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FLOW CYTOMETRY ANALYSIS USING SYSMEX UF1000I CHARACTERIZE UROPATHOGENS BASED ON 3
BACTERIAL-, LEUKOCYTE- AND ERYTHROCYTE COUNTS IN URINE SPECIMEN AMONG PATIENTS WITH 4
URINARY TRACT INFECTION 5
6
7
8
Tor Monsen1#
,, Patrik Ryden
2,3 9
1Department of Medical Microbiology, Umeå University, Sweden
. 2Department Mathematics 10
and Mathematical Statistics, Umeå University, University, Sweden. 3Computational Life 11
science Cluster (CLiC), Umeå University, University, Sweden. 12
13
14
15
16
# Corresponding author. 17
Tor Monsen, MD, PhD, associate professor, Department of Clinical Microbiology Umeå 18
University Hospital, and University of Umeå, SE-90185 Umeå, Sweden; 19
E-mail: [email protected] 20
21
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Short running headline: Flow cytometry, leukocyte, erythrocyte, uropathogens 24
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JCM Accepts, published online ahead of print on 3 December 2014J. Clin. Microbiol. doi:10.1128/JCM.01974-14Copyright © 2014, American Society for Microbiology. All Rights Reserved.
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Abstract 27
Urinary tract infections (UTIs) are the second most common bacterial infection. Urine culture is 28
gold standard for diagnosis but new techniques such as flow cytometry analysis (FCA) have 29
been introduced. 30
The aim of the present study was to evaluate FCA characteristics regarding bacteriuria, 31
leukocyteuria and erythrocyturia in relation to cultured uropathogens in specimens among 32
patients with suspected UTI We also wanted to evaluate whether the FCA characteristics can 33
identify uropathogens prior to culture. 34
From a prospective study, 1,587 consecutive urine specimens underwent FCA prior to culture 35
during January and February 2012. In- and outpatients (79.6% and 19.4%, respectively) were 36
included of whom women represented 67.5%. In total 620 specimens yielded growth of which 37
Escherichia coli represented 65%, Enterococci 8%, Klebsiella 7% and Staphylococci 5%. 38
For uropathogens the outcome of FCA was compared against the results for specimens with E. 39
coli and those with negative culture. E. coli had high bacterial- (median 17,914 /µL), leukocyte- 40
(348/µL) and erythrocyte counts (23/µL). With the exception of Klebsiella spp., the majorities of 41
uropathogens had considerable or significantly lower bacterial counts than E. coli. High 42
leukocyte counts were found in specimens with Staphylococcus aureus, Proteus mirabilis, 43
Pseudomonas aeruginosa and streptococci. For the three latter species and also Staphylococcus 44
saprophyticus elevated erythrocyte counts were found. 45
In essence, FCA adds new information of the bacterial-, leukocyte- and erythrocyte counts in 46
urine specimens for different uropathogens. Based on FCA characteristics, uropathogen can 47
be classified and identified prior to culture. E. coli and Klebsiella spp. have similar FCA 48
characteristics. 49
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Introduction 51
Urinary tract infections (UTIs) are caused by pathogenic microorganisms in the urinary tract 52
causing an inflammatory response with presence of red- and white blood cells in the urine. The 53
inflammatory response and clinical manifestations depends on the etiologic organism, the 54
severity of the infection and the immune status of the patient (1). 55
Urinary tract infections (UTIs) are the second most common bacterial infection and are 56
associated with high morbidity and costs. The annual incidence is estimated to more than 175 57
million UTI episodes worldwide. In US, UTI account annually for more than 7 million physician 58
visits, more than 1 million emergency department visits and more than 100,000 hospitalizations 59
(2, 3). 60
In outpatients UTI belong to the most frequent bacterial infections and antibiotics given for 61
treatment represent approximately 15% of all antibiotics prescribed to human in US, to an 62
estimated annual cost of > US $1 billion (3). In addition, the indirect annual cost is estimated to 63
approximately $1.6 billion (4). 64
Bacteria in urine can be classified in primary-, secondary-, tertiary- or doubtful uropathogens 65
according to their pathogen capacity, frequency of appearance or association with contamination 66
of urine specimens (5). E. coli is the most prevalent uropathogen and is responsible for 67
approximately 80% of lower UTI while S. saprophyticus, Klebsiella and Proteus spp. and other 68
uropathogens are less prevalent (6, 7, 8, 9, 10, 11), ECDC surveillance data 2012 69
(http://www.ecdc.europa.eu/en/publications/publications/annual-epidemiological-report-70
2012.pdf). E. coli is a more common cause of community- than nosocomial UTI (12, 13). 71
Urine culture is gold standard for diagnosis of UTI but culture is laborious, moderate costly 72
with a turnaround time of 24 to 48 hours. Recently fully automated and cost-effective diagnostic 73
instruments as flow cytometry analysis (FCA) have been introduced to improve the efficiency of 74
handling urine specimens. FCA makes it possible to rule out urine specimens which contain 75
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significant numbers of bacteria from those who do not. 76
The first generation automated FCA instrument, Sysmex UF50 (Medical Electronics, Kobe, 77
Japan) showed variable results but the next generation the Sysmex UF-500i and UF-1000i, have 78
improved sensitivity, specificity and a separate measurement channel for detection of bacteria 79
(14, 15, 16, 17, 18). In urine specimens, FCA identifies and enumerates bacteria, leukocytes, 80
erythrocytes and other cells. Culture negative specimens are identified and ruled out before 81
culture is performed which reduce the turnaround time, workload and cost (14, 15, 16). 82
However, the instrument has not been evaluated to predict identification of uropathogens prior to 83
urine culture. 84
The aim of the present study was to examine the FCA characteristics as bacterial-, 85
leukocyte- and erythrocyte counts associated with different uropathogens in urine specimens 86
among patients with suspected UTI. Moreover to evaluate whether the causative uropathogen 87
