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Journal of Clinical Microbiology, December 1998, p. 3624-3628, Vol. 36, No. 12
0095-1137/98/$04.00+0
Copyright © 1998, American Society for Microbiology. All rights reserved.
Pooling of Urine Samples for Screening for Neisseria
gonorrhoeae by Ligase Chain Reaction: Accuracy and
Application
Katherine A.
Kacena,1,2
Sean B.
Quinn,2
Suzanne C.
Hartman,2
Thomas C.
Quinn,2,3 and
Charlotte A.
Gaydos2,*
Division of Disease Control, International
Health, School of Hygiene and Public Health,1
and
Division of Infectious Diseases, School of
Medicine,2 The Johns Hopkins University,
Baltimore, and
The National Institute of Allergy and
Infectious Diseases, National Institutes of Health,
Bethesda,3 Maryland
Received 12 June 1998/Returned for modification 30 July
1998/Accepted 9 September 1998
 |
ABSTRACT |
The accuracy of detection of genital Neisseria
gonorrhoeae infection in pooled urine samples by ligase chain
reaction (LCR) was examined in three populations. Firstly, urine
specimens from 300 female military recruits (FMR) were tested by LCR
individually and in pools of four and six. Secondly, 300 urine
specimens from middle-school students (MSS) were tested
individually by LCR, and then the processed specimens were stored
frozen for subsequent testing in pools of 4 and 10. Thirdly, 600 frozen
urine specimens from high-school students (HSS) were tested by
using the LCR pooling algorithm, i.e., testing processed specimens in
pools of four in one test unit dose, and retesting individual specimens
from positive pools. Finally, the pooling algorithm results were
compared to culture results for a subset of 344 students from the
original 600 HSS from whom cervical or urethral samples were taken at
the discretion of the school nurse practitioners. Compared to
individual testing of specimens by LCR in the FMR population, the
pooling-by-four algorithm was 100% sensitive (5 of 5) and 100%
pool specific (70 of 70), and the pool-by-six algorithm was 100%
sensitive (5 of 5) and 100% pool specific (45 of 45). In the MSS
population, the pool-by-4 algorithm was 95.8% sensitive (23 of 24) and
100% (52 of 52) pool specific, and the pool-by-10 algorithm was 95.8%
sensitive (23 of 24) and 100% (17 of 17) pool specific. In the subset
of 344 HSS from whom endocervical or urethral specimens were collected for culture, 31 were positive by LCR in urine and 26 were positive by
culture. After results discrepant between culture and LCR were adjudicated by a confirmatory LCR test, the pooling algorithm was
93.8% (30 of 32) sensitive and 99.7% (311 of 312) specific. Culture
from these 344 HSS was 81.3% (26 of 32) sensitive. The pooling algorithm reduced the cost of the N. gonorrhoeae LCR assay by 60% compared to individual testing of
the HSS specimens and was both sensitive and specific.
 |
INTRODUCTION |
Twenty-two states in the United
States still report gonorrhea rates above the Healthy People 2000 national objective of 100 cases or fewer per 100,000 persons
(3). Furthermore, in certain geographic regions and among
non-Hispanic blacks, the gonorrhea rate is up to 10 times higher than
the national goal (3). It is estimated that annually there
are 62 million incident gonorrhea cases worldwide (15), of
which 800,000 occur in the United States (5).
Neisseria gonorrhoeae infections are frequently
asymptomatic, particularly in women (5). Women are at risk
of developing long-term sequelae from the infection, including pelvic
inflammatory disease, chronic pelvic pain, ectopic pregnancy, and
infertility. Perinatal transmission can lead to ophthalmia neonatorum
(5). Treatment of gonorrhea reduces genital shedding of
human immunodeficiency virus type 1 (HIV-1) in coinfected males
(2), and there is epidemiologic evidence of decreased HIV
transmission efficiency when coinfected subjects receive gonorrhea
treatment (9). Routine screening and treatment of high-risk
individuals could prevent transmission to sexual partners, sequelae due
to infection, and perinatal transmission and could reduce sexual
transmission of HIV.
