OBJECTIVES: 

To develop and validate a prediction model to estimate the risk of Medical Emergency Team (MET) review, within 48 hours of an emergency admission, using information routinely available at the time of hospital admission.

DESIGN: 

Development and validation of a multivariable risk model using prospectively collected data. Transparent Reporting of a multivariable model for Individual Prognosis Or Diagnosis recommendations were followed to develop and report the prediction model.

SETTING: 

A 560-bed teaching hospital, with a 22-bed ICU and 24-hour Emergency Department in Melbourne, Australia.

PATIENTS: 

A total of 45,170 emergency admissions of 30,064 adult patients (≥18 yr), with an inpatient length of stay greater than 24 hours, admitted under acute medical or surgical hospital services between 2015 and 2017.

MEASUREMENTS AND MAIN RESULTS: 

The outcome was MET review within 48 hours of emergency admission. Thirty candidate variables were selected from a routinely collected hospital dataset based on their availability to clinicians at the time of admission. The final model included nine variables: age; comorbid alcohol-related behavioral diagnosis; history of heart failure, chronic obstructive pulmonary disease (COPD), or renal disease; admitted from residential care; Charlson Comorbidity Index score 1 or 2, or 3+; at least one planned and one emergency admission in the last year; and admission diagnosis and one interaction (past history of COPD × admission diagnosis). The discrimination of the model was comparable in the training (C-statistics 0.82; 95% CI, 0.81–0.83) and the validation set (0.81; 0.80–0.83). Calibration was reasonable for training and validation sets.

CONCLUSIONS: 

Using only nine predictor variables available to clinicians at the time of admission, the MET-risk model can predict the risk of MET review during the first 48 hours of an emergency admission. Model utility in improving patient outcomes requires further investigation.

中文翻译：

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紧急入院时急诊住院患者临床恶化的医疗急救团队风险预测模型的开发和验证*

目标： 

开发和验证预测模型，以在紧急入院后 48 小时内使用入院时常规可用的信息来估计医疗急救小组 (MET) 审查的风险。

设计： 

使用前瞻性收集的数据开发和验证多变量风险模型。遵循个体预后或诊断建议的多变量模型的透明报告以开发和报告预测模型。

环境： 

位于澳大利亚墨尔本的一家拥有 560 个床位的教学医院，设有 22 个床位的 ICU 和 24 小时急诊室。

患者： 

2015 年至 2017 年间，共有 30,064 名成年患者（≥18 岁）急诊入院，住院时间超过 24 小时，接受急诊内科或外科医院服务，共计 45,170 例。

测量和主要结果： 

结果是在紧急入院后 48 小时内进行 MET 审查。根据入院时临床医生的可用性，从常规收集的医院数据集中选择了 30 个候选变量。最终模型包括九个变量：年龄；合并酒精相关行为诊断；心力衰竭、慢性阻塞性肺病 (COPD) 或肾病病史；从住宿护理中入院；查尔森合并症指数评分 1 或 2，或 3+；过去一年至少有一次计划入院和一次紧急入院；入院诊断和一种交互作用（COPD 既往病史×入院诊断）。该模型的辨别力在训练（C 统计量 0.82；95% CI，0.81–0.83）和验证集（0.81；0.80–0.83）中具有可比性。校准对于训练和验证集是合理的。

结论： 

MET 风险模型仅使用临床医生在入院时可用的九个预测变量，就可以预测急诊入院前 48 小时内 MET 审查的风险。改善患者预后的模型效用需要进一步研究。