The rising incidence of Acute Kidney Injury (AKI) comes at a price. Patients tend to survive intensive care (ICU) but will be discharged with various degrees of chronic kidney disease (CKD), placing an increasing strain on the healthcare system. At present, the cost to the NHS is estimated to be between £434 and £620 million (€490-700 mil), which is more than the costs associated with breast cancer, or lung and skin cancer combined. However, this increased cost and strain could be unnecessary, as research has shown that 30% of the reported 100,000 deaths in the UK could have been prevented with the right care and treatment.^1,2 These unfavourable statistics are the result of late detection of AKI, as to date, a superior method of detection has not been found.
Recent research has supported the use of Heart Type Fatty Acid Binding Protein (H-FABP), a traditional cardiac biomarker, and its potential utility as a clinical diagnostic biomarker for cardiac surgery-associated AKI. Cardiac surgery associated acute kidney injury (CSA-AKI) is a serious complication affecting approximately 33% – 94% of patients undergoing heart surgery, it is also associated with a high incidence of mortality and morbidity.³
A number of studies have been conducted focusing on measuring the levels of H-FABP before and after surgery. It was found that patients who developed AKI had higher levels of H-FABP both pre and postoperatively compared to patients who did not have AKI. Figure 1 shows the perioperative H-FABP levels based on AKI status. Day 1 represents 0 – 6 hours after surgery, Day 2 represents 24 – 48 hours after surgery and Day 3 represents 48 – 72 hours after surgery. As illustrated by the box plots, patients with severe AKI had the highest levels of H-FABP across all 3 days compared to those with any and no AKI.⁴
Researchers found that post-operative (Day 1) H-FABP levels in patients with severe AKI increased by 13-fold and an increase of 8 -fold was observed for the same time point in patients who experienced any AKI. In day 2 and 3, H-FABP levels began to decline, however, a slower rate of decline was observed in patients who experienced AKI.⁴
In the follow-up of this study, 10.8% of the patient cohort died which was found to have associations with preoperative levels. Patients with elevated preoperative log (H-FABP) were significantly more likely to die compared to patients with normal or low levels. They concluded that H-FABP explained <10% of the variability in known kidney injury biomarkers and that it is possible that H-FABP is capturing a different aspect of the pathophysiology of AKI when compared to traditional kidney biomarkers.⁴
Further studies conducted looked at the prognostic value of H-FABP levels collected on admission and found that a level of ≥ 15.7 ng/ml and the presence of AKI were independent predictors of 180-day mortality. Figure 2 is a Kaplan-Meier survival curve which shows that prognosis, including all-cause death, had a significantly poorer outcome for mortality in the high serum H-FABP with AKI group.⁴
Patients with H-FABP levels of less than 15.6 ng/ml and no AKI had nearly a 100% chance of event free survival over the 180 days. In comparison, patients with levels greater than 15.7 ng/ml, with AKI had a steady decrease in event free survival over the 180 days levelling out at just above 40%.⁴
Randox Laboratories are manufacturers of an automated biochemistry H-FABP assay exhibiting clinical utility for the early risk assessment of AKI including cardiac surgery-associated AKI. Applications detailing instrument-specific settings are available for a wide range of biochemistry analysers.

References
1. Kidney Care UK. [Online] [Cited: February 15, 2019.] https://www.kidneycareuk.org/news-and-campaigns/facts-and-stats/.
2. Centers for Disease Control and Prevention. [Online] March 16, 2018. [Cited: February 22, 2019.] https://www.cdc.gov/mmwr/volumes/67/wr/mm6710a2.htm.
3. Prediction and Prevention of Acute Kidney Injury after Cardiac Surgery. Shin, Su, et al. s.l. : Hindawi, 2016.
4. Perioperative heart-type fatty acid binding protein is associated with acute kidney injury after cardiac surgery. Schaub, J, et al. 3, s.l. : NCBI, 2015, Vol. 88.