The traditional "gold standard" for detection of N. gonorrhoeae has been culture; however, culture requires
clinician-obtained cervical or urethral specimens and strictly
controlled conditions during transportation of specimens (10,
14). The ligase chain reaction (LCR) test has been shown to be
highly sensitive and specific for the detection of N. gonorrhoeae infection (1, 13). One advantage of LCR is
that it can be used to detect gonorrhea in first-catch urine (FCU),
which avoids invasive sample collection procedures. The sensitivities
and specificities of LCR of FCU are 98.0 and 100% in men and 94 to 95 and 100% in women, respectively (12, 13). The reported
sensitivity of culture of cervical- or urethral-swab samples compared
to LCR of FCU for the detection of N. gonorrhoeae was
95.9% in men but only 84 to 95% in women (12, 13). The LCR
test of FCU targets the opa gene, which has as many as 11 copies per N. gonorrhoeae genome, thus increasing sensitivity (11).
Although the cost of LCR is higher than that of culture, an algorithm
of testing processed specimens in pools and then retesting specimens
from presumptively positive pools individually could significantly
decrease the assay cost of this expensive diagnostic test, as has been
shown for Chlamydia trachomatis LCR (6). In this
study, we examined the accuracy of procedures involving pooling of FCU
specimens for the detection of N. gonorrhoeae by LCR
compared to individual testing of specimens by LCR. We then applied the
pooling algorithm, i.e., testing processed specimens which had been
collectively pooled into one single test unit dose and retesting
individual specimens from each positive pool, to determine the
prevalence of gonorrhea in a high-school population. Additionally, we
compared the results of the urine LCR pooling algorithm for the
detection of N. gonorrhoeae with those of culture for a
subset of patients from whom cervical- or urethral-swab samples had
been taken for culture.
 |
MATERIALS AND METHODS |
Study populations, specimen handling, and testing.
As part
of ongoing studies designed to prevent pelvic inflammatory disease, FCU
specimens were collected from three study populations. Subjects were
asked to collect 15 to 20 ml of urine from the first part of the urine
stream, after having not urinated for at least 2 h. A variety of
pretesting storage conditions and populations were studied to determine
the effect of freezing of both unprocessed urine and processed urine on
the accuracy of the pooling algorithm, as well as the effect of the
prevalence of N. gonorrhoeae infection (Table
1).
FMR.
FCU specimens (n = 300) from young
adult female military recruits (FMR) were processed and tested
individually for detection of N. gonorrhoeae by LCR.
Processed samples were stored at 4°C and were retested 2 to 3 days
later in 75 pools of four and in 50 pools of six. Thus, these samples
were never frozen (Table 1).
MSS.
Three hundred (never frozen) FCU specimens from female
and male middle-school students (MSS) were processed and tested
individually during 1996 to 1997, and the remaining processed specimens
were stored at
70°C. After that school year's collection was
completed, the frozen processed specimens were thawed and retested in
75 pools of 4 and 30 pools of 10. Thus, these samples were frozen after
processing (Table 1).
HSS.
FCU specimens (n = 600) from sexually
active female and male high-school students (HSS) were collected during
the 1996-to-1997 school year and stored as unprocessed urine at
70°C. For a subset of 344 subjects, at the time of the visit for
urine specimen collection, a cervical or urethral swab was obtained, at
the discretion of the school nurse practitioners, for culture of
N. gonorrhoeae by standard methods (10, 14).
After the school year's collection was completed, the urine samples
were thawed, processed, and tested for gonorrhea by LCR in 150 pools of
four. Processed urine specimens from presumptively positive pools
(i.e., pools with LCR sample/cutoff ratios [S/CO] of
0.8) were
retested individually to complete the pooling algorithm. Thus, these
urine samples were frozen before the processing step (Table 1).
Pooling algorithm definition.
The pooling algorithm is a
two-step testing procedure whereby specimens are first tested in
pools of two or more in a single test unit dose. Specimens from pools
which test negative (S/CO < 0.8) are all considered negative.
Specimens from positive pools are retested individually to determine
which specimen(s) in the pool is (are) positive. The number of
specimens tested in each pool is dependent on the prevalence of the
organism in the population and may range from 2 to 10.
Urine specimen processing for LCR.
