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

项目总结 脓毒症是一种威胁生命的疾病，由感染引起的免疫反应失衡引起，导致器官 如果不治疗，就会失败和死亡。中低收入国家(LMIC)背负着不成比例的 肺炎、腹泻和疟疾等急性感染引起的败血症导致的儿童死亡。及时 儿童脓毒症的认识和治疗是改变病程、预防感染的关键 死亡率。新的临床工具具有巨大的潜力，可以加速诊断严重的 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 还可以有效地监测治疗反应，减少对昂贵的实验室诊断和 在高资源环境中使用的重症监护设备。 虽然在脓毒症治疗中早期开始使用抗菌药物是确凿的，但指导 静脉输液(IVF)治疗严重脓毒症的方法可能有所不同 地理区域，甚至营养状况。2020年败血症幸存者运动建议那些 居住在资源有限的医疗保健系统所在地区会因脓毒症而获得较低的初始液体量 治疗基于一项具有狭隘概括性的研究，该研究表明 接受生理盐水丸剂治疗严重脓毒症的儿科患者。营养不良和严重营养不良的儿童 脓毒症也是液体受限的。 该项目旨在利用预测建模和移动健康(MHealth)工具来评估 体外受精对小儿脓毒症严重程度的影响。通过利用开发的机器学习模型 在家长奖下，可以在LMIC设置中实时分析试管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移动电话的连续生命体征参数 可以确定体外受精对脓毒症严重程度的影响。这项研究可以阐明这样的好处 在患有严重脓毒症的LMIC儿童中，包括特定人群，如 营养不良的儿童。鉴于对这一亚群合适的液体体积的研究有限，这项研究 提供一个机会来确定安全和最佳的液体管理实践。 通过这项研究，我们旨在有助于了解体外受精治疗脓毒症的效果。 儿童的严重程度，特别是在LMIC环境中。这些发现可以指导流体管理实践，为 为营养不良患者量身定做治疗策略，改善儿童脓毒症患者的预后 全世界。

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.