Association of physiological stress markers at the emergency department to readmission and death within 90 days: a prospective observational study
Keywords:
Emergency department, chest pain, shortness of breath, copeptin, MR-proADM, MR-proANP, readmission, multimorbidity
Abstract
Background: Predicting the risk of readmission or death in patients at the emergency department (ED) is essential in identifying patients who would benefit the most from interventions. We aimed to explore the prognostic value of mid-regional proadrenomedullin (MR-proADM), mid-regional pro-atrial natriuretic peptide (MR-proANP), copeptin, and high-sensitivity troponin T (hs-TnT) to identify patients with a higher risk of readmission and death among patients presenting with chest pain (CP) and/or shortness of breath (SOB) in the ED.
Methods: This single-center prospective observational study included non-critically ill adult patients with a chief complaint of CP and/or SOB who visited the ED at Linköping University Hospital. Baseline data and blood samples were collected, and patients were followed up for 90 days after inclusion. The primary outcome was a composite of readmission and/or death from non-traumatic causes within 90 days of inclusion. Binary logistic regression was used and receiver operating characteristics (ROC) curves were constructed to determine the prognostic performance for predicting readmission and/or death within 90 days.
Results: A total of 313 patients were included and 64 (20.4%) met the primary endpoint. MR-proADM > 0.75 pmol/L (odds ratio [OR]: 2.361 [95% confidence interval [CI]: 1.031 – 5.407], P = 0.042) and multimorbidity (OR: 2.647 [95% CI: 1.282 – 5.469], P = 0.009) were significantly associated with readmission and/or death within 90 days. MR-proADM increased predictive value in the ROC analysis to age, sex, and multimorbidity (P = 0.006).
Conclusions: In non-critically ill patients with CP and/or SOB in the ED, MR-proADM and multimorbidity may be helpful for the prediction of the risk of readmission and/or death within 90 days.
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References
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2. Shebehe J, Hansson A. High hospital readmission rates for patients aged >/=65 years associated with low socioeconomic status in a Swedish region: a cross-sectional study in primary care. Scand J Prim Health Care. 2018;36:300–7. doi: 10.1080/02813432.2018.1499584
3. Health at a glance 2013: OECD indicators. OECD: Paris; 2013.
4. Farrohknia N, Castren M, Ehrenberg A, Lind L, Oredsson S, Jonsson H, et al. Emergency department triage scales and their components: a systematic review of the scientific evidence. Scand J Trauma Resusc Emerg Med. 2011;19:42. doi: 10.1186/1757-7241-19-42
5. Dean NC, Jones JP, Aronsky D, Brown S, Vines CG, Jones BE, et al. Hospital admission decision for patients with community-acquired pneumonia: variability among physicians in an emergency department. Ann Emerg Medi. 2012;59:35–41. doi: 10.1016/j.annemergmed.2011.07.032
6. Kansagara D, Englander H, Salanitro A, Kagen D, Theobald C, Freeman M, et al. Risk prediction models for hospital readmission: a systematic review. JAMA. 2011;306:1688–98. doi: 10.1001/jama.2011.1515
7. Heining L, Giesa C, Ewig S. MR-proANP, MR-proADM, and PCT in patients presenting with acute dyspnea in a medical emergency unit. Lung. 2016;194:185–91. doi: 10.1007/s00408-015-9837-0
8. Cinar O, Cevik E, Acar A, Kaya C, Ardic S, Comert B, et al. Evaluation of mid-regional pro-atrial natriuretic peptide, procalcitonin, and mid-regional pro-adrenomedullin for the diagnosis and risk stratification of dyspneic ED patients. Am J Emerg Med. 2012;30:1915–20. doi: 10.1016/j.ajem.2012.04.009
9. Schuetz P, Hausfater P, Amin D, Amin A, Haubitz S, Faessler L, et al. Biomarkers from distinct biological pathways improve early risk stratification in medical emergency patients: the multinational, prospective, observational TRIAGE study. Crit Care. 2015;19:377. doi: 10.1186/s13054-015-1098-z
10. Schönauer R, Els-Heindl S, Beck-Sickinger AG. Adrenomedullin – new perspectives of a potent peptide hormone. J Pept Sci. 2017;23:472–85. doi: 10.1002/psc.2953
11. Idzikowska K, Zielińska M. Midregional pro-atrial natriuretic peptide, an important member of the natriuretic peptide family: potential role in diagnosis and prognosis of cardiovascular disease. J Int Med Res. 2018;46:3017–29. doi: 10.1177/0300060518786907
