Scotland. 2 Department of Biochemistry,. Raigmore Hospital, Inverness,. Scotland. 3Department ..... 1800 CLINICAL CHEMISTRY. Vol. 25. No. 10. 1979 ...
CLIN. CHEM.25/10, 1799-1805(1979)
Intra-IndividualVariationin CommonlyAnalyzedSerum Constituents Barbara Morrison,1 A. Shenkln,1 A. McLelland,’ D. A. Robertson,2 Margaret Barrowman,1 Sheila Graham,1 Gillian Wuga,’ and K. J. M. Cunningham3
Concentrations of 27 commonly estimated serum constituents were measured in blood sampled from 20 apparently healthy volunteers at 0830, 1230, and 1630 hours on each of four days, at weekly intervals. Time-dependent statistically significant (p 0.01) variation was observed in 12 of the constituents. The 15 constituents that showed no statistically significant diurnal variation Included the immunoglobulins, other specific proteins, enzymes, cholesterol, calcium, copper, and magnesium. On the different days of the study consistent temporal patterns were observed in urea, creatinine, phosphate, zinc, bilirubin, triglyceride, total protein, and albumin. The magnitude of variation was particularly great in potassium, iron, zinc, and bilirubin. In general, day-to-day changes in concentration exceeded within-day changes, except for potassium, phosphate, and zinc, for which greater changes could be observed within-day than from one day to another at the same time. AdditIonal Keyphrases:
diurnal and circadian variation day-to-day and within-day changes normal values variation, source of intra-indivk*jal variation reference ranges .
#{149}
.
Many constituents of biological fluids are frequently serially estimated, to assess changes in the condition of a patient, or the effect of therapy. If observed changes in concentration are to be correctly interpreted, it is necessary to know what variation may normally occur in the concentration of that constituent when no pathological condition is present. Several studies
of variation
of serum
constituents
in individual
normal
subjects have been reported. The relevance to populationbased reference ranges has been discussed (1,2), together with methods of assessing inter- and intra-individual variation. Statland and co-workers, in a series of studies (3-6), have discussed various factors that contribute to intra-individual variation, considering both within-day and short-term dayto-day variation, and various aspects of long-term variation have been studied by Cotlove and co-workers (7-9). Although these
studies
variation
demonstrated
significant
in many serum constituents,
intra-individual
of this type of variation occurring in a single individual was not investigated. In this study we were concerned not only with within-day variation but also with the consistency on four ‘Department Scotland. 2 Department
of Biochemistry,
the probability
Royal Infirmary,
Glasgow G4 OSF,
of Biochemistry,
Raigmore
Hospital,
Inverness,
of Biochemistry,
Western
Infirmary,
Glasgow,
Scotland 3Department Scotland.
ReceivedJan.
31, 1979; accepted
July
12, 1979.
different
days of any variation
in 27 serum
observed
during
an 8-h period
constituents.
Materials and Methods Subjects Nine men and 11 women,
ages 19 to 30 years,
took part
in
the study. Brief medical histories, including details of weight and height, diet, and medication, were recorded. None of the subjects
was a heavy
smoker;
alcohol
consumption
in the
group was moderate and occasional. Two of the women took oral contraceptives, and other medication was only such as might be expected in any group of ostensibly healthy subjects. It was not considered to be necessary to exclude any subject from the study on the basis of medical histories. Subjects performed their normal work, which involved no strenuous exercise, throughout the day.
Samples blood samples were drawn at 0830 hours fast, at 1230 hours, and again at 1630 hours on each of four days, at weekly intervals. Breakfast was taken between 0830 and 0900 hours and lunch from 1245 to 1345 hours, no other food being consumed between the sampling times. All subjects were required to sit quietly for 10 mm before each blood sample was collected, and the same veneTwenty-milliliter after an overnight
puncture
technique
was used throughout.
