Concept of segmentation in nosocomial epidemiology: Epidemiological relation among antimicrobial-resistant isolates of Pseudomonas aeruginosa

Journalof Infection (1997) 35, 269-276

Concept of Segmentation in Nosocomial Epidemiology: Epidemiological Relation among Antimicrobial-resistant Isolates of Pseudomonas aeruginosa M. Kinoshita 1, E. Sawabe 2, and N. Okamura .1 tDepartment of Clinical/Microbiology and Immunology, School of Allied Health Sciences, Faculty of Medicine, and 2Clinical Microbiology Laboratory, University Hospital, Tokyo Medical and Dental University, 1~5~45 Yushima, Bunkyo-ku, Tokyo 113, Japan Typing studies on 271 clinical strains of Pseudomonas aeruginosa isolated from the University Teaching Hospital were conducted to obtain their serotypes, antimicrobial susceptibility patterns and plasmid profiles. These strain typing data were arranged through multivariate statistical analysis by computation to classify individual strains. Plots in the scatter diagrams obtained from both principal component analysis and quantification theory type III expressed the clinical strains of P. aeruginosa with various degrees of antimicrobial resistance. Epidemiological relation among these clinical strains was analysed in those scatter diagrams by segmentation, in combination with their epidemiological information (date and place of isolation, type of specimen, etc.). The results showed that the serotype E strains both with high-level resistance to gentamicin and with a plasmid of 3.9 x 106 dalton, and the strains resistant to more than five antimicrobial agents, were colonized and localized each in certain clinical wards for inpatients. It was suggested that segmentation analysis could be of practical use in the management of nosocomiai infection control against P. aeruginosa with antimicrobial resistance.

Introduction Pseudomonas aeruginosa is one of the most common pathogens affecting patients with compromised immunity and those with cystic fibrosis. 1,2 The problem regarding nosocomial infection by P aeruginosa, especially with antimicrobial resistance, has thus come to occupy an important position in epidemiological investigation in hospitals. 3,4 For epidemiological purposes there are several methods for ~;yping P. aeruginosa stains, such as serotype, susceptibility to bacteriophages or to antimicrobial agents, profiles of bacteriocin (pyocin) production or of plasmids, and restriction fragment length polymorphism of chromosomal DNA. s-9 Each of these methods has been reported to be effective in certain clinical settings or communities. However, there have been few reports on nosocomial epidemiology in which both typing data on P. aeruginosa strains and epidemiological information are compiled and integrated in such a way as to make a comprehensive judgment on the control of P. aeruginosa infection. Segmentation is defined as that process by which * Address all correspondence to: N. Okanmra, School of Allied Health Sciences, Faculty of Medicine, TokyoMedical and Dental University, 1-5-45 Yushima, Bunkyo-ku,Tokyo 113, Japan. Accepted for publication 28 February 1997. 0163M:453/97/060269 +08 $12.00/0

samples are classified into a number of subgroups (segments) based on the analysis of multi-dimensional variables.l°'n It has as its objective the grouping of individual samples so that we can allocate our effort proportionately to the present and/or future worth of the group, and so that the responses to our efforts will be similar. Thus, ideally the response will be literally the same within the segment, but will vary substantially among segments. This implies that different types and amounts of eflbrt will be directed at different segments. All these ideas could be of practical use in the management of infection control against some pathogenic bacteria even in a hospital. Here we report a new approach, segmentation, lbr epidemiological estimation of clinical isolates of R aeruginosa with various degrees of antimicrobial resistance. The results, obtained by compiling and integrating the data obtained by three different typing methods, could be satisfactorily explained at sight in the segmentation scheme.