could be predicted in urine specimens prior to urine culture based on its FCA characteristics. 88
89
90
Material and Methods 91
Collection of Urine Specimens 92
During January and February 2012, 1,587 urine specimens from in- and outpatients were 93
collected in non-preservative tubes, stored and transported at <6ºC to the Department of 94
Clinical Microbiology Laboratory at University Hospital of Umeå for analysis. Specimens 95
were cultured within 3 hours after arrival to the laboratory and all specimens were from the 96
county of Västerbotten, Sweden. 97
98
Urinalysis 99
Prior to culture the urine specimens were analysed with flow cytometry (UF-1000i, Sysmex, 100
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TOA medical Electronics, Kobe, Japan). Specimens arrived after 4 PM were analysed and 101
stored at +60C until culture was performed the next morning. The instrument was supported 102
by the software version of 00-15. 103
In summary, the flow cytometry instrument aspirates urine which is split in two volumes in the 104
instrument prior to a fluorescent dyes staining. In the first volume, the sediment stain, 105
polymethine stains nucleic acid in the cells and in the second volume only nucleic acids in 106
bacteria are stained. After staining the specimen is delivered to the flow cell for particle analysis 107
by use of a red semiconductor laser. Particles are characterized according to impedance, 108
scattering and fluorescence light from forward- and side scatter lights. The forward scatter 109
provides information on particle size and the sides scatter information on the internal complexity 110
and the surface. In addition, fluorescence intensity provides information on the nucleic acid 111
content of each particle. 112
Particle concentration of counted bacteria, leukocytes and erythrocytes in urine specimens were 113
denoted U-bacteria, U-leucocytes and U-erythrocytes. 114
115
Culture and bacterial identification 116
Quantitative urine culture was performed by inoculation with a 10 µL calibrated plastic loop 117
(Sarstedt, Nurnbrecht, Germany) on cystine-lactose electrolyte-deficient (CLED) agar 118
(Acumedia Manufacturers, Inc. Baltimore, Maryland, USA). Agar plates were incubated in air 119
at 35° C for 18 to 20 h before counting of colony forming units (CFU/mL). 120
Species identification was performed as previously described (6). Briefly, Gram-negative and 121
Gram-positive uropathogens were identified by BrillianceTM
UTI agar (Oxoid Ltd, 122
Basingstoke, UK). Gram-negative bacteria were identified further with biochemical tests; 123
ornitine-, inositol and Triple sugar iron-test as described (19). Acinetobacter spp. were also 124
identified by species specific growth on CHROMagarTM
Acinetobacter (Chromagar, Paris, 125
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France). 126
Gram-positive bacteria were identified by catalase reaction. Staphylococci were identified 127
with species specific growth on CHROMagarTM
. In addition S. aureus was identified by its 128
DNAse activity. S. saprophyticus was identified by novobiocin susceptibility and coagulase 129
negative staphylococci other than S. saprophyticus were denoted “CoNS”. Enterococci and 130
streptococci were identified by esculin, agglutination to type specific serum (Streptex, Murex 131
Biotech Ltd. Dartford, England) and species specific growth on UTI-Brilliance agar. In 132
addition diagnosis of Streptococcus agalactiae (GBS) was supported by species specific 133
growth on chromagar (StrepB, Bio-Rad, Marns-la-Conquetta, France). 134
135
Inclusion criteria 136
Urine specimens yielding growth of >108 CFU/L of an identified pathogen were included 137
irrespectively of presence of UTI symptoms. Urine specimens yielding growth of 106
to 107 138
CFU/L of were included if reported presence UTI symptoms and/or laboratory tests indicating 139
UTI (nitrite test positive and/or moderate to high leukocyturia). Among these, specimens with 140
one pathogen were included as well as those with mixed flora containing a single dominating 141
pathogen (bacterial count at least 10 times higher than any other species which was judged as 142
the uropathogen and identified (6). Specimens with less than 106 CFU/L were classified as 143
negative cultures. Specimens from patients with urinary catheter, mixed flora without a 144
dominating uropathogen, pregnant women and specimens that lacked clinical information of 145
UTI were excluded. 146
147
Statistical analysis 148
All presented values are median values if not otherwise stated. Differences between 149
proportions were analyzed using the proportion z-test, Wilcoxon's rank sum test was used to 150
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compare differences between groups, and Spearman’s rank correlation was used to study the 151
dependencies between variables. The two-sided alternative hypothesis was used for all tests 152
and p-values < 0.05 were considered as significant. Importantly, we did not correct the p-153
values for multiple testing. We performed 220 tests looking at differences between 154
photogenes, negative controls and the dominating species E. coli, and 83 of those tests 155
resulted in a p-value < 0.05. The expected number of false positives is at most 11 (under the 156
extreme assumption that the null hypothesis is true for all tests) and a conservatively estimate 157
of the false discovery rate is 13.3%. If we assume that the null hypothesis is true for half of 158
the considered tests then an upper limit of the false discovery rate is 6.6%. In addition 108 159
direct comparisons between the photogenes were made and for those tests we presented the 160
observed p-values as well as the locally adjusted p-values obtained using Bonferroni 161
correction. For some bacteria/groups of bacteria the numbers of isolates were rather few and 162
the corresponding tests had relatively weak power. As a consequence, the observed p-values 163
were judge taking the sample size and the observed effect size into account. The uropathogens 164
were clustered using hierarchical clustering (using average linkage) based on the Manhattan 165
distance between the standardized U-bacterial-, U-leukocyte- and U-erythrocyte counts. The 166