All samples
were
centrifuged for 10 mm at 3000 rpm as soon as clotting was complete (about 1 h after withdrawal) and the serum was separated and divided into aliquots. All aliquots of serum were stored at -20 #{176}C until at least one week after the last samples were collected before analyses were begun.
Analytical
Methods
The serum
constituents
which also contains their “within-batch”
analyzed
are shown in Table
1,
notes on the analytical methods used and coefficients of variation (CVs) calculated
at nonpathological concentrations in our laboratory. All 12 from each subject were analyzed in one batch for each serum constituent, to obviate between-batch analytical
samples
variation.
Statistical Methods For each of the 27 constituents studied the following calculations were performed: i) The overall mean and standard deviation for each sampling time was calculated for each serum constituent. ii) “Repeated measures” analysis of variance. The results were set out in matrixes of three time points for each of the four days of the study. Complete matrixes were obtained from 14 subjects, the others having failed to supply one or more of the blood samples. A repeated-measures analysis of variance (ANOvA) program was developed for a DEC PDP 11/34 pro(I
IPJI(’b.I
(‘5.1LAITPV
%JnI
oc
Pin
IA
1070
1700
Table 1. Serum Constituents Analyzed, Together with Brief Descriptions of Methods Used, and Our Within-batch CVs for Them Analytical
Sodian
II 343 flame phOtter
0.5
Potassium
IL 343 flame photometer
1 .0
U
II, 5(4-0005
1 .0
Co2
U
II,
S64-000B FJ4
3.0
Urea
U
II.
564-0001
FD4
2.5
PHd
2.5
Total
88 II,
Protein
U
S(4-OOll
II.
P04
564-0030 P04
Albumin
U
IgA
Automated imeunoprecipltation
3.0
IgG
Madification of Technicon AlP syst
2.0 5.0
Iranoferrin
2.0
Calcium
U
II.
FJ4
1.5
Phosphate
U
II, 5(4-0004 P44
2.0
Iron
U
Copper
Atomic absorption,
5(4-0003
s.d.
140.7 4.10 103.6 24.35 4.86 77.01
1.64 0.26 1.79 2.14 1.52 13.86
140.2 4.07 102.7 24.17 4.78 71.86
1.65 0.23 1.55 2.21 1.08 13.89
140.8 3.95 102.8 24.97 5.10 75.22
1.72 0.26 1.73 2.08 1.17 14.81
69.40 47.84 1.86 10.21 1.18 3.21 0.27 3.54
3.19 2.66 0.67 1 .92 0.50
70.73 49.01
3.48 2.87
70.82
1.84
0.63
49.06
10.23 1 .67 3.29 2.27 3.54
2.02 0.53
1.87 10.18 1.20 3.36 0.28
3.14 2.67 0.64 1.94 0.54 0.70 0.07
3.51
0.69
2.37 1.30 17.77 14.98 12.96 0.81 240.3
0.08 0.16 7.17 3.82 2.43 0.07 58.9
2.40 1.20 18.47 15.42 12.19 0.81
0.08 0.15 7.56 4.19 2.32 0.06 54.1
0.83 232.3
0.08 0.17 6.64 3.95 2.42 0.07 53.9
22.03
8.31
22.58
8.53
22.21
8.41
13.36
3.06
13.42
2.64
13.95
8.68
163.6 8.46
42.72 4.83
173.8 8.21
51.05 4.83
172.6 7.23
82.99 3.91
5.05
0.99
1.14
0.67
jasol/L
isr1/L n’nol/L
ioiml/L
0.63
0.07 0.66
0.64 0.07 0.66
228.2
2.39 1.31
17.07 15.23
11.05
3.0
Perkin Elmer 403
3.0
Magnesium
3.0
LOBReaction
alulnotransferase
Rate analyser
5.0
5.0
Alanine a.tnotransferase
4.0
at -20
5(4-0018 ((4
3.0
Population
Cholesterol
U I!,
SE4-00l6 (144
2.0
Triglyceride
U II. 5(4-0023 ((5
3.0
phosphatase U
irubln
II.
