Background: Accurate efficient prognostication in acute medical admissions remains challenging.Methods: We constructed a Vital Sign based Risk Calculator using vital parameters and Major Disease Categories to predict 30-day in-hospital mortality using a multivariable fractional polynomial model.

Results: We evaluated 113,807 admissions in 58,126 patients. The Vital Sign based Risk Calculator predicted 30-day inhospital mortality to increase from 2 points - 3.6% (95%CI 3.4, 3.7) to 12 points - 14.8% (95%CI 14.0, 15.7). AUROC was 0.74 (95%CI 0.72, 0.74). The addition of illness severity and comorbidity data improved AUROC to 0.90 (95%CI 0.89, 0.90).

Conclusion: The Vital Sign based Risk Calculator is limited by its simplicity; inclusion of illness severity and comorbidity data improve prediction.

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References

1. Langlands A, Dowdle R, Elliott A, Gaddie J, Graham A, Johnson G, et al. RCPE UK Consensus Statement on Acute Medicine, November 2008. British journal of hospital medicine (London, England : 2005). 2009;70(1 Suppl 1):S6-7.
2. Rooney T, Bennett K, Silke B. Reduced mortality and length of stay in a teaching hospital after establishment of an acute medical admission unit (AMAU): A 5-year prospective study. European Journal of Internal Medicine. 2008;19(1):E3.
3. Rooney T, Moloney ED, Bennett K, O’Riordan D, Silke B. Impact of an acute medical admission unit on hospital mortality: a 5-year prospective study. Qjm. 2008;101(6):457-65.
4. Moloney ED, Smith D, Bennett K, O’Riordan D, Silke B. Impact of an acute medical admission unit on length of hospital stay, and emergency department ‘wait times’. QJM. 2005;98(4):283-9.
5. Conway R, O’Riordan D, Silke B. Long-term outcome of an AMAU--a decade’s experience. Quarterly Journal of Medicine. 2014;107(1):43-9.
6. Scott I, Vaughan L, D. B. Effectiveness of acute medical units in hospitals: a systematic review. Int J Qual Health Care. 2009;21(6):397-407.
7. Byrne D, Silke B. Acute medical units: review of evidence. Eur J Intern Med. 2011;22(4):344-7.
8. Bell D, Lambourne A, Percival F, Laverty AA, Ward DK. Consultant input in acute medical admissions and patient outcomes in hospitals in England: a multivariate analysis. PloS one. 2013;8(4):e61476.
9. Asadollahi K, Hastings IM, Beeching NJ, Gill GV. Laboratory risk factors for hospital mortality in acutely admitted patients. QJM. 2007;100(8):501-7.
10. Froom P, Shimoni Z. Prediction of hospital mortality rates by admission laboratory tests. Clin Chem. 2006;52(2):325-8.
11. Silke B, Kellett J, Rooney T, Bennett K, O’Riordan D. An improved medical admissions risk system using multivariable fractional polynomial logistic regression modelling. Quarterly Journal of Medicine. 2010;103(1):23-32.
12. Conway R, Byrne D, O’Riordan D, Silke B. Patient risk profiling in acute medicine: the way forward? QJM. 2015;108(9):689-96.
13. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-83.
14. Chotirmall SH, Callaly E, Lyons J, O’Connell B, Kelleher M, Byrne D, et al. Blood cultures in emergency medical admissions: a key patient cohort. Eur J Emerg Med. 2014.
15. Conway R, Galvin S, Coveney S, O’Riordan D, Silke B. Deprivation as an outcome determinant in emergency medical admissions. QJM. 2013;106(3):245-51.
16. Conway R, Byrne D, O’Riordan D, Silke B. Comparative influence of Acute Illness Severity and comorbidity on mortality. Eur J Intern Med. 2020;72:42-6.
17. Lyngholm L, Nickel CH, Kellett J, Chang S, Cooksley T, Brabrand M. Normal gait, albumin and d-dimer levels identify low risk emergency department patients: a prospective observational cohort study with 365-day 100% follow-up. Qjm. 2020;113(2):86-92.
18. Nickel CH, Kellett J, Nieves Ortega R, Lyngholm L, Hanson S, Cooksley T, et al. A simple prognostic score predicts one-year mortality of alert and calm emergency department patients: A prospective two-center observational study. International journal of clinical practice. 2020;74(5):e13481.
19. Chang CY, Abujaber S, Pany MJ, Obermeyer Z. Are vital sign abnormalities associated with poor outcomes after emergency department discharge? (1747-4892 (Electronic)).
20. Conway R, Byrne D, Cournane S, O’Riordan D, Silke B. Fifteenyear outcomes of an acute medical admission unit. Ir J Med Sci. 2018;187(4):1097-105.
