Prenatal Presentation of a Covered Cloacal Exstrophy Variant; Early Diagnostic Challenges Within the Broad Spectrum of the Exstrophy-Epispadias Complex
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Updated: Jul 17, 2025

Vessel-sparing Excision and Primary Anastomosis
Published on: January 7, 2019
Maya R Overland1, Edward R Oliver2, Susan J Back3
1Division of Urology, Department of Surgery, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia.
Insights
Accurate prenatal detection of bladder exstrophy and epispadias complex variants is crucial. This study highlights the spectrum of these rare conditions and the need for more outcome data.
Area of Science:
- Urology
- Developmental Biology
- Medical Genetics
Background:
- The bladder exstrophy and epispadias complex encompasses a range of congenital anomalies.
- Accurate prenatal diagnosis is vital for family preparation and resource allocation.
Observation:
- This study details a case of covered cloacal exstrophy diagnosed prenatally.
- Four additional cases illustrate the spectrum from isolated epispadias to cloacal exstrophy.
Findings:
- The bladder exstrophy and epispadias complex presents with diverse phenotypes.
- Prenatal diagnosis aids in managing these rare conditions.
Implications:
- There is a need for long-term, multi-institutional data on outcomes for these rare variants.
- Improved detection, characterization, and prognostication are essential for patient care.
Abstract:
There is a broad range of variant phenotypes that can occur within the bladder exstrophy and epispadias complex spectrum. Accurate prenatal detection helps prepare families and to coordinate subspecialty resources. Here, we present the case of a patient with prenatally diagnosed patient with covered cloacal exstrophy variant along with four additional cases illustrating the nonlinear spectrum from isolated epispadias to cloacal exstrophy. Given the rarity of these variants overall and of each subtype within the spectrum, there is a need for long-term multi-institutional outcomes data to improve detection, characterization, and prognostication for these patients.