The presence of hemoglobin (hemolysis), bilirubin (icterus) and lipids (lipemia) in serum can affect the measurement and reporting of many clinical chemistry laboratory test results. This is not only in the validity of the test results themselves, but also whether a result is, or should be, reported. Quality assurance of serum indices is not as rigorous as for other clinical chemistry assays. This article highlights the variation in practice which is ultimately affecting the patient and their care pathway.

by Dr Rachel Marrington and Finlay MacKenzie

Introduction
There are a number of interferences that affect the analytical accuracy of clinical chemistry assays. These can be both endogenous and exogenous and can cause falsely elevated or falsely reduced results that can have serious clinical consequences. The most widely recognized endogenous interference is hemolysis. Hemolysis occurs when red blood cells are ruptured either in vivo, or in vitro, and their contents are released into blood plasma. There can be increased values [potassium, aspartate aminotransferase (AST)] and decreased values (sodium) because of the concentration gradient between the cells and plasma. Hemoglobin and other intracellular components can interfere with chemical reactions, and also hemoglobin absorbs light at 415 nm and, therefore, can cause an apparent increase in concentration for assays using this wavelength of absorbance [1]. Icterus is caused by elevated bilirubin present in the serum resulting in a yellow coloured serum, and is most frequently caused from liver disease. Lipemia is due to the presence of a high concentration of lipids in the blood, which cause light scattering in spectrophotometric assays.

Although most laboratory staff are fully aware of what the measurement of hemolysis, icterus and lipemia (HIL) indices is meant to achieve, there is a bit of a ‘black hole’ in how their instruments have been set up. Most automated clinical chemistry analysers automatically measure the presence of the serum indices of HIL by absorbance alone and report a number with no units to the user. The manufacturer’s engineers are usually the people who set the analysers up but unfortunately there appears to be a variety of ways to do this, and because there is no ‘correct’ way, differences have inadvertently crept in. Manufacturers use different paired wavelengths for the determination of the serum indices, and have different methods of reporting – numerical (e.g. 1, 2, 3) and category/non-numerical (e.g. +++) [2]. Automatic algorithms, which differ between manufacturer, will either allow, or not allow an individual result to be reported.

A typical large laboratory in the UK analyses approximately 6000 specimens for serum indices daily. Although internal quality control (IQC) is carried out on all clinical chemistry ‘real’ assays prior to results being released, it is not routine for laboratories to apply IQC procedures to serum indices. Laboratories accredited to ISO15189:2012 are accredited at the reportable test level, and as serum indices are not reported, these are not always covered within the scope of accreditation. There is, therefore, a large scope for errors within a laboratory’s serum indices to impact on analytical results.

EQA scheme design
Birmingham Quality has established an external quality assessment (EQA) scheme for serum indices – UK NEQAS for Serum Indices. The scheme not only looks at hemolysis, icterus and lipemia as individual analytes but also systematically looks at the impact that these serum indices have on particular analytes, which changes from month to month, and is called ‘Analyte X’. Laboratories are asked whether they would report the result for the measured analyte based on the serum indices. This scheme is available worldwide but the majority of participants are UK based.

The innovative report style from Birmingham Quality allows two data presentations from the same analyte – standard report format for numerical (index) data, and pie charts for the category data (Fig. 1a and 1b, respectively). Method mean concentrations are used as the target value for numerical results and the consensus category for individual manufacturers.

HIL performance
By their very nature, indices have no real ‘unit’ associated with them. That said, they do have a tenuous linkage with concentrations of hemoglobin, bilirubin and triglyceride. The usual units for these analytes in the UK are g/L, µmol/L and mmol/L and many instruments are indeed set up in these units. Similarly, many are set up in mg/dL, which though perfectly common in the US and the non-UK, non-Scandinavian, European countries, are never used in the UK but yet have representation here. Now although this doesn’t particularly matter to an individual laboratory, we have the unintended situation of two machines in the same laboratory having been set up in different units.

Hemolysis
Semi-quantitative hemolysis results are correlated to an approximate hemoglobin concentration, and, as such, the units are g/L, mg/dL or µmol/L.