12. Christ-Crain M. Vasopressin and copeptin in health and disease. Rev Endocr Metab Disord. 2019;20:283–94. doi: 10.1007/s11154-019-09509-9
13. Khan SQ, O’Brien RJ, Struck J, Quinn P, Morgenthaler N, Squire I, et al. Prognostic value of midregional pro-adrenomedullin in patients with acute myocardial infarction: the LAMP (Leicester Acute Myocardial Infarction Peptide) study. J Am Coll Cardiol. 2007;49:1525–32. doi: 10.1016/j.jacc.2006.12.038
14. Peacock WF. Novel biomarkers in acute heart failure: MR-pro-adrenomedullin. Clin Chem Lab Med. 2014;52:1433–5. doi: 10.1515/cclm-2014-0222
15. Valenzuela-Sánchez F, Valenzuela-Méndez B, Rodríguez-Gutiérrez JF, Estella-García Á, González-García M. New role of biomarkers: mid-regional pro-adrenomedullin, the biomarker of organ failure. Ann Transl Med. 2016;4:329. doi: 10.21037/atm.2016.08.65
16. Katan M, Christ-Crain M. The stress hormone copeptin: a new prognostic biomarker in acute illness. Swiss Med Wkly. 2010;140:w13101. doi: 10.4414/smw.2010.13101
17. Koch A, Yagmur E, Hoss A, Buendgens L, Herbers U, Weiskirchen R, et al. Clinical relevance of copeptin plasma levels as a biomarker of disease severity and mortality in critically ill patients. J Clin Lab Anal. 2018;32:e22614. doi: 10.1002/jcla.22614
18. Tzikas S, Keller T, Ojeda FM, Zeller T, Wild PS, Lubos E, et al. MR-proANP and MR-proADM for risk stratification of patients with acute chest pain. Heart. 2013;99:388–95. doi: 10.1136/heartjnl-2012-302956
19. Davidson LT, Gauffin E, Henanger P, Wajda M, Wilhelms D, Ekman B, et al. Admission of patients with chest pain and/or breathlessness from the emergency department in relation to risk assessment and copeptin levels – an observational study. Ups J Med Sci. 2022;127. doi: 10.48101/ujms.127.8941
20. Socialstyrelsen. Så tycker de äldre om äldreomsorgen 2017. En rikstäckande undersökning av äldres uppfattning om kvaliteten i hemtjänst och särskilt boende. 2018. Available from: www.socialstyrelsen.se [cited December 2022].
21. Maisel A, Mueller C, Nowak R, Peacock WF, Landsberg JW, Ponikowski P, et al. Mid-region pro-hormone markers for diagnosis and prognosis in acute dyspnea: results from the BACH (Biomarkers in Acute Heart Failure) trial. J Am Coll Cardiol. 2010;55:2062–76. doi: 10.1016/j.jacc.2010.02.025
22. Kutz A, Hausfater P, Amin D, Amin A, Canavaggio P, Sauvin G, et al. The TRIAGE-ProADM score for an early risk stratification of medical patients in the emergency department – development based on a multi-national, prospective, observational study. PLoS One. 2016;11:e0168076. doi: 10.1371/journal.pone.0168076
23. Hausfater P, Claessens YE, Martinage A, Joly LM, Lardeur JY, Der Sahakian G, et al. Prognostic value of PCT, copeptin, MR-proADM, MR-proANP and CT-proET-1 for severe acute dyspnea in the emergency department: the BIODINER study. Biomarkers. 2017;22:28–34. doi: 10.1080/1354750x.2016.1201541
24. Stalenhoef JE, van Nieuwkoop C, Wilson DC, van der Starre WE, Delfos NM, Leyten EMS, et al. Biomarker guided triage can reduce hospitalization rate in community acquired febrile urinary tract infection. J Infect. 2018;77:18–24. doi: 10.1016/j.jinf.2018.05.007
25. Saeed K, Wilson DC, Bloos F, Schuetz P, van der Does Y, Melander O, et al. The early identification of disease progression in patients with suspected infection presenting to the emergency department: a multi-centre derivation and validation study. Crit Care (London, England). 2019;23:40. doi: 10.1186/s13054-019-2329-5
26. Bahrmann P, Christ M, Hofner B, Bahrmann A, Achenbach S, Sieber CC, et al. Prognostic value of different biomarkers for cardiovascular death in unselected older patients in the emergency department. Eur Heart J Acute Cardiovasc Care. 2016;5:568–78. doi: 10.1177/2048872615612455
27. Marengoni A, Angleman S, Melis R, Mangialasche F, Karp A, Garmen A, et al. Aging with multimorbidity: a systematic review of the literature. Ageing Res Rev. 2011;10:430–9. doi: 10.1016/j.arr.2011.03.003
28. van den Akker M, Buntinx F, Roos S, Knottnerus JA. Problems in determining occurrence rates of multimorbidity. J Clin Epidemiol. 2001;54:675–9. doi: 10.1016/s0895-4356(00)00358-9
29. Salive ME. Multimorbidity in older adults. Epidemiol Rev. 2013;35:75–83. doi: 10.1093/epirev/mxs009
30. Yilman M, Erenler AK, Baydin A. Copeptin: a diagnostic factor for critical patients. Eur Rev Med Pharmacol Sci. 2015;19:3030–6.
