跳至主要内容
临床试验/NCT05806762
NCT05806762招募中不适用

Prediction of Rehospitalization Following a Sepsis Admission Using a Wearable Biopatch and Deep Learning Model

University of California, San Diego1 个研究点 分布在 1 个国家目标入组 200 人开始时间: 2023年5月1日最近更新:
适应症

试验速览

阶段
不适用
状态
招募中
入组人数
200
试验地点
1
主要终点
Hospital readmission

研究概览

简要总结

The goal of this observational study is to learn about the utility of biopatches predicting 30-day readmissions in patients discharged from the hospital with sepsis.

The main question[s] it aims to answer are:

• Does the application of a biopatch provide data that can improve prediction of an unplanned 30-day readmission following a hospitalization for sepsis.

Participants will be asked to wear a biopatch on their chest for 30-days following hospital discharge or until readmission to the hospital.

详细描述

Study Design: Longitudinal cohort study with repeated measure of outcomes and predictors.

The BioIntelliSense patch is an FDA approved wearable device that is applied to the chest with a 30-day battery lifespan and allows for real-time monitoring of heart rate, respiratory rate, skin temperature, general activity, severe cough episodes, and sedentary body position, among others.

Outcomes of Interest: Hospital readmission within 30 days of discharge following an index admission with a diagnosis of sepsis is the primary outcome of interest for this study. We will calculate the positive predictive value (PPV) of readmission prediction as the the primary outcome of interest from the following approaches: analytic score plus biopatch, analytic score alone, LACE+ score. Secondary outcomes include area under the curve of the receiver operator characteristic (AUCroc) of predictive scores (analytic score and biopatch, analytic score alone, LACE+ score) and number of patients readmitted to the hospital within 30 days of discharge.

Protocol for Patient Selection and Application of Biopatch: Patients who meet "Sepsis 3" definition will be identified with institutional review board (IRB)-approved screening protocols. Our previously derived and validated machine-learning algorithm to predict unplanned 30-day readmissions will then generate daily predictions about 30-day readmission probability which will be recorded, as well as LACE+ scores. As a patient approaches discharge, the treatment team and patient (or legally authorized representative) will be approached about potential enrollment. If there is agreement to enroll in this prospective study, then we will apply the patch at the time of discharge. Patients will then be followed with the BioIntellisence patch with augmented and real-time risk predictions based on data obtained from this. For this proposal, we will use data from the BioIntelliSense patch and are not providing clinicians with data on risk of readmission.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

入排标准

年龄范围
18 Years 至 —(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • Age >= 18 years Development of sepsis, defined by recent international guidelines (Suspected infection AND 2-point change in sequential organ failure assessment (SOFA) score), in emergency department or hospital Admission to hospital from emergency department

排除标准

  • Transition to comfort measures within 6 hours of time of sepsis Discharge from the emergency department Admission to bone marrow transplant service Severe burn or other dermatologic condition that will prevent application to skin

结局指标

主要结局

Hospital readmission

时间窗: 30 days

Patients with an index hospitalization with sepsis will be followed to see if they have an unplanned readmission to the hospital.

次要结局

  • Area under the curve of the receiver operating characteristic(30 days)
  • Positive predictive value(30 days)

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

Gabriel Wardi

Associate Professor

University of California, San Diego

研究点 (1)

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