Clinica Chimica Acta Volume 412 Issue 9-10 2011 [Doi 10.1016%2Fj.cca.2011.01.010] Paola Brunori;...
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Evaluation of bilirubin concentration in hemolysed samples, is it really impossible?
The altitude-curve cartography approach to interfered assays
Paola Brunori a,, Piergiorgio Masi a, Luigi Faggiani a, Luciano Villani a, Michele Tronchin b, Claudio Galli b,Clarissa Laube a, Antonella Leoni a, Maila Demi a, Antonio La Gioia a
a Azienda USL 6 Livorno, Italyb Abbott Diagnostic Division, Roma, Italy
a b s t r a c ta r t i c l e i n f o
Article history:
Received 18 November 2010
Received in revised form 6 January 2011
Accepted 6 January 2011
Available online 14 January 2011
Keywords:
Bilirubin
Icterus
Hemolysis
Interference
Neonatal jaundice
Background: Neonatal jaundice might lead to severe clinical consequences. Measurement of bilirubin in
samples is interfered by hemolysis. Over a method-depending cut-off value of measured hemolysis, bilirubin
value is not accepted and a new sample is required for evaluation although this is not always possible,
especially with newborns and cachectic oncological patients. When usage of different methods, less prone to
interferences, is not feasible an alternative recovery method for analytical signicance of rejected data might
help clinicians to take appropriate decisions.
Methods: We studied the effects of hemolysis over total bilirubin measurement, comparing hemolysis-
interfered bilirubinmeasurement with the non-interfered value. Interference curves wereextrapolated overa
wide range of bilirubin (030 mg/mL) and hemolysis (H Index 01100).
Results: Interference altitude curves werecalculated and plotted.A bimodal acceptance table was calculated.
Non-interfered bilirubin of given samples was calculated, by linear interpolation between the nearest lower
and upper interference curves.
Conclusions: Rejection of interference-sensitive data from hemolysed samples for every method should be
based not upon the interferent concentration but upon a more complex algorithm based upon the
concentration-dependent bimodal interaction between the interfered analyte and the measured interferent.
The altitude-curve cartography approach to interfered assays may help laboratories to build up their ownmethod-dependent algorithm and to improve the trueness of their data by choosing a cut-off value different
from the one (10% interference) proposed by manufacturers.
When re-sampling or an alternative method is not available the altitude-curve cartography approach might
also represent an alternative recovery method for analytical signicance of rejected data.
2011 Elsevier B.V. All rights reserved.
1. Introduction
Hemolysis (H) is the most common cause of blood sample
inadequacy and interferes in different ways with several assays [1].
As far as bilirubin (B) measurement is concerned, the interference of
hemolysis is caused by two kinds of events:
1. Physical interference (light absorption of the heme group) and
chemical interference (inhibition of diazotization).
2. Physiological catabolism of plasma/serum heme groups into
bilirubin.
When a hemolysed sample arrives in the laboratory physiological
generation of bilirubin from hemoglobin may be easily prevented or,
at least, limited e.g. by immediate measurement of bilirubin, while
physicalchemical interferences are already present and may only be
evaluated in order to accept (or reject) the results from the analyzer.
Evaluation of hemolysis might be performed in a visual, qualitative
way but also in a semiquantitative way using interference assays that
are normally available in modern clinical chemistry analyzers.
Interference assays are to be preferred for better reliability [2]. For
every bilirubin methoda cut-off value for hemolysis(H) is established
Clinica Chimica Acta 412 (2011) 774777
Abbreviations:Bil, bilirubin (total)total bilirubin value; Bil, value of Bil in a non-
hemolytic sample; BilHmeas, measured value of Bil in a hemolytic sample; Bil index,
icterus index value; H, hemolysishemolysis index value; Hhigh, calculated value of H
for the nearest higher interference curve; Hlow, calculated value of H for the nearest
lower interference curve; Hmeas, measured value of H in a hemolytic sample; I%,
interference; I%chosen, chosen interference level for altitude curves; I%low, nearest
lower interference curve; I%high, nearest higher interference curve; l%mis, measured
interference; POCT, point of care testing.
