title: Severity of post-partum hemorrhage after vaginal delivery is not predictable from clinical variables available at the time post-partum hemorrhage is diagnosed.
abstract: OBJECTIVE
  Identify women at risk of severe post-partum hemorrhage (PPH) by building a prediction model based on clinical variables available at PPH diagnosis.
  
  
  METHODS
  We analyzed data on a cohort of 7236 women with PPH after vaginal delivery from 106 maternity units. Severe PPH was defined as the loss of more than 2000 mL of blood, peripartum drop in hemoglobin of 4 g/dL or more, transfusion of at least four packed red blood cells, embolization, hemostasis surgery, transfer to an intensive care unit or death. The Akaike criterion helped selecting the covariates of a multivariate logistic regression model. The performance of the model was studied through building a receiver-operator curve (ROC). The relative utility of the final model was used to determine the importance of the model in decision-making.
  
  
  RESULTS
  Among all PPH, the prevalence of severe cases was 18.5%. Several clinical variables were significantly associated with severe PPH (e.g. parity, multiple pregnancy, labor induction, instrumental delivery). The multivariate prediction model was built. The area under the ROC for prediction of severe cases was 0.63 (95% confidence interval, 0.62-0.65). Nevertheless, the sensitivity and specificity of the prediction model were 0.49 and 0.70, respectively, for a threshold at 0.20 (near prevalence). The relative utility was 0.19 for a threshold near prevalence (20%).
  
  
  CONCLUSIONS
  Because of important misclassifications, even the best model we could build with the available clinical data cannot be reasonably recommended for routine use. Every patient with PPH should receive most optimal management. Other types of information, possibly laboratory data, are probably needed.
authors.affiliation: Department of Biostatistics, Hospices Civils de Lyon, Lyon, France; University of Lyon, Lyon, France; University of Lyon 1, Villeurbanne, France; UMR 5558, Laboratory of Biometry and Evolutionary Biology, Team of Health and Biostatistics, National Center for Scientific Research, Villeurbanne, France.
authors.forename: Marion
authors.initials: M
authors.lastname: Cortet
authors.forename: Delphine
authors.initials: D
authors.lastname: Maucort-Boulch
authors.forename: Catherine
authors.initials: C
authors.lastname: Deneux-Tharaux
authors.forename: Corinne
authors.initials: C
authors.lastname: Dupont
authors.forename: René-Charles
authors.initials: RC
authors.lastname: Rudigoz
authors.forename: Pascal
authors.initials: P
authors.lastname: Roy
authors.forename: Cyril
authors.initials: C
authors.lastname: Huissoud
mesh_terms: D000328:Adult; D001810:Blood Volume; D017707:Erythrocyte Transfusion; D005113:Extraction, Obstetrical; D005260:Female; D006454:Hemoglobins / Q000378:metabolism; D006488:Hemostasis, Surgical; D006801:Humans; D007751:Labor, Induced; D008962:Models, Theoretical; D010298:Parity; D006473:Postpartum Hemorrhage / Q000097:blood / Q000175:diagnosis* / Q000628:therapy; D011237:Predictive Value of Tests; D011247:Pregnancy; D011272:Pregnancy, Multiple; D012372:ROC Curve; D012720:Severity of Illness Index; D055357:Uterine Artery Embolization; D055815:Young Adult
chemical_list: D006454:Hemoglobins
keywords: expected utility; morbidity; post-partum hemorrhage; prediction