R-package PVclust (20) was used to identify robust clusters in the observed dendrogram. All 167
statistical analyses were conducted using R version 2.9.1 (R Development Core Team, 2009). 168
169
170
Results 171
A total of 1,587 consecutive urine specimens from patients with suspected UTI were eligible 172
for urine culture and flow cytometer analysis. Of these 772 were excluded due to specimens 173
from urine catheters (125), mixed flora without a dominating pathogen (608), pregnancy 174
(128) and those without clinical information (5). The remaining 823 specimens were included 175
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of whom 620 were culture positive and 203 culture negative. The majority (67.5%, p < 0.001) 176
of specimens originated from women. The mean age for men and women was 61.9 (standard 177
deviation 20.8) and 59.9 (standard deviation 25.5) years, respectively. Outpatients represented 178
79.6% and inpatients 19.4%. Of the included specimens 54.4% yielded growth of > 108 179
CFU/L, 17.3% had 107-10
8 CFU/L, 4.4% had 10
6-10
7 and 24.9% were culture negative. 180
The dominating species was E. coli 64.5%, followed by Enterococcus spp. 8.2%, Klebsiella 181
spp. 7.2% and Staphylococcus spp. 5.0% (Table 1). 182
Among culture positive, 91% of specimens had 108, 7% had 10
7, 2% had 10
6 CFU/L of which 183
mixed flora was found in 17%, 53% and 0% of these specimens, respectively. Among patients 184
with 108 and <10
8 CFU/L, E. coli represented 65.6 and 63.4% of the uropathogens, 185
respectively. The distributions of uropathogens other than E. coli were also similar in both 186
groups. 187
Overall, specimens with gram-negative bacteria were associated with significantly (p <0.001) 188
higher U-bacterial counts (median 16,777/µL) compared with gram-positive bacteria 189
(2,271/µL). 190
We found significant correlations between: the concentration of uropathogens (bacteria/µL) 191
and U-leukocyte counts (Spearman’s rho = 0.26, p < 0.001), the concentration of U-bacteria- 192
and U-erythrocyte counts (Spearman’s rho = 0.15, p < 0.001) as U-leukocyte counts and U-193
erythrocyte counts (Spearman’s rho = 0.51, p < 0.001) (Figure 1 D-E). The outcomes of 194
bacterial-, leukocyte- and erythrocyte counts (particles/µL) for groups- or individual 195
uropathogens were compared against the FCA characteristics for E. coli as well as specimens 196
with negative culture (Table 1 and Figure 1-3). 197
Specimens with E. coli had high U-bacterial- (17,914/µl), U-leukocyte- (348/µL) and U-198
erythrocyte counts (23/µL) compared with culture negative specimens (33, 7 and 9/µL, 199
respectively), (Table 1). 200
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Among gram-negatives, urine specimens with Klebsiella spp. were associated with higher U-201
bacterial counts (24,240/µL, p=0.46) but lower U-leukocyte (160/µL, p < 0.05) and U-202
erythrocyte- (18/µL, p=0.67) counts than those with E. coli. Among Klebsiella, K. oxytoca 203
was associated with higher U-leukocyte counts than K. pneumoniae (351 vs 153/µL) but both 204
species had similar U-erythrocyte counts (16 and 17/µL, respectively), (Table 1). 205
In comparison, specimens with Citrobacter spp. (9 isolates) have significant lower U-206
erythrocyte counts (6/µL, p<0.05) and lower U-bacterial counts (8,405/µL, p=0.27) and U-207
leukocyte counts (144/µL, p=0.09) than E. coli. The 12 isolates of P. mirabilis had 208
significantly lower U-bacterial counts (1,956/µL, p < 0.05), higher U-leukocyte- (903/µL, p 209
0.48) and U-erythrocyte counts (52/µL, p 0.15) than E. coli. In contrast, P. vulgaris had 210
despite high U-bacteria counts (13,107/µL), low U-leukocyte- (79/µL) and high U-211
erythrocyte counts (197/µL). Of the 12 Pseudomonas isolates, 11 represented P. aeruginosa 212
which had significantly lower U-bacterial- (6,888/µL, p < 0.05), higher U-leukocyte counts 213
(1,278/µL, p=0.08) and significantly higher U-erythrocyte counts (73/µL, p < 0.05) than E. 214
coli (Table 1). 215
Among gram-positive bacteria, staphylococci were the second most common genus after 216
enterococci (31 isolates vs. 51). Staphylococci had significantly lower U-bacterial counts 217
(3,392/µL, p < 0.05) and higher U-leukocyte counts (466 /µL, p <0.05) - and U-erythrocyte 218
counts (24/µL, p=0.53) than E. coli. 219
Enterococci (E. faecalis and E. faecium, 42 and 9 isolates, respectively) were associated with 220
significantly lower bacterial counts (2,103/µL, p <0.05) than E. coli and E. faecalis had higher 221
U-leukocyte counts than E. faecium (200 vs. 34/µL, p 0.45). Alpha-haemolytic streptococci 222
and GBS were both associated with low leukocyte counts (64 and 36/µL, respectively) and 223
low erythrocyte counts (19 and 19/µL, respectively). However GBS had low bacterial counts 224
(272/µL). 225
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The relation between the most common uropathogens are summarised in a 3-dimensional plot 226
of the outcome of FCA (U-leukocyte-, U-erythrocyte- and U-bacterial counts) (Figure 2) and 227
relation between uropathogens is presented in the dendrogram (Figure 3). According to these 228
findings uropathogens could be classified into four groups (I-IV, Figure 3). The first group 229
consists of E. coli, K. pneumoniae and K. oxytoca, the second of P. aeruginosa, P. mirabilis, S. 230
aureus and the third of Citrobacter spp. Finally the fourth group consists of Alpha- 231
Streptococci, CoNS, E. faecalis, E. faecium, Morganella morganii, Enterobacter spp., GBS 232
and Citrobacter that cluster together with the culture negative specimens. 233
234
235
Discussion 236
In this study we evaluated the presence of leukocyte- and erythrocyturia for different 237
uropathogens among patients with suspected UTI measured by FCA analysis. In addition the 238
FCA results for different uropathogen were compared with E. coli, the most prevalent 239
uropathogen and to the culture negative specimens. 240
The distribution of uropathogens in the present study was consistent with previous reports 241
(6, 21). However, S. saprophyticus represented only <1% of the uropathogens but a similar 242
prevalence has been reported by others (22). The low prevalence of S. saprophyticus in the 243
