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Bruno AM, Federspiel JJ, McGee P, Pacheco LD, Saade GR, Parry S, Longo M, Tita ATN, Gyamfi-Bannerman C, Chauhan SP, Einerson BD, Rood K, Rouse DJ, Bailit J, Grobman WA, Simhan HN. Validation of Three Models for Prediction of Blood Transfusion during Cesarean Delivery Admission. Am J Perinatol 2024; 41:e3391-e3400. [PMID: 38134939 PMCID: PMC11153014 DOI: 10.1055/a-2234-8171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2023]
Abstract
OBJECTIVE Prediction of blood transfusion during delivery admission allows for clinical preparedness and risk mitigation. Although prediction models have been developed and adopted into practice, their external validation is limited. We aimed to evaluate the performance of three blood transfusion prediction models in a U.S. cohort of individuals undergoing cesarean delivery. STUDY DESIGN This was a secondary analysis of a multicenter randomized trial of tranexamic acid for prevention of hemorrhage at time of cesarean delivery. Three models were considered: a categorical risk tool (California Maternal Quality Care Collaborative [CMQCC]) and two regression models (Ahmadzia et al and Albright et al). The primary outcome was intrapartum or postpartum red blood cell transfusion. The CMQCC algorithm was applied to the cohort with frequency of risk category (low, medium, high) and associated transfusion rates reported. For the regression models, the area under the receiver-operating curve (AUC) was calculated and a calibration curve plotted to evaluate each model's capacity to predict receipt of transfusion. The regression model outputs were statistically compared. RESULTS Of 10,785 analyzed individuals, 3.9% received a red blood cell transfusion during delivery admission. The CMQCC risk tool categorized 1,970 (18.3%) individuals as low risk, 5,259 (48.8%) as medium risk, and 3,556 (33.0%) as high risk with corresponding transfusion rates of 2.1% (95% confidence interval [CI]: 1.5-2.9%), 2.2% (95% CI: 1.8-2.6%), and 7.5% (95% CI: 6.6-8.4%), respectively. The AUC for prediction of blood transfusion using the Ahmadzia and Albright models was 0.78 (95% CI: 0.76-0.81) and 0.79 (95% CI: 0.77-0.82), respectively (p = 0.38 for difference). Calibration curves demonstrated overall agreement between the predicted probability and observed likelihood of blood transfusion. CONCLUSION Three models were externally validated for prediction of blood transfusion during cesarean delivery admission in this U.S. COHORT Overall, performance was moderate; model selection should be based on ease of application until a specific model with superior predictive ability is developed. KEY POINTS · A total of 3.9% of individuals received a blood transfusion during cesarean delivery admission.. · Three models used in clinical practice are externally valid for blood transfusion prediction.. · Institutional model selection should be based on ease of application until further research identifies the optimal approach..
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Affiliation(s)
- Ann M Bruno
- Department of Obstetrics and Gynecology, University of Utah Health Sciences Center, Salt Lake City, Utah
| | - Jerome J Federspiel
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Duke University School of Medicine, Durham, North Carolina
| | - Paula McGee
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, The George Washington University Biostatistics Center, Washington, District of Columbia
| | - Luis D Pacheco
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Texas Medical Branch, Galveston, Texas
| | - George R Saade
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Texas Medical Branch, Galveston, Texas
| | - Samuel Parry
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Monica Longo
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland
| | - Alan T N Tita
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Alabama at Birmingham, Birmingham, Alabama
| | - Cynthia Gyamfi-Bannerman
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Columbia University, New York, New York
| | - Suneet P Chauhan
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Texas Health Science Center at Houston, Children's Memorial Hermann Hospital, Houston, Texas
| | - Brett D Einerson
- Department of Obstetrics and Gynecology, University of Utah Health Sciences Center, Salt Lake City, Utah
| | - Kara Rood
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, The Ohio State University, Columbus, Ohio
| | - Dwight J Rouse
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Brown University, Providence, Rhode Island
| | - Jennifer Bailit
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, The MetroHealth Medical System, Case Western Reserve University, Cleveland, Ohio
| | - William A Grobman
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Northwestern University, Chicago, Illinois
| | - Hyagriv N Simhan
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Pittsburgh, Pittsburgh, Pennsylvania
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Dulaney BM, Elkhateb R, Mhyre JM. Optimizing systems to manage postpartum hemorrhage. Best Pract Res Clin Anaesthesiol 2022; 36:349-357. [PMID: 36513430 DOI: 10.1016/j.bpa.2022.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 10/18/2022] [Indexed: 11/13/2022]
Abstract
Systems to optimize the management of postpartum hemorrhage must ensure timely diagnosis, rapid hemodynamic and hemostatic resuscitation, and prompt interventions to control the source of bleeding. None of these objectives can be effectively completed by a single clinician, and the management of postpartum hemorrhage requires a carefully coordinated interprofessional team. This article reviews systems designed to standardize hemorrhage diagnosis and response.
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Affiliation(s)
- Breyanna M Dulaney
- Department of Anesthesiology, University of Arkansas for Medical Sciences, 4301 W. Markham St. #515, Little Rock, AR 72205, USA
| | - Rania Elkhateb
- Department of Anesthesiology, University of Arkansas for Medical Sciences, 4301 W. Markham St. #515, Little Rock, AR 72205, USA
| | - Jill M Mhyre
- Department of Anesthesiology, University of Arkansas for Medical Sciences, 4301 W. Markham St. #515, Little Rock, AR 72205, USA.
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Latest advances in postpartum hemorrhage management. Best Pract Res Clin Anaesthesiol 2022; 36:123-134. [PMID: 35659949 DOI: 10.1016/j.bpa.2022.02.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 02/16/2022] [Indexed: 11/20/2022]
Abstract
Hemorrhage is the leading cause of maternal mortality worldwide. A maternal health priority is improving how healthcare providers prevent and manage postpartum hemorrhage (PPH). Because anesthesiologists can help facilitate how hospitals develop approaches for PPH prevention and anticipatory planning, we review the potential utility of PPH risk-assessment tools, bundles, and protocols. Anesthesiologists rely on clinical and diagnostic information for initiating and evaluating medical management. Therefore, we review modalities for measuring blood loss after delivery, which includes visual, volumetric, gravimetric, and colorimetric approaches. Point-of-care technologies for assessing changes in central hemodynamics (ultrasonography) and coagulation profiles (rotational thromboelastometry and thromboelastography) are also discussed. Anesthesiologists play a critical role in the medical and transfusion management of PPH. Therefore, we review blood ordering and massive transfusion protocols, fixed-ratio vs. goal-directed transfusion approaches, coagulation changes during PPH, and the potential clinical utility of the pharmacological adjuncts, tranexamic acid, and fibrinogen concentrate.
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