The Problems with Risk Prediction during an Emergency Medical Admission Using Laboratory Data – Evidence from Potassium

The Problems with Risk Prediction during an Emergency Medical Admission Using Laboratory Data – Evidence from Potassium

Background: The prediction of clinical outcomes using biochemical markers is an important tool.

Methods: We calculated a risk score for all emergency admissions 2002-2017. We related potassium and mortality in a multivariable fractional polynomial model. We investigated the potassium distribution and relationship of potassium to mortality over time.

Results: There were 106,586 admissions in 54,928 patients. Mortality was higher for those with an admission potassium above the median – 6.1% vs 4.6% (p<0.001), OR 1.07 (95%CI: 1.06, 1.09). There was a progressive increase in mortality from the lowest – 8.9% (95%CI: 8.3%, 9.4%) to highest potassium decile – 14.2% (95%CI: 13.5%, 14.8%). The frequency of admission hypokalaemia and the mortality at any given potassium decreased over time.

Conclusion: Admission potassium predicts mortality.

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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. 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.
  3. 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.
  4. Byrne D, Silke B. Acute medical units: review of evidence. Eur J Intern Med. 2011;22(4):344-7.
  5. 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.
  6. 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.
  7. Hall MJ, Levant S, DeFrances CJ. Trends in Inpatient Hospital Deaths: National Hospital Discharge Survey, 2000–2010 2013 [Available from: https://pdfs.semanticscholar.org/1ba6/6dde91e1ef7e8f7eb80da6423cf572bc24ce.pdf.
  8. Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: a severity of disease classification system. Crit Care Med. 1985;13(10):818-29.
  9. Olsson T, Lind L. Comparison of the rapid emergency medicine score and APACHE II in nonsurgical emergency department patients. Acad Emerg Med. 2003;10(10):1040-8.
  10. Sakr Y, Krauss C, Amaral AC, Rea-Neto A, Specht M, Reinhart K, et al. Comparison of the performance of SAPS II, SAPS 3, APACHE II, and their customized prognostic models in a surgical intensive care unit. Br J Anaesth. 2008;101(6):798-803.
  11. Froom P, Shimoni Z. Prediction of hospital mortality rates by admission laboratory tests. Clin Chem. 2006;52(2):325-8.
  12. 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.
  13. Asadollahi K, Hastings IM, Beeching NJ, Gill GV. Laboratory risk factors for hospital mortality in acutely admitted patients. QJM. 2007;100(8):501-7.
  14. 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.
  15. Kellett J, Deane B. The Simple Clinical Score predicts mortality for 30 days after admission to an acute medical unit. QJM. 2006;99(11):771-81.
  16. Kellett J, Rasool S, McLoughlin B. Prediction of mortality 1 year after hospital admission. QJM. 2012;105(9):847-53.
  17. Kellett J. Prognostication--the lost skill of medicine. Eur J Intern Med. 2008;19(3):155-64.
  18. 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.
  19. Conway R, Creagh D, Byrne DG, O’Riordan D, Silke B. Serum potassium levels as an outcome determinant in acute medical admissions. Clinical medicine (London, England). 2015;15(3):239-43.
  20. Loprinzi PD, Hall ME. Effect of Serum Potassium on All-Cause Mortality in the General US Population. Mayo Clinic Proceedings. 2017;92(2):320.
  21. Vach W. Regression Models as a Tool in Medical Research: Chapman & Hall/CRC; 2013. 473 p.
  22. Conway R, Byrne D, Cournane S, O’Riordan D, Silke B. Fifteenyear outcomes of an acute medical admission unit. Irish Journal of Medical Science. 2018:1-2.
  23. Beeknoo N, Jones R. Factors Influencing A & E Attendance, Admissions and Waiting Times at Two London Hospitals. British Journal of Medicine & Medical Research. 2016;17(10):1-29.
  24. 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.
  25. 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.
  26. Courtney D, Conway R, Kavanagh J, O’Riordan D, Silke B. High-sensitivity troponin as an outcome predictor in acute medical admissions. Postgrad Med J. 2014:1-7.
  27. 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.
  28. Chotirmall SH, Picardo S, Lyons J, D’Alton M, O’Riordan D, Silke B. Disabling disease codes predict worse outcomes for acute medical admissions. Intern Med J. 2014;44(6):546-53.
  29. Cournane S, Conway R, Byrne D, O'Riordan D, Silke B. Predicting Outcomes in Emergency Medical Admissions Using a Laboratory Only Nomogram. Computational and Mathematical Methods in Medicine. 2017;2017(1):1-8.
  30. 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.