Hemolysed specimens are prepared endogenously by allowing serum to remain on red blood cells for a period of time, or by the addition of exogenous material. There is generally good agreement within a method and the between method imprecision [percent coefficient of variation (%CV)] is fairly consistent across the concentration range 0.5–10 g/L at approximately 5 % for Abbott and Roche, and approximately 12 % for Siemens and Ortho J&J.

Icterus
Semi-quantitative icterus results are correlated to an approximate bilirubin concentration, and, as such, the units are µmol/L or mg/dL.

Icteric specimens are prepared as either endogenous, or by the addition of exogenous material. The between method imprecision varies between manufacturer and is likely to reflect the differences in measurement approach. Differences between methods have been observed. For example, an unspiked sample was distributed which had endogenous elevated triglycerides (specimen 111C in Fig. 1). Two methods – Beckman Synchron and Beckman AU Olympus – have identified a significant amount of icterus present, whereas other major methods haven’t. Analytically this is because of secondary interference due to overlapped absorbance not being corrected. Clinically this means that there is the potential that results would not be reported because of an incorrect icterus result being reported on a lipemic sample, when analytically they may be valid for icterus.

Lipemia
Lipemia results are roughly correlated to triglyceride concentration and in most cases are calibrated/anchored to intralipid concentration, and reported as g/L, mg/dL or mmol/L. Many manufacturers use more than one ‘unit’ for serum indices. For hemolysis and icterus the numerical results are obviously different; however, for lipemia there is only a factor of 1.13 between g/L and mmol/L. As serum indices are usually reported without a unit there is the potential for error if the units that are measured are not the same as when interpreted.

Lipemia shows higher between method imprecision %CVs on all methods. Specimens are either distributed with endogenously elevated lipids, or intralipid is added. Both cases show similarly high %CV, which is likely to be due to differences in the light scattering of turbid samples. However, there is also the possibility that although participants are advised to mix EQA material prior to analysis, they may not always. This problem is not unique to EQA specimens, as a delay in analysis of separated clinical specimens, or ‘add-on’ tests means that lipemic material could have separated before being sampled.

Analyte X
Analyte X is a unique and sophisticated concept where the laboratory is challenged for a specified different analyte every month. The participant reports the value obtained for this variable analyte and also an interpretation of whether they would report that result for analyte X based on the serum indices they obtained. This allows an assessment of the impact of serum indices on the numerical result of the analyte, and the participant can directly compare different methods. The interpretative element demonstrates for the first time the variation in clinical practice.

Significant differences in practice for the interpretation of serum indices both within and between manufacturers have been observed. For example, three specimens of the same base material were distributed with varying degrees of hemolysis for the analysis of total protein (Fig. 2). Specimen 106A was slightly hemolysed (overall consensus mean 0.7 g/L) and specimen 106C was grossly hemolysed (overall consensus mean 4.7 g/L). Beckman AU, Roche and Siemens did not show any significant change in the total protein result reported for all three specimens; however, Abbott and Ortho J&J both showed an increase in total protein as the amount of hemolysis increased. All methods showed a mixture of whether a laboratory would or would not report the total protein result, even with the grossly hemolysed specimen (Fig. 2b). This shows differences in algorithms being used even within manufacturers. Approximately 20 % of Abbott participants and approximately 25% of Ortho J&J participants would report an elevated total protein result in the presence of gross hemolysis. The consequences of this erroneously high total protein result could lead to additional testing. This would not only cause the clinician to unnecessarily waste time, but could also cause concern for the patient.

