10000 Participants Needed

Risk Prediction Model for Postpartum Hemorrhage

HE
TB
Overseen ByTracie Baker, CCRP
Age: Any Age
Sex: Female
Trial Phase: Academic
Sponsor: Holly Ende
No Placebo GroupAll trial participants will receive the active study treatment (no placebo)

Trial Summary

Do I need to stop my current medications for this trial?

The trial information does not specify whether you need to stop taking your current medications. It's best to discuss this with the trial coordinators or your healthcare provider.

What data supports the effectiveness of the treatment Novel PPH Risk Prediction Model for predicting postpartum hemorrhage?

The research highlights the development of various prediction models and tools that assess risk factors for postpartum hemorrhage (PPH), suggesting that a reliable risk assessment tool can help optimize interventions and reduce adverse outcomes. This implies that the Novel PPH Risk Prediction Model could be effective in identifying women at risk and improving maternal health by preventing severe PPH.12345

Is the Novel PPH Risk Prediction Model safe for humans?

The research articles focus on predicting postpartum hemorrhage risk using various models and data but do not provide specific safety information about the models themselves. These models are tools for prediction and do not involve direct treatment or intervention, so they are generally considered safe to use.15678

How does the Novel PPH Risk Prediction Model treatment differ from other treatments for postpartum hemorrhage?

The Novel PPH Risk Prediction Model is unique because it focuses on predicting the risk of postpartum hemorrhage (excessive bleeding after childbirth) using a combination of clinical and biological data, rather than treating the condition after it occurs. This approach aims to identify women at risk before severe bleeding happens, potentially allowing for preventive measures to be taken.12359

What is the purpose of this trial?

This research project aims to enhance the safety of childbirth by using advanced computer models to predict the risk of postpartum hemorrhage (PPH).PPH is a significant concern for mothers during and after delivery. Current risk assessment tools are basic and do not adapt to changing conditions. This study will investigate whether a new and recently validated model for predicting PPH, combined with a provider-facing Best Practice Advisory (BPA) regarding currently recommended strategies triggered by an increased predicted risk, can improve perinatal outcomes.This study will compare the current category based risk assessment tool with a new, enhanced prediction model which calculates risk based on 21 factors, automatically updates as new information becomes available during labor and, if elevated, provides a provider-facing Best Practice Advisory (BPA) recommending consideration of strategies that are institutionally agreed to represent high-quality practice.Investigators hypothesize that the enhanced care approach will result in improved perinatal outcomes.The goal of the study is to improve the wellbeing of mothers during childbirth by harnessing the power of modern technology and data analysis.

Research Team

HE

Holly Ende, MD

Principal Investigator

Vanderbilt University Medical Center

Eligibility Criteria

This trial is for pregnant individuals at risk of postpartum hemorrhage (PPH). Participants should be giving birth where the study is being conducted. There are no specific inclusion or exclusion criteria provided, but typically participants would need to be of childbearing age and not have conditions that could interfere with the study.

Inclusion Criteria

All vaginal and cesarean deliveries occurring at Vanderbilt University Medical Center

Exclusion Criteria

Patients who are discharged prior to delivery will be excluded from subsequent analysis
I am not planning a hysterectomy before delivery for placenta issues.

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Intervention

Participants are assigned to either the standard care arm or the novel PPH risk prediction model arm. The intervention arm includes additional risk prediction and Best Practice Advisory (BPA) for elevated risk cases.

Duration of labor and delivery

Postpartum Monitoring

Participants are monitored for postpartum outcomes, including morbidity and mortality, up to 30 days postpartum.

30 days

Follow-up

Participants are monitored for safety and effectiveness after treatment, including postpartum hospital discharge outcomes.

2-4 days

Treatment Details

Interventions

  • Novel PPH Risk Prediction Model
Trial Overview The trial tests a new computer model predicting PPH against current basic tools. It uses 21 factors to assess risk in real-time during labor, providing instant recommendations if there's an increased risk.
Participant Groups
2Treatment groups
Active Control
Group I: Novel PPH Risk Prediction Model - Comparator Arm BActive Control1 Intervention
Standard Care with addition of a recently developed, novel PPH risk prediction model.
Group II: Standard Care - Comparator Arm AActive Control1 Intervention
Standard Care, which includes a category-based risk assessment tool as part of nursing admission workflow. The prophylactic interventions in the intervention are recommended by the tool but not specifically tied to provider-facing clinical decision support.

Find a Clinic Near You

Who Is Running the Clinical Trial?

Holly Ende

Lead Sponsor

Trials
1
Recruited
10,000+

Vanderbilt University Medical Center

Collaborator

Trials
922
Recruited
939,000+

Findings from Research

In a study of 7236 women with post-partum hemorrhage (PPH), severe cases were identified in 18.5% of participants, with several clinical factors like parity and labor induction linked to increased risk.
A prediction model developed to identify severe PPH had a moderate performance (ROC area of 0.63), but its sensitivity (49%) and specificity (70%) were insufficient for routine clinical use, indicating a need for additional data, such as laboratory results, to improve accuracy.
Severity of post-partum hemorrhage after vaginal delivery is not predictable from clinical variables available at the time post-partum hemorrhage is diagnosed.Cortet, M., Maucort-Boulch, D., Deneux-Tharaux, C., et al.[2022]
A prediction model for postpartum hemorrhage (PPH) was developed using data from 5,807 singleton pregnancies, identifying four key risk factors: nulliparity, fetal macrosomia, mode of delivery, and history of PPH.
The model demonstrated good predictive performance with a C-statistic of 0.751, and external validation confirmed its reliability, suggesting that the nomogram could help clinicians assess individual PPH risk and improve management strategies.
Predicting risk of postpartum haemorrhage during the intrapartum period in a general obstetric population.Maher, GM., McKernan, J., O'Byrne, L., et al.[2022]
In a study of over 3 million births in Norway from 1967 to 2017, postpartum hemorrhage (PPH) occurred in 9.3% of cases, with retained placenta being the most common cause of severe PPH (29.3%).
The study found that the sex of the newborn affects PPH risk, with male infants associated with a lower risk of PPH, particularly for retained placenta and uterine atony, while a history of cesarean section significantly increased the risk of PPH due to dystocia.
Risk factors and recurrence of cause-specific postpartum hemorrhage: A population-based study.Linde, LE., Rasmussen, S., Moster, D., et al.[2022]

References

Severity of post-partum hemorrhage after vaginal delivery is not predictable from clinical variables available at the time post-partum hemorrhage is diagnosed. [2022]
Predicting risk of postpartum haemorrhage during the intrapartum period in a general obstetric population. [2022]
Risk factors and recurrence of cause-specific postpartum hemorrhage: A population-based study. [2022]
Nomogram to predict postpartum hemorrhage in cesarean delivery for twin pregnancies: a retrospective cohort study in China. [2023]
Risk Factors for Postpartum Hemorrhage and its Severe Forms with Blood Loss Evaluated Objectively - A Prospective Cohort Study. [2023]
Machine Learning and Statistical Models to Predict Postpartum Hemorrhage. [2022]
A Framework for Improving Characterization of Obstetric Hemorrhage Using Informatics Data. [2023]
Prediction of postpartum hemorrhage in pregnant women with immune thrombocytopenia: Development and validation of the MONITOR model in a nationwide multicenter study. [2021]
Development and Validation of a Predictive Tool for Postpartum Hemorrhage after Vaginal Delivery: A Prospective Cohort Study. [2023]
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