Materials and Methods Bacterial strains A total of 2 71 strains of P. aeruginosa out of 233 patients were isolated between 1 April 1993 and 10 March 1994 © 1997 The British Societyfor the Study of Infection

270

M. Kinoshita et aL

Table 1. Antimicrobial susceptibility of 271 clinicaI isolates of P. aeruginosa to: gentamicin GM), amikacin (AMK),piperacillin (PIPC), ceftazidime (CAZ),cefsulodin (CFS), aztreonam (AZT), oIloxacin (OFLX),tosufloxacin (TFLX)and imipenem (IPM). Antimicrobial agent

Range

GM AMK PIPC CAZ CFS AZT OFLX TFLX IPM

0.2 ->100 3.13 0.78 ->100 6.25 0.1 ->100 3.13 0.2 ->100 1.56 0.2 ->100 3.13 0.05 ->100 6.25 _<0.025->100 1.56 _<0.025->25 0.39 _<0.025->100 1.56

MIC (gg/ml) 50% 90% 25 25 50 6.25 12.5 25 6.25 3.13 12.5

Breakpoint of antimicrobial resistance >-12.5 >50 >_100 >_25 _>50 _>25 >- 6.25 >~ 3.13 >-12.5

from eight clinics for outpatients and 15 clinical wards for inpatients in the university hospital. In principle, one strain per patient was selected as far as there was no difference in serotypes among strains from the same patient. Escherichia coli V517 and K-12 W677(NR1) were also used as the sources of size reference markers of plasmid DNA, All of the strains were maintained in skimmed milk at - 80 °C.

Tokyo), and imipenem (IPM; BANYU Pharmaceutical Co., Ltd., Tokyo) were used in this study.

Plasmid profiling Plasmid DNAs were extracted by the alkaline sodiumdodecyl-sulfate lysis method of Kado and Liu, ~s with minor modifications. The samples (20#1) were mixed with 2 #1 of bromocresol purple (0.25% in 50% glycerol0.05 M Tris-acetate pH 7.9), and electrophoresed through 0.7% agarose gel in a Tris-borate-EDTA buffer (pH 8.0). The gel was run at 100 V for 1.5 h at room temperature. The plasmid DNA samples from E. coli V5179'16 and K12 W677(NR1) were used as plasmid reference markers. The measurement of migration distances of DNA bands and the size estimation of plasmids were done according to the method of Macrina et al. 16

Data set To describe the relationships among clinical isolates, their epidemiological information was collected on the basis of the following items: date (time series) and place (23 categories) of isolation, type of specimen (39 categories), and supplementary information on patients (ex. sex and age).

SerotBping Based on serotyping as described by H o m m a et al., ~2'13 a slide agglutination test using viable bacteria was done. An 18 h nutrient agar culture (at 37 °C) of each strain was used as antigen, and a set of 14 monoclonal antibodies (MAbs) (Meiji Seika Co., Tokyo) was used.

Antimicrobial susceptibity testing Antimicrobial susceptibility testing was done by the agar dilution method,14 using Mueller-Hinton agar (Difco) with a final inoculum of 5 x 103 CFU. The m i n i m u m inhibitory concentration (MIC) was defined as the lowest drug concentration that inhibited the visible growth of E aeruginosa after 1 8 - 2 0 h at 37 °C. The MIC breakpoint of each antimicrobial agent (Table I) was difined according to the references previously described. 7 As antimicrobial agents, gentamicin (GM; Schering-Plough K.K., Osaka), amikacin (AMK; BANYU Pharmaceutical Co., Ltd., Tokyo), piperacillin (PIPC; Toyama Chemical Industries Co., Tokyo), ceftazidime (CAZ; Nippon Glaxo Co., Ltd., Tokyo), cefulodin (CFS; TAKEDA Chemical Industries Ltd., Osaka), aztreonam (AZT; Eisai Co., Ltd., Tokyo), ofloxacin (OFLX; DAIICHI Pharmaceutical Co., Ltd., Tokyo), tosufioxacin (TFLX); Toyama Chemical Industries Co.,

Multivariate statistical analysis Statistical data processing of the results obtained from serotyping, antibiogram typing and plasmid profiling were performed by using a commercial computer-software HALBAU (version 4.1: Gendaisugaku-sha, Tokyo). As a data reduction technique to 'summarize' the results on scatter diagrams, principal component analysis (PCA) was performed on the original data matrix of antimicrobial susceptibility patterns 17'1s in order to analyse the data derived from multivariate normal distribution. Quantification theory type III (QTIII), which is the same method as dual scaling in correspondence analyses, was applied to a contingency table including all the response data from serotyping, antimicrobial susceptibity testing and plasmid profiling. 19-21