Urine specimens
from the three study populations were collected, transported, and
processed according to the manufacturer's instructions for the
urine-based LCR assay for N. gonorrhoeae (Abbott
Laboratories, Abbott Park, Ill.). One milliliter of each urine specimen
was centrifuged at
9,000 × g for 15 ± 2 min at room temperature. The supernatant was removed, and the pellet was resuspended into 1.0 ml of LCR urine specimen resuspension buffer
and vortexed. Preparations were then heated at 97 ± 2°C for
15 ± 1 min to extract the DNA.
LCR assay setup, DNA amplification, and detection.
Specimens
were amplified individually by LCR, according to the manufacturer's
instructions. When specimens were tested individually, a volume of 100 µl of each processed urine specimen was placed into its own LCR
gonorrhea amplification vial (unit dose). For pooling by four, 25 µl
of each of the four processed specimens was placed into a single unit
dose. For pools of six, 17 µl of each of the six processed specimens
was placed into a single unit dose. For each pool of 10, 10 µl of
each of 10 processed specimens was placed into a single unit dose. The
total volume of the specimen(s) was then 100 µl for each unit dose.
Two negative controls, two positive calibrators, and a positive
processing control were included in every amplification run in
accordance with the manufacturer's instructions.
Unit dose tubes containing DNA preparations were amplified in an LCR
thermocycler (Abbott Laboratories) under the following conditions: 40 cycles of denaturation (at 93°C for 1 s), annealing (at 59°C
for 1 s), ligation (at 62°C for 1 min 10 s), and soaking (at 25°C). Amplified DNA was detected in an LCR automated machine which performed a particle-based enzyme immunoassay with a fluorescent signal. For individually tested samples, an S/CO of
1.2 was
considered positive, and borderline-negative samples (S/CO of
0.8 and
<1.2) were retested, as specified by the manufacturer. Retested
specimens were considered positive if the S/CO was
1.2. For the
pooling algorithm, specimens from pools with S/CO of
0.8 were
retested individually as described above.
Culture.
Urethral swabs from males and endocervical swabs
from females were cultured at the Maryland State Health
Laboratory on selective medium (Thayer-Martin agar) by standard
techniques (8). Suspicious colonies were tested by an
oxidase assay and a Gram stain. Oxidase-positive, gram-negative
diplococci were confirmed by a direct fluorescent antibody (DFA)
test (Syva, San Jose, Calif.) as N. gonorrhoeae. If the
DFA was negative, two additional tests, a latex agglutination test
(Gonogen; Becton Dickinson, Cockeysville, Md.) and a carbohydrate fermentation test (Quadraferm; Biomerieux, Marcy l'Etoile, France), were used to identify N. gonorrhoeae isolates.
Adjudication of discordant pooling algorithm LCR and culture
results for HSS.
Culture-positive specimens for N. gonorrhoeae were considered to be true positives. Discrepant
specimens which were culture negative and urine LCR positive were
retested by a second urine LCR using different probes (targeting the
pilin gene) by Abbott Laboratories. If the pilin gene LCR was positive,
the discrepant specimen was resolved as a true positive. If the pilin
gene LCR was negative, the original positive LCR was considered to be a false positive. The positive gold standard or positive "patient infection status" was considered to be either a positive culture or a
culture-negative, LCR-positive result that was resolved as a true
positive by the pilin gene LCR test. Discrepant specimens which were
culture positive and LCR negative were retested by the original
opa gene LCR and were also tested by the pilin gene LCR,
although the results were not used for adjudication, i.e., the original
LCR-negative results were considered false negatives.
Cost analysis.
A model was developed to determine the pool
size that yielded the greatest cost savings. Binomial distribution was
used to estimate the number of pools that would be likely to be
positive given a selected pool size and population disease prevalence. Next, the optimal pooling number for a range of disease prevalences was
calculated. For a dichotomous outcome (i.e., a positive or negative
test result for a genital N. gonorrhoeae infection), independence was assumed (i.e., the order of the samples received was
random with regard to the distribution of the positive or negative
samples in the population). The expected percentage of positive pooled
assays was determined by the equation s = [1
(1
r/n)c] × 100%, where s is the
expected number of positive pools, r is the number of
positive samples tested, n is the total number of samples
tested, r/n is the prevalence of disease, and c
is the number of specimens pooled (7). This equation
accounted for the probability that 1 to c samples in the
pool were positive. The calculated cost of the amplification unit dose
per individual LCR test was $6.32, which included the cost of positive
calibrators, negative controls, and positive processing controls
(6).
 |
RESULTS |
Sensitivity and specificity of the pooled assays in FMR and MSS
populations.
