Few patients being assessed and treated in acute situations in hospitals have only one set of laboratory investigations undertaken. While the more esoteric and specialist investigations may be done less frequently, readily available tests in laboratory medicine such as urea and electrolytes, liver function tests, bone studies and full blood count are often requested on a daily basis, if not more often. Although this practice is often considered inappropriate and wasteful, it does give serial results on individuals: these should be used to add value in both laboratory and clinical management. Although fixed numerical decision limits based on risk, for example, have many advantages and are becoming more widely applied throughout medicine, laboratories fulfil accreditation and other requirements by reporting population-based reference intervals, sometimes partitioned according to age, gender or other important factors, with almost every test result. These remain the basis of interpretation of numerical results when no previous data are available on an individual, as in some diagnosis and screening settings. However, it is now well recognized that withinsubject biological variation (CVI) is much smaller than between-subject biological variation (CVG) for nearly all quantities assayed in laboratory medicine. As a result, traditional reference intervals have limited value in diagnosis and screening because many patients will have results that are highly unusual for them but that still lie within the reference intervals, irrespective of whether these are generated by the individual laboratory, transferred, validated or harmonized. Conventional reference intervals are of even more limited use in the assessment of serial results generated on an individual. Each individual has values that span only a part of the conventional reference interval. In consequence, individuals can have significant changes in results when these all lie within the reference interval. In addition, results can change from inside the interval to outside (and vice versa) without significance. Making better use of differences in serial laboratory results is required. In this issue, Garner et al. report an investigation on the detection of acute kidney injury (AKI) in hospital patients by comparing three of the proposed AKI definitions and a very simple delta check using serial serum creatinine results. Unsurprisingly, it was found that use of the different definitions proposed for AKI detected different populations of patients, although all definitions make use of rises in serum creatinine concentration in an individual. However, it was demonstrated that the laboratory delta check detected 98% of all the patients identified by Acute Kidney Injury Network (AKIN), Risk, Injury, Failure (RIFLE) and Waikar & Bonventre strategies combined and therefore suggested that the delta check could provide a practical way of detecting AKI patients. This work could be emulated for other quantities for which use of differences in serial results is of clinical importance. Delta check functionality is embedded in most laboratory information management systems (LIMS). Although there are a number of ways to select the delta check values, setting is usually done somewhat empirically with the aim of detecting major blunders, such as the submission for analysis of samples from different patients but which have been labelled with a single identifier, but not flagging too many cases for further time-consuming, but often inconsequential, investigation by professionals in laboratory medicine. Garner et al. selected the delta check value of an increase of 26 mmol/L in serum creatinine for the detection of AKI using the criteria set in the AKIN and Waikar & Bonventre strategies for diagnosis of Stage 1 AKI, and this simple approach did appear to be potentially clinically useful. Others have proposed similarly simple numerical criteria for interpretation of differences in serial results: recent examples include that reductions of at least 25% and 50% are considered minimal and partial responses to treatment for monoclonal proteins in serum and a change of 20% is significant for serum troponin. The question arises as to whether such criteria should be used as delta check values in the laboratory and then differences greater than the delta check values notified to users in some way so as to point out that these are of potential clinical interest. The question of communication of information on the patients identified by the delta check was not addressed by Garner et al. In addition, a perhaps more interesting question is whether there are better, more scientific, ways to set criteria for interpretation of differences in serial results and whether these criteria can then be applied as delta check values and for other purposes in laboratory medicine. Garner et al. discuss the use of reference change values (RCV) and consider that RCV could potentially provide a more efficient means of detecting AKI patients. Differences in serial results from an individual may be due to the
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Apr 28, 2016
Selcuk Matyar + 7