Clustering-based segmentation By clustering-based segmentation] °'11'22 the formation of each segment was done with a view towards clustering plots according to their patterns of distribution in the scatter diagrams obtained from both PCA and QTIII. In association with the epidemiological information, the

Segmentation in Nosocomial Epidemiology

271

Table 1I. Frequency of isolation of P. aeruginosastrains with antimicrobial resistance to: gentamicin (GM), amikacin (AMK), piperacillin (PIPC), ceftazidime (CAZ), cefsulodin (CFS), aztreonam (AZT), ofloxacin (OFLX), tosufloxaein (TFLX) and/or imipenem (IPM). Serotype A B C I) E F G H I K M UT* Total %

Number of resistant/number of strains tested (%) 0/17 (0) 4/20 (20.0) 4/10 (40.0) 1/6 (16.7) 29/49 (59,2) 8/15 (53,3) 18/53 (34.0) 2/7 (28.6) 11/32 (34.4) 1/2 (50,0) 12/24 (50.0) 20/36 (55.6) i10/271 (40.6)

GM

AMK

PIPC

Number of strains resistant to: CAZ CFS AZT OFLX

TFLX

IPM

0 2 1 0 17 6 4 1 2 0 5 3 41 15.1

0 0 0 0 2 3 1 0 0 0 4 2 12 4.4

0 0 3 0 6 3 2 2 4 0 2 3 25 9.2

0 0 3 0 1 1 1 2 2 0 3 3 16 5.9

0 1 0 O 8 5 4 0 2 0 5 5 30 11.1

0 2 1 1 13 1 6 0 2 0 2 12 40 14.8

0 0 2 0 0 3 2 1 2 0 2 4 16 5.9

0 0 2 1 6 5 4 2 3 1 4 10 38 14.0

0 2 4 1 12 6 11 0 5 0 8 10 59 21.8

*UT: Untypable.

considerable characteristics of e a c h s e g m e n t were exa m i n e d to decide w h a t to use as a basis for m o r e detailed s e g m e n t a t i o n . There were some s e g m e n t s suggesting the localization of some specific strains w i t h a n t i m i c r o b i a l resistance. S e g m e n t a t i o n w a s carried o u t a g a i n in terms of k)calization in the s a m e scatter d i a g r a m s (Figs 1, 2).

Results Serotype Serotypes of all 271 clinical isolates were G (19.6%), E (18.1%), Untypable (13.3%), f (11.8%), M (8.9%), B (7.4%), A (6.3%), F (5.5%), C (3.7%), H (2.6%), D (2.2%) a n d K (0.7°/0) in o r d e r of f r e q u e n c y of isolation. Strains with serotypes J, L a n d N were n o t detected.