Corresponding author. Laboratorio Ospedale Villamarina, via Forlanini 22, 57025
Piombino (LI), Italy.
E-mail address:[email protected](P. Brunori).
0009-8981/$ see front matter 2011 Elsevier B.V. All rights reserved.
doi:10.1016/j.cca.2011.01.010
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by the manufacturer's insert sheet [3] or laboratory experience.
Therefore the Bil value of a given sample might be rejected if the H
value exceeds this threshold; in this case a new sample without
Hemolysis should be obtained for a correct measurement of
bilirubin. In most cases this is not a great problem, but for newborns
a new sample might not be easy to obtain since vein diameter in
babies is very small, the newborn total blood volume may not allow a
second sampling and, nally, newborn spontaneous hemolysis might
be the causative agent of high bilirubin concentration[4].The measurement of bilirubin in neonatology is a critical point,
since high concentration of bilirubinat birth maygenerate permanent
and severe encephalopathy (kernicterus). Classical kernicterus is a
well-described clinical tetrad of (i) abnormal motor control, move-
ments and muscle tone, (ii) an auditory processing disturbance with
or without hearing loss, (iii) oculomotor impairments, especially
impairment of upward vertical gaze, and (iv) dysplasia of the enamel
of deciduous teeth[5].
Measurements must be accurate and with a short TAT since
evolution of bilirubin in newborns may be very fast, and the clinical
protocol must also take into account the patient's age (in hours)and B
increment speed. The clinicians, therefore, are asking for a different
solution in this context[6].
A second source of problems is that, conventionally, the interfer-
ence cutoffpoint is chosen when interference is equal to 10%, which is
very close, but greater, than 9.8%, that represents the European
inaccuracy goal for bilirubin [7] without considering any other
possible source of inaccuracy.
Therefore we decided to investigate in depth the inuence of
hemolysis on bilirubin measurements in order to propose a different
approach.
2. Methods
Pools of sera with different values of bilirubin(Bil) were generated
from blood donors' samples without relevant hemolysis (inclusion
criteria was a free hemoglobin concentration b20 mg/dL) and were
divided into quotes and frozen until usage. Immediately before
testing, red blood cells from donors without increased Bil wereseparated from plasma, manually hemolysed and centrifuged. The
hemolysed supernatant was used to generate interfering samples by
dilution with a phosphate-buffered saline solution. Samples for
measurement were generated adding 1 part of one interfering sample
and 9 part of one icteric sample. Final free hemoglobin concentration
in the above-mentioned samples ranged from 35 to 1050 mg/dL. Non-
interfered samples (nal free hemoglobin concentration ranged from
2 to 12 mg/dL) were generated by adding 1 part of saline solution
instead of the interfering sample. For each sample we measured the
interference index (Hmeas) and total bilirubin (BilHmeas) with the
reagent (total bilirubin LN 8G6220, Abbott Diagnostics, Chicago, IL)
and instruments (ARCHITECT ci8200, Abbott Diagnostics, Chicago, IL)
routinely used in our laboratory. Each point was measured at least
twice with two different instruments. Subsequent data processingwas performed using a standard worksheet (MS Excel) program. Data
were compared with non-interfered bilirubin (Bil) to calculate
interference (I%) as
I% = BilHmeas BilB
= BilB 100:
The theoretical values of I%=5%, 10%, 15%, 20%, 25%,
30%,35%,40%,45%,50%,55%,60%,65%, 70%, 75%, 80%,
85%, 90% and95%were chosen(I%chosen) forcalculatingthe valuesof
experimental interference altitude curves. Data for I%chosen were
calculate from H (HI%) and Bil (BilI%) for any chosen interference
altitudecurve between two experimental points (BilHmeas1; Hmeas1)
and (BilHmeas2; Hmeas2) whose I% were respectively lower (I%meas1)
and greater (I%meas2) than the chosen I% (I%chosen), using classical
interpolation formulas
HI% = Hmeas1 + I%chosen I%meas1 = I%meas2 I%meas1 Hmeas2 Hmeas1
BilI% = BilHmeas1 + I%chosen I%meas1 = I%meas2 I%meas1
BilHmeas2 BilHmeas1 :
Later, second order regression curves with the formula
H = A Bil2
+ B Bil + C
were calculated over (HI%; BilI%) points of the chosen interference
altitudecurves.
