Evidence map›Paper›PMID 42618684›Full record

ArticleEmergency radiology2026

Artificial intelligence and the phantom pneumothorax: Clinical reasoning still matters.

Fulvio Cacciapuoti, Antonio Ruocco, Salvatore Crispo, Massimiliana Abbate, Giuseppina Dell'Aversano Orabona, Osvaldo Cuomo, Ciro Mauro

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Article in Emergency radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

7 authors.

Fulvio CacciapuotiDivision of Cardiology "Antonio Cardarelli" Hospital, Via Antonio Cardarelli, 9, Naples, 80131, Italy. fulvio.cacciapuoti@aocardarelli.it.ORCID http://orcid.org/0000-0002-7687-6346
Antonio RuoccoDivision of Cardiology "Antonio Cardarelli" Hospital, Via Antonio Cardarelli, 9, Naples, 80131, Italy.
Salvatore CrispoDivision of Cardiology "Antonio Cardarelli" Hospital, Via Antonio Cardarelli, 9, Naples, 80131, Italy.
Massimiliana AbbateDivision of Cardiology "Antonio Cardarelli" Hospital, Via Antonio Cardarelli, 9, Naples, 80131, Italy.
Giuseppina Dell'Aversano OrabonaDivision of Radiology "Antonio Cardarelli" Hospital, Naples, Italy.
Osvaldo CuomoPostgraduate School of Cardiology "Federico II" University, Naples, Italy.
Ciro MauroDivision of Cardiology "Antonio Cardarelli" Hospital, Via Antonio Cardarelli, 9, Naples, 80131, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) has become increasingly integrated into chest radiograph interpretation, demonstrating excellent diagnostic performance for several thoracic abnormalities, including pneumothorax. Nevertheless, current AI systems remain predominantly image-based and do not inherently incorporate procedural or clinical information into diagnostic interpretation. We report the case of an 81-year-old man who underwent uncomplicated left-sided dual-chamber permanent pacemaker implantation. Routine post-procedural chest radiography, analyzed by an AI-assisted interpretation system, generated a positive alert for a right apical pneumothorax, highlighting the suspected abnormality with automated visual annotation. The alert was immediately considered clinically discordant by the treating team, given the left-sided venous access, normal oxygen saturation, hemodynamic stability, and absence of respiratory symptoms. Because of this clinicoradiological discordance, chest computed tomography was performed and definitively excluded pneumothorax, confirming a false-positive AI interpretation. The patient required no additional intervention and experienced an uneventful recovery. This case highlights the importance of integrating AI-generated findings with procedural details, bedside clinical assessment, and, when clinically indicated, confirmatory imaging in the presence of clinicoradiological discordance. Although AI can accurately identify many radiographic abnormalities, accurate diagnosis ultimately depends on integrating imaging findings with procedural information, clinical presentation, and pre-test probability. This case also emphasizes that AI should be regarded as a clinical decision-support tool rather than an autonomous diagnostic system and highlights the continuing importance of physician oversight in ensuring patient safety during AI-assisted post-procedural imaging interpretation.

Indexed as

Artificial intelligenceAutomation biasChest radiographyClinical reasoningPacemaker implantationPatient safetyPneumothorax

Identifiers

PMID42618684

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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.