21. Conway R, Byrne D, O’Riordan D, Silke B. Outcomes in acute medicine - Evidence from extended observations on readmissions, hospital length of stay and mortality outcomes. Eur J Intern Med.2019;66:69-74.
22. Coary R, Byrne D, O’Riordan D, Conway R, Cournane S, Silke B. Does admission via an acute medical unit influence hospital mortality? 12 years’ experience in a large Dublin hospital. Acute medicine. 2014;13(4):152-8.
23. O’Loughlin R, Allwright S, Barry J, Kelly A, Teljeur C. Using HIPE data as a research and planning tool: limitations and opportunities. Ir J Med Sci. 2005;174(2):40-5; discussion 52-7.
24. O’Callaghan A, Colgan MP, McGuigan C, Smyth F, Haider N, O’Neill S, et al. A critical evaluation of HIPE data. Ir Med J. 2012;105(1):21-3.
25. Sauerbrei W, Meier-Hirmer C, Royston P. Multivariable regression model building by using fractional polynomials: description of SAS, STATA and R programs. Comput Stat Data Anal. 2006;50:3463-85.
26. Royston P, Reitz M, Atzpodien J. An approach to estimating prognosis using fractional polynomials in metastatic renal carcinoma. Br J Cancer. 2006;94(12):1785-8.
27. Kopelman PG, Sanderson AJ. Application of database systems in diabetes care. Medical informatics = Medecine et informatique.1996;21(4):259-71.
28. Courtney D, Conway R, Kavanagh J, O’Riordan D, Silke B. High-sensitivity troponin as an outcome predictor in acute medical admissions. Postgraduate medical journal. 2014;90(1064):311-6.
29. Chin JL, O’Dowd S, Adnan WA, Bennett K, O’Riordan D, Mellotte GJ, et al. Using the MDRD value as an outcome predictor in emergency medical admissions. Nephrology, dialysis, transplantation: official publication of the European Dialysis and Transplant Association - European Renal Association. 2011;26(10):3155-9.
30. O’Sullivan E, Callely E, O’Riordan D, Bennett K, Silke B. Predicting outcomes in emergency medical admissions – role of laboratory data and co-morbidity. Acute medicine. 2012;2:59-65.
31. Silke B, Kellett J, Rooney T, Bennett K, O’Riordan D. An improved medical admissions risk system using multivariable fractional polynomial logistic regression modelling. QJM. 2010;103(1):23-32.
32. Conway R, Byrne D, O’Riordan D, Silke B. Emergency readmissions are substantially determined by acute illness severity and chronic debilitating illness: A single centre cohort study. Eur J Intern Med. 2015;26(1):12-7.
33. Subbe CP. Death after Discharge - Every heart beat counts (probably)! Acute Medicine. 2019;18(2):62-3.
34. Brabrand M, Folkestad L, Clausen N, Knudsen T, Hallas J. Risk scoring systems for adults admitted to the emergency department: a systematic review. Scand J Trauma Resusc Emerg Med. 2010;18(1):8.
35. Hucker TR, Mitchell GP, Blake LD, Cheek E, Bewick V, Grocutt M, et al. Identifying the sick: can biochemical measurements be used to aid decision making on presentation to the accident and emergency department. Br J Anaesth. 2005;94(6):735-41.
36. Prytherch D, Sirl J, Schmidt P, Featherstone P, Weaver P, Smith G. The use of routine laboratory data to predict in-hospital death in medical admissions. Resuscitation. 2005;66:203–7.
37. Brink A, Alsma J, Fortuin A, Bramer W, Zietse R, Lingsma HF, et al. Prediction models for mortality in adult patients visiting the Emergency Department: a systematic review. Acute Medicine. 2019;18(3):171-83.
38. Aragón MJ, Chalkley M. How do time trends in inhospital mortality compare? A retrospective study of England and Scotland over 17 years using administrative data. BMJ open. 2018;8(2):e017195.
39. Conway R, Byrne D, O’Riordan D, Silke B. Outcomes in acute medicine - Evidence from extended observations on readmissions, hospital length of stay and mortality outcomes. Eur J Int Med. 2019.
40. Pimentel MAF, Redfern OC, Gerry S, Collins GS, Malycha J, Prytherch D, et al. A comparison of the ability of the National Early Warning Score and the National Early Warning Score 2 to identify patients at risk of in-hospital mortality: A multi-centre database study. Resuscitation. 2019;134:147-56.
41. Conway R, O’Riordan D, Silke B. Targets and the emergency medical system--intended and unintended consequences. European journal of emergency medicine : official journal of the European Society for Emergency Medicine. 2015;22(4):235-40.