5.06 0.88
‘
0.97 0.28
5.07 0.92
1.00 0.32
fourth day, we could detect no trends in the results for any serum constituent that could be attributed to the different storage intervals. This concurs with the findings of various workers (11, 12) that all the constituents measured are stable
at 37 C.
optimised
iulfL
CholesterOl Triglyceride
3.0
U II. plsosphotungstlcacid
Ur.te
Aspartotn aminoU/I tronsferase A1nine amino#{149} Cra no P erase Alkaline Phosphatose Bilirabin JIOl/L
1.5
II. SF4-0025 fL,
Zinc
RU
mean
3.0
in
Alkaline
s.d.
2-Macg1obolin
3.0
Ceruloplasmin
mean
‘
na1/L
l6
s.d.
‘m,ol/L
Calcium Phosphate Iron Copper Zinc Magnesium orate
123_0
mean
Total protein Albumin IgA IgG 1gM Transferrin Ceruloplasmin
1 .0
1gM
Aspartate
Sodium Potassium Chloride Total Co Urea Creatinine
1.0
564-0014 FC4
II.
08
within-batch CVI
Method
Chloride
Creatinine
Table 3. Population Means (±SD) for Each Serum Constituent at 0830, 1230, and 1630 Hours
#{176}C.
Means
The population serum There
constituent is a strong
mean and standard
deviation
for each
at the three times are shown in Table 3. suggestion of circadian variation in certain
cessor, and an example of the output is given in Table 2. The model we used identifies times as a fixed effect and treats
measurements-for example, phosphate, total protein, and zinc. However, in most other constituents, inter-individual
subjects
and days as random
differences
between
different
effects.
Differences
times of day are evaluated
in results
by the “be-
tween-times” sum of squares, and consistency of response among the 14 subjects by the “subjects x times” interaction sum of squares (SOS).The calculation is more fully described by Winer (10). Because the F-tests are only approximate unless correlations between results at any two times of day are identical for all subjects, significance was judged at the 1%
rather
than the 5% level,
Analysis of variance-Sodium Source of variation T
consistency
SOS
DF
M.s.
F
21.94
9.30
Betweentimes SubjectX times Dayswithinsubjects Residual
T 1
14.00 28.00
49.08 58.67
7.00 1.08 2.36
6.50
1
2 26 42
84
0.70
Overall Mean time values: 0830-
1
140.607 1230-
1.54
167
140.018 1630-
In mol/L
Calculation completed.
____________________________________________________
CLINICAL CHEMISTRY. Vol. 25. No. 10. 1979
all 14 subjects,
were
the immuno-
globulins, transferrin and a2-macroglobulin, calcium, iron, copper, and magnesium, the three enzymes, and cholesterol.
significant
can
140.643
be divided
and consistent
of day and those methods
13
485.00
across
Remaining assays
285.25
1800
Results from the ANOVA program are summarized in Table 4. Significant variation with time was detected in 12 of the 27 analytes, and consistency of response among subjects was found for all but six methods: potassium, urea, ceruloplasmin,
showing
T
Mean time valuesexpressed
that any
is obscured.
These analytes will be excluded from further discussion, cept for iron, which merits particular attention.
Table 2. Example of “Repeated-Measures” ANOVA Table
1
to such an extent
individuals
Repeated-Measures ANOVA
with
Although the samples taken on the first day of the study had been stored three weeks longer than those taken on the
subjects
the means
within particular
phosphate, bilirubin, and triglycerides (triacylglycerols). The methods showing no significant time-to-time variation,
Results
Between
have affected
such variation
ex-
into two groups: those variation
in which no consistent
between response
times was
found.