Testing of processed (never frozen) FMR specimens
pooled by four was 100% sensitive (5 of 5) and 100% pool specific (70 of 70) compared to individual testing. Testing of processed FMR
specimens pooled by six was also 100% sensitive (5 of 5) and
100% specific (45 of 45). Testing of MSS specimens which were
stored frozen and pooled by four was 95.8% sensitive (23 of 24) and
100% (52 of 52) pool specific. Testing of MSS specimens pooled
by 10 was 95.8% sensitive (23 of 24) and 100% (13 of 13) specific
(Table 2). Although in the MSS group the
pool-by-4 and pool-by-10 testing algorithms each missed one positive
specimen (1 of 24), each algorithm missed a different specimen.
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TABLE 2.
Accuracy of detection of genital N. gonorrhoeae infection by LCR testing of pooled urine samples
compared to individual testing of specimens
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|
Comparison of testing of specimens by using the LCR pooling
algorithm with culture for HSS.
The prevalence of N. gonorrhoeae in the subset of 344 HSS by the pooling algorithm was
7.1% (23 of 322) in females and 36.4% (8 of 22) in males (Table
3). The prevalence of N. gonorrhoeae by culture was 5.9% (19 of 322) in females and 31.8%
(7 of 22) in males. Two female subjects who had culture-positive
specimens had urine specimens which were negative by the LCR pooling
algorithm. For the two female subjects who were culture positive and
LCR negative, the repeat testing by LCR targeting the opa
gene was positive, as was the LCR targeting the pilin gene. Seven
subjects (six female and one male) had urine specimens that were
positive by the LCR algorithm but had negative culture specimens.
Six of the seven discrepant results (from five females and one male) were adjudicated as true positives, and one was not confirmed and was
considered to be a false positive after testing by the LCR targeting
the pilin gene. The specimen was also negative when retested by
the original LCR targeting the opa gene. After the resolution of discrepant results, the performance characteristics of the pooling algorithm for the subset of 344 HSS specimens cultured for gonorrhea were 91.7% (22 of 24) sensitivity and 99.7% specificity for females and 100% (8 of 8) sensitivity and 100% specificity for males (Table 4). Culture from these
344 HSS was 79.2% (19 of 24) and 87.5% (7 of 8) sensitive for females
and males, respectively (Table 4).
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TABLE 3.
Comparison of pooled algorithm testing of urine by LCR
with culture for the detection of N. gonorrhoeae
after analysis of discrepancies for 344 HSS
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TABLE 4.
Resolved performance characteristics of the LCR urine
pooling algorithm and culture for the detection of N. gonorrhoeae after analysis of
discrepant resultsa
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|
Cost savings and public-health implications.
By using only the
LCR pooling algorithm, the prevalence of N. gonorrhoeae
in the entire HSS population was 6.5% (39 of 600). In the
subset of 344 specimens which were also cultured, 30 of 31 (96.8%) LCR-positive specimens were adjudicated as true
positives. However, screening of the 256 students who were not
tested by culture detected eight additional LCR-positive
specimens, seven of which were confirmed by a second LCR test targeting
a different gene (i.e., the pilin gene). The unconfirmed positive
specimen was considered to be a false positive.
Thus, the pooling algorithm identified 37 positives which could be
confirmed, detected 2 positives which could not be confirmed, and
failed to detect 2 confirmed positives. Cultures performed in the HSS
population at the discretion of the nurse practitioners detected only
26 positives among 344 students cultured. Thus, screening everyone by
using the urine LCR pooling algorithm detected 11 more of the 39 confirmed positives than culturing selected patients only. When the
pooling algorithm was used, 306 assays were performed to test 600 specimens, including the retesting of positive pools. The overall assay
cost per specimen tested with the pooling algorithm was half (51%) the
assay cost per specimen tested individually. Figure
1 demonstrates the expected unit dose cost savings at different population prevalences.