Antimicrobial susceptibility The results of the a n t i m i c r o b i a l susceptibility test are s h o w n in Table fI. Based on the breakpoints, the relative isolation f r e q u e n c y strains w i t h i n the s a m e serotype was d e t e r m i n e d (Table [). The total n u m b e r of a n t i m i c r o b i a l resistant strains w a s 110 (40.6%). Serotypes of t h e resistant strains were E (59.2%), U n t y p a b l e (55.6%), F (53.3%) a n d M (50.0%), in order of isolation frequency of resistant strains w i t h i n the s a m e serotype. No resistant strain w i t h serotype A w a s detected. Serotype E was the factor significantly associated w i t h a n t i m i c r o b i a l resistance to GM (P
Segmentation in scatter diagrams obtained from PCA PCA s u m m a r i z e d 2 4 3 9 (271 x 9 ) d a t a points into a smaller n u m b e r of linear c o m b i n a t i o n s of the original d a t a points w i t h o u t distorting the relations a m o n g the original variables. The four first principal c o m p o n e n t s (PCs) a c c o u n t e d for 82.7% of the variance. The eigenvalue of the fourth principal c o m p o n e n t (PC) was ;~ = 1.018. Figure 1 shows the result of the a n t i m i c r o b i a l susceptibility test w h i c h was a n a l y s e d in terms of localization b y s e g m e n t a t i o n in two of the six scatter d i a g r a m s obtained from PCA. In Fig. 1A, the first PC s h o w n on the horizontal axis was a size factor, expressing the fact t h a t the m a i n variability a m o n g the samples consists of the g e n e r a l level of the a n t i m i c r o b i a l resistance to n i n e antimicrobial agents. The fourth PC s h o w n on the vertical axis described differences in the a n t i m i c r o b i a l resistance to some agents. The plots r e p r e s e n t i n g the a n t i m i c r o b i a l susceptible strains c o n c e n t r a t e d on the left side of the h o r i z o n t a l axis as a cluster (segment S), being m o r e or less a w a y from the point O. In contrast, the plots r e p r e s e n t i n g the a n t i m i c r o b i a l resistant strains were scattered to the right on the h o r i z o n t a l axis further a w a y from the s e g m e n t S, reflecting various degrees of a n t i m i c r o b i a l resistance to all the agents. They were also distributed u p w a r d or d o w n w a r d on the vertical axis, reflecting m a i n l y the relative degrees of a n t i m i c r o b i a l resistance to GM vs. AZT a n d IPM. The f o r m a t i o n of segments was t h e n performed first at the points further a w a y from the point O of the scatter d i a g r a m , t h a t is, the points with high-level a n d / o r multiple a n t i m i c r o b i a l resistance. As in Fig. 1A, there were 17 multiple resistant

M. Kinoshita e t al.

272

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Figure 1. Clustering of P. aeruginosa strains in the scatter diagrams obtained from principal component analysis (PCA). (Q) Susceptible; (A) resistant to antimicrobial agents. S, segment of antimicrobial susceptible strains; MR-l, segment of multiple resistant strains to more than five antimicrobial agents (MRs) originating from ward 5; MR-2, MRs originating from ward 12; GR, segment of high-level resistant strains to GM (MIC >100) originating from wards 5, 9, 12, and ICU.

strains to more than five antimicrobial agents observed in this investigation. In all these multiple-resistant strains, six strains originating from ward 5 (segment MR-l) and seven strains from ward 12 (segment MR-2) were clustered as each segment. Others were isolated each from the ward numbers 3, 9, 11, and 15. The wards 3, 5, 9, 11, 12, and 15 were clinical wards for inpatients. In Fig. 1B, the second PC shown on the horizontal axis expressed a relative scale of antimicrobial resistance to fluoroquinolones vs. PIPC, CAZ, CFS and AZT. The second and fourth PCs were shape factors. The segment S of antimicrobial susceptible strains was located around the centre of the diagram. Although antimicrobial susceptible strains were isolated from all clinical wards and outpatient clinics except ward number 24, there were no statistical relationships between their serotypes and their place of isolation. In contrast, antimicrobial resistant strains were scattered in all directions further away from the segment S around the point O, reflecting the various degrees of antimicrobial resistance. Clustered plots in the oval (segment GR) shown in both Fig. 1A and 1B represented high-level resistant strains to GM (MIC >100). All of these strains were

isolated from the four clinical wards for inpatients and belonged to the serotype E.

Plasmid profile Fourteen plasmids different in their molecular weight were detected in 46 strains (Table III), and a total of 17 different plasmid profiles were observed (Table IV). A plasmid with molecular wt. of 3.9 x 106 dalton (D-coded one), was detected each in a total of 11 strains which belonged to the segment GR in Fig. 1A and lB. All of these strains belonged to the serotype E, and had highlevel resistance to GM (MIC>IO0), as mentioned above. The restriction patterns of each plasmid by restriction enzyme Sau3AI were also the same in these strains (data not shown).

