Evidence map›Paper›PMID 37465227›Full record

ArticleJournal of education & teaching in emergency medicine2020

Hemoptysis Due to Diffuse Alveolar Hemorrhage.

Zoltan Buchwald, Amrita Vempati

Open access · greenAbstract read
In one paragraph

Article in Journal of education & teaching in emergency medicine, 2020. 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
0.1field-weighted citation impact, top 46% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

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

2 authors at 1 institution in 1 country.

Zoltan BuchwaldCreighton University School of Medicine Phoenix Program, Maricopa Medical Center, Department of Emergency Medicine, Phoenix, AZ.
Amrita VempatiCreighton University School of Medicine Phoenix Program, Maricopa Medical Center, Department of Emergency Medicine, Phoenix, AZ.
Maricopa Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Audience: This scenario was developed to educate junior and senior emergency medicine (EM) residents. Introduction: EM Model of Practice recommends that the residents are able to manage patients in a critical condition from massive hemoptysis. Mild to moderate hemoptysis can be self-limiting and often can be managed with conservative measures; however, massive hemoptysis is a life-threatening emergency that needs to be managed promptly. Mortality from massive hemoptysis is about 13%-18%.1 There are several causes for hemoptysis ranging from pulmonary to vascular causes. Diffuse alveolar hemorrhage (DAH) causes hemoptysis only 0.2% which makes it a very rare but devastating disease.2 Hemoptysis from DAH can present a significant challenge to an EM physician since it can present in various ways including chest pain, shortness of breath or hemoptysis. Up to 40% of the patients can present without hemoptysis which makes it a diagnostic dilemma.3 Patients presenting with massive hemoptysis from DAH require management for hypovolemic shock, hypoxic respiratory arrest and potential cardiac arrest. The physicians also need to perform adequate ventilator management to help with alveolar recruitment. This simulation case can help discuss some of the nuances of the management of hemoptysis and DAH. Objectives: By the end of this simulation session, learners will be able to: (1) recognize worsening respiratory status of a patient with hemoptysis and intervene appropriately, (2) manage a patient with severe hemoptysis and perform appropriate ventilator management, (3) manage sinus tachycardia with QT prolongation on the ECG caused by cocaine and hypomagnesemia, (4) address various etiologies of hemoptysis, (5) discuss the causes of massive hemoptysis and management options, and (6) review ventilation strategies in an intubated hypoxic patient. Educational Methods: This session was conducted using high-fidelity simulation, which was immediately followed by an in-depth debriefing session. Each session had 3 EM residents from various levels of training on the team and 7 observers. There was 1 simulation instructor running the session and 1 simulation technician who acted as a nurse. Research Methods: After the simulation and debriefing session was complete, an online survey was sent via surveymonkey.com to all the participants. The survey collected responses to the following questions: (1) the case was believable, (2) the case had right amount of complexity, (3) the case helped in improving medical knowledge and patient care, (4) the simulation environment gave me a real-life experience and, (5) the debriefing session after simulation helped improve my knowledge. A Likert scale was used to collect the responses. Results: Seven learners responded to the survey. One hundred percent of them either agreed or strongly agreed that the case was beneficial in learning and improving patient care. They also agreed that it helped in improving medical knowledge. The post-session debrief was found to be very helpful by all the learners. Discussion: High-fidelity simulation was a cost-effective yet realistic way to manage severe hemoptysis, PEA (pulseless electrical activity), and persistent hypoxia in patients with diffuse alveolar hemorrhage. Starting the case with severe hypoxia that quickly progresses to PEA helps the learner to manage the patient quickly and effectively. Overall, learners enjoyed managing the patient, followed by discussing the various management strategies. Topics: Hemoptysis, diffuse alveolar hemorrhage, medical simulation, respiratory.

Identifiers

PMID37465227
PMCPMC10332551
OpenAlexW4384663110

What OpenQuestion holds

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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.