Discussion
With the increase of tracked automation, separated specimens are no longer ‘handled’ by the operator, and, therefore, no visual inspection takes place. The laboratory is entirely reliant on the use of algorithms based on absorbance of the specimen to decide whether individual analytical results should be reported or not. Serum indices are usually only measured once. This may be soon after a specimen has been centrifuged or sometime later. It is known that lipemic specimens ‘separate’ over time; therefore, any delay in analysis, or the addition of any subsequent ‘add-on’ tests, may result in the sampling of an incorrect portion of serum. Serum indices are not usually reported to a clinician, and may be presented on the analyser only as a number with no units. Therefore, there is a reliance by the laboratory on the manufacturer that the numbers correlate with the correct cut-off values for particular analytes. Data from the UK NEQAS for Serum Indices Scheme has shown variation within a manufacturer on the reporting of analytes based on the HIL result; therefore, either laboratories are changing cut-offs, or manufacturers are not setting laboratories up the same way. Manufacturers extensively test their assays for interferences prior to being released, and inform laboratories of this in their kit inserts. The laboratory is responsible for verifying that these levels of interference are suitable for their requirements.

Hemolysed, icteric or lipemic specimens either result in patients not receiving results, and, therefore, needing to be re-bled, or incorrect results being reported for specific analytes. Either way, the patient’s care is affected. Hemolysis is considered one of the most common interferents and the incidence with which a laboratory receives hemolysed specimens varies widely and is dependent on how specimens are collected [2]. A study of the incidence of hemolysed samples in an Emergency Medicine department in the UK concluded that 10.7 % of specimens were hemolysed over the seven-day sampling period. [3] Overall incidence data for specimens/tests rejected because of hemolysis, icterus or lipemia is not available; however, the impact on the laboratory, clinician and patient is likely to be significant.

Conclusion
The UK NEQAS for Serum Indices Scheme has shown that there is generally good analytical performance within individual manufacturers for hemolysis and icterus. Lipemia shows more variation in results. Variations are observed between manufacturers and in the application of the serum index to interpretation of a clinical chemistry result.

Automation has allowed the clinical chemistry analysis a more rapid throughput; however, human contact with specimens has now been reduced, which has increased reliance on computer algorithms. The UK NEQAS for Serum Indices Scheme has, and continues to show, variation in practice which consequently affects patient care both in terms of repeat testing and the validity of results.

References
1. Thomas L. Haemolysis as influence and interference factor. eJIFCC 2002; 13(4): http://www.ifcc.org/media/477061/ejifcc2002vol13no4pp095-098.pdf.
2. Farrell CJL, Carter AC. Serum indices: managing assay interference. Ann Clin Biochem 2016; 53: 527–538.
3. Berg JE, Ahee P, Berg JD. Variation in phlebotomy techniques in emergency medicine and the incidence of haemolysed samples. Ann Clin Biochem 2011; 48: 562–565.

The authors
Rachel Marrington* PhD, FRCPath and Finlay MacKenzie MSc (Director and consultant clinical scientist)
Birmingham Quality (UK NEQAS), Queen Elizabeth Hospital Birmingham, Birmingham, UK

*Corresponding author
E-mail: rachel.marrington@uhb.nhs.uk

Pre-eclampsia is a condition that affects approximately 2–8% pregnancies worldwide and, although the cause is not really understood, is thought to be due to poor function of the placenta. Early signs that create suspicion of pre-eclampsia in the mother typically include hypertension, proteinuria and edema (particularly of the pitting type) of the ankles. Symptoms of more severe pre-eclampsia can include pulmonary edema, headaches, visual disturbance, epigastric/right upper quadrant abdominal pain and vomiting, before the development of seizures (eclampsia). Symptoms in the fetus include fetal growth restriction.
Left untreated, pre-eclampsia is associated with a high risk of adverse outcome for both the mother and fetus. The only treatment is delivery of the baby and the placenta. Diagnosis of pre-eclampsia is challenging because of the vagueness of the symptoms, but becomes suspected with new onset hypertension after 20 weeks’ gestation. The management of women presenting with pre-eclampsia from 37 weeks of gestation is through planned delivery. However, the management of patients with suspected pre-eclampsia earlier in pregnancy involves careful surveillance, and therefore increased use of health resources, balancing the risk to maternal health against the risk of preterm delivery for the fetus. Angiogenic factors, such as vascular endothelial growth factor (VEGF), placental growth factor (PlGF) and soluble fms-like tyrosine kinase-1 (sFlt-1) have shown potential for the diagnosis of pre-eclampsia in cohort studies. Recently, however, the results of study using a stepped-wedge cluster-randomized controlled trial measuring PlGF levels alongside the use of a clinical management algorithm have been published in The Lancet (Duhig KE, et al. Lancet 2019; pii: S0140-6736(18)33212-4). The study involved more than 1000 women with suspected pre-eclampsia and the women were divided into two groups – where the PlGF levels were either made known (revealed PlGF) or not (concealed PlGF). The results showed that in the revealed PlGF group, time to diagnosis fell from 4.1 to 1.9 days compared with the concealed PlGF group and that serious maternal complications fell from 5.3% (24 of 447 women) to 4% (22 of 573 women). The findings from the study, have resulted in NHS England deciding to make the test more widely available, allowing more timely patient management and more appropriate use of resources in high-risk women, so helping to avoid life-threatening complications for both mother and baby as well as providing reassurance when
pre-eclampsia is ruled out.

