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Development of a Mobile Health Personalized Physiologic Analytics Tool for Pediatric Patients with Sepsis

Development of a Mobile Health Personalized Physiologic Analytics Tool for Pediatric Patients with Sepsis
为脓毒症儿科患者开发移动健康个性化生理分析工具
批准号:
10878034
负责人:
Stephanie Chow Garbern
金额:
$16.38万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-08-10 至 2025-04-30

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PROJECT SUMMARY Sepsis is a life-threatening condition caused by an imbalanced immune response to infection, leading to organ failure and death if untreated. Low- and middle-income countries (LMICs) bear a disproportionate burden of childhood deaths due to sepsis resulting from acute infections like pneumonia, diarrhea, and malaria. Timely recognition and treatment of sepsis in children are crucial for altering the disease course and preventing mortality. There is immense potential for novel clinical tools that can expedite the identification of severe sepsis, multiple organ dysfunction syndrome (MODS), and predict the highest mortality risk. These tools can also effectively monitor treatment responses, decreasing the need for expensive laboratory diagnostics and critical care monitoring equipment used in high-resource settings. While early initiation of antimicrobial drugs is well-established in sepsis treatment, the guidance for administration of intravenous fluids (IVF) for treatment of severe sepsis can vary depending on the geographical region and even nutrition status. The 2020 Surviving Sepsis Campaign advises that children who reside in areas with resource-limited healthcare systems receive lower initial fluid volumes based for sepsis treatment based on a study with narrow generalizability that demonstrated increased mortality rates among pediatric patients who received normal saline boluses for severe sepsis. Children with malnutrition and severe sepsis are also fluid restricted. This project aims to leverage predictive modeling and mobile health (mHealth) tools to evaluate the impact of IVF administration on sepsis severity in pediatric patients. By utilizing machine learning models developed under the parent award, real-time analysis of IVF effects on sepsis severity can be performed in LMIC settings. Utilizing continuous vital sign parameters transmitted from a wearable device to a mobile phone, real-time measurement of IVF impact on sepsis severity can be determined. This research can shed light on the benefits or harms of fluid administration in LMIC children with severe sepsis, including specific populations like malnourished children. Given the limited studies on appropriate fluid volumes for this subgroup, this research offers an opportunity to determine safe and optimal fluid administration practices. Through this research, we aim to contribute to the understanding of IVF administration effects on sepsis severity in children, particularly in LMIC settings. The findings can guide fluid management practices, inform tailored treatment strategies for malnourished patients, and improve outcomes for pediatric sepsis patients worldwide.
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Development of a Mobile Health Personalized Physiologic Analytics Tool for Pediatric Patients with Sepsis
  • 批准号:
    10880477
  • 项目类别:
  • 资助金额:
    $24.71万
  • 财政年份:
    2021
  • 负责人:
    Stephanie Chow Garbern
  • 依托单位:
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