Cargando…
Development of the “POP” scoring system for predicting obstetric and gynecological diseases in the emergency department: a retrospective cohort study
BACKGROUND: Obstetric and gynecological (OBGY) diseases are among the most important differential diagnoses for young women with acute abdominal pain. However, there are few established clinical prediction rules for screening OBGY diseases in emergency departments (EDs). This study aimed to develop...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7203896/ https://www.ncbi.nlm.nih.gov/pubmed/32375643 http://dx.doi.org/10.1186/s12873-020-00332-z |
_version_ | 1783529958460620800 |
---|---|
author | Okada, Asami Okada, Yohei Fujita, Hiroyuki Iiduka, Ryoji |
author_facet | Okada, Asami Okada, Yohei Fujita, Hiroyuki Iiduka, Ryoji |
author_sort | Okada, Asami |
collection | PubMed |
description | BACKGROUND: Obstetric and gynecological (OBGY) diseases are among the most important differential diagnoses for young women with acute abdominal pain. However, there are few established clinical prediction rules for screening OBGY diseases in emergency departments (EDs). This study aimed to develop a prediction model for diagnosing OBGY diseases in the ED. METHODS: This single-center retrospective cohort study included female patients with acute abdominal pain who presented to our ED. We developed a logistic regression model for predicting OBGY diseases and assessed its diagnostic ability. This study included young female patients aged between 16 and 49 years who had abdominal pain and were examined at the ED between April 2017 and March 2018. Trauma patients and patients who were referred from other hospitals or from the OBGY department of our hospital were excluded. RESULTS: Out of 27,991 patients, 740 were included. Sixty-five patients were diagnosed with OBGY diseases (8.8%). The “POP” scoring system (past history of OBGY diseases + 1, no other symptoms + 1, and peritoneal irritation signs + 1) was developed. Cut-off values set between 0 and 1 points, sensitivity at 0.97, specificity at 0.39, and negative likelihood ratio (LR-) of 0.1 (95% CI: 0.02–0.31) were considered to rule-out, while cut-off values set between 2 and 3 points, sensitivity at 0.23 (95% CI 0.13–0.33), specificity at 0.99 (95% CI 0.98–1.00), and positive likelihood ratio (LR+) of 17.30 (95% CI: 7.88–37.99) were considered to rule-in. CONCLUSIONS: Our “POP” scoring system may be useful for screening OBGY diseases in the ED. Further research is necessary to assess the predictive performance and external validity of different data sets. |
format | Online Article Text |
id | pubmed-7203896 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-72038962020-05-12 Development of the “POP” scoring system for predicting obstetric and gynecological diseases in the emergency department: a retrospective cohort study Okada, Asami Okada, Yohei Fujita, Hiroyuki Iiduka, Ryoji BMC Emerg Med Research Article BACKGROUND: Obstetric and gynecological (OBGY) diseases are among the most important differential diagnoses for young women with acute abdominal pain. However, there are few established clinical prediction rules for screening OBGY diseases in emergency departments (EDs). This study aimed to develop a prediction model for diagnosing OBGY diseases in the ED. METHODS: This single-center retrospective cohort study included female patients with acute abdominal pain who presented to our ED. We developed a logistic regression model for predicting OBGY diseases and assessed its diagnostic ability. This study included young female patients aged between 16 and 49 years who had abdominal pain and were examined at the ED between April 2017 and March 2018. Trauma patients and patients who were referred from other hospitals or from the OBGY department of our hospital were excluded. RESULTS: Out of 27,991 patients, 740 were included. Sixty-five patients were diagnosed with OBGY diseases (8.8%). The “POP” scoring system (past history of OBGY diseases + 1, no other symptoms + 1, and peritoneal irritation signs + 1) was developed. Cut-off values set between 0 and 1 points, sensitivity at 0.97, specificity at 0.39, and negative likelihood ratio (LR-) of 0.1 (95% CI: 0.02–0.31) were considered to rule-out, while cut-off values set between 2 and 3 points, sensitivity at 0.23 (95% CI 0.13–0.33), specificity at 0.99 (95% CI 0.98–1.00), and positive likelihood ratio (LR+) of 17.30 (95% CI: 7.88–37.99) were considered to rule-in. CONCLUSIONS: Our “POP” scoring system may be useful for screening OBGY diseases in the ED. Further research is necessary to assess the predictive performance and external validity of different data sets. BioMed Central 2020-05-06 /pmc/articles/PMC7203896/ /pubmed/32375643 http://dx.doi.org/10.1186/s12873-020-00332-z Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Okada, Asami Okada, Yohei Fujita, Hiroyuki Iiduka, Ryoji Development of the “POP” scoring system for predicting obstetric and gynecological diseases in the emergency department: a retrospective cohort study |
title | Development of the “POP” scoring system for predicting obstetric and gynecological diseases in the emergency department: a retrospective cohort study |
title_full | Development of the “POP” scoring system for predicting obstetric and gynecological diseases in the emergency department: a retrospective cohort study |
title_fullStr | Development of the “POP” scoring system for predicting obstetric and gynecological diseases in the emergency department: a retrospective cohort study |
title_full_unstemmed | Development of the “POP” scoring system for predicting obstetric and gynecological diseases in the emergency department: a retrospective cohort study |
title_short | Development of the “POP” scoring system for predicting obstetric and gynecological diseases in the emergency department: a retrospective cohort study |
title_sort | development of the “pop” scoring system for predicting obstetric and gynecological diseases in the emergency department: a retrospective cohort study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7203896/ https://www.ncbi.nlm.nih.gov/pubmed/32375643 http://dx.doi.org/10.1186/s12873-020-00332-z |
work_keys_str_mv | AT okadaasami developmentofthepopscoringsystemforpredictingobstetricandgynecologicaldiseasesintheemergencydepartmentaretrospectivecohortstudy AT okadayohei developmentofthepopscoringsystemforpredictingobstetricandgynecologicaldiseasesintheemergencydepartmentaretrospectivecohortstudy AT fujitahiroyuki developmentofthepopscoringsystemforpredictingobstetricandgynecologicaldiseasesintheemergencydepartmentaretrospectivecohortstudy AT iidukaryoji developmentofthepopscoringsystemforpredictingobstetricandgynecologicaldiseasesintheemergencydepartmentaretrospectivecohortstudy |