Multicentre, prospective observational study of the correlation between the Glasgow Admission Prediction Score and adverse outcomes

• Main Authors: Dominic Jones, Allan Cameron, Colin A O'Keeffe, Eilidh Logan
• Format: Article
• Language: English
• Published: BMJ Publishing Group 2019-08-01
• Series: BMJ Open
• Online Access: https://bmjopen.bmj.com/content/9/8/e026599.full

ObjectivesTo assess whether the Glasgow Admission Prediction Score (GAPS) is correlated with hospital length of stay, 6-month hospital readmission and 6-month all-cause mortality. This study represents a 6-month follow-up of patients who were included in an external validation of the GAPS’ ability to predict admission at the point of triage.SettingSampling was conducted between February and May 2016 at two separate emergency departments (EDs) in Sheffield and Glasgow.ParticipantsData were collected prospectively at triage for consecutive adult patients who presented to the ED within sampling times. Any patients who avoided formal triage were excluded from the study. In total, 1420 patients were recruited.Primary outcomesGAPS was calculated following triage and did not influence patient management. Length of hospital stay, hospital readmission and mortality against GAPS were modelled using survival analysis at 6 months.ResultsOf the 1420 patients recruited, 39.6% of these patients were initially admitted to hospital. At 6 months, 30.6% of patients had been readmitted and 5.6% of patients had died. For those admitted at first presentation, the chance of being discharged fell by 4.3% (95% CI 3.2% to 5.3%) per GAPS point increase. Cox regression indicated a 9.2% (95% CI 7.3% to 11.1%) increase in the chance of 6-month hospital readmission per point increase in GAPS. An association between GAPS and 6-month mortality was demonstrated, with a hazard increase of 9.0% (95% CI 6.9% to 11.2%) for every point increase in GAPS.ConclusionA higher GAPS is associated with increased hospital length of stay, 6-month hospital readmission and 6-month all-cause mortality. While GAPS’s primary application may be to predict admission and support clinical decision making, GAPS may provide valuable insight into inpatient resource allocation and bed planning.