QJM Advance Access published online on October 21, 2009
QJM, doi:10.1093/qjmed/hcp149
An improved medical admissions risk system using multivariable fractional polynomial logistic regression modelling
From the 1Division of Internal Medicine, St. James's Hospital, Dublin 8, 2Department of Medicine, Nenagh Hospital, Nenagh, County Tipperary and 3Department of Pharmacology and Therapeutics, Trinity Centre for Health Sciences, St. James's Hospital, Dublin 8, Ireland
Address correspondence to T. Rooney, c/o Bernard Silke, MD, DSc, FRCP, Department of Pharmacology and Therapeutics, Trinity Centre for Health Sciences, St. James's Hospital, Dublin 8, Ireland. email: rooneyterence{at}gmail.com
Received 8 January 2009 and in revised form 10 August 2009
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Abstract |
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Aim: To develop and validate an in-hospital mortality risk prediction tool for unselected acutely ill medical patients using routinely collected physiological and laboratory data.
Design: Analysis of all emergency medical patients admitted to St James's Hospital (SJH), Dublin, between 1 January 2002 and 31 December 2007. Validation using a dataset of acute medical admissions from Nenagh Hospital 2000–04.
Methods: Using routinely collected vital signs and laboratory findings, a composite 5-day in-hospital mortality risk score, designated medical admissions risk system (MARS), was developed using an iterative approach involving logistic regression and multivariable fractional polynomials. Results are presented as area under receiver operating characteristics curves (AUROC) as well as Hosmer and Lemeshow goodness-of-fit statistics.
Results: A total of 10 712 and 3597 unique patients were admitted to SJH and Nenagh Hospital, respectively. The final score included nine variables [age, heart rate, mean arterial pressure, respiratory rate, temperature, urea, potassium (K), haematocrit and white cell count]. The AUROC for 5-day in-hospital mortality was 0.93 [95% confidence interval (CI) 0.92–0.94] for the SJH cohort (Hosmer and Lemeshow test, P = 0.32) and 0.92 (95% CI 0.90–0.94) for the external Nenagh hospital validation cohort (Hosmer and Lemeshow test, P = 0.28).
Conclusions: In-hospital mortality estimation using only routinely collected emergency department admission data is possible in unselected acute medical patients using the MARS system. Such a score applied to acute medical patients at the time of admission, could assist senior clinical decision makers in promptly and accurately focusing limited clinical resources. Further studies validating the impact of this model on clinical outcomes are warranted.