Evidence map›Paper›PMID 41644851›Full record

SynthesisNeurosurgical review2026

Comparative predictive performance of computed tomography scoring systems in traumatic brain injury: a systematic review, Bayesian comparison, and meta-analysis.

Armin Khavandegar, Zahra Ramezani, Elaheh Khodadoust, Mahgol Sadat Hassan Zadeh Tabatabaei, Tahereh Maleki, Negin Safari Dehnavi, Mario Ganau, Lara Prisco, Ghazaleh Kheiri, Nasim Ramzi and 10 more

Abstract readSystematic ReviewMeta-AnalysisComparative Study
PubMed Publisher
In one paragraph

Synthesis in Neurosurgical review, 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

20 authors.

Armin KhavandegarSina Trauma and Surgery Research Center, Sina Hospital, Tehran University of Medical Sciences (TUMS), Hassan Abad Square, Imam Khomeini Avenue, 11365-3876, Tehran, Iran.ORCID http://orcid.org/0000-0002-4761-8938
Zahra RamezaniSina Trauma and Surgery Research Center, Sina Hospital, Tehran University of Medical Sciences (TUMS), Hassan Abad Square, Imam Khomeini Avenue, 11365-3876, Tehran, Iran.ORCID http://orcid.org/0009-0003-8472-9412
Elaheh KhodadoustSina Trauma and Surgery Research Center, Sina Hospital, Tehran University of Medical Sciences (TUMS), Hassan Abad Square, Imam Khomeini Avenue, 11365-3876, Tehran, Iran.ORCID http://orcid.org/0009-0003-4551-5139
Mahgol Sadat Hassan Zadeh TabatabaeiSina Trauma and Surgery Research Center, Sina Hospital, Tehran University of Medical Sciences (TUMS), Hassan Abad Square, Imam Khomeini Avenue, 11365-3876, Tehran, Iran.ORCID http://orcid.org/0000-0003-1551-2239
Tahereh MalekiSchool of Medicine, Tehran University of Medical Sciences, Tehran, Iran.ORCID http://orcid.org/0000-0002-7288-0372
Negin Safari DehnaviSchool of Medicine, Tehran University of Medical Sciences, Tehran, Iran.ORCID http://orcid.org/0009-0003-5851-8611
Mario GanauNuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.ORCID http://orcid.org/0000-0002-8676-1147
Lara PriscoNuffield Division of Anaesthetics, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.ORCID http://orcid.org/0000-0001-6727-7870
Ghazaleh KheiriDepartment of Neurosurgery, Children's Medical Center, Tehran University of Medical Science, Tehran, Iran.ORCID http://orcid.org/0000-0001-6272-2402
Nasim RamziNeurology Department, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.ORCID http://orcid.org/0009-0008-6704-5373
Maral MoafiCell Biology and Anatomical Sciences, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.ORCID http://orcid.org/0000-0002-4099-4017
Roberto ParisiLaboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, via S. Allende, 1, Baronissi, SA, 84081, Italy.ORCID http://orcid.org/0009-0003-7025-169X
Sadra KheiriDepartment of Neurosurgery, Isfahan University of Medical Sciences, Isfahan, Iran.ORCID http://orcid.org/0009-0002-0342-8793
Soroush MozaffariSchool of Medicine, Tehran University of Medical Sciences, Tehran, Iran.ORCID http://orcid.org/0009-0000-4473-1479
Mustafa RamezanianSchool of Medicine, Tehran University of Medical Sciences, Tehran, Iran.ORCID http://orcid.org/0009-0001-9457-3090
Seyed Mohammad Sina Hosseini SharifSchool of Medicine, Tehran University of Medical Sciences, Tehran, Iran.ORCID http://orcid.org/0009-0005-6892-8969
Seyed Mohammad Sajad Hosseini SharifSchool of Medicine, Tehran University of Medical Sciences, Tehran, Iran.ORCID http://orcid.org/0009-0009-4610-102X
Shahrzad NooriSina Trauma and Surgery Research Center, Sina Hospital, Tehran University of Medical Sciences (TUMS), Hassan Abad Square, Imam Khomeini Avenue, 11365-3876, Tehran, Iran.ORCID http://orcid.org/0009-0008-8747-4933
Shayan DabbaghNeurosurgery Department, School of Medicine, Tehran university of medical sciences, Tehran, Iran.ORCID http://orcid.org/0009-0005-6500-586X
Mahdi Sharif-AlhoseiniSina Trauma and Surgery Research Center, Sina Hospital, Tehran University of Medical Sciences (TUMS), Hassan Abad Square, Imam Khomeini Avenue, 11365-3876, Tehran, Iran. msharif@tums.ac.ir.ORCID http://orcid.org/0000-0001-7213-2107

Funding

Tehran University of Medical Sciences and Health Services 1400-3-163-56137
6 · The paper itself

Abstract

Various computed tomography (CT)-based Traumatic brain injury (TBI) scoring systems, including Marshall, Rotterdam, Helsinki, Stockholm, and the more recent NeuroImaging Radiological Interpretation System (NIRIS), have been specifically developed to estimate prognosis based on radiological features. We aimed to comprehensively compare the CT scoring systems’ predictive accuracy across diverse clinical outcomes. Bayesian multilevel logistic regression was applied to assess the predictive performance of scoring systems for in-hospital, 1-month, 6-month, and 12-month mortality, as well as unfavorable outcomes. Moreover, area under the curve (AUC) values were pooled across all outcomes using random-effects models. Pooled meta-analysis on AUC aimed to evaluate the predictive performance of each CT scoring system across different outcomes. A total of 32 studies involving 23,529 patients were included. In 32 included studies, the Rotterdam scoring system was the most frequently used in 26 studies (81%). Followed by Marshall in 17 studies (53%), Helsinki in 10 studies (31%), Stockholm in four studies (12%), and the NIRIS system in only one study (3%). The pooled meta-analysis on AUC across all outcomes for the Rotterdam score using AUC was 0.774 (0.751–0.797). The Marshall score revealed a moderate predictive AUC of 0.695 (0.660–0.729). The Helsinki score had a pooled AUC of 0.772 (0.746–0.798). The Stockholm score demonstrated a relatively higher accuracy with an AUC of 0.778 (0.739–0.818). The Bayesian comparative analysis indicated that the Helsinki score has relatively higher accuracy for 6-month mortality (AUC: 0.838; 0.673–0.952) and 6-month unfavorable outcomes (AUC: 0.785; 0.666–0.904). The Stockholm score showed the highest accuracy for 12-month unfavorable outcomes (AUC: 0.687; 0.577–0.780) and 12-month mortality (AUC: 0.614; 0.430–0.769). For shorter-term outcomes, the Marshall score had relatively higher accuracy for in-hospital mortality (AUC: 0.777; 0.593–0.901), while the Rotterdam score demonstrated relatively better performance for 1-month mortality (AUC: 0.753; 0.567–0.867). While the overlapping credible intervals suggest that no single system consistently outperformed the others, Marshall and Rotterdam scores showed relatively higher predictive accuracy for short-term outcomes, while Helsinki and Stockholm performed relatively better for longer-term prognostication. Evidence for NIRIS remains limited. We recommend Marshall/Rotterdam for acute-phase risk stratification and Helsinki/Stockholm for longer-term prediction, with future research focusing on multimodal models integrating clinical, imaging, and biomarker data.

Indexed as

Brain Injuries, TraumaticTomography, X-Ray ComputedBayes TheoremHumansPredictive Value of TestsPrognosisComputed tomographyNeurosurgeryNeurotraumatologyPrognosticationTraumatic brain injury

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.