Evidence map›Paper›PMID 36779446›Full record

ArticleAnnals of the Royal College of Surgeons of England2023

Predictors of long-term survival in 5,680 patients admitted to a UK major trauma centre with thoracic injuries.

P Ariyaratnam, A Lee, R Milton, M Troxler, I F Barlow, G Ferrier, Dja Scott

Open access · greenAbstract read
In one paragraph

Article in Annals of the Royal College of Surgeons of England, 2023. 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
0.3field-weighted citation impact, top 44% of its field
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 citations in OpenAlex.

  1. Article
  2. Article
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

7 authors at 3 institutions in 1 country.

P AriyaratnamUniversity Hospitals Plymouth NHS Trust, UK.
A LeeUniversity of Hull, UK.
R MiltonThe Leeds Teaching Hospitals NHS Trust, UK.
M TroxlerThe Leeds Teaching Hospitals NHS Trust, UK.
I F BarlowThe Leeds Teaching Hospitals NHS Trust, UK.
G FerrierUniversity of Hull, UK.
Dja ScottThe Leeds Teaching Hospitals NHS Trust, UK.
Leeds Teaching Hospitals NHS Trust · GBUniversity of Hull · GBUniversity Hospitals Plymouth NHS Trust · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe long-term outcomes of chest trauma are largely unknown. We sought to determine the predictors of in-hospital and long-term survival in patients admitted to a major trauma centre (MTC) with chest injuries and to evaluate spatial patterns of injury in our network area.

methodsRetrospective analysis of data collected on the National Trauma Audit Research Network (TARN) database using multivariate analysis and Cox regression analysis. Spatial analysis was performed using ArcGis 10.7.1.

resultsSome 5,680 patients were admitted with chest trauma between December 1999 and December 2019. Median patient age was 45 years and the median Injury Severity Score (ISS) was 20. The proportion of patients who had an operation was 39.8%. Age, blood transfusion, head injury, shock, emergency thoracotomy and heart disease were predictors of hospital mortality (

conclusionsThe MTC is geographically central to areas with high numbers of trauma incidents. Although emergency thoracotomy was a predictor of poor in-hospital outcomes, having surgery for concomitant injuries improved outcomes. Patients surviving to discharge have good long-term survivals.

Indexed as

Thoracic InjuriesTrauma CentersHospitalizationHumansInjury Severity ScoreRetrospective StudiesUnited KingdomSurvivalTrauma surgery

Identifiers

PMID36779446
PMCPMC10313447
OpenAlexW4320506986

What OpenQuestion holds

Textmetadata
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.