present study is explained by the high mean age (59.9 year) of the included women and that 244
the study was performed during the winter season. In addition elderly are more likely to have 245
asymptomatic bacteriuria, altered sense of UTI symptoms and probably also a weakened 246
immune response (23), factors that differs from younger adults and may influence the 247
conclusions of the present study to an overall population of patients with UTI. Gram-positive 248
bacteria were often associated with lower bacterial counts than gram-negative bacteria 249
presumably because the former often form aggregates (staphylococci) or chains (streptococci) 250
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(24). The bacterial counts of aggregated bacteria may be underestimated by the instrument 251
and incorrectly reported with lower counts in contrast to gram-negative bacteria which are 252
present in the urine as single planktonic bacteria. In other studies, the urinalysis instrument 253
has been shown to correlate well to manual microscopy (25). 254
Bacterial-, leukocyte- and erythrocyte counts differ among gram-negative uropathogens. 255
Citrobacter were associated with nearly lack of erythrocyturia (<10 erythrocytes/µL) 256
indicating that Citrobacter are less: invasive, virulent or immunostimulating compared with 257
other uropathogens. In contrast, high erythrocyte counts were observed for P. vulgaris 258
(197/µL) and S. saprophyticus (154/µL). Whether the high erythrocyte count is an effect of 259
invasiveness or inflammatory response to an uropathogen or both, is unclear. However, both 260
these species are urease producers a property which has been reported as an important 261
bacterial virulence factor, essential for colonization and associated with gastric peptic ulcers 262
in man (26). For Pseudomonas and P. mirabilis we found high erythrocyte- and leukocyte 263
counts despite low bacterial counts. Virulence factors as exotoxins and at least four different 264
proteases have been reported in Pseudomonas that may cause bleeding and tissue necrosis 265
(27, 28). 266
However, specimens with high bacterial counts were associated with a high leukocyte and 267
erythrocyte counts (Figure 1 D-E) indicating that the bacterial load is of importance for the 268
inflammatory response of leukocytes and erythrocytes in urine during UTI. 269
Finally, U-leukocyte and U-erythrocyte counts for the most common uropathogen species 270
were plotted and presented in a 3 dimensional figure (Figure 2). As can be seen, E. coli and K. 271
pneumoniae/oxytoca have similar characteristics in the present study. However E. coli is by 272
far a more common cause of UTI and has virulence factors of importance that are not 273
measured by FCA (29). Despite this the FCA characteristics of the uropathogens differs from 274
the present Swedish classification in primary-, secondary- and doubtful uropathogens (5). In 275
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particular urine specimens with S. saprophyticus show lower U-leukocyte counts compared to 276
those with P. aeruginosa, S. aureus and P. mirabilis although S. saprophyticus is classified as 277
a primary UTI pathogen. 278
The fourth group of uropathogens represented by GBS, E. faecalis, Enterobacter spp. and M. 279
morganii is associated with low leukocyte and erythrocyte counts similar to what was seen in 280
culture negative specimens. 281
Urinalysis with automated FCA has four diagnostic potentials. First, the ability to separate 282
gram-negative- from gram-positive bacteria based on bacterial counts (30, 31). Secondly, to 283
predict bacterial species (e.g Citrobacter) or groups of bacteria (e.g. E. coli / Klebsiella). Such 284
information can assist the clinician in deciding which antimicrobial (or not) that should be 285
initiated for treatment pending the outcome of urine culture. Thirdly, the quality of a urine 286
specimen could be examined by the numbers of epithelial cells present in the specimen. High 287
epithelial cell counts indicate suboptimal sampling which may affect the interpretation of 288
culture results. Fourthly, the outcome of FCA can guide laboratory staff to improve diagnosis 289
in culture negative specimens with high U-leukocyte counts. In the present study 24.9% of the 290
specimens were culture negative, despite clinical signs of UTI, which is in accordance to 291
other studies (6, 32, 33). Culture negative specimens may be due to suboptimal culture 292
conditions in particular for anaerobic bacteria. In the present study 203 specimens were 293
culture negative of whom 30 and 22 specimens had more than 100 or 200 U-leukocytes, 294
respectively. In these specimens, an expanded urine culture protocol compared with standard 295
protocols should have been applied for detection of fastidious bacteria. 296
The Sysmex UF-1000 instrument also measures additional results than bacterial-, leukocyte- and 297
erythrocyte counts. Adding other FCA results (e.g. squamous cells, conductivity, pH etc) into 298
consideration might improve characterization and diagnosis of uropathogens. Inclusion of 299
improved staining techniques (fluorophores) that identify the four most prevalent uropathogens 300
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would identify nearly 90% of the causative uropathogens. Further studies are warranted to 301
improve diagnosis uropathogens in urine specimens using FCA and to confirm the results from 302
the present study, especially as some of the bacteria are present in a low number. 303
The urine specimens analysed in this study does (probably) not represent specimens from an 304
average population but rather specimens from a selected population of patients who were 305
examined due to suspected UTI, pyelonephritis, failure of treatment or control after treatment. 306
Contrary, the results are representative for urine specimens that are examined in our 307
laboratory. 308
In essence, except ruling out culture negative urine specimens, FCA improves handling of 309
urine specimens and diagnosis of UTI. The outcome of FCA adds information of the numbers 310
of uropathogens and the leukocyte- and erythrocyte counts in urine specimens among patients 311
with suspected UTI. According to these FCA characteristics, uropathogens can be classified 312
