Machine Learning for Risk Stratification in the Emergency Department: a Pilot Clinical Trial
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 1,300
- 试验地点
- 2
- 主要终点
- RISK-INDEX performance
研究概览
简要总结
Rationale
Identifying emergency department (ED) patients at high and low risk shortly after admission could help decision-making regarding patient care. Several clinical risk scores and triage systems for stratification of patients have been developed, but often underperform in clinical practice. Moreover, most of these risk scores only have been diagnostically validated in an observational cohort, but never have been evaluated for their actual clinical impact. In a recent retrospective study that was conducted in the Maastricht University Medical Center (MUMC+), a novel clinical risk score, the RISKINDEX, was introduced that predicted 31-day mortality of sepsis patients presenting to an ED. The RISKINDEX hereby also outperformed internal medicine specialists. Observational follow-up studies underlined the potential of the risk score. However, it remains unknown to what extent these models have any beneficial value when it is actually implemented in clinical practice.
Objective
To determine the diagnostic accuracy, policy changes and clinical impact of the RISKINDEX as basis to conduct a large scale, multi-center randomised trial.
Study design
The MARS-ED study is designed as a multi-center, randomized, open-label, non-inferiority pilot clinical trial.
Study population
Adult patients who are assessed and treated by an internal medicine specialist in the ED of whom a minimum of 4 different laboratory results (hematology or clinical chemistry, required for calculation of ML risk score) are available within the first two hours of the ED visit.
Intervention
Physicians will be presented with the ML risk score (the RISKINDEX) of the patients they are actively treating, directly after assessment of regular diagnostics has taken place.
Main study parameters
Primary
- Diagnostic accuracy, policy changes and clinical impact of a novel clinical risk score (the RISKINDEX)
Secondary
- Policy changes due to presentation of ML score (treatment policy, requesting ancillary investigations, treatment restrictions (i.e., no intubation or resuscitation)
- Intensive care (ICU) and medium care (MC) admission
- Length of admission
- Mortality within 31 days
- Readmission
- Patient preference
- Feasibility of novel clinical risk score
详细描述
See our protocol paper, PMID 38263188
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Diagnostic
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Adult, defined as ≥ 18 years of age
- •Assessed and treated by an internal medicine specialist (gastroenterologists included) in the ED
- •Willing to give written consent, either directly or after deferred consent procedure (see section 11.2).
排除标准
- •<4 different laboratory results available (hematology or clinical chemistry) within the first two hours of the ED visit (calculation ML prediction score otherwise not possible)
- •Unwilling to provide written consent, either directly or after deferred consent procedure (see section 11.2).
研究组 & 干预措施
Standard care
Routine clinical care. Physicians will actively be asked to self-report their clinical impression of each included patient and policy will be monitored.
RISKINDEX
Routine clinical care. Physicians will actively be asked to self-report their clinical impression of each included patient and policy will be monitored. In the intervention group, physicians will be presented with the RISKINDEX. Subsequently, self-report will again be initiated to evaluate the physicians' response to the ML score and possible policy changes due to the intervention.
干预措施: RISK-INDEX (Other)
结局指标
主要结局
RISK-INDEX performance
时间窗: 31 days
Discriminatory performance of ML risk score to predict 31-day mortality. This will be calculated using an area under the receiver operating characteristic curves (AUC).
Policy changes
时间窗: As soon as RISK-INDEX score is presented
Policy changes after presentation of RISK-INDEX. This will be assessed by a filled out questionnaire by the physician where they state whether a policy change has been made as a result of the RISK-INDEX outcome.
次要结局
未报告次要终点