The source of the significant findings in the first group was elucidated by reference to overall mean-time values over all
days and for all 20 subjects (Table 3). These overall means, which parallel the meanscalculated during the ANOVA (Table 2), clarify whether significance is due to results from one particular time of day or whether results at all three times of day vary substantially from one another. One of the implications of the findings of consistent response among all days and subjects is that the “pattern” of the relationships of the overall means to one another will be
Table 4. Instances of Significant Variation between Times of Day and Consistency of Response among Subjects, by “RepeatedMeasures” Analysis of Variance Variation
betweentimes
Consistent
Sodium
P
0.01
YES
Potassium
p
0.01
MO
Chloride
p
0.01
YES
CO2
p
0.01
Urea
poo.Ol
Creatinine
p
0.001
YES
Total
#{149} 0.001
YES
p
0.01
YES
IgA
MS.
196
MS.
YES
1gM
N.S.
YES
Iransferrin
N.S.
YES
Ceruloplasnin
N.S.
NO
a24iacroglobulin
N.S.
YES
Calcium
MS.
YES
Phosphate
P
Iron
N.S.
Copper
N.S.
Zinc
p
Magnesium
N.S.
Yb
Orate
p
YES
Aspartate aminotransferase
44.5.
YES
Al ani ian aminotrensferase
MS.
YES
Alkaline
Oft
0.001
NO
Cholesterol
N.S.
YES
Triglyceride
N.S.
NO
approach
8
YEt
0.001
YES
on graphing
0
YES
p#{176}000l
of each subject
12
NO
0.001
MS.
sponse
14
YES
Bilirsbin
reproducible
response
YES
p
phosphatase
the pattern
Mean
and this
in this way.
Patterns of Variation We prepared graphs of the mean of day for each individual subject uent.
The patterns
values for
each
16.30
time
subject
Fig. 1. Means for the results on the four days (at 0830, 1230,and 1630 hours) for zinc In each subject
of the mean time re-
over all four days of the trial,
12.30
0830
is further discussed below. The second group of which showed no consistent time-to-time variation,
analytes, was also examined
pmoljl
NA
Albumin
Protein
16 Zinc
values at the three times for each serum constit-
cant between-time variation has been reported, we saw no fluctuations in results. In serum iron, for example, a substantial and unpredictable variation is seen on plotting all 12 values for several individuals (Figure 4) but this is masked by the large residual term in the ANOVA. The constituents showing no consistent time-to-time variation were: potassium, urea, ceruloplasmin, phosphate, bilirubin, and triglycerides. Potassium shows considerable variation in individuals (Figure 5) and within different days of the study, as does hilirubin, with a trend towards an overall decrease throughout the day. Phosphate
(Figure
6) and urea dip at mid-day, like creatiare sufficiently unpre-
nine, but here the size of the changes
shown by these graphs reflect the patterns
suggested by the overall means of the methods in the first group of interest outlined above, and give the clinical biochemist a better appreciation of the range of results to be expected in these apparently normal, healthy subjects. For example, the concentration of zinc in serum appears to decline steadily throughout the day, the highest values being found in the samples collected during fasting (Figure 1). In addition, the graphs of all 12 results for several subjects suggest that serum zinc follows the same pattern of variation on each day of the study in most individuals (Figure 2). The graph of mean results for creatinine in the serum of each subject at each time of day (Figure 3) again reflects the overall means in that the mid-day sample shows lower results than the other two (Table 3). Similar parallels were seen in each constituent in this group of analytes that showed significant between-time variation with consistent patterns. However, it should not be assumed that, where no signifi-
ZINC pmoI
Fig. 2. Complete sets of results for zinc for six subjects CLINICAL CHEMISTRY, Vol. 25, No. 10, 1979
1801
mmol/l
K mmol/l
Creatinine
4.4
4.3
100
42
4’l
80
4’O
3.9
60
3’8#{149} 08’30
12’30
16.30
3.7
Fig. 3. Means for the results on the four days for creatinine in each subject dictable
to indicate a lack of consistency between individ-
0830
1230
uals. Ceruloplasmin and triglycerides are the only analytes showing no significant time-to-time variation and yet an inconsistent response. For ceruloplasmin a graph of the mean times for all subjects shows a generally flat curve, except for a single subject who showed a substantial increase in the value at 1630 hours on all four days of the study. Triglycerides, not surprisingly, do show some increase in the value at 1630 hours, but again the magnitude of response is variable, almost certainly depending on the size of the lunchtime meal.