  31. Pun PH, Goldstein BA, Gallis JA, Middleton JP, Svetkey LP. Serum Potassium Levels and Risk of Sudden Cardiac Death Among Patients With Chronic Kidney Disease and Significant Coronary Artery Disease. Kidney International Reports. 2017;2(6):1122-31.
  32. Prytherch DR, Sirl JS, Schmidt P, Featherstone PI, Weaver PC, Smith GB. The use of routine laboratory data to predict in-hospital death in medical admissions. Resuscitation. 2005;66(2):203-7.
  33. Wannamethee G, Whincup PH, Shaper AG, Lever AF. Serum sodium concentration and risk of stroke in middle-aged males. J Hypertens. 1994;12(8):971-9.
  34. Mohammed AA, Kimmenade RRJv, Richards M, Bayes-Genis A, Pinto Y, Moore SA, et al. Hyponatremia, natriuretic peptides, and outcomes in acutely decompensated heart failure: results from the International Collaborative of NT-proBNP Study. Circ Heart Fail. 2010;3(3):354-61.
  35. Forfia PR, Mathai SC, Fisher MR, Housten-Harris T, Hemnes AR, Champion HC, et al. Hyponatremia Predicts Right Heart Failure and Poor Survival in Pulmonary Arterial Hypertension. Am J Respir Crit Care Med. 2008;177(12):1364-9.
  36. Subbe CP, Kruger M, Rutherford P, Gemmel L. Validation of a modified early warning score in medical admissions. Q J Med. 2001;94:521-6.
  37. Rhee K, Fisher C, Willitis N. The Rapid Acute Physiology Score. Am J Emerg Med. 1987;5:278-86.
  38. Goodacre S, Turner, T., Nicholl, J. Prediction of mortality among emergency medical admissions Emerg Med J. 2006;23:371-5.
  39. Whelan B, Bennett K, O’Riordan D, Silke B. Serum sodium as a risk factor for in-hospital mortality in acute unselected general medical patients. QJM. 2009;102(3):175-82.
  40. Asadollahi K, Beeching N, Gill G. Hyponatraemia as a risk factor for hospital mortality. QJM. 2006;99(12):877-80.
  41. Stachon A, Segbers E, Hering S, Kempf R, Holland-Letz T, Krieg M. A laboratory-based risk score for medical intensive care patients. Clin Chem Lab Med. 2008;46(6):855-62.
  42. Waikar SS, Mount DB, Curhan GC. Mortality after Hospitalization with Mild, Moderate, and Severe Hyponatremia. The American Journal of Medicine. 2009;122(9):857-65.
  43. Freire AX, Bridges, L., Umpierrez, G.E., Kuhl, D., Kitabchi, A.E. Admission Hyperglycemia and Other Risk Factors as Predictors of Hospital Mortality in a Medical ICU Population. Chest. 2005;128:3109-16.
  44. Goldwasser P, Feldman J. Association of serum albumin and mortality risk. J Clin Epidemiol. 1997;50(6):693-703.
  45. Umpierrez GE, Isaacs SD, Bazargan N, You X, Thaler LM, Kitabchi AE. Hyperglycemia: An Independent Marker of In-Hospital Mortality in Patients with Undiagnosed Diabetes. J Clin Endocrinol Metab. 2002;87(3):978-82.
  46. Suleiman M, Hammerman H, Boulos M, et al. Fasting glucose is an important independent risk factor for 30-day mortality in patients with acute myocardial infarction: a prospective study. Circulation. 2005;111:754-60.
  47. Stranders I, Diamant M, Van Gelder RE, et al. Admission blood glucose level as risk indicator of death after myocardial infarction in patients with and without diabetes mellitus. Arch Intern Med. 2004;164:982-8.
  48. Krinsley JS. Association between hyperglycemia and in-creased hospital mortality in a heterogeneous population of critically ill patients. Mayo Clin Proc. 2003;78:1471-8.
  49. BTS Guidelines for the Management of Community Acquired Pneumonia in Adults. Thorax. 2001;56 Suppl 4:IV1-64.
  50. 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.

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The Problems with Risk Prediction during an Emergency Medical Admission Using Laboratory Data – Evidence from Potassium

5th April 2019
PMID: 32608389
Authors Affiliations
Richard Conway MED Directorate, St James’s Hospital, Dublin 8, Ireland.
Declan Byrne BSc Human Nutrition, MB Bch BAO, MRCPI, Dist Pharmaceutical Medicine, MSc Pharmaceutical Science
Seán Cournane Medical Physics and Bioengineering Department, St. Vincent’s University Hospital, Dublin 4.
Deirdre O’Riordan MED Directorate, St James’s Hospital, Dublin 8, Ireland.
Bernard Silke MED Directorate, St James’s Hospital, Dublin 8, Ireland.

The Problems with Risk Prediction during an Emergency Medical Admission Using Laboratory Data – Evidence from Potassium

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Conway R, Byrne D, Cournane S, O'Riordan D, Silke B. The Problems with Risk Prediction during an Emergency Medical Admission Using Laboratory Data - Evidence from Potassium. Acute Med. 2019;18(1):20-26. PMID: 32608389.

The Problems with Risk Prediction during an Emergency Medical Admission Using Laboratory Data – Evidence from Potassium

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