Cargando…

Predicting peripartum blood transfusion in women undergoing cesarean delivery: A risk prediction model

OBJECTIVE: There has been an appreciable rise in postpartum hemorrhage requiring blood transfusions in the United States. Our objective is to better define patients at greatest risk for peripartum transfusion at the time of cesarean in order to identify cases for early intervention and monitoring. M...

Descripción completa

Detalles Bibliográficos
Autores principales: Ahmadzia, Homa K., Phillips, Jaclyn M., James, Andra H., Rice, Madeline M., Amdur, Richard L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6294610/
https://www.ncbi.nlm.nih.gov/pubmed/30551126
http://dx.doi.org/10.1371/journal.pone.0208417
_version_ 1783380761775177728
author Ahmadzia, Homa K.
Phillips, Jaclyn M.
James, Andra H.
Rice, Madeline M.
Amdur, Richard L.
author_facet Ahmadzia, Homa K.
Phillips, Jaclyn M.
James, Andra H.
Rice, Madeline M.
Amdur, Richard L.
author_sort Ahmadzia, Homa K.
collection PubMed
description OBJECTIVE: There has been an appreciable rise in postpartum hemorrhage requiring blood transfusions in the United States. Our objective is to better define patients at greatest risk for peripartum transfusion at the time of cesarean in order to identify cases for early intervention and monitoring. METHODS: Our study is a secondary analysis of a retrospective cohort study. Cases of intraoperative and immediate postpartum blood transfusion among women undergoing cesarean delivery were identified. Multivariable logistic regression models were used to identify antepartum and intrapartum risk factors that were independently associated with blood transfusion. A risk calculator was then developed to predict the need for transfusion. RESULTS: Of 56,967 women, 1488 (2.6%) required any blood transfusion. The strongest risk factors for peripartum blood transfusion included anemia (odds ratio [OR] 3.7, 95% CI 3.3–4.3), abruption on presentation (OR 3.3, CI 2.6–4.1), general anesthesia (OR 5.2, CI 4.4–6.1) and abnormal placentation (OR 92.0, CI 57.4–147.6). An antepartum (model 1) and combined antepartum plus intrapartum risk model (model 2) were developed (model 1 AUC = 0.77, model 2 AUC = 0.83) and internally validated. CONCLUSIONS: Among women who required cesarean delivery, we were able to identify risk factors which predispose women to peripartum blood transfusion and developed a prediction model with good discrimination.
format Online
Article
Text
id pubmed-6294610
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-62946102018-12-28 Predicting peripartum blood transfusion in women undergoing cesarean delivery: A risk prediction model Ahmadzia, Homa K. Phillips, Jaclyn M. James, Andra H. Rice, Madeline M. Amdur, Richard L. PLoS One Research Article OBJECTIVE: There has been an appreciable rise in postpartum hemorrhage requiring blood transfusions in the United States. Our objective is to better define patients at greatest risk for peripartum transfusion at the time of cesarean in order to identify cases for early intervention and monitoring. METHODS: Our study is a secondary analysis of a retrospective cohort study. Cases of intraoperative and immediate postpartum blood transfusion among women undergoing cesarean delivery were identified. Multivariable logistic regression models were used to identify antepartum and intrapartum risk factors that were independently associated with blood transfusion. A risk calculator was then developed to predict the need for transfusion. RESULTS: Of 56,967 women, 1488 (2.6%) required any blood transfusion. The strongest risk factors for peripartum blood transfusion included anemia (odds ratio [OR] 3.7, 95% CI 3.3–4.3), abruption on presentation (OR 3.3, CI 2.6–4.1), general anesthesia (OR 5.2, CI 4.4–6.1) and abnormal placentation (OR 92.0, CI 57.4–147.6). An antepartum (model 1) and combined antepartum plus intrapartum risk model (model 2) were developed (model 1 AUC = 0.77, model 2 AUC = 0.83) and internally validated. CONCLUSIONS: Among women who required cesarean delivery, we were able to identify risk factors which predispose women to peripartum blood transfusion and developed a prediction model with good discrimination. Public Library of Science 2018-12-14 /pmc/articles/PMC6294610/ /pubmed/30551126 http://dx.doi.org/10.1371/journal.pone.0208417 Text en © 2018 Ahmadzia et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Ahmadzia, Homa K.
Phillips, Jaclyn M.
James, Andra H.
Rice, Madeline M.
Amdur, Richard L.
Predicting peripartum blood transfusion in women undergoing cesarean delivery: A risk prediction model
title Predicting peripartum blood transfusion in women undergoing cesarean delivery: A risk prediction model
title_full Predicting peripartum blood transfusion in women undergoing cesarean delivery: A risk prediction model
title_fullStr Predicting peripartum blood transfusion in women undergoing cesarean delivery: A risk prediction model
title_full_unstemmed Predicting peripartum blood transfusion in women undergoing cesarean delivery: A risk prediction model
title_short Predicting peripartum blood transfusion in women undergoing cesarean delivery: A risk prediction model
title_sort predicting peripartum blood transfusion in women undergoing cesarean delivery: a risk prediction model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6294610/
https://www.ncbi.nlm.nih.gov/pubmed/30551126
http://dx.doi.org/10.1371/journal.pone.0208417
work_keys_str_mv AT ahmadziahomak predictingperipartumbloodtransfusioninwomenundergoingcesareandeliveryariskpredictionmodel
AT phillipsjaclynm predictingperipartumbloodtransfusioninwomenundergoingcesareandeliveryariskpredictionmodel
AT jamesandrah predictingperipartumbloodtransfusioninwomenundergoingcesareandeliveryariskpredictionmodel
AT ricemadelinem predictingperipartumbloodtransfusioninwomenundergoingcesareandeliveryariskpredictionmodel
AT amdurrichardl predictingperipartumbloodtransfusioninwomenundergoingcesareandeliveryariskpredictionmodel