Mean value for each subject Fig. 5. Means of results on the four days for potassium in each
subject
when the difference between two consecutive results was greater than the analytical variation of the method. The results for all 20 subjects were included. Nine patterns
Reproducibility
of Pattern of Variation
in Individual
Subjects In an attempt to assess the reproducibility of variation in any one serum constituent from one day to another, we recorded the pattern of change for each subject on each day. For this purpose, a change was considered to have taken place only
Iron
21
10 --.-.,____
______ dayl
d2
doy3
Fig. 4. Complete sets of results for iron for three subjects with normal iron concentrations and for two subjects with low serum iron Referencerange,9-30 cmoI/L
1802
CLINICAL CHEMISTRY, Vol. 25. No. 10, 1979
163O
can readily
be defined
in this way (Figure
7).
The patterns observed on each day of the study for each subject (each “subject-day”) were recorded [detailed data can be obtained from the authors or the editorial office of this journal], and the overall frequency with which the nine patterns occur is shown in Table 5. There was no statistically significant difference (by chisquare test) between the distribution of these patterns in men and women for any of the serum constituents. The small numbers of subjects of each sex make it undesirable to draw conclusions from this analysis. The discounting of changes that were within the limits of analytical variation for the methods has resulted in a flattening of the curves for some constituents, and pattern 5, where there is no significant change throughout the day, is seen to be the dominant pattern for many serum constituents. It was the case for more than half of the subject-days with respect to sodium, chloride, C02, IgA, ceruloplasmin, calcium, copper, urate, the transaminases, and cholesterol, and when other patterns did occur in these constituents, they were with few exceptions either 6, 7, 8, or 9-i.e., the patterns in which there is no change between two consecutive times. In some constituents-for example, transferrin-discrepancies between the findings of the ANOVA and this study of patterns may be accounted for by the fact that patterns were recorded for all 20 subjects, whereas ANOVA was only performed for the subjects who had complete matrixes. No dominant pattern can be detected in some of the parameters in Table 5. However, when some of the patterns are
Phosphate m mcI/I
/;\
1’5
\
1’4
\/
4
\._.
5
6
12,
1’l, #{149}sss,44.
#{149},/#{149}#{149}#{149}
1’0
.;/
1’9
8
9
Fig. 7. Nine possible patterns of variation
A specimen
o ‘8
for “lipid”
analysis
during fasting for triglycerides
08’30 Mean
12.30 values
for
16.30
each subject
Fig. 6. Means of results on the four days for phosphate
in each
subject grouped together, such as those that show a morning increase (patterns 1, 2, and 9) or those that show an overall fall throughout the day (patterns 3, 6, and 8), certain trends ap-
pear. Urea and creatinine commonly show lowet values at midday (patterns 4, 6, and 7). However, in urea this is due most often to an increase during the afternoon (patterns 4 and 7), whereas in creatinine it is due mainly to a decline during the morning (patterns 4 and 6). Total protein, albumin, and transferrin all show increasing values in the morning (patterns 1, 2, and 9), this being most marked in albumin, where pattern 5 seldom occurs. It can be concluded that the increase in total protein in the morning is
accounted for largely by an increase in serum albumin. The pattern of variation in serum phosphate, which is clearly shown in Figure 6 and in the population means (Table 3), is pattern 4, where lowest values are found only at mid-day. When individual results are examined, on only 33 of 73 subject-days was this pattern observed. However, patterns 6 and 7 also have lowest values at mid-day, as well as at one other time of day, and when occurrences of these two patterns were included with pattern 4, phosphate was seen to be lowest at mid-day on 70% of subject-days. In serum zinc, pattern 5 and those patterns that show an overall increase throughout the day (patterns 1, 7, and 9) seldom occurred. The dominant patterns were those in which values during fasting were highest, i.e., patterns 3, 6, and 8. Similarly bilirubin tended to decrease from the fasting value-patterns 3, 6, and 8 on most occasions-but here other patterns were not uncommon. Afternoon increases in triglycerides were more commonly seen than morning increases, this probably reflecting the type of dietary intake at lunch.