into four classes of which Klebsiella and E. coli had similar characteristics. Specimens 313
containing Citrobacter were associated with nearly absence of erythrocyturia. Urine specimen 314
examined by FCA may predict the causative uropathogen by its FCA characteristics which 315
may have clinical implications in guiding the clinicians towards appropriate antimicrobial 316
treatment pending culture results. 317
318
319
ACKNOWLEDGMENTS 320
We acknowledge Tamara Matti, Department of Infectious Diseases, University Hospital of 321
Umeå for support and registration of datasets and Dr. Kjell Leonardsson, Swedish University 322
of Agricultural Science, Umeå for the assistance in the presentation of Figure 2. The study 323
was financed by the University of Umeå, Sweden. 324
We declare no conflict of interest. 325
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326
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18. Wang J, Zhang Y, Xu D, Shao W, Lu Y. 2010. Evaluation of the Sysmex UF-1000i for the 376
diagnosis of urinary tract infection. Am J Clin Pathol. 133:577-582. 377
19. Burman LG, Ostensson R. 1978. Time- and media-saving testing and identification of 378
microorganisms by multipoint inoculation on undivided agar plates. J Clin Microbiol. 379
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20. Suzuki R, Shimodaira H. 2006. PVclust: an R package for assessing the uncertain in 381
hierarchical clustering. Bioinformatics Applications Note. 22:1540-1542 382
21. Nys S, van Merode T, Bartelds AI, Stobberingh EE. 2006. Urinary tract infections in 383
general practice patients: diagnostic tests versus bacteriological culture. J Antimicrob 384
Chemother. 57:955-958. 385
22. Barrett SP, Savage MA, Rebec MP, Guyot A, Andrews N, Shrimpton SB. 1999. Antibiotic 386
sensitivity of bacteria associated with community-acquired urinary tract infection in 387
Britain. J Antimicrob Chemother. 44:359-365. 388
23. Beveridge LA, Davey PG, Phillips G, McMurdo MET. 2011. Optimal management of 389
urinary tract infections in older people. Clinical Interventions in Aging 6:173-180 390
24. Versalovic J, Carroll KC, Funke G, Jorgensen JH, Landry MLL, Warnock DW. 2011. 391
Manual of Clinical Microbiology. 10th ed. Versalovic J, Carroll KC, Funke G, Jorgensen 392
JH, Landry MLL, Warnock DW, editors. Washington DC ASM Press, American Society 393
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25. Ottiger C, Huber AR. 2003. Quantitative urine particle analysis: integrative approach for 395
the optimal combination of automation with UF-100 and microscopic review with KOVA 396
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26. Konieczna I, Zarnowiec P, Kwinkowski M, Kolesinska B, Fraczyk J, Kaminski Z, 398
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Møller N. 2011. Characteristics of Escherichia coli causing persistence or relapse of 407
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particle analyzer UF-1000i screening for urinary tract infection in nonpregnant women. 411
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31. Wada A, Kono M, Kawauchi S, Takagi Y, Morikawa T, Funakoshi K. 2012. Rapid 413
discrimination of Gram-positive and Gram-negative bacteria in liquid samples by using 414
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Gai X, Wolfe AJ, Schreckenberger PC. 2014. Urine is not sterile: use of enhanced urine 419
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Microbiol. 52:871-876. 421
422
423
424
425
426
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Table 1 427
Bacteria-, leukocyte and erythrocyte counts (median values) in urine among patients with suspected urinary tract infection estimated by flow 428
cytometer analysis. 429
430
Group Bacteria Number Percentage
Positive
Cell counts – median value / µL
Bacterial cells WBCa RBC
b
ECc Escherichia coli
400 64.5 17,914 348 23
KCc
Klebsiella pneumoniae
Klebsiella oxytoca
Klebsiella ”other”
All Klebsiella spp.(Kd)
Enterobacter spp.
33
10
2
45
5
5.3
1.6
0.3
7.2
1.5
20,866
27,239
29,817
24,240
4,345
(+,+*)
(+,+)
(+,+*)
(-,+*)
(-,+*)
153
351
70
160
166
(-*,+*)
(+,+*)
(-,+)
(-*,+*)
(-*,+*)
16
17
55
18
30
(-,+)
(-,+)
(+,+)
(-,+*)
(+,+)
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Citrobacter spp.
Citrobacter freundi
Acinetobacter spp.
Pantoea spp.
Aggregated
9
1
1
1
62
0.2
0.2
0.2
0.2
10.0
8,405
15,220
163
7,143
15,346
(-,+*)
(-,+)
(-,+)
(-,+*)
(-,+*)
144
226
118
56
157
(-,+*)
(-,+)
(-,+)
(-,+)
(-*,+*)
9
7
24
15
17
(-*,+)
(-,-)
(+,+)
(-,+)
(-,+*)
PRc Proteus vulgaris
Proteus mirabilis
Morganella morganii
Providentia rettgeri
Aggregated
3
12
5
1
21
0.5
1.9
0.8
0.2
3.4
13,107
1,955
249
30,689
2,128
(-,+*)
(-*,+*)
(-*,+)
(+,+)
(-*,+*)
79
902
207
9
207
(-,+)
(+,+*)
(-,+*)
(-,+)
(-,+*)
197
52
19
8
38
(+,+)
(+,+*)
(-,+)
(-,-)
(+,+*)
PSc P. aeruginosa
Pseudomonas ”other”
Aggregated
11
1
12
1.8
0.2
1.9
6,888
3,467
5,177
(-*,+*)
(-,+)
(-*,+*)
1,278
294
1,175
(+,+*)
(-,+)
(+,+*)
73
12
62
(+*,+*)
(-,+)
(+*,+*)
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STc S. saprophyticus
d
S. aureuse
CoNS f
Aggregated
4
10
17
31
0.6
1.6
2.7
5.0
3,732
474
4,383
3,392
(-,+*)
(-*,+*)
(-*,+*)
(-*,+*)
200
936
462
466
(-,+)
(+,+*)
(+,+*)
(+,+*)
154
32
19
24
(+,+)
(+,+*)
(-,+*)
(+,+*)
ENc Enterococcus faecalis
Enterococcus faecium
Aggregated
42
9
51
6.8
1.5
8.2
2,623
1,116
2,103
(-*,+*)
(-*,+*)
(-*,+*)
200
34
120
(-*,+*)
(-,+*)
(-*,+*)
19
35
20
(-*,+*)
(+,+*)
(-,+*)
SRc Alpha-streptococci
Streptococci Group C
Streptococci Group A
Streptococci Group G
Gemella hemolysans
Aggregated
11
4
1
3
1
20
1.8
0.6
0.2
0.5
0.2
3.2
2,877
1,286
111
467
4,503
1,583
(-*,+*)
(-,+*)
(-,+)
(-,+*)
(-,+)
(-*,+*)
64
1,399
782
96
973
269
(-,+*)
(+,+*)
(+,+)
(-,+*)
(+,+)
(-,+*)
19
59
6
28
16
22
(-,+*)
(+,+)
(-,-)
(+,+)
(-,-)
(-,+*)
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GBc Streptococcus
agalactiae
20 3.2 272 (-*,+*) 36 (-*,+*)
19 (-,+*)
OTc Candida glabrata
Diptheroid rod
H. influenzae
Aggregated
1
1
1
3
0.2
0.2
0.2
0.5
518
18,266
2,263
2,263
(-,+)
(+,+)
(-,+)
(-,+*)
94
65
434
94
(-,+)
(-,+)
(+,+)
(-,+*)
4
40
108
40
(-,-)
(+,+)
(+,+)
(+,+)
NEc,g
Negative / No growth 195 NA 33 7 9
431
a WBC= white blood cells/ leukocytes;
b RBC= red blood cells/erythrocytes.