Standard drug testing is regularly carried out using urine, blood or oral fluid. However, fingerprints present a good alternative, as the sample collection is non-invasive, rapid and safe. Herein, we describe the application of two different testing methods for the detection of cocaine in fingerprint samples.

by Dr Catia Costa, Dr Mahado Ismail and Dr Melanie J. Bailey

Drug abuse in the United Kingdom is on the rise and it is a cause for concern, with widespread financial and social implications [1, 2]. The ever-growing drug and alcohol culture in the UK has led to the implementation of workplace drug testing in many industries, especially those in high-risk operational environments. Consequently, there has been a surge in the demand for drug-screening suppliers to develop faster and more reliable testing. This demand is set to increase the market value of drug and alcohol testing in the UK from £167 million to £231 million by 2019 [3].

Conventionally, drug testing is carried out using biological matrices such as blood, urine and, more recently, oral fluid. These matrices and methods of analysis, although established, present a few problems relating to sample collection and transportation. The collection of blood requires medically trained personnel and sample collection is considered invasive, whereas urine carries privacy concerns. Oral fluid is an alternative matrix used for non-invasive drug testing, although sample collection can be time-consuming. All these three matrices are also biohazardous, making sample storage and transportation a potential issue. The potential use of fingerprints for drug testing has become the subject of many recent publications. Fingerprint samples present a good alternative for drug testing as collection is non-invasive and rapid, and there are no known biohazards associated with the sample. Additionally, the fingerprint pattern can be used for donor identification.

Chemical analysis of fingerprints
The chemical information embedded in a fingerprint sample has been reviewed by many, and several publications have explored the detection of substances such as cocaine [4–6], heroin [7], methadone [8], lorazepam [9], methamphetamines [10], caffeine [11] and cough medicine [12] in fingerprints after administration of the substances. These reports are predominantly based on liquid chromatography-mass spectrometry (LC-MS), which is very well established in the field of toxicology for its quantitative potential as well as its sensitivity and reliability. New advances in the field of mass spectrometry saw the rise of ambient ionization mass spectrometry techniques that allow the sample to be analysed in its native state, under ambient conditions. Examples include desorption electrospray ionization (DESI), liquid extraction surface analysis (LESA) and paper spray, which have been applied to the detection of cocaine and metabolites in fingerprint samples [4–6].

Most of these reports in the literature have looked at fingerprint samples collected after administration of the substances. However, no research has investigated the significance of the detection of these substances compared to a large background population of non-drug users. This is of particular importance as a positive test result may be the outcome of contamination by contact with contaminated surfaces or handling the parent drug rather than ingestion. This directly highlights the need for a sampling strategy that removes any contact residue while providing enough fingerprint material for the analysis.

