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Intrapartum Risk Factors and Prediction of Obstetric Hemorrhage-Related Morbidity.
Abbas, Diana; Wang, Michelle J; Claus, Lindsey; Alexander, Megan; Srivastava, Akanksha; Young, Sara; Tummala, Swetha; Iverson, Ronald; Yarrington, Christina; Comfort, Ashley.
  • Abbas D; Boston University School of Medicine, Boston, Massachusetts.
  • Wang MJ; Department of Obstetrics and Gynecology, Boston Medical Center, Boston, Massachusetts.
  • Claus L; Department of Obstetrics and Gynecology, Boston Medical Center, Boston, Massachusetts.
  • Alexander M; Boston University School of Medicine, Boston, Massachusetts.
  • Srivastava A; Boston University School of Medicine, Boston, Massachusetts.
  • Young S; Boston University School of Medicine, Boston, Massachusetts.
  • Tummala S; Boston University School of Medicine, Boston, Massachusetts.
  • Iverson R; Boston University School of Medicine, Boston, Massachusetts.
  • Yarrington C; Boston University School of Medicine, Boston, Massachusetts.
  • Comfort A; Department of Obstetrics and Gynecology, Boston Medical Center, Boston, Massachusetts.
Am J Perinatol ; 2022 Dec 29.
Article en En | MEDLINE | ID: mdl-36351443
ABSTRACT

OBJECTIVE:

The aim of this study was to assess whether inclusion of intrapartum risk factors improves our obstetric hemorrhage risk stratification tool in predicting obstetric hemorrhage, transfusion, and related severe morbidity. STUDY

DESIGN:

This is a retrospective cohort study using all live deliveries at a single institution over a 2-year period (n = 5,332). Obstetric hemorrhage risk factors, hemorrhage burden, and severe maternal morbidity index outcomes were assessed through chart abstraction. Hemorrhage risk was assessed at (1) "time of admission" through chart abstraction and (2) "predelivery" by calculation after inclusion of all abstracted intrapartum risk factors. Admission high risk was compared with predelivery high risk for sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, and negative likelihood ratio in predicting obstetric hemorrhage, obstetric hemorrhage requiring transfusion, and obstetric hemorrhage-related severe morbidity. Significance levels were calculated using descriptive statistical methods including chi-squared tests and McNemar's tests.

RESULTS:

The sensitivities of the risk assessment tool using admission risk classification for high-risk patients is 25% for obstetric hemorrhage, 37% for obstetric hemorrhage requiring transfusion, and 22% for obstetric hemorrhage-related severe morbidity. After intrapartum factor inclusion, the sensitivities increase to 55% for obstetric hemorrhage, 59% for obstetric hemorrhage requiring transfusion, and 47% for obstetric hemorrhage-related severe morbidity. This "predelivery" risk assessment is significantly more sensitive across all three end points (p < 0.001 for all three outcomes). While the positive likelihood ratios for obstetric hemorrhage are equal on admission and predelivery (2.10 on admission and predelivery), they increase after intrapartum factor inclusion for obstetric hemorrhage requiring transfusion and obstetric hemorrhage-related severe morbidity (on admission, 2.74 and 1.6, respectively, and predelivery 4.57 and 3.58, respectively).

CONCLUSION:

Inclusion of intrapartum risk factors increases the accuracy of this obstetric hemorrhage risk stratification tool in predicting patients requiring hemorrhage management with transfusion and obstetric hemorrhage-related severe morbidity. KEY POINTS · There are little data to validate intrapartum hemorrhage risk reassessment.. · Including intrapartum factors improves risk stratification for transfusion and related morbidity.. · Future research should clinically validate risk reassessment in the intrapartum period..

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Año: 2022 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Año: 2022 Tipo del documento: Article