31. Searle J, Slagman A, Stockburger M, Vollert JO, Muller C, Muller R, et al. Use of copeptin in emergency patients with cardiac chief complaints. Eur Heart J Acute Cardiovasc Care. 2015;4:393–402. doi: 10.1177/2048872614554197
32. Carlsson AC, Bandstein N, Roos A, Hammarsten O, Holzmann MJ. High-sensitivity cardiac troponin T levels in the emergency department in patients with chest pain but no myocardial infarction. Int J Cardiol. 2017;228:253–9. doi: 10.1016/j.ijcard.2016.11.087
33. Roos A, Sartipy U, Ljung R, Holzmann MJ. Relation of chronic myocardial injury and non-ST-segment elevation myocardial infarction to mortality. Am J Cardiol. 2018;122:1989–95. doi: 10.1016/j.amjcard.2018.09.006
34. Polyakova EA, Mikhaylov EN. The prognostic role of high-sensitivity C-reactive protein in patients with acute myocardial infarction. J Geriatr Cardiol. 2020;17:379–83. doi: 10.11909/j.issn.1671-5411.2020.07.007
35. Muzafarova T, Motovska Z. Laboratory predictors of prognosis in cardiogenic shock complicating acute myocardial infarction. Biomedicines. 2022;10:1328. doi: 10.3390/biomedicines10061328
36. Lucci C, Cosentino N, Genovese S, Campodonico J, Milazzo V, De Metrio M, et al. Prognostic impact of admission high-sensitivity C-reactive protein in acute myocardial infarction patients with and without diabetes mellitus. Cardiovasc Diabetol. 2020;19:183. doi: 10.1186/s12933-020-01157-7
37. Jing Z, Chun C, Ning S, Hong Z, Bei H, Wan-Zhen Y. Systemic inflammatory marker CRP was better predictor of readmission for AECOPD than sputum inflammatory markers. Arch Bronconeumol. 2016;52:138–44. doi: 10.1016/j.arbres.2015.01.011
38. Hallgren J, Aslan AKD. Risk factors for hospital readmission among Swedish older adults. Eur Geriatr Med. 2018;9:603–11. doi: 10.1007/s41999-018-0101-z
39. Howie-Esquivel J, Dracup K. Effect of gender, ethnicity, pulmonary disease, and symptom stability on rehospitalization in patients with heart failure. Am J Cardiol. 2007;100:1139–44. doi: 10.1016/j.amjcard.2007.04.061
40. Bellou V, Belbasis L, Konstantinidis AK, Tzoulaki I, Evangelou E. Prognostic models for outcome prediction in patients with chronic obstructive pulmonary disease: systematic review and critical appraisal. BMJ (Clinical research ed). 2019;367:l5358. doi: 10.1136/bmj.l5358
41. Schwab C, Hindlet P, Sabatier B, Fernandez C, Korb-Savoldelli V. Risk scores identifying elderly inpatients at risk of 30-day unplanned readmission and accident and emergency department visit: a systematic review. BMJ Open. 2019;9:e028302. doi: 10.1136/bmjopen-2018-028302
42. Smith LN, Makam AN, Darden D, Mayo H, Das SR, Halm EA, et al. Acute myocardial infarction readmission risk prediction models: a systematic review of model performance. Circ Cardiovasc Qual Outcomes. 2018;11:e003885. doi: 10.1161/circoutcomes.117.003885
Published
2023-05-03
How to Cite
Davidson L. T., Schilling U. M., Arnqvist H. J., Nystrom F. H., & Chisalita S. I. (2023). Association of physiological stress markers at the emergency department to readmission and death within 90 days: a prospective observational study. Upsala Journal of Medical Sciences, 128(1). https://doi.org/10.48101/ujms.v128.9300
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