Detection of cocaine in fingerprints
The detection of cocaine in fingerprints has been studied and reported by Ismail et al. [7]. This study looked at fingerprints collected from the background population (i.e. non-drug users) and from patients at a drug rehabilitation clinic. Both sets of samples were collected as presented and after handwashing, followed by wearing nitrile gloves for 10 minutes. Fingerprint results were supported by oral fluid analysis and patient testimony. Analysis of samples collected from patients (n=13) at the rehabilitation clinic yielded a 100% detection rate for cocaine for samples collected as presented and after handwashing. However, the detection of the cocaine metabolite, benzoylecgonine (BZE), decreased from 94% from samples collected as presented, to 87% for samples collected after handwashing. To evaluate the significance of the results above, fingerprint samples collected from the background population were analysed to investigate the prevalence of these substances in non-drug users. Samples collected as presented (n=99 samples) returned a 13% and 5% detection rate for cocaine and BZE, respectively. After handwashing, cocaine was only detected in 1% of the samples analysed (n=100) and no BZE was present. These findings suggest that cocaine can be detected in the background population owing to environmental exposure (e.g. contact with bank notes). However, after using a handwashing procedure, cocaine and benzoylecgonine were not prevalent. Collection of fingerprint samples after a hand-cleaning procedure is therefore advantageous to reduce potential false-positive rates that can be observed from environmental exposure.

As previously mentioned, the use of chromatographic methods is well established in the field of toxicology. However, such methods often rely on extensive sample preparation and analysis. To overcome this issue we have developed paper spray-mass spectrometry (PS-MS) for the detection of cocaine in under 4 minutes from fingerprints collected from patients seeking treatment at a rehabilitation centre [5]. For this method fingerprints are collected on a triangular piece of paper, which is in turn placed on the paper spray source for analysis. An internal standard, solvent and voltage are applied to the paper, resulting in the extraction and ionization of the fingerprint residues before detection on the mass spectrometer (Fig. 1). The method was evaluated with 239 fingerprint samples collected from drug users at the National Health Service (NHS)  rehabilitation clinics and from the background population. A positive result was based on the detection of cocaine or one of its two main metabolites, BZE and ecgonine methyl ester (EME). A 99% true-positive rate was achieved on the samples collected from patients at drug rehabilitation centres, which was supported by standard saliva drug testing and patient testimony. Analysis of samples collected from the general population yielded a 2.5% false-positive rate. This follows from the work by Ismail et al. [7] described above, where in the absence of a hand-cleaning procedure cocaine was detected in the background population. Both studies highlight the need for a well-defined sample collection procedure to eliminate false-positive results while maintaining true-positives.

This method has since its publication been shortened to 30 seconds and it has also been applied to the detection of heroin, morphine, codeine, 6-AM and explosive materials. This highlights the potential for the technique to be on a par with current testing methods that target a wide range of substances.

Fingerprint visualization
Another advantage of using fingerprints for drug testing is the possibility to integrate a fingerprint visualization step for donor identification. This would be of particular benefit for preventing cheating and also in cases of disputed results where one would be able to prove that the results were derived from the correct person. Silver nitrate was used to visualize fingerprint samples collected from drug users by treating the substrate before sample collection. Upon collection, samples were exposed to ultraviolet light to bring out the fingerprint pattern (Fig. 2). Analysis of fingerprint samples collected from drug users after silver nitrate development yielded a 100% detection rate for cocaine, showing great potential for this development step to be included in the fingerprint testing routine.

The future: treatment adherence monitoring
Treatment non-adherence is a well-known problem in the NHS and it is estimated that it can cost over £500 million each year [13]. Thus, the establishment of an adherence monitoring tool could result in substantial savings for the NHS. Fingerprint testing offers the opportunity for remote testing where the samples can be collected by the patient at home and sent to the laboratory for analysis. In cases of non-adherence, medical professionals may intervene and ensure the patient is receiving adequate treatment. This is of particular interest for conditions known to have poor adherence rates such as diabetes, cardiovascular diseases and mental health disorders [14] or for highly infectious diseases such as tuberculosis.