After completing this phase a worksheet was build to plot into
altitude curves any experimental (BilHmeas; Hmeas). In this worksheet
H values in the interference curves are calculated for the given value
of (BilHmeas) and compared to (Hmeas). The H value of the nearest
lower altitude curve of (BilHmeas; Hmeas) is dened as Hlowand the H
value of the nearest higher altitude curve of (BilHmeas; Hmeas) is
dened as Hhigh. This procedure allows to calculate the position of
Hmeas in the line (Hlow: Hhigh) and therefore to evaluate the
interference according to the formula
I% = I%low + Hmeas Hlow = Hhigh Hlow
I%high I%low
:
Therefore Bil is calculated with the formula
BilBcalc = Bilmeas= 1 + I% :
Four fresh samples (verication samples), with signicant Bil
values were treated like the former ones to test the worksheet and
compared their measured Bil (1 part of saline instead of interference
sample) with the calculated Bil.
3. Results
Fig. 1A shows average bulk decay curves of B versus H. Visual
analysis of bulk decay curves was used to evaluate the coverage of the
measured area and eventually to check the single experimental points
in order to replicate eventual non-tting points before proceeding
with calculations.
Fig. 1.Bulk bilirubin measurements (A: mg/dL) and interferences (B: %) versus index
measurements (H).
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Fig. 1B shows the interaction of I% and H for the same data. The
manufacturer indication for interference cutoff point (absolute value
of interference 10% which correspond to I%10%) indicates an H
value of 31. The decay trends of Bil=0.99 mg/dL and Bil=1.73 mg/
dL when H=31 show an absolute value of interference greater than
10% (17% and 13% respectively) while two other ones show absolute
values of interference between 5% and 10% (8.5%, and 5% for
Bil= 4.46 mg/dL, Bil= 5.94 mg/dL, respectively), and negligible
(b
5%) for the other ones (Bil=8.43 mg/dL, Bil=12.62 mg/dL andBil= 29.98 mg/dL).
I% =10% was found at H values of 19, 24, 35, 49, 65, 84, and 109
f or Bi l = 0.99 mg/dL, Bi l = 1.73 mg/dL, Bi l = 4.46 mg/dL,
Bil =5.94 mg/dL, Bil =8.43 mg/dL, Bil=12.62 mg/dL, and
Bil=29.98 mg/dL, respectively.
Fig. 2 shows calculated altitude data points obtained with
previous data interpolation as described above, with their second-
order tting polynomial curves. Calculated points for curves 80%,
85%, 90% and 95% were less than 4 for each curve, therefore the
second-ordertting polynomial curve for this data was forced to be a
rst-order polynomial curve.
Square correlation coefcient (R2) ranged from 0.977 for
I%chosen=5%, to 0.999 for I%chosen=80%. Fit parameters were
used to generate data pairs (BilTmisversus Hmis) inTable 1for three
chosen altitudecurves: 2.5%, 5%, 7.5% and 10% respectively.
Fit parameters from 5%, 10%, 15%, 20%, 25%, 30%,
35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%,
90%and95%curves respectivelywere used to generate an altitude
plot, as shown inFig. 3, in a worksheet le.Table 2shows data of four
verication samples that were treated as described above, and were
used to test the worksheet le. Baseline H (samples with saline)
showed free hemoglobin b20 mg/dL for all samples except #4 (free
hemoglobin=66 mg/dL). InTable 2the icterus index value (Bilindex)
is also shown as a comparison.
Data calculation was not possible for sample 1C (Bilmisb0.1 mg/dL).