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FIG. 1.
Cost-saving ability of pooling of processed urine
specimens before performance of the urine LCR test for the detection of
N. gonorrhoeae infections. The graph shows the cost in
U.S. dollars (USD) per amplification unit dose when the pooling
algorithm was used, depending on the number of specimens per pool and
taking into account various prevalences of infection in the population
screened. A baseline total cost of $6.32 per unit dose was used.
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|
 |
DISCUSSION |
Pooling of processed urine specimens for detection of
N. gonorrhoeae by LCR produced accurate results
compared to results of individual testing of specimens by LCR.
The cutoff ratio of the LCR test for the pooled samples was not
reduced from the cutoff for individual specimens, as was necessary in
the pooled chlamydia testing described previously (6). The
high sensitivity and specificity of LCR were not affected by pooling of
as many as 10 samples, whether they were stored frozen or were never
frozen. Freezing of processed or unprocessed urine samples had no
effect on the accuracy of testing of pooled samples. Consequently, the pooling algorithm could be used in laboratories with a high volume of
samples or in laboratories conducting epidemiological research where
specimens are stored frozen and tested at a later time.
It is unknown why one LCR pooling algorithm-positive specimen was
unable to be adjudicated as a true positive. This specimen was
pool positive and individual test positive but negative when tested
later for adjudication by both the opa and the pilin gene LCR. N. gonorrhoeae from cervical or urethral swabs of
patients with low levels of infection seems less likely to be cultured successfully. Similarly, low levels of target DNA in processed specimens could be less likely to be able to be amplified over time and
after multiple cycles of freezing and thawing. Although it cannot be
determined, it is possible that this specimen was from a patient with a
low organism load. Because it was unable to be adjudicated, it was
considered to be a false-positive result in this study according to our
definition of a true positive.
A theoretical concern is that pooling would dilute the low-level
positive sample below the limit of detection of the assay. However,
review of the manufacturer's data presented in the package insert from
individually tested specimens (n = 3,362)
indicated that "low-positive" samples (with S/CO of
<2.0) constituted only 3.3% of positive specimens. In the FMR
and MSS data presented in this paper, none of the specimens were low positives.
A potential limitation of the pooling algorithm is the chance for
technician error in the pooling of processed samples in the LCR run.
The use of tray maps simplifies this process. We have used the
following process for eliminating technician error. Samples are be
organized by skipping a space after each pool group in the specimen
rack. Thus, pooling adds no significant complexity to the process of
setting up individual unit dose assays. Additional technician error can
be avoided when samples from presumptively positive pools (detected in
the previous run) are retested individually at the beginning of the
batch before the routine testing of the new pool groups. Therefore,
each run has a combination of samples that are retested individually
and new pooled samples from the next group of specimens.
Pooling is a technique which could be used in high-volume laboratories
such as state public-health labs and reference labs for significant
cost savings. Public-health screening programs which are
currently using culture can benefit from the ease of specimen
collection, higher sensitivity, and lower cost of pooled LCR.
Specific populations or laboratories that might benefit from pooling
include any laboratory where, as a minimum, both turnaround time and
volume allow for a combination of 19 pools and retests per day. With 96 specimens at a population prevalence of about 4%, pooling by 6 would
allow for the completion of one full run (38 test unit doses) per day.
The run would theoretically include, on average, 16 pools of 6 and 22 individual retests.
Use of the pooling algorithm could benefit investigators and program
planners in two ways: (i) money saved by using the pooling algorithm
could be applied to other areas of disease prevention, and/or (ii) the
amount of money allocated to screening would allow more specimens
to be tested for the same total cost. Pooling of urine samples for the
detection of genital N. gonorrhoeae infection is a
cost-saving strategy, simple to perform, and could be applicable in
screening programs in the United States and in population-based research worldwide. In addition, a combined chlamydia and gonorrhea detection program which uses pooling of processed urine
specimens for LCR testing could be used in populations at
significant risk for both pathogens and would detect most infections
for less cost, since the same processed urine specimen can be used for
both the chlamydia and gonorrhea LCR tests. Although not considered
here, technician cost can be estimated as previously described in
detail for LCR pooling for the detection of chlamydia (12).