must therefore be collected estimation, but not necessarily
for cholesterol estimation. In the remaining analytes-potassium, IgG, 1gM, a2-macroglobulin, iron, magnesium, and alkaline phosphat#{225}se-no grouping of patterns reveals any characteristic trends. Some of these, however, are not without interest. For example, serum iron, which is widely believed to decline throughout the day (13), was frequently observed to increase above the fasting values, and the highest values occurred at mid-day (patterns 2, 84 and 9) on nearly half the occasions. Another interesting feature of this diurnal variation in serum iron was that it generally paralleled the variation in bilirubin. No simple arithmetical relationship could be established between iron and bilirubin values, but in only nine of the 144 (i.e., morning changes and afternoon changes on 72 subject days) comparisons we made did iron values change in the opposite direction to bilirubin.
Table 5. Number of Observations of Each Pattern for Each Serum Constituent Pattern
1
2
3
4
5
6
7
8
9
Sodi no
O 1 O 1 1 O
0 18 0 1 0 1
0 15 0 0 3 3
7 18 1 6 17 26
50 1 62 38 14 9
7 5 5 6 9 23
7 1 2 11 27 2
1 7 2 1 0 S
1 5 0 8 1 2
Total protein Albumin 19* IgO 1q11 Trunsferrin Coruloplasmln ,2-Macroglobulln
6
13
0
3
1 3 0 1 0 1
6 6 9 6 4 1
3 2 5
5 4 6
16 ii
2 11 6 10 3 2
23 5 39 17 30 16 42 28
4 7
3 3 1 10 2 1
4
7
4
6
6 7 3
11 5 13
8 7 3 0
14 2 15 6
Calcium Phosphate Iron Copper Zinc
0 2 2 1 0
0 0 7 0 25 3 4
1 33 0 1 6 8 5
49 12 16 43 6 12 41
1 11 5 3 7 5 17
38
10
7
9
55 13
1 1
Potassium Chloride CO Aria Creatiol,e
is
in
2
Maqnesino
6
Orate
0
5 1 13 a 7 3 1
2 2 2 3
7 3 15 14
0 0 0 23
0
2 7
0 0
Aspartate Ilanine
i notransferase #ini,otransferase
Alkaline phosphatase Bill robin Cholesterol Triglyceride
9
8
3
4
9 1 2 13
40 16
4
7 5
6
15
6
2 7 7 3 0 19 3
44
9
2 13 2 19 5 2
4 9 12 2 12 0
4
4
3
4
6
9 15 4
20
CLINICAL CHEMISTRY, Vol. 25, No. 10, 1979
2 2 10 4
5 8 1 3
A
1803
\
mm#{231}vl
K
\
Table 6. Maximum Changes Recorded in Any One Individual, and Means of All Subjects’ Maximum Changes
UI
\
\\
4.1
Maximum Change
UI
I”
a\
‘S
Recorded between
\ \a
2’
3.
doyl
doy2
day3
doy4
showing
consistent
patterns
of variation
the four days
on
Potassium is particularly interesting in that pattern 5 does not occur here, and patterns 2 and 4 are found in equal numbers. A morning decrease (patterns 3, 4, and 6) was observed on about
Times
Days
Times
Sodium nmlol/L Potassium mmol/L Chloride rnmol/L Total CO nnuol/L Urea lrnno/L Creatjnjne jmol/L
4.0 1.2 4.0 6.0 1.5 27
5.0 1.1 4.0 5.0 3.1 26
2.25 0.58 2.7b 2.90 0.71 13.5
Total protein gIL
7,7) 5.0 0.66
10.0 7.0 0.82 7.0
4.35 3.45 0.27
Albumin g/L
Fig. 8. Complete sets of results for potassium for three subjects
half of subject-days,
and an increase
(patterns
1, 2,
and 9) during the morning on a third, reflecting the lack of uniformity in diurnal variation of potassium shown in Figures 8 and 9.
