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: RHODE ISLAND HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-10 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10878034
• 关键词: Affect; Area; Award; Bolus Infusion; Cellular Phone; Cessation of life; Child; Childhood; Clinical; Critical Care; Dangerousness; Data; Development; Diagnostic; Diarrhea; Disease; Equipment; Geographic Locations; Healthcare Systems; IV Fluid; Immune response; Infection; Laboratories; Life; Liquid substance; Malaria; Malnutrition; Monitor; Multiple Organ Failure; Normal saline; Organ failure; Parents; Patient-Focused Outcomes; Physiological; Pneumonia; Population; Practice Management; Research; Resource-limited setting; Resources; Sepsis; Severities; Subgroup; Technology; Time; Veins; acute infection; analytical tool; antimicrobial drug; improved outcome; individualized medicine; intravenous administration; low and middle-income countries; low income country; mHealth; machine learning model; mortality; mortality risk; novel; nutrition; pediatric patients; pediatric sepsis; predictive modeling; prevent; septic patients; temporal measurement; tool; transmission process; treatment response; treatment strategy; wearable device

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.

项目概要 脓毒症是一种危及生命的疾病，由对感染的免疫反应失衡引起，导致器官衰竭 如果不治疗就会失败和死亡。低收入和中等收入国家（LMIC）承担着不成比例的负担 儿童因肺炎、腹泻和疟疾等急性感染引起的败血症而死亡。及时 识别和治疗儿童败血症对于改变病程和预防至关重要 死亡。新型临床工具具有巨大的潜力，可以加快严重疾病的识别 脓毒症、多器官功能障碍综合征（MODS），并预测最高的死亡风险。这些工具可以 还可以有效监测治疗反应，减少对昂贵的实验室诊断的需求 在资源丰富的环境中使用的重症监护监测设备。 虽然早期开始使用抗菌药物在脓毒症治疗中已得到广泛认可，但指南 用于治疗严重脓毒症的静脉输液 (IVF) 的给药可能因情况而异 地理区域甚至营养状况。 2020 年拯救败血症运动建议儿童 居住在医疗保健系统资源有限的地区，因败血症而接受的初始液体量较低 治疗基于一项具有狭窄普遍性的研究，该研究表明死亡率增加 因严重败血症而接受生理盐水推注的儿科患者。患有严重营养不良的儿童 败血症也限制液体。 该项目旨在利用预测模型和移动健康（mHealth）工具来评估 体外受精治疗对儿科患者脓毒症严重程度的影响。通过利用开发的机器学习模型 根据家长奖，可以在中低收入国家环境中实时分析体外受精对脓毒症严重程度的影响。 利用从可穿戴设备实时传输到手机的连续生命体征参数 可以确定 IVF 对脓毒症严重程度影响的测量。这项研究可以揭示其好处 中低收入国家患有严重脓毒症的儿童（包括特定人群，如 营养不良的儿童。鉴于对该亚组适当液体量的研究有限，本研究 提供了确定安全和最佳输液实践的机会。 通过这项研究，我们的目标是帮助了解 IVF 治疗对脓毒症的影响 儿童的严重程度，特别是在中低收入国家。研究结果可以指导液体管理实践，告知 为营养不良患者量身定制治疗策略，并改善儿科脓毒症患者的预后 全世界。