Evidence map›Paper›PMID 40861544›Full record

ReviewCureus2025

The Initial Assessment and Management of Cervical Spine Injuries: A Comprehensive Review.

Nur Amelia S Shaharudin, Olivia A Dunseath, Nur Aina Azmi, Ning Yee Aun

Abstract readReview
In one paragraph

Review in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

4 authors.

Nur Amelia S ShaharudinTrauma and Orthopaedics, Barts Health NHS Trust, London, GBR.
Olivia A DunseathTrauma and Orthopaedics, Barts Health NHS Trust, London, GBR.
Nur Aina AzmiEmergency Department, Rotherham General Hospital, Sheffield, GBR.
Ning Yee AunPsychiatry, Hertfordshire Partnership University Foundation Trust, Hertfordshire, GBR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cervical spine injuries (CSIs) are the most frequently encountered spinal injuries resulting from blunt trauma, owing to the cervical region's anatomical vulnerability and high mobility. Early recognition and spinal motion restriction (SMR) are essential in preventing secondary spinal cord injury (SCI), particularly in pre-hospital settings. This literature review explores the comprehensive management of suspected CSIs from the pre-hospital setting to definitive care in the hospital. It highlights the importance of clinical suspicion based on the mechanism of injury, appropriate application of SMR, and the role of imaging modalities such as CT and MRI in diagnosis. Clinical decision tools, including the National Emergency X-Radiography Utilization Study (NEXUS) criteria and Canadian C-Spine Rules (CCR), are discussed in relation to reducing unnecessary imaging while maintaining patient safety. The review also addresses current debates around cervical collar use, the necessity of structured neurological assessments, and the importance of multidisciplinary collaboration. Classification systems such as the Subaxial Cervical Spine Injury Classification System (SLIC) and AO Spine Trauma Classification are evaluated for their role in guiding treatment decisions. Effective care for CSI requires timely intervention, accurate imaging, and coordination among emergency, radiology, intensive care, and spinal surgical teams to minimise neurological complications and improve outcomes.

Indexed as

advanced trauma life support (atls)axis fracture: cervical spine traumacervical spine fracturereview of literaturespine and traumaspine imaging

Identifiers

PMID40861544
PMCPMC12376935

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.