Short summary

A prospective nationwide multicenter flashmob study, which aim is to assess if loss of mobility at arrival to hospital is a predictor for short term mortality, and if loss of mobility can differentiate risk of patients with seemingly identical vital signs and thus improve in-hospital prognostication.

Rationale

Prior retrospective and smaller prospective studies have shown that mobility - and especially loss of mobility - measured at arrival to hospital is a powerful predictor for outcome (Brabrand et al., 2018, Brabrand and Kellett, 2014, Nissen et al., 2019, Brabrand et al., 2015, Kellett and Deane, 2006). When combined with vital signs, aggregated as an early warning score, loss of mobility has been able to add substantial differentiation of risk, even in patient groups with seemingly identical vital signs. As such, patients with almost completely normal vital signs that had loss of mobility had the same risk as patients with the most abnormal vital signs with preserved mobility (Brabrand et al., 2018).

Currently, patients are risk assessed based primarily on vital signs. But if vital signs can be substantiated with mobility, an even stronger risk prediction can be performed and disposition improved.

At the moment, we do not know with certainty why mobility is such a strong predictor for short term mortality. One possibility is that mobility is a marker of resilience and physiological reserve (Brabrand and Kellett, 2014).

As previously mentioned, prior studies have been retrospective or small. With this prospective nationwide multicenter study, we aim to assess if loss of mobility at arrival to hospital is a predictor for short term mortality and if loss of mobility can differentiate risk of patients with seemingly identical vital signs and thus improve in-hospital prognostication.

Description of the cohort

All adult patients arriving with ambulance to the emergency department, who are not in need of urgent treatment (surgical or medical trauma call or thrombolysis), and who do not have trauma to the lower limbs.

Data and biological material

Data will be collected either from the patient, ambulance or patient records, at the bedside or extracted from national databases. Data collected bedside (e.g. vital signs, mobility assessment) and data extracted from the national database (co-morbidities, diagnoses and prescriptions).

Collaborating researchers and departments

Aalborg University

• Professor Erika Christensen

University of Southern Denmark

• Associate Professor John Kellett

University Hospital of South Manchester

• dr. Tim Cooksley

University of Basel

• Professor Christian Nickel