c denotes all uropathogens or group of uropathogens presented in the 432
right column. ddenote all Klebsiella species only (K);
e Staphylococcus saprophyticus;
f Staphylococcus aureus;
g Coagulase negative 433
staphylococci; f Negative control 434
“+” (“-“) indicates that the observed value is higher (lower) than the value observed for 435
E. coli / negative culture. * indicate that the corresponding p-value < 0.05. 436
437
438
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Figure 1 439
Bacterial- leukocyte and erythrocyte counts per microlitre (logarithmic scale with base 2) in 440
urine for uropathogens, groups of uropathogen and specimens with negative culture estimated 441
by flow cytometry analysis. 442
443
444
445
446
447
448
449
450
Figure A: log. bacterial counts vs. bacterial counts. Figure B: log. leukocyte counts vs. 451
bacterial counts. Figure C: log. erythrocyte counts vs. bacterial counts. Figure D: log. 452
leukocyte counts vs. bacterial counts. Figure E: log. erythrocyte counts vs. bacterial counts. 453
Figure F: log. erythrocyte counts vs. leukocyte counts /µl (logarithmic values) in urine. 454
EC = E. coli / lane 1 = E. coli (red colour in figure D-F); KC/2 = Klebsiella spp., Enterobacter 455
spp., Citrobacter spp., Acinetobacter spp., Pantoea spp. K = Klebsiella spp., PR/3 = Proteus 456
spp., Morganella spp. and Providentia rettgeri group; EN/4 = Enterococcus spp. group; PS/5 457
= Pseudomonas spp. group; ST/6 = Staphylococcus spp. group; SR/7 = Streptococci (A,C,G), 458
Alpha-haemolytic streptococci and Gemella hemolysans group; GB/8= Streptococci 459
agalactiae (GBS). NE/0 = specimens with negative culture (green colour, in figure D-F). 460
The median for E. coli and the negative culture are shown with solid and dashed lines (A-F) 461
respectively. 462
463
464
465
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Figure 2 466
Three dimensional plot of the median bacterial-, leukocyte- and erythrocyte counts per 467
microliter in urine estimated from flow cytometry analysis for different uropathogens among 468
patients with suspected urinary tract infection. 469
470
471
472
473
474
475
476
477
“Star” (in left lower corner) represents culture negative specimens. 478
Y-axis: RBC = erythrocyte blood cell counts/µl. X-axis: Bacterial counts/µl. Z-axis: WBC= 479
white blood cell counts/µl (leukocytes). Alpha-strep = alpha haemolytic streptococci 480
481
482
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Figure 3. 483
Dendrogram (hierarchical) presenting relationship between bacteria and bacterial clusters 484
based on bacteria-, leukocyte- and erythrocyte counts//µl (median values) for bacteria ≥5 in 485
numbers. 486
487
488
489
490
491
492
493
494
495
Dendrogram based on bacteria with ≥5 in numbers. * Presented order for au value (left) and 496
bp value (right). Clusters analysis on uropatogens (cluster I-IV). “High” au/bp values (%) 497
indicate robust clusters. 498
499
500
501
502
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05
10
15
EC KC K PR PS ST EN SR GBNE
Bac teria
log
Ba
cte
ria
l co
un
ts
05
10
EC KC K PR PS ST EN SR GBNE
Bac teria
log
Le
uko
cyte
co
un
ts
05
10
15
EC KC K PR PS ST EN SR GBNE
Bac teria
log
Ery
thro
cyte
co
un
ts
1
1
1
11
1 1
1
1
1
11
1
1
1
1
1
1
1
1
1
1
1
11
1
1
1
1
1
11
1
1
11
1
1
1
1
1
1
1
1
11
1
1
1
1
1
1
1
1
11
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1 1
11
1
1
1
1
1
11
1
1
11
1
1
1
1
1
111
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
11
11
1 1
1
11
1
1
1
11
1
11
1
1
1
1
1
11
1111
1
1
11
1
11
1
1111
1
1
11
1
11
11
1
1
1
11
1
1
1
1
11
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
11
1
1
1
11
1
1
1
1
11
1
1
11
1
11
1
1
1
1
1
1
1
1
1
1
1
11
1
1
1
1
1
11
1
11
11
1
1
1
1
1
1
1
1
1
1
1
11
1
1
1
1
1
1
1
1
11
11
1
1
11
1
1
1
1
111
1
1
1
1
11
1
1
1
1
1
111
1
11
11
1
1
11
11
1
1
1
1
11
1
1
1
1
1
11
1
1
1
1
1
1
11
11
1
1
1
1
1
11
1
1
1
1
1
11
1
1
1
1
1
1
1
11
1
1
1
1
1
11
1
1
1
1
1
1
1
1
1
11
1
1
1
1
1
1
11
1
1
1
1
1
11
1
1
1
1
1
1
2
2
222
2
2
2
2
22
2 2
2
2
2
2
22
2
2
22
2
22
2
2
2
2
22
2
2
2
22
