ReviewAbdominal radiology (New York)2024
Imaging the acute complications of gender-affirming surgeries: a primer for radiologists in the emergency setting.
Review in Abdominal radiology (New York), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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.
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0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gender-affirming surgery (GAS) is increasingly being performed. GAS is tailored to the patient leading to a diverse spectrum of radiologic post-operative findings. Radiologists who are unfamiliar with expected anatomic alterations after GAS may misdiagnose important complications leading to adverse patient outcomes. This collaborative multi-institutional review aims to: Describe relevant embryology and native anatomy. Describe relevant Gender-Affirming Surgery (GAS) techniques and expected neo-anatomy with associated complications, including common terminology. Review expected imaging appearance of neo-anatomy/postoperative findings. Review multi-modality [ultrasound, plain film, retrograde urethrogram, computed tomography] emergent imaging findings. Understand unique patient evaluation and imaging protocol considerations in the GAS population. Discuss pearls and pitfalls of imaging in the acute post-GAS setting.
Indexed as
Identifiers
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Registered trials
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.