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GPT estimates pneumothorax size to guide care

Chest X-Ray evaluation using GPT for tube thoracostomy or conservative care in non-tension spontaneous pneumothorax
Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine · Added 22 April 2026

Tested whether a vision-enabled GPT model could estimate pneumothorax size and guide tube thoracostomy vs conservative care, and it matched radiologist measurements closely with good agreement to real-world ED decisions.

Study type

Cohort

Design

Single-centre retrospective observational study of vision-enabled GPT on chest radiographs

Participants

101 adults with confirmed spontaneous pneumothorax

Main finding

Sensitivity 86.8%, specificity 93.8%, accuracy 90.1%, AUC 0.90 for tube thoracostomy within 24h; depth agreement ICC 0.893, MAE 0.69 cm

Caveat

Single-centre retrospective design with confirmed pneumothorax only; no prehospital or prospective testing

Bottom line

Hypothesis-generating

Learning goal

Weigh how artificial intelligence imaging tools could support my judgement on conservative care versus intervention in spontaneous pneumothorax.

More

• Topic: Other
• Daily scan: 22 April 2026

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