Bilcalc of all other samples were in agreement with the measured Bil. It
should be considered that, a not-null value of index is also present in
samples with saline. Therefore the correction formula was used also
with Bilmeasto generate a corrected Bilmeas. Comparison of all Bilcalcversus corrected Bilmeas showed a better agreement than the
comparison versus non-corrected Bilmeas. Average bias of Bilcalc versus
corrected Bilmeas was 37% (50% versus non-corrected Bilmeas) for
sample #1.Average bias of Bilcalc versus corrected Bilmeas was 9% (11%
versus non-corrected Bilmeas) for sample #2. Average bias of Bilcalcversus corrected Bilmeas was 2% (4% versus non-corrected Bilmeas)
for sample #3. Average bias of Bilcalc versus corrected Bilmeas was1%
(8% versus non-corrected Bilmeas) for sample #4.
Fig. 4 shows a bias and precision plot from the data of the
verication samples.
4. Discussion
Bilirubin measurement must identify the infants at risk for
permanent brain damages (kernicterus) and other pathological
conditions [6]. It is of concern that many bilirubin automated kit
methods suffer from hemolysis interference. Since hemolysis may be
one of the causes of high bilirubin concentration, many methods often
fail to measure bilirubin.
Interference is not only a matter of hemoglobin concentration but
depends also upon bilirubin concentration since the same value of H
produces different values of I% upon different bilirubin concentrationsand therefore it is a double-factor event. The interaction is
reproducible, therefore a mathematical approach might expand
measuring possibilities beyond their traditional limits. It is clear that
evaluation of bilirubin from the icterus index is a possible approach,
but is not recommended[3] since it may generate untrue, although
precise, measurement. A different approach might be non-invasive
patient-side (POCT) measurement of transcutaneous bilirubin with
multiwavelength spectral reectance analysis[8].
Multiwavelength spectral reectance analysis, is methodologically
similar to the above-mentioned index method, without the need of
blood sampling, and therefore without needle-induced hemolysis.
Fig. 2.
Altitude-curve
points with regression curves.
Table 1
Bimodal acceptance table for data rejection.
Bil Tmeas(mg/dL) H index Hb (mg/dL) values for interference curves
2.5% 5.0% 7.5% 10%
0 1 3 3 3
1 3 7 9 12
2 5 10 16 21
3 7 14 21 29
4 8 17 27 37
5 10 20 32 45
6 12 23 37 52
7 13 26 42 58
8 14 29 47 65
9 16 32 51 70
11 17 34 55 76
12 18 37 59 81
13 19 39 62 86
14 21 41 66 90
15 22 43 69 94
16 23 45 71 98
17 23 47 74 101
18 24 49 76 103
19 25 50 78 106
20 26 51 80 108
21 27 54 82 111
22 27 55 83 111
23 28 56 84 11224 28 57 84 112
25 29 57 84 111
Fig. 3. Usageof altitudecurves: a patient () withBilmeas=15.0 mg/dLand Hmeas=600
is evaluated to be affected by a 39% interference therefore Bilcalc=24.5 mg/dL.
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Nevertheless, transcutaneous bilirubin measurement might overesti-
mate blood bilirubin[10], when signicant skin bilirubin is present.
The altitude curve approach produces a reliable estimation of
interference and Bil. This approach may improve traditional data
rejectiondening thehemolysis cutoffpoint no more as a singlepoint,
but asa function ofBilHmeas (Table 1). Indications fordata rejectionare
traditionally indicated by manufacturers when the absolute value of
interference is equal to 10%, which is very close, but greater, than 9.8%,
that represents the European inaccuracy goal for bilirubin[7]without
considering any other possible source of inaccuracy. With the
altitude curve approach more restrictive cutoffs are available,
therefore in Table 1 not only the traditional minimal (10%)
curve is indicated but also the 2.5% (desirable as of the
European total inaccuracy goal), the 5% (acceptable as of the
European total inaccuracy goal) and 7.5% (permissiveas of the
European total inaccuracy goal) curves respectively.
Interference plots like inFigs. 2and3or a commercial worksheetlike inTable 2may help evaluate Bil from BilHmeasand Hmeas if the
laboratory is more condent with data calculation.