2
2
22
2
2
2
2
2
2
22
2
22
2
2
2
2
2
2
2
2
2
3
3
3
3
3
33
3
3
33
3
3
33
3
3
3
3
3
3
4
4
4
4
4
4
4
4
4
4
4
4
5
5
5
5
55
5
5
5
555
5
55
5
55
5
5
5
5
5
5
55
5
5
5
5
5
6
6
6
6
6
6
66
6
6
66
6
66
6
6
6
6
66
6
6
6
666
666
6
6
6
6
6
66
66
6
66
6
6
6
6
6
6
6
6
6
7
7
777
7
7
7
7
77
77
7
7
7
7
7
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
88
8
8
0
0
0
0
0
0
0
000
0
0
0
0
00
0
0
00
000
0
0
0
000
0
000
0
0
000
0
0000
0
00
0000
0
0
00
0
0
00
0
0
0
0
0
0
0
0
0
0
0
00
0
0
0
0
00
00
0
0
00
00
0
0
0
00
0
0
0
0
0
0
0
0
0
00
0
00
0
0
0
0
0
00
0
0
0
000
0
0
0
00
0
0
0
0
00
0
0
0
0
000
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
00
00
0
00
0
0
0
0
0
00
0
00
000
0
0
00
0
0
0
0
0
0
0
log Bac terial counts
log
Le
uko
cyte
co
un
ts
4 6 8 10 12 14 16
02
46
81
01
2
1
11
1
11
1
1
1
1
1
1
1
1
1 1
1
1
1
11 1
1
11
1
1
1
1
11
1
1
1
111
1
111
1
1
1
11
1
11
1
1
1
11
1
1
1
1
1
1
111
1
1
1
11
1
11
1
11
1
1
11
1
1
1
1
1
1
11
1
1
11
11111
1
1
1
1
11
1
1
11
1
1
1
1
1
1
1
1
1
11
1
1
1
1
1
1 1
1 111
1
1
11
1
1
1
1
1111
11
11
11
11
1
11
1
111
1
11
1
111
1
11
1
1
1
111
1111
1
1
1
11
1
1
11
1
1
1
1
1
1
11
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
11
1
1
11
1
1
1
1
111
1
1
11
1
1
111
1
11
1
1
1
1
1
1
1
1
1
1
11
1
1
1
1
1
1
1
1
1
1
1
11
1
1
1
11
1
111
1
1
111
1
1
1
1
1
1
1
1
11
1
1
1
1
1
11
1
11
1
1
1
1
1
11
1
11
1
11
1
1
1
1111
1
1
1
11
11
1
1
11
111
1
1
11
11
1
1
1
1
1
1
11
1111
1111
1
1
1
1
11
1
1
1
11
1
1
1
1
1111
11
1
1
11111
1
1
1
11
1
1
1
1
1
1
11
1
11
1
1
1
1
2
2
2
222
2
2
22
2
2
22
22
2
2
2
2
2
2
22
2
2
2
2
222
2
2
22
2
22
22
2
2
22
2
2
2
2222
2
2
2
2
2
2
2
2
2
2
2
3
3
33
3
3
33
3
33
3
33
3
3
3
3
3
3
3
44
4
44
44
4
4
4
4
4
5
5
5
5
5
5
5
5
5555
5
55 5
5
5
5
5
5
5
5
555
5
5
5
5
5
6
6
6
66
6 6
6
6
6
6
6
66
666
6
6
66
6
6
6
6666
666
6
6
66
6
666
6
6
6
6
6
6
6
6
6 6
66
7
7
7
7
77
7
7
7 7
7
7
7
7
7
77
7
8
88
8
8
8
8
8
8
8
88
8
88
8
88
88
0
0
0
0
0
0
0
0
0
0
000
0
0
00
0
0
0
0
0000
0
0
0
00
0
0
00
000
0
0
0
000
0
000
0
0
000
0
0000
0
00
0000
0
0
00
0
0
000
0
0
0
0
0
0
0
0
0
0
00
0
0
0
0
00
00
0
0
00
00
00
0
00
0
0
0
0
0
0
0
0
0
00
0
00
0
0
0
0
0
00
0
0
0
000
0
0
0
00
0
0
0
0
00
0
0
0
0
000
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
000
00
0
00
0
0
0
0
0
00
0
00
000
0
0
00
0
0
0
0
0
0
0
log Bac terial counts
log
Ery
thro
cyte
co
un
ts
5 10 15
05
10
15
1
1
1
111
111
1
11111
1
11
1
1
1
1
1
1
1
1
111
11
1
1
111
1
1
1
11
1
1
1
1
11
11
1
1
11
1
1
111
1
1
11
1
1
1
1
1
1
1
1
1
1
11
1
111
1
1
11111
1111
1
1
1
11
1
1
1
1
1
1
1
1
1
1
1
1
11
1
11
1
111
1
1
11
11
11
1
11
11
1
1
1
1
1
1
1111
1
1
1
1
111
11
11
11
1
1
1
1
111
1
11
11
1
1
11
1
1
1
11
1
1
1
11111
1
1
111
1
1
1
111
11
1
1
1
1
1
11
1
1
1
1
1
1
1
1
11
11
1
1
1
1
111
1
1
1
1
1
11
1
11
1
1
1
11
111
11
1
1
1
1
1111
1
111
1
1
1
1
11
1
1
1
1
1
1
11111
1
111
1
1111
1
1
1
11
1
1
11
1
1
1
111
1
1
1
1
111
1
1
1
1
1
1
11
1
1
1
1
111
1
1
1
111
1
1
1
1
1
11
11
1
11
1
1
1
1
1
1
1
1
1
11
1
1
11
1
1
1
1
1
11
1
1
1
11
1
111
1
1
1
1
1
1
1
1
1111
1
1
1
1
1
1
1
1
1
1
11
1
1
11
1
111
1
1
1
1
1
2
2
2
22
2
2
2
2
2
2
2
2
22
22
2
2
2
2
2
2
2
2
2
22
222
2
2
2
222
2
2222
22
22
2
2
2
2
2
2
2
2
22
2
2
2
2
2
3
3
33
3
3
33
3
33
3
33
3
3
3
3
3
3
3
44
4
44
44
4
4
4
4
4
5
5
5
5
5
5
5
5
5555
5
55 5
5
5
5
5
5
5
5
555
5
5
5
5
5
6
6
6
6
6
6
6
6
6666
6
6
66
6
6
6
66
6
6
6
6
6
6
6
666
6
6
6
66666
6
6
6
6
66
6
6
6
666
7
77
7
7
7
77
7
7
7 7
7
7
7
7
7
77
7
8
88
8
8
8
8
8
8
8
88
8
88
8
88
88
000000000
000
0
00000
0
00
0
000
000
00
0
0000
00
0
00
0
00
0
0
000
0
0
00
0
000
0
000
0
0
000
0
000
00
00
0
0
0
0
0000
00
0
0
0
0
0
0
0
0
0
0
000
0
0
00
00
00
0
0
0
00
0
0
00
0
0
00
0
0
0
00
0
00
00
0
0
00
0
00
0
0
0
0
0
000
0 0
0
0
00
0
0
0
0
0
0
0
00
00
0
0
0
0
0
0
00
0
0
0
0
0
00
0
0
0
0
0
0
0
0
0
0
0
0
00
0
00
00
0
0
0
0
0
00
0
log Leukocy te counts
log
Ery
thro
cyte
co
un
ts
0 2 4 6 8 10 12
05
10
15
A B C
D E F on January 28, 2020 by guesthttp://jcm
.asm.org/
Dow
nloaded from
Escherichia coli
Pseudomoas aeruginosa
Klebsiella pneumoniaeKlebsiella oxytoca
Streptococcus Group C
Proteus mirabilisStaphylococcus aureus
Staphylococcus saprophyticus
Coagulase-negative staphylococci
Citrobacter spp.
