1.
Validation of three models for prediction of blood transfusion during cesarean delivery admission
Bruno, A., Federspiel, J. J., McGee, P., Pacheco, L., Saade, G., Parry, S., Longo, M., Tita, A., Gyamfi-Bannerman, C., Chauhan, S., et al
American journal of perinatology. 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. METHODS 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 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% 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.
2.
Non-clinical interventions to prevent postpartum haemorrhage and improve its management: A systematic review
Gaucher L, Occelli P, Deneux-Tharaux C, Colin C, Gaucherand P, Touzet S, Dupont C
European journal of obstetrics, gynecology, and reproductive biology. 2019;240:300-309
Abstract
Postpartum haemorrhages (PPHs) account for around 200 deaths per year in the developed regions of the world. However, the efficacy of pharmacological and clinical interventions to prevent or manage PPHs is well established. Our objective was to determine the effectiveness of non-clinical interventions targeting healthcare professionals, organisations or facilities in preventing PPH or improving its management. We conducted a systematic review using the PRISMA four-step model. The MEDLINE and Cochrane databases were searched up to March 2019. Inclusion criteria were interventional studies, published in English of French language, aiming to reduce PPH outcomes for women in hospitals, regardless of study design. The studies' methodological quality was assessed according to the Cochrane EPOC criteria. We found 32 studies that met the inclusion criteria. None met all the methodological quality criteria. Six types of non-clinical interventions were identified: guideline dissemination, audit with feedback, simulation, training, clinical pathway and multifaceted interventions. Eleven studies reported a significant reduction in PPH rates and/or its complications, five studies reported a significant increase and 16 studies no significant results. The heterogeneity of the studies prevents us from identifying an effective non-clinical intervention in reducing PPH rates.