ThoméDepartment of Neurosurgery, Medical University of Innsbruck, Innsbruck, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveSpinal infection (SI) is associated with substantial morbidity and mortality, and optimal treatment strategies remain debated, particularly in medically fragile patients. The Mortality in Spinal Infection (MSI-20) score was developed as the first dedicated prognostic tool for mortality risk estimation, but external validation in large cohorts has been lacking. This study aimed to externally validate the MSI-20 in a large multicenter registry cohort and assess its performance, clinical thresholds, and generalizability.

methodsThis retrospective multi-institutional registry study included 1,122 adult patients with clinically, radiologically, and laboratory-confirmed SI treated at 6 tertiary referral centers between 2010 and 2023. The multicenter registry design enabled robust analysis of this relatively rare outcome. MSI-20 scores were calculated according to the original definition. Predictive performance was evaluated using receiver operating characteristic (ROC) analysis with 95% confidence intervals. Mortality across score strata and center-wise performance were analyzed, with exploratory assessment of additional baseline predictors.

resultsMean age was 66.4±13.1 years, and overall mortality was 18.3%. The MSI-20 demonstrated fair discriminative ability (area under the curve [AUC], 0.68; 95% confidence interval [CI], 64-72). The optimal ROC threshold was 3.5; a cutoff ≥4 yielded sensitivity 0.49 and specificity 0.74 (F1 score, 0.38). Mortality increased progressively, approaching 50% (47.4%) at scores ≥9. Performance was consistent across centers (AUC, 0.60-0.75). Exploratory univariable analyses did not identify additional baseline variables with consistent strong associations beyond the MSI-20 components.

conclusionThis large multicenter registry study provides the first external validation of the MSI-20, confirming reproducibility and generalizability. The score demonstrated fair discrimination and a clear risk gradient across increasing score categories. Given its simplicity and high negative predictive value, the MSI-20 may serve as an adjunctive tool to support risk communication, multidisciplinary discussion, patient counseling, and preoperative optimization in spinal infection.

Indexed as

MortalityMSI-20Risk StratificatioScore validationSpinal infectionSpondylodiscitis

Identifiers

PMID42563307
PMCPMC13448032

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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.