Segmentation in scatter diagrams obtained from QTIII Figure 2 shows one of the scatter diagrams obtained from the calculations of scores assigned to a total of 271 isolates through QTIII. Being similar to the first PC in

Segmentation in Nosocomial Epidemiology Table III. Fourteen plasmids detected in 46 clinical isolates of R aeruginosa. Plasmid code

Molecular weight*

Number of strains (%)

a B C D E F G H I

1.4 2.0 2.9 3.9 4.4 13.9 16.7 26.2 32.3

9 (3.3) lO (3.7) 3 (1.1) 11 (4.1) 1 (0.4) 2 (0.7) 2 (0.7) 2 (0.7) 2 (0.7)

j

61.4

2 (0.7)

79.8 101 120 i55

3 (1.1) 6 (2.2) 7 (2.6) 2 (0.7) 46 (17.0)

K L M N Total * x 106 dalton.

PCA, horizontal axis (I) was estimated to express the fact that the main variability among the samples consists of the general level of the antimicrobial resistance to all the agents. Vertical axis (IV) was also estimated to reflect each relative scale of resistance to GM vs. fluoroquinolones. As shown in Fig. 2, a configuration of samples was supplied by clustering and scaling technique. Plots representing antimicrobial susceptible strains were scattered on the left side, and resistant strains on the right side of the horizontal axis. Clustered plots in the two ellipses (GR-1 and GR-2) in the upper side of Fig. 2 were all serotype E strains with both D-coded plasmid (3.9 x 104 dalton) and high-level resistance to GM (MIC>100). The D-coded plasmid was significantly associated with resistance to GM (MIC> 100) (P
273

As for the multiple-resistant strains to more than five antimicrobial agents, 13 strains were isolated from wards 5 and 12, and four strains which were isolated each from four wards were grouped as segments (segments MR-l/2 and MR-3). In contrast to the GM-resistant strains in the segment GR-1 and GR-2, the multiple resistant strains with serotype F in the segment MR-l/2 had also been detected in our hospital between June 1991 and April 1992 (Table V). 7 Table V summarizes the characteristics of the E aeruginosa strains in the segments GR-1 and MR-l/2. In the segment GR-1, statistical localization of the GM-resistant strains with serotype E in [CU and ward 9 suggests colonization of the particular strain(s) in these places. From ward 9 a multiple-resistant strain was also isolated (MR-3 in Fig. 2). In the segment MR-l/2, 13 muultipleresistant strains were isolated from wards 5 and 12. As each number of multiple-resistant strains was small, it was uncertain whether they were actually colonized in these environments. In addition, the GM-resistant, serotype E strains with D-coded plasmid were also isolated from wards 5 and 12 (GR-2 in Fig. 2).

Discussion Although multivariate statistical analyses such as cluster analysis have often been used 2>2s for the epidemiological study of the population structure of clinical strains, we showed, in the present report, another approach which permitted us to discover epidemiological relationship among P. aeruginosa strains with various degrees of antimicrobial resistance in our hospital. Our approach was the application of 'segmentation' in the scatter diagrams obtained from both PCA and QTIII. The reasons why we chose this approach were as follows. Firstly, in nosocomial epidemiology, the previous approach to examining raw data directly was limited in efficiency by the number of samples and typing methods. For nosocomial infection control especially, a rapid comprehensive judgment with high objectiveness was required to evaluate the results obtained by several typing methods. According to our approach, all the results obtained from the three typing methods could be satisfactorily and quickly explained at sight without misjudgment (Fig. 2). Secondly, it was difficult to find rapidly what remarkable relation there was by the previous approach. Our present approach with clustering-based segmentation permitted us to discover it rapidly. Thirdly, in nosocomial epidemiology, we had to look at all the strains of P. aeruginosa isolated in our hospital as the 'mass', which lacked homogeneity in its response to our attempt for infection control, because the behaviour of bacteria was complex and there was no

274

M. Kinoshita et aL

Table IV. Seventeen plasmid profiles observed in 4 6 clinical isolates of E Plasmid profile

Pattern

Serotype

GM

I

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A

.

i

G

+

II

H

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H CEM

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+ --

IV

V

VI

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Antimicrobial resistance pattern* AMK

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46

* + : Resistant; - - : susceptible. Plasmid code. U T , Untypable.