Running specimens pooled for both chlamydia and gonorrhea testing by
LCR would most significantly reduce technician time, specimen
processing costs, and LCR assay costs.
Laboratory managers should consider two points before using pooling.
First, processed specimens from presumptive positively pools need to be
amplified and detected individually. This additional step adds a
minimum delay of 3 h to the laboratory turnaround time until
individual test results on specimens in presumptively positive pools
are known. Second, the estimated cost savings to be gained for a
particular laboratory depend on a combination of the salaries of
technicians and their benefits, institutional overhead, and the
prevalence of gonorrhea in the populations the laboratory serves.
Pooling of samples from patients in a population where the prevalence
of gonorrhea may be 20% or greater is not advised and would be
minimally cost saving. The pooling algorithm would be cost saving at
lower prevalences of infection.
The study laboratory has met Clinical Laboratory Improvement Act
requirements for the modification of a manufacturer's package insert
directions for performance of a test by a clinical laboratory using a
diagnostic kit cleared by the Food and Drug Administration. The
investigators considered the performance and documentation of the
required study adequate for using the pooling algorithm protocol in
testing of clinical specimens in the study laboratory. Each laboratory
that wishes to introduce pooling must meet the requirements set forth
to modify the package insert from a test cleared by the Food and Drug
Administration. These requirements are explained more fully as
regulations set forth in the Federal Register (4).
Pooling of processed urine samples for LCR testing of
N. gonorrhoeae will decrease the cost of screening,
providing more evidence to health planners that screening programs can
and should be implemented. An additional application of pooling
of urine specimens by LCR is the detection of genital
C. trachomatis infections (6). The
cost savings of pooling of urine for both N. gonorrhoeae and C. trachomatis should also be
considered. Although LCR failed to detect two cervical
culture-positive specimens, this strategy of screening everyone in a
population by testing urine specimens detected 11 more of the 39 true
positives (28.2%) than the strategy of performing culture on specimens
collected from the portion of females who received pelvic examinations
where cervical swabs were taken or on specimens from males where
urethral swabs were obtained due to their clinical presentation of
signs and symptoms. Screening of urine from sexually active students by
using the pooling algorithm was more sensitive (92 and 100%) than
culture (79 and 88%) in women and men, respectively, and more cost
saving than performing individual LCR assays for N. gonorrhoeae.
In conclusion, the LCR urine pooling algorithm for the detection of
N. gonorrhoeae was accurate compared to testing of
specimens individually and selective culturing of specimens, and it
could be used as a cost-saving public-health measure for screening of populations at risk for gonorrhea, especially when a cervical or
urethral swab cannot be obtained.
 |
ACKNOWLEDGMENTS |
We thank Guillermo Madico for review of the manuscript; J. Mehsen
Joseph of the Maryland State Health Laboratory for the culture results;
Susan Olson and Patricia Plier of Abbott Laboratories for performance
of the pilin gene LCR assays; Sandra Leister and Jennifer Girdner for
laboratory support; Dorothy Ellis for the collection of data and
specimens from the FMR population; Alain Joffe, Geraldine Waterfield,
and Patricia Hauptman of the Baltimore City Health Department
School-Based Health Centers for collaboration in the schools; and
Annette Baldwin, Kristen Byrnes, Gloria Conner, Laura Davidson,
Bernadette Deely, Sharon Hobson, Nancy Kilbane, Maureen Rochelle,
Catherine Searson, Helen Thomas, and Nancy Woodhead for the collection
of specimens and data in the MSS and HSS populations in the
school-based clinics.
 |
FOOTNOTES |
*
Corresponding author. Mailing address: The Johns
Hopkins University, Division of Infectious Diseases, Ross Research
Bldg., Room 1159, 720 Rutland Ave., Baltimore, MD 21205. Phone: (410) 614-0933. Fax: (410) 614-9775. E-mail:
cgaydos{at}welchlink.welch.jhu.edu.
 |
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Journal of Clinical Microbiology, December 1998, p. 3624-3628, Vol. 36, No. 12
0095-1137/98/$04.00+0
Copyright © 1998, American Society for Microbiology. All rights reserved.
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