Magnitude of Variation For many of the constituents variation can be demonstrated,
where statistically
significant
the actual changes recorded are too small to be of routine clinical interest. The magnitude of the variation in sodium, chloride, and C02, for example, was usually within the limits of analytical variation, and when changes within the limits of the precision of the method are excluded (Table 5), these analytes appear to remain constant throughout the day. In other serum constituents, some of which do not show statistically significant variation, the difference between two samples taken at different times of day may still be large. Nonetheless, it may be difficult to interpret the clinical significance of such a change in concentration. Serum iron, for example, frequently changed by as much as 10 zmol/L during the course of a day (Figure 4). In seven of the subjects, iron values fell outside our reference range (9-30 zmolfL) at one or more times during the study; in one subject, two of the 12 results were above the upper limit of the reference range and one below the lower limit. One low value
for serum iron is therefore not necessarily representative of the individual’s iron status. In only two subjects was serum iron found to be relatively constant, and in these two mdi-
Means of all
Subjects.Maximum Changes between
IgA (J/L IqG gIL 1gM gIL Transferrin Ceruloplasmin
6.2 g/L g/L
g/L
2-Macroglobu1in Calcium mol/L Phosphate mol/L Iron ljmol/L Copper pmol/L Zinc jjmol/L Magnesium nnnol/L
0.41 1.18
0.44
0.16 1.23
0.14 1.35
Aspartate aminotransferase Alanine aminotransferase Alkaline phosphatase O/L
3.05 3.20 1.46 14.3
5.18 4.10
0.36
1.81 1.28 0.58
2.15 0.31
0.05
0.50
0.07 0.64
0.56
0.20
0.20
0.10
0.12
0.35
0.28
22.0 7.1 12.4
25.0 12.3
6.90 1.97
0.25 12.3 3.37
10.7 1.31 180
4.16 0.11 34.5
3.84 1,12
20
7
9
5 53 4
6 63 5
0.31 0.56
0.68 0.59
U/L 11 14 OIL 164
Bilirubin jmol/L
6
16 165 13
Cholesterol Triglyceride
0.50 2.35
1.8 1.6
mol/L mol/L
2.65 0.55
(1.45
0.22 go
Urate pmol/L
1 . 39
Days
68.5
viduals the iron concentration was very low and suggestive of iron deficiency (Figure 4). To assess the magnitude of variatiOn for each serum constituent, we recorded the maximum range of results observed
in each subject within a day, and from one day to another at the same time of day. Table 6 shows the means of these figures, together with the greatest changes recorded in any one individual. In general, the maximum changes observed were greater in a between-day comparison than for the between-times comparison. However, it is noteworthy that phosphate and zinc, the two serum constituents that show the most distinct patterns of diurnal variation, vary more during the course of a day
than they do from day to day. Potassium also varies more within a day than from day to day, but in this case it is the actual, rather than the relative, magnitude of the variation that is important, because changes of more than 0.5 mmol/L in a day were encountered in more than half the subjects. Statland et al. noted similar changes in potassium values (3) and found greater changes when strenuous exercise was taken (4).
KmmoVI
We conclude
‘#{188}
/
dictably
/
.