1

simple relationship between our effort for infection control and the eradication of pathogens. Furthermore, in trying to eliminate the pathogens in a certain way, infection control practice obviously had to be operated within certain limitations of action. According to our approach, we could select more important strains among all the strains isolated instead of approaching them all equally. This could be of practical use in the management of nosocomial infection control. As for the plots in the scatter diagrams obtained from PeA and QTIII, there was the following characteristic; the more antimicrobial-resistant the strains were, the further away distributively outside from the point O they spread in the diagrams. Because antimicrobial resistance in R aeruginosa is important as far as the nosocomial colonization and/or infection was concerned, we first

sought to find the epidemiological relationship among high-level and/or multiple antimicrobial resistant strains by using segmentation. With the characteristics in the scatter diagrams described above, we picked up the plots located further away from the point O and carried out segmentation with relative ease. Although almost the same result was obtained both with PeA and QTIII for more objective estimation, we thought it important to use more than two multivariate statistical analyses in drawing the scatter diagrams. Typing studies performed on clinical strains without any epidemiological information may not be desirable. Strain typing data as response data do not substitute for epidemiological information. 26 The two data sets should be developed independently but analysed together to determine whether a remarkable epidemiological relation exists. This implies

Segmentation in Nosocomial Epidemiology IV

that the typing studies are undertaken to obtain the response data, which are then analysed with epidemiological information together by clustering-based segmentation• In summary, by using this approach, remarkable relations among R aerugiosa with antimicrobial resistance could be determined rapidly. Our approach is concise and convenient for practical use, and appears to be suitable for those who are dealing with a large number of samples on a day-to-day basis in a hospital.

[

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Acknowledgments

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1/2

We t h a n k T. Fukanoki, O. S a k a m o t o and T. Chida for their t e c h n i c a l assistance.

References 1 Speert DP, Campbell ME. Hospital epidemiology of Pseudomonas aeruginosa from patients w i t h cystic fibrosis. ] Hosp Infect 1 9 8 7 ; 9: 11-21. 2 Zimakoff J, Hoiby N, Rosendal K, Guilbert JR Epidemiology of Pseudomonas aeruginosa infection a n d the role of c o n t a m i n a t i o n of the e n v i r o n m e n t in a cystic fibrosis clinic. ] Hosp Infect 1 9 8 3 ; 4: 31-40. 3 Podersen SS, Koch C, Hoiby N. A n epidemic spread of m u k i r e s i s t a n t Pseudomonas aeruginosa in a cystic fibrosis centre. I Antimicrob Chemother 1 9 8 6 ; 17: 5 0 5 - 5 1 6 . 4 R i c h a r d P, Le Floch R, C h a m o u x C, P a n n i e r M, Espaze E, Richer H. Pseudomonas aeruginosa o u t b r e a k in a b u r n unit: role of antimicrobials in the e m e r g e n c e of multiply r e s i s t a n t strains. ] Infect Dis 1 9 9 4 ; 170: 3 7 7 - 3 8 3 . 5 The I n t e r n a t i o n a l Pseudomonas aeruginosa ~ p i n g Study Group. A m u l t i c e n t e r c o m p a r i s o n of m e t h o d s for t y p i n g strains of Pseudomonas aeruginosa p r e d o m i n a n t l y from patients w i t h cystic fibrosis ] Infect Dis 1994; 169: 1 3 4 - 1 4 2 .

- 5 . 0 - ] R e s i s t a n t to AZT and fluoroquinolones

Figure 2, Clustering P, aeruginosa strains in the scatter d i a g r a m s obtained from. quantification t h e o r y type III (OTII1). A n t i m i c r o b i a l susceptible ( Q ) a n d r e s i s t a n t (A) strains were scattered, reflecting the various degrees of a n t i m i c r o b i a l resistance, serotype, a n d the presence of plasmids. M R - l / 2 , s e g m e n t of multiple r e s i s t a n t strains to more t h a n five a n t i m i c r o b i a l a g e n t s (MRs) o r i g i n a t i n g from w a r d s 5 a n d 12; MR-3, MRs o r i g i n a t i n g from w a r d s 3, 9, 11 a n d 15; GR-1, s e g m e n t of serotype E strains w i t h D-coded plasmid a n d w i t h high-level resistance to GM (MIC > 1 0 0 ) o r i g i n a t i n g from ICU a n d w a r d 9; GR-2, s e g m e n t of the strains w i t h the s a m e characteristics as GR-1 o r i g i n a t i n g from w a r d s 5 a n d 12. N u m b e r s (3, 6) in the s e g m e n t GR-1 express the n u m b e r of isolated strains.