References
1. Barber S, Harker R, Pratt A. Human and financial costs of drug addiction. House of Commons Library 2017.
2. Health matters: preventing drug misuse deaths (GOV.CO.UK2017). Public Health England 2017 (https: //www.gov.uk/government/publications/health-matters-preventing-drug-misuse-deaths/health-matters-preventing-drug-misuse-deaths).
3. Eurofins Workplace Drug Testing launches new holistic ‘wrap around service’ to assist UK plc. Eurofins 2018 (https: //www.eurofins.co.uk/forensic-services/press-releases/uk-growing-drug-culture/).
4. Bailey MJ, Bradshaw R, Francese S, Salter TL, Costa C, Ismail M, Webb RP, Bosman I, Wolff K, de Puit M. Rapid detection of cocaine, benzoylecgonine and methylecgonine in fingerprints using surface mass spectrometry. Analyst 2015; 140(18): 6254–629.
5. Costa C, Webb R, Palitsin V, Ismail M, de Puit M, Atkinson S, Bailey MJ. Rapid, secure drug testing using fingerprint development and paper spray mass spectrometry. Clin Chem 2017; 63(11): 1745–17525.
6. Bailey MJ, Randall EC, Costa C, Salter TL, Race AM, de Puit M, Koeberg M, Baumert M, Bunch J. Analysis of urine, oral fluid and fingerprints by liquid extraction surface analysis coupled to high resolution MS and MS/MS – opportunities for forensic and biomedical science. Anal Methods 2016; 8(16): 3373–3382.
7. Ismail M, Stevenson D, Costa C, Webb R, de Puit M, Bailey M. Noninvasive detection of cocaine and heroin use with single fingerprints: determination of an environmental cutoff. Clin Chem 2018; 64(6): 909–917.
8. Jacob S, Jickells S, Wolff K, Smith N. Drug testing by chemical analysis of fingerprint deposits from methadone-maintained opioid dependent patients using UPLC-MS/MS. Drug Metab Lett 2008; 2(4): 245–247.
9. Goucher E, Kicman A, Smith N, Jickells S. The detection and quantification of lorazepam and its 3-O-glucuronide in fingerprint deposits by LC-MS/MS. J Sep Sci 2009; 32(13): 2266–2272.
10. Zhang T, Chen X, Yang R, Xu Y. Detection of methamphetamine and its main metabolite in fingermarks by liquid chromatography-mass spectrometry. Forensic Sci Int 2015; 248: 10–14.
11. Kuwayama K, Tsujikawa K, Miyaguchi H, Kanamori T, Iwata YT, Inoue H. Time-course measurements of caffeine and its metabolites extracted from fingertips after coffee intake: a preliminary study for the detection of drugs from fingerprints. Anal Bioanal Chem 2013; 405(12): 3945–3952.
12. Kuwayama K, Yamamuro T, Tsujikawa K, Miyaguchi H, Kanamori T, Iwata YT, Inoue H. Time-course measurements of drugs and metabolites transferred from fingertips after drug administration: usefulness of fingerprints for drug testing. Forensic Toxicol 2014: 32(2): 235–242.
13. Trueman P, Taylor D, Lowson K, Bligh A, Meszaros A, Wright D, Glanville J, Newbould J, Bury M, et al. Evaluation of the scale, causes and costs of waste medicines. York Health Economics Consortium/School of Pharmacy, University of London 2010.
14. Cutler RL, Fernandez-Llimos F, Frommer M, Benrimoj C, Garcia-Cardenas V. Economic impact of medication non-adherence by disease groups: a systematic review. BMJ Open 2018; 8(1): e016982.

The authors
Catia Costa*¹ PhD, Mahado Ismail² PhD and Melanie J. Bailey² PhD
¹Ion Beam Centre, University of Surrey, Surrey, GU2 7XH, UK
²Department of Chemistry, University of Surrey, Surrey, GU2 7XH, UK

*Corresponding author
E-mail: c.d.costa@surrey.ac.uk