Development of a self assessed questionnaire for the diagnosis of acute pelvic pain

Acute pelvic pain is the main reason for emergency gynecologic consultation. The possible etiologies of acute pelvic pain are numerous and include both gynecological and non gynecological diseases. Some of these conditions may, in the absence of early diagnosis and appropriate treatment, have very serious consequences. In this work, we developed qualitatively a standardized self-assessed questionnaire dedicated to gynecological emergencies by structured interviews. We then developed clinical prediction rules for (i) the diagnosis of tubal rupture in patients who have ectopic pregnancies and (ii) the diagnosis of adnexal torsion. After a definition of the concept of potentially at risk emergencies in gynecology, we have proposed (iii) a clinical prediction rule based on our questionnaire. Following the development of these models, we selected items from the self-assessed questionnaire in order to propose a simplified version. Using our models for triaging and diagnosis of patients with gynecologic emergencies may optimize the management of patients. In groups at high risk of disease, patients may benefit from faster medical management with a possible decrease in morbidity. For patients classified as low risk, decrease of complementary tests and unnecessary surgery could also allow a reduction of iatrogenic morbidity.

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Source https://theses.hal.science/tel-00691369
Author Huchon, Cyrille
Maintainer CCSD
Last Updated May 20, 2026, 18:34 (UTC)
Created May 20, 2026, 18:34 (UTC)
Identifier NNT: 2012PA05S005
Language fr
Rights https://about.hal.science/hal-authorisation-v1/
contributor Recherche Epidémiologique en Santé Périnatale et Santé des Femmes et des Enfants (UMR_S 953) ; Université Paris-Sud - Paris 11 (UP11)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)
creator Huchon, Cyrille
date 2012-04-06T00:00:00
harvest_object_id ac1a7e40-865d-4194-bc86-6e5899c34d66
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2026-03-30T00:00:00
set_spec type:THESE