Evidence map›Paper›PMID 40964178›Full record

ArticleBreathe (Sheffield, England)2025

"Massive" haemoptysis.

Ali Hafiz, Anmol Baidwan

Abstract read
In one paragraph

Article in Breathe (Sheffield, England), 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. 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

2 authors.

Ali HafizDepartment of Internal Medicine, Mary Washington Healthcare, Fredericksburg, VA, USA.
Anmol BaidwanDepartment of Internal Medicine, Mary Washington Healthcare, Fredericksburg, VA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Massive haemoptysis is a life-threatening condition requiring immediate and systematic management. Initial steps should focus on airway stabilisation, haemodynamic support and rapid identification of the bleeding source. Due to the complexity in diagnosis and management, along with a high associated mortality rate, massive haemoptysis offers an excellent opportunity for simulation training. Herein we present a simulated case of massive haemoptysis in a hospitalised patient. The scenario is crafted to help learners develop proficiency in the rapid recognition and multidisciplinary management of this high-risk condition, with an emphasis on airway protection and haemodynamic stabilisation. The script is widely adaptable across institutions and medical disciplines, and customisable to the needs of diverse learner populations.

Identifiers

PMID40964178
PMCPMC12439295

What OpenQuestion holds

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LicenceCC BY-NC
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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.