Table V, A n t i m i c r o b i a l resistance p a t t e r n s of R aeruginosa strains in the s e g m e n t s GR-1 and M R - l / 2 .

Segment

Clinical ward

Serotype

GM

AMK

GR-1

Number 9

E

+I

.

e

+~

-

ICU

E

+ ]

.

E

+~

-

+$

.

Number 5

F H M UT[[ C E F F M UT

+ +

---

-

-

+/+/+ + + + --

+/ -+ + + --

+ + +/+ + ÷ --+ +

+ + + + + + -+ +

MR-I/2

N u m b e r 12

* + : Resistant; -- : susceptible; + / - : J" MIC: > 1 0 0 Bg/ml. SMIC: 1 0 0 I~g/ml. § - : No plasmids. ]1UT: Untypable.

PIPC .

A n t i m i c r o b i a l resistance pattern* CAZ CFS AZT OFLX

.

.

+$ .

.

r e s i s t a n t or susceptible.

.

. .

.

.

.

.

.

.

.

.

.

.

. + + + + + ---+

TFLX

. + + + + + + + + + +

. + . + + -k + + --

.

. + + + + --

IPM

Plasmid profile

N u m b e r of strains

+

IV

4

+

IV

2

+

IV

2

+

iv

1

-

--§

+/+ + -+ +

-VIII --

1 1 2 2 2 1 1 1

.

1

1

276

M. Kinoshita et al.

6 Bergan T. Epidemiological markers for Pseudomonas aeruginosa. Acta Path Microbiol Scand Section B 1973; 81: 70-101. 7 Sawabe E, Shiraki M, Thoi H et al. Serotypes and antimicrobial susceptibilities of 250 isolates of Pseudomonas aeruginosa strains. Jpn J Med Technol 1994; 43:1040-1044 (in Japanese). 8 Fyfe JA, Harris G, Govan ]RW. Revised pyocin typing method for Pseudomonas aeruginosa. J Clin Microbiol 1984; 20: 47-50. 9 Poh CL, Yap EH, Tay L, Bergan T. Plasmid profiles compared with serotyping and pyocin typing for epidemiologcal surveillance of Pseudomonas aeruginosa. ] Med Microbiol 1988: 25: 109-114. 10 Katahira H. Market segmentation. In: Katahira H, ed. Marketing science 3rd ed. Tokyo: University of Tokyo Press, 1991:97-122 (in Japanese). 11 Wind Y. Issues and advances in segmentation research. J Market Res 1978; 15: 317-337. 12 Homma ]Y. Designation of the thirteen O-group antigens of Pseudomonas aeruginosa; an amendment for the tentative proposal in 1976. Jpn J Exp Med 1982; 52: 317-320. 13 Homma JY, Ghoda A. Goto S e t al. (The Serotyping Committee for the Japan Pseudomonas aeruginosa Society). Proposal of an international standard for the intraspecific serologic classification of Pseudomonas aeruginosa. Jpn J Exp Med 1979; 49: 89-94. 14 Mitsuhashi S, Goto S, Jo K et al. Revised version of the standardization method for determination of minimum inhibitory concentrations (MIC). Chemotherapy (Tokyo) 1981; 2 9 : 7 6 - 7 9 (in Japanese). 15 Kado CI, Liu S. Rapid procedure for detection and isolation of large and small plasmids. J Bacteriol 1981; 145: 1365-1373. 16 Macrina FL, Kopecko DJ, Jones K, Ayers D], McCowen SM. A multiple plasmid-containing Escherichia coli strain: Convenient source of size reference molecules. Plasmid 1978; 1: 417-420. 17 Boot R, Thuis H, Wieten G. Multifactorial analysis of antibiotic

18

19

20 21 22

23 24

25

26

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