Evidence map›Paper›PMID 42290953›Full record

ReviewClinical medicine insights. Pediatrics2026

Self-Poisoning With Ibuprofen in Youth: A What, When and Why Clinical Framework.

Babak Dehestani, Louisa Kelly, Fiona McNicholas

Abstract readReview
In one paragraph

Review in Clinical medicine insights. Pediatrics, 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

3 authors.

Babak DehestaniDepartment of Child and Adolescent Liaison Psychiatry, Children's Health Ireland, Tallaght Hospital, Dublin, Ireland.ORCID https://orcid.org/0000-0001-7916-0653
Louisa KellyDepartment of Child and Adolescent Liaison Psychiatry, Children's Health Ireland, Tallaght Hospital, Dublin, Ireland.ORCID https://orcid.org/0000-0003-3389-6440
Fiona McNicholasDepartment of Child and Adolescent Psychiatry, School of Medicine and Medical Science, University College Dublin, Ireland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deliberate self-poisoning (DSP) among children and adolescents has been steadily increasing over the past decade worldwide with paracetamol and ibuprofen the most common medications used. Assessment and management often fall to Emergency Department (ED) staff with varied psychiatric experience. We outline an easy-to-use psychiatry framework for ED clinicians to guide them in assessing and managing young people who present with DSP with Ibuprofen. A "what, when and why" framework derived from the authors' clinical experience in child and adolescent liaison psychiatry and emergency care, is outlined. This may guide ED clinicians in the assessment of what medication is ingested, when DSP occurred on as well as when to initiate treatment and how to explore why the DSP episode took place. DSP with Ibuprofen has the potential to cause severe physical sequelae ranging from renal and liver impairment to severe gastro-intestinal bleeds and thrombocytopaenia. Establishing what was used in the DSP episode and when it occurred is therefore crucial to allow for timely treatment and management. Establishing reasons why the young person took the overdose, along with thorough risk assessment is crucial in aiding safe discharge planning. Given the importance of timely intervention, the suggested framework provides an easy-to-remember method for assessment, informing management and discharge planning.

Indexed as

children and adolescentsdeliberate self-poisoningemergency psychiatryibuprofenpsychiatric liaison

Identifiers

PMID42290953
PMCPMC13254133

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.