Morganella morganii
GBS
Enterocuccus faecalisEnterobacter spp.
Enterocccus faecium
α-strept
RB
C
LK
C
Bacterial counts
Escherichia coli
Pseudomoas aeruginosa
Klebsiella pneumoniaeKlebsiella oxytoca
Streptococcus Group C
Proteus mirabilis
Staphylococcus aureusStaphylococcus saprophyticus
Coagulase-negative staphylococci
Citrobacter spp.
Morganella morganii
GBS
Enterocuccus faecalisEnterobacter spp.
Enterocccus faecium
α-strept
RB
C
WB
CBacterial counts
on January 28, 2020 by guesthttp://jcm
.asm.org/
Dow
nloaded from
au / bp *
97 70
96 70 85 58
42 100
91 36 3
3 22
85 53
62 33
85 53
41
79 30
66 92
22
99 on January 28, 2020 by guesthttp://jcm
.asm.org/
Dow
nloaded from
Table 1
Bacteria-, leukocyte and erythrocyte counts (median values) in urine among patients with suspected urinary tract infection estimated by flow
cytometer analysis.
Group Bacteria Number Percentage
Positive
Cell counts – median value / µL
Bacterial cells WBCa RBC
b
ECc Escherichia coli
400 64.5 17,914 348 23
KCc
Klebsiella pneumoniae
Klebsiella oxytoca
Klebsiella ”other”
All Klebsiella spp.(Kd)
Enterobacter spp.
33
10
2
45
5
5.3
1.6
0.3
7.2
1.5
20,866
27,239
29,817
24,240
4,345
(+,+*)
(+,+)
(+,+*)
(-,+*)
(-,+*)
153
351
70
160
166
(-*,+*)
(+,+*)
(-,+)
(-*,+*)
(-*,+*)
16
17
55
18
30
(-,+)
(-,+)
(+,+)
(-,+*)
(+,+)
on January 28, 2020 by guesthttp://jcm
.asm.org/
Dow
nloaded from
Citrobacter spp.
Citrobacter freundi
Acinetobacter spp.
Pantoea spp.
Aggregated
9
1
1
1
62
0.2
0.2
0.2
0.2
10.0
8,405
15,220
163
7,143
15,346
(-,+*)
(-,+)
(-,+)
(-,+*)
(-,+*)
144
226
118
56
157
(-,+*)
(-,+)
(-,+)
(-,+)
(-*,+*)
9
7
24
15
17
(-*,+)
(-,-)
(+,+)
(-,+)
(-,+*)
PRc Proteus vulgaris
Proteus mirabilis
Morganella morganii
Providentia rettgeri
Aggregated
3
12
5
1
21
0.5
1.9
0.8
0.2
3.4
13,107
1,955
249
30,689
2,128
(-,+*)
(-*,+*)
(-*,+)
(+,+)
(-*,+*)
79
902
207
9
207
(-,+)
(+,+*)
(-,+*)
(-,+)
(-,+*)
197
52
19
8
38
(+,+)
(+,+*)
(-,+)
(-,-)
(+,+*)
PSc P. aeruginosa
Pseudomonas ”other”
Aggregated
11
1
12
1.8
0.2
1.9
6,888
3,467
5,177
(-*,+*)
(-,+)
(-*,+*)
1,278
294
1,175
(+,+*)
(-,+)
(+,+*)
73
12
62
(+*,+*)
(-,+)
(+*,+*)
on January 28, 2020 by guesthttp://jcm
.asm.org/
Dow
nloaded from
STc S. saprophyticus
d
S. aureuse
CoNS f
Aggregated
4
10
17
31
0.6
1.6
2.7
5.0
3,732
474
4,383
3,392
(-,+*)
(-*,+*)
(-*,+*)
(-*,+*)
200
936
462
466
(-,+)
(+,+*)
(+,+*)
(+,+*)
154
32
19
24
(+,+)
(+,+*)
(-,+*)
(+,+*)
ENc Enterococcus faecalis
Enterococcus faecium
Aggregated
42
9
51
6.8
1.5
8.2
2,623
1,116
2,103
(-*,+*)
(-*,+*)
(-*,+*)
200
34
120
(-*,+*)
(-,+*)
(-*,+*)
19
35
20
(-*,+*)
(+,+*)
(-,+*)
SRc Alpha-streptococci
Streptococci Group C
Streptococci Group A
Streptococci Group G
Gemella hemolysans
Aggregated
11
4
1
3
1
20
1.8
0.6
0.2
0.5
0.2
3.2
2,877
1,286
111
467
4,503
1,583
(-*,+*)
(-,+*)
(-,+)
(-,+*)
(-,+)
(-*,+*)
64
1,399
782
96
973
269
(-,+*)
(+,+*)
(+,+)
(-,+*)
(+,+)
(-,+*)
19
59
6
28
16
22
(-,+*)
(+,+)
(-,-)
(+,+)
(-,-)
(-,+*)
on January 28, 2020 by guesthttp://jcm
.asm.org/
Dow
nloaded from
GBc Streptococcus
agalactiae
20 3.2 272 (-*,+*) 36 (-*,+*)
19 (-,+*)
OTc Candida glabrata
Diptheroid rod
H. influenzae
Aggregated
1
1
1
3
0.2
0.2
0.2
0.5
518
18,266
2,263
2,263
(-,+)
(+,+)
(-,+)
(-,+*)
94
65
434
94
(-,+)
(-,+)
(+,+)
(-,+*)
4
40
108
40
(-,-)
(+,+)
(+,+)
(+,+)
NEc,g
Negative / No growth 195 NA 33 7 9
a WBC= white blood cells/ leukocytes;
b RBC= red blood cells/erythrocytes.
c denotes all uropathogens or group of uropathogens presented in the
right column. ddenote all Klebsiella species only (K);
e Staphylococcus saprophyticus;
f Staphylococcus aureus;
g Coagulase negative
staphylococci; f Negative control
“+” (“-“) indicates that the observed value is higher (lower) than the value observed for
E. coli / negative culture. * indicate that the corresponding p-value < 0.05.
on January 28, 2020 by guesthttp://jcm
.asm.org/
Dow
nloaded from
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