3
doy 2
doy3
doy4
Fig. 9. Complete sets of results far potassium for three subjects in whom no consistent pattern of variation was detected 1804 CLINICALCHEMISTRY,Vol. 25, No. 10, 1979
that some serum constituents throughout
the day (sodium,
remain chloride,
preC02,
IgA, ceruloplasmin, calcium, copper, urate, aspartate and alanine aminotransferases, and cholesterol) or else vary by amounts that are too small to be of interest in routine clinical biochemistry. For some constituents, however, it may be possible to predict the extent and direction of the diurnal variation that may be encountered. Urea, creatinine, total protein, albumin,
-
day 1
constant
transferrin, generally
phosphate, zinc, vary in characteristic
a day. For interpretation
bilirubin, and patterns during
triglycerides the course of
of the results of these analyses
it is
to know the time of day at which samples are drawn. When results for samples taken on different days are to be compared, blood should be collected at the same time each day. As for the remaining constituents, we cannot predict the extent or direction of diurnal variation on the basis of the data presented here. Attempts to standardize blood collection will reduce, but not exclude, intra-individual variation, which may still be considerable. The magnitude of the variation found in many serum constituents is very large. If variation occurs to the same extent in bed-rest patients as in the healthy subjects, it must be taken into account when interpreting biochemistry results obtained in clinical laboratories. A study of intra-individual variation in bed-rest patients is therefore now in progress. necessary
We thank the technicians of this department who performed the analyses,and the 20 students who, without payment, took part in the study.
References 1. Pickup, J. F., Harris, E. K., Kearns, M., and Brown, S. S., Intraindividual variation of some serum constituents and its relevance to population-based reference ranges. Clin. Chem. 23,842 (1977).
2. Harris, E. K., Effects of intra- and inter-individual variation on the appropriate use of normal ranges. Clin. Chem. 20, 1535 (1974). 3. Statland, B. E., Winkel, P., and Bokelund, H., Factors contributing to intra-individual variation of serum constituents. 1. Within-day variation of serum constituents in healthy subjects. Clin. Chem. 19, 1374 (1973). 4. Statland, B. E., Winkel, P., and Bokelund, H., Factorscontributing
variation of serum constituents. 2. Effects of exerciseand diet on variation of serum constituents in healthy subjects. Clin. C/hem. 19, 1380 (1973). 5. Statland, B. E., Winkel, P., and Bokelund, H., Factors contributing to intra-individual variation of serum constituents. 4. Effects of posture and tourniquet application on variation of serum constituents to intra-individual
in healthy subjects. Clin. Chem. 20, 1513 (1974). 6. Winkel, P., Statland, B. E., and Bokelund, H., Factors contributing to intra-individual variation of serum constituents. 5. Short-term day-to-day and within-hourvariationof serum constituentsinhealthy subjects. Clin. Chem. 20, 1520 (1974). 7. Williams, G. Z., Young, D. S., Stein, M. R., and Cotlove, E., Biological and analytic components of variation in long-term studies of serum constituents in normal subjects. I. Objectives, subject selection, laboratory procedures and estimation of analytical deviation. Clin.
(‘hem. 16, 1016 (1970). 8. Harris, E. K., Kanofsky, P., Shakarji, G., and Cotlove, E., Studies of serum constituents in normal subjects.II. Estimating biological components of variation.Clin. Chem. 16, 1022 (1970).
9. Cotlove, E., Harris,
E. K., and Williams, G. Z., Biological and analytic components of variation in long-term studies of serum constituents in normal subjects. Ill. Physiological and medical implications. Clin. Chem. 16, 1028 (1970).
10. Winer, B. S., chap. 7 in Statistical Principles in Experimental Design, 1st ed., McGraw-Hill, New York, NY, p 3181. II. Wild ing, P., Zilva, J. E., and Wilde, C. E., Transport ofspecimens for clinical chemistry analysis.Ann. Clin. Biochem. 14, 301 (1977). l2. Ballantyne, F. C., Morrison, B. A., and Ballantyne, D., Effect of storage on estimatesof protein (‘him. Acta 87,455 (1978).
13.
Henry,
concentrations
in human plasma.
Clin.
R. J., Cannon,
(‘hemistrv, Principles York, NY, p 685.
D. C., and Winkelman, J. W., Clinical and Tech nics, 2nd ed., Harper and Row, New
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