The altitude curveapproach has its own limitations, rst of all it
may estimate chemicalphysical interference but not the physiolog-
ical after-sampling production of bilirubin from hemolised samples
[1]. Furthermore, results of this work are limited to the method in use
in our laboratory, but other laboratories that employ different
methods or instruments may use the same approach to build their
own altitude curves. While the choice of different reagents less
prone to interference by hemolysis will be of more help in specialized
settings[9], this method will be useful in most general labs that serve
both in- and outpatients, as it is common in Italy and generally in
Europe; in these settings it is difcult to envision theusage of different
reagents according to the population assayed. If reagents more
sensitive to hemolysis are in use, our method may be useful, and
though it is validated only for the Architectreagent, it may be adapted
also to different ones. The altitude-curve cartography approach may
give new sights and solutions to the problem of interferences,
especially where a new sampling is not possible or convenient, and
the interfered analyte should be quickly determined to drive
important therapeutic decisions, like bilirubin in the neonatology
eld.
References
[1] BradyJ, O'Leary N. Interference due to hemolysis inroutine photometric analysisa survey. Ann Clin Biochem 1998;35:12834.
[2] Glick MR, Ryder KW, Glick SJ, et al. Unreliable visual estimation of the incidenceand amount of turbidity, hemolysis, and icterus in serum from hospitalizedpatients. Clin Chem 1989;35:8379.
[3] Manufacturer's insert sheetAbbott Laboratories 8G62.[4] Cohen RS, Wong RJ, Stevenson DK. Understanding neonatal jaundice a perspective
on causation. Pediatr neonatol 2010;51:1438.[5] Shapiro SM. Chronic bilirubin encephalopathy: diagnosis and outcome. Semin
Fetal Neonatal Med 2010;15:15763.[6] Kirk JM. Neonatal jaundice: a critical review of the role and practice of bilirubin
analysis. Ann Clin Biochem 2008;45:45262.[7] http://www.westgard.com/europe.htm.[8] Bhutani VK, Gourley GR, Adler S, Kreamer B, Dalin C, Johnson LH. Noninvasive
measurement of total serum bilirubin in a multiracial predischarge newbornpopulation to assess the risk of severe hyperbilirubinemia. Pediatrics 2000;106:e17.
[9] Algeciras-Schimnich A, Cook WJ, Milz TC, Saenger AK, Karon BS. Evaluation ofhemoglobin interference in capillary heel-stick samples collected for determina-tion of neonatal bilirubin. Clin Biochem 2007;40:13116.
[10] Ahmed M, Mostafa S, Fisher G, Reynolds TM. Comparison between transcutaneousbilirubinometry and total serum bilirubin measurements in preterm infantsb35 weeks gestation. Ann Clin Biochem 2010;47:727.
Table 2
Effect of addition of saline or hemolysed sera (A, B, C, D, E, F and G) over bilirubin
measurement. Uncorrected Bil is Bilmeasof saline-added samples, and corrected Bil is
Bilcalcof saline-added samples.
Sample Addition
(10%) of
Bilmeas(mg/dL)
Hmeas
(mg/dL of Hb)
Calculated
interference
Bilcalc(mg/dL)
Bilindex(mg/dL)
#1 Saline 0.9 8 9% 1.0 1.5
A 0.6 47 50% 1.2 1.5
B 0.3 85 80% 1.5 1.5
C b0.1 170 N. a. N. a. N. a.#2 Saline 2.9 3 1% 2.9 2.6
A 2.4 42 20% 3.0 2.7
B 1.9 88 44% 3.4 2.6
C 1.1 168 66% 3.2 2.6
#3 Saline 6.7 12 3% 6.9 5.8
B 5.4 94 21% 6.9 5.8
C 4.4 173 39% 7.2 5.8
E 2.7 311 61% 6.9 5.7
#4 Saline 15.7 66 7% 16.9 15.7
D 13.5 223 23% 17.5 15.6
F 10.8 420 38% 17.6 15.4
G 7.7 699 51% 15.7 15.3
Fig. 4.Bias and precision plot from the data of the verication samples.
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