Laboratory risk factors for hospital mortality
Sir,The work by Asadollahi et al.1 is interesting, but far from novel. They state that there has been little robust research into early predictive factors of hospital mortality. However, they fail to acknowledge the considerable body of work already addressing this problem, much of which incorporates laboratory data to some extent.2–10 They also suggest that risk assessment on the basis of laboratory investigations has been concentrated on specific diagnostic categories or high-risk groups of patients, and that there are no specific mortality prediction systems for general acute admissions.1 In addition, they claim that the findings of their research raise the possibility of developing a laboratory-based predictive scoring system to estimate risk of hospital mortality.
It is surprising that Asadollahi's literature search did not identify any of the above papers,2–10 but specifically a prospective study published in 2005.10 This paper presented results for nearly 10 000 unselected medical admissions, was not limited to specific diagnostic categories or risk groups, and offered a suitable algorithm for calculating risk of in-hospital death.10 The study identified that the risk of hospital death could be predicted using routinely available data very early on after hospital admission, and raised the possibility that the surveillance and treatment of patients might be categorized by risk assessment means.
Portsmouth Hospitals NHS Trust & University of Portsmouth
Portsmouth
UK
email: david.prytherch{at}googlemail.com
References
1. Asadollahi K, Hastings IM, Beeching NJ, Gill GV. Laboratory risk factors for hospital mortality in acutely admitted patients. Q J Med (2007) 100:501–7.[Web of Science]
2. Vroonhof K, van Solinge WW, Rovers MM, Huisman A. Differences in mortality on the basis of complete blood count in an unselected population at the emergency department. Lab Hematol (2006) 12:134–8.[CrossRef][Medline]
3. Vroonhof K, van Solinge WW, Rovers MM, Huisman A. Differences in mortality on the basis of laboratory parameters in an unselected population at the Emergency Department. Clin Chem Lab Med (2005) 43:536–41.[CrossRef][Web of Science][Medline]
4. 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) 94:735–41.
5. Khuri SF, Daley J, Henderson W, et al. The Department of Veterans Affairs’ NSQIP: the first national, validated, outcome-based, risk-adjusted, and peer-controlled program for the measurement and enhancement of the quality of surgical care. National VA Surgical Quality Improvement Program. Ann Surg (1998) 228:491–507.[CrossRef][Web of Science][Medline]
6. Best WR, Khuri SF, Phelan M, et al. Identifying patient preoperative risk factors and postoperative adverse events in administrative databases: results from the Department of Veterans Affairs National Surgical Quality Improvement Program. J Am Coll Surg (2002) 194:257–66.[CrossRef][Web of Science][Medline]
7. Copeland GP, Jones D, Walters M. POSSUM: a scoring system for surgical audit. Br J Surg (1991) 78:355–60.[Medline]
8. Prytherch DR, Whiteley MS, Higgins B, Weaver PC, Prout WG, Powell SJ. POSSUM and P-POSSUM for Predicting Mortality. Br J Surg (1998) 85:1217–20.[CrossRef][Web of Science][Medline]
9. Prytherch DR, Sirl JS, Weaver PC, Schmidt P, Higgins B, Sutton GL. Towards a national clinical minimum dataset for general surgery. Br J Surg (2003) 90:1300–5.[CrossRef][Web of Science][Medline]
10. 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) 66:203–7.[CrossRef][Web of Science][Medline]
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