Evidence map›Paper›PMID 41625097›Full record

ArticleSurgical neurology international2025

Predicting outcomes in severe traumatic brain injury: A prospective analysis of clinical, radiological, and laboratory indicators.

Mohamed Salah Mohamed, Ahmed Mohammed AlaaEldin AbdElfatah Shalaby, Ahmed Mohamed Ezzat Abdel Fattah Mostafa

Abstract read
In one paragraph

Article in Surgical neurology international, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Observational
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

3 authors.

Mohamed Salah MohamedDepartment of Neurosurgery, Zagazig University, Zagazig, Egypt.
Ahmed Mohammed AlaaEldin AbdElfatah ShalabyDepartment of Neurosurgery, Zagazig University, Zagazig, Egypt.
Ahmed Mohamed Ezzat Abdel Fattah MostafaDepartment of Neurosurgery, Zagazig University, Zagazig, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Traumatic brain injury (TBI) is a primary cause of mortality and disability globally, with severe cases often resulting in long-term impairment. This study investigated key admission characteristics that predict outcomes in severe TBI patients, enhancing early mortality prediction through a comprehensive prognostic tool. Methods: This prospective study involved 240 patients with severe TBI (Glasgow Coma Scale [GCS] ≤8) admitted to our university hospitals over 2.5 years. Clinical, radiological, and laboratory data were collected, including GCS, Best motor response (BMR), pupil reactivity, hypotension, and the Marshall computed tomography (CT) score. Transcranial Doppler (TCD) pulsatility index (PI) and S100B protein levels were also assessed. Outcomes were assessed by the Glasgow outcome score (GOS). Results: Key findings demonstrated significant correlations between GCS, BMR, pupil reactivity, hypotension, and CT scores with GOS outcomes. Lower GCS scores and higher PI on Day 3 were associated with increased mortality. The madras head injury prognostic scale (MHIPS) effectively predicted outcomes with a strong correlation to GOS ( Conclusion: This study underscores the importance of integrating clinical, radiological, and laboratory parameters into prognostic models for severe TBI. The findings emphasize the predictive power of the TCD-measured PI and S100B protein levels as practical tools for estimating patient outcomes and mortality risk, facilitating improved clinical decision-making and resource allocation in intensive care settings.

Indexed as

Glasgow Coma ScaleMadras head injury prognostic scalePrognostic toolsTranscranial DopplerTraumatic brain injury

Identifiers

PMID41625097
PMCPMC12860328

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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.