PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
January 20, 20260 citationsOpen Access

Acute Fatty Liver of Pregnancy and Mimicking Alleviating Factors: A True Diagnostic Challenge in Resource-Limited Settings. Case Report and Literature Review

View Full Paper
VLValenzuela Pacheco LibertadGPGómez Pineda María PaulaNENuñez Ramírez María Eugenia

Key Points

  • This research aims to address the diagnostic challenges of acute fatty liver of pregnancy in resource-limited environments.
  • Presented a clinical case with mimicking symptoms
  • Reviewed literature on differential diagnoses
  • Highlighted Swansea criteria for diagnosis
  • Proposed a diagnostic algorithm for low-resource settings
  • Identified multiple conditions mimicking AFLP
  • Emphasized the importance of Swansea criteria in diagnosis
  • Suggested strategies to improve outcomes in low-resource hospitals

Abstract

Acute fatty liver of pregnancy (AFLP) is a rare but potentially life-threatening obstetric complication, with an estimated incidence ranging from 1 in 7,000 to 20,000 pregnancies. Despite advances in diagnosis and treatment, its high maternal–fetal morbidity and mortality rates make it a true clinical challenge, particularly in hospitals with limited resources. This paper presents a complex clinical case with multiple variants simulating other pathologies, along with a comprehensive literature review that integrates international, regional, and national evidence. The analysis focuses on the diagnostic difficulty posed by differential entities such as HELLP syndrome, intrahepatic cholestasis, viral hepatitis, autoimmune diseases, dyslipidemias, and abdominal tumors. In addition, key clinical and laboratory tools—particularly the Swansea criteria—are highlighted as essential for standardizing diagnosis when specialized tests are unavailable. Based on the literature synthesis and the case analysis, a diagnostic algorithm and a table of pragmatic strategies tailored for low-resource settings are proposed, aiming to reduce delays and improve maternal–fetal outcomes.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Libertad et al. (2026) studied this question.

synapsesocial.com/papers/696f1a9f9e64f732b51eef4fhttps://doi.org/10.5281/zenodo.18278256
Ask AI
Helpful
Bookmark
Share
View Full Paper