Evidence map›Paper›PMID 30246212›Full record

ArticleSingapore medical journal2019

A national trauma database analysis of alcohol- associated injuries.

Maxine Aiting Lam, Su Xian Lee, Kenneth Wei Jian Heng

Abstract read
In one paragraph

Article in Singapore medical journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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.

Maxine Aiting LamEmergency Department, Tan Tock Seng Hospital, Singapore.
Su Xian LeeEmergency Department, Tan Tock Seng Hospital, Singapore.
Kenneth Wei Jian HengEmergency Department, Tan Tock Seng Hospital, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionKnowledge of the pattern of alcohol-associated injury (AAI) is lacking in Singapore. We aimed to determine the local demographic pattern, injury mechanism, injury severity and outcomes of AAI.

methodsData on trauma cases presenting to emergency departments in 2012-2013 was extracted from the National Trauma Registry. Cases with missing data fields and those aged 1-15 years were excluded. Patients were classified as alcohol positive (A+) or negative (A-) based on clinical assessment. The two groups' demographics, injury mechanism, injury severity, mortality and disposition were compared. Logistic regression analysis was used to determine independent associations with mortality.

results105,468 trauma cases met the inclusion criteria. 3.9% were A+ and their peak age range was 25-44 years. The A+ group had more Indian males (p < 0.001), and significantly more assaults, self-harm and falls (p < 0.001). Injuries in the A+ group were more common in public areas and less common in homes, recreational facilities and workplaces. Outcomes in the A+ group showed higher mean Injury Severity Score and mortality (p < 0.001). Significantly more A+ patients were admitted to hospital but had shorter mean length of stay (p < 0.001). Multivariate logistic regression revealed age > 44 years and male gender as independent predictors of mortality.

conclusionAAI in Singapore is associated with more severe injuries and resource utilisation. Using data from the registry, 'at risk' demographic groups are identified for targeted injury prevention. However, alcohol use is not an independent predictor of mortality in trauma cases.

Indexed as

RegistriesAdolescentAdultAgedAlcoholismFemaleHumansInjury Severity ScoreMaleMiddle AgedSingaporeWounds and Injuriesalcoholemergency departmentinjurytrauma

Identifiers

PMID30246212
PMCPMC6482423

What OpenQuestion holds

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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.