Antibiotic resistance evolution among E. coli strains causing

urinary tract infections 

Author: Sándor Szabolcs - student

Coordinator: Dr. Barabás Hajdu Enikő – Assistant Professor

Urinary tract infections (UTI) are one of the most common type of bacterial infectious diseases. They are most common in infants and people over the age of 70, and predominantly affect women. [1]

Statistically every 2nd adult woman is affected by UTI once in her lifetime. [2]

The #1 cause for UTI is E. coli infection.

Introduction

The aim of this study was to:1. Assess the resistance of E. coli strains

towards certain antibiotics. 2. Evaluate the evolution of antibiotic

resistance over the course of approximately 3 years.

Aim

In this retrospective study we analyzed a sample of 510 bacterial cultures positive for E. coli infection for which antibiotic sensitivity tests (AST) were performed between 1st May 2012- 1st March 2015

Materials and Methods

Samples were considered positive if the culture resulted in > 100.000 CFU/ml. [3]

Cultures having lower values were excluded We excluded ESBL (beta lactamase enzyme)

and Hodge (carbapenemase enzyme) positive strains

Statistical software: Graphpad Statistical test: linear regression

Materials and Methods

We followed:1. resistant cases per month and year,2. evolution of resistance during a year and

its possible connection with both time and seasons,

3. maximum number of resistant strains and their possible connection with both time and/or seasons.

Materials and Methods

The analyzed antimicrobial drugs were:1. Ampicillin (AMP) 2. Amoxicillin (AMC)3. Cephotaxime (CTX)4. Cephtadizime (CAZ)5. Cephuroxim (CXM)6. Cephepime (FEP)7. Gentamycine (GM)8. Nalidixic Acid (NA)9. Trimetophrim/Sulfametoxazole (STX)10. Tetracycline (TE) 11. Levofloxacin (LEV)12. Norfloxacin (NOR)13. Nitrofurantoin (F)

Materials and methods

aminopenicilins

Cephalosporins

fluoroquinolones

Sulphonamid

broad-spectrum bacteriostatic drug

aminoglycoside

nitrofurane

quinolone

AB 2012 2013 2014

AMP 51.11% 53.33% 57.78%

CTX 0.00% 0.00% 5.56%

AMC 6.67% 6.67% 6.11%

CAZ - 0.56% 0.00%

CXM 4.44% 1.82% 3.33%

FEP - 0.56% 0.00%

GN - 3.03% 3.89%

LEV/CIP 11.11% 20.00% 29.44%

NOR 16.67% 20.00% 30.00%

F 1.11% 1.67% 0.56%

NA 18.33% 22.78% 29.44%

SXT 6.86% 22.22% 39.44%

TE 16.00% 32.00% 38.33%

Results I.Antibiotic resistance percentages during the examined

periods

6/13 antibiotics had a resistance value of approx. or greater than 30% by the year 2014

None of the tested antibiotics remained at the value of 0%

Results II.-III.Antibiotic resistance evolution per

year

Should we take into consideration the values of 2015 Jan. and Febr.?◦ Yes, but only IF:• between 2013-2014 the antibiotic resistance

did not peak during January or February AND the AVERAGE (AVG) value of the AB resistance DID NOT EXCEED the AVERAGE of the YEAR, we considered the 2015 values valid.

• Tetracycline(TE) peaked in January, thus it was excluded.

Question

Results II.AMP resistance evolution

AMP

2012 2013 2014 20150.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

AMP is a special case In 2012 it was not

regularly tested, but the 2015 average already exceeded previous resistance rates:

p= 0.0167(0.0404)- significant(S)

Diff = 12.22% (increase of 23.9% in 3+ years)

Results II.LEV/CIP resistance evolution

LEV/CIP

2012 2013 2014 20150.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00% P= 0.046 - S Diff = 18.89%

(increase of +170%) Fastest yearly

increase – 80.01% between 2012-2013

Results II+AMC resistance evolution

AMC

2012 2013 2014 20150.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%

7.00%

8.00%

9.00% p=0.035-S (although 2012-2014 p= 0.17 – NS)

Diff = 4.95% (decrease of 59,78%)

Results II+GN resistance evolution

GN

2013 2014 20150.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%

7.00%

8.00% p= 0.18 (NS) although the steady increase is obvious

Results III.NOR resistance evolution

NOR

2012 2013 2014 20150.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00% p= 0.17 (NS) - [2012-2014]

BUT the values of 2015 may increase

Results III.NA resistance evolution

NA

2012 2013 2014 20150.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00% p= 0.0728– Not quite significant

(NQS) [2012-2014]

Results III.SXT resistance evolution

SXT

2012 2013 2014 20150.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

40.00%

45.00% p= 0.26 (NS) - [2012-2014]

Results IV.Assessment of yearly and

comparison of seasonal resistance values

Janu

ary

Febr

uary

Mar

chApr

ilMay

June Ju

ly

Augus

t

Sept

embe

r

Octob

er

Novem

ber

Decem

ber

0

2

4

6

8

10

12

2012201320142015

Janu

ary

Febr

uary

Mar

chApr

ilMay

June Ju

ly

Augus

t

Sept

embe

r

Octob

er

Novem

ber

Decem

ber

0

1

2

3

4

5

6

2012201320142015

Results IV.Aminopeniciline comparison of resistance evolution

during 2012-2015 per year and month

AMP AMC

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 260

2

4

6

8

10

12

AMP

AMC

Results IV Aminopenicillines – linear resistance evolution per month during 2012-2015

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 340

0.5

1

1.5

2

2.5

3

3.5

4

4.5

CTXCXMCAZ

Results IV. Cephalosporines -linear resistance evolution per month during 2012-2015

Janu

ary

Febr

uary

Mar

chApr

ilMay

June Ju

ly

Augus

t

Sept

embe

r

Octob

er

Novem

ber

Decem

ber

0

1

2

3

4

5

6

7

8

201220132014

Janu

ary

Febr

uary

Mar

chApr

ilMay

June Ju

ly

Augus

t

Sept

embe

r

Octob

er

Novem

ber

Decem

ber

0

1

2

3

4

5

6

7

8

2012201320142015

Results IV. Fluorochinolones -seasonal antibiotic resistance values

CIP/LEV NOR

Results IV.Fluoroquinolones linear resistance evolution per month during 2012-2015

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 320

1

2

3

4

5

6

7

8

CIP/LEVNOR

Janu

ary

Febr

uary

March

April

MayJu

ne July

Augus

t

Sept

embe

r

Octob

er

Novem

ber

Decem

ber

0

1

2

3

4

5

6

7

8

2012201320142015

Results IV.NA- seasonal antibiotic resistance values

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 340

1

2

3

4

5

6

7

8

Results IV.NA- linear resistance evolution per month during

2012-2015

Janu

ary

Febr

uary

March

April

MayJu

ne July

Augus

t

Sept

embe

r

Octob

er

Novem

ber

Decem

ber

0

2

4

6

8

10

12

2012201320142015

Results IV.SXT- seasonal antibiotic resistance values

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 300

2

4

6

8

10

12

SXT

Results IV.SXT- linear resistance evolution per month during

2012-2015

Janu

ary

Febr

uary

March

April

MayJu

ne July

Augus

t

Sept

embe

r

Octob

er

Novem

ber

Decem

ber

0

2

4

6

8

10

12

2012201320142015

Results IV.TE - seasonal antibiotic resistance values

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 290

2

4

6

8

10

12

TE

TE

Results IV.TE- linear resistance evolution per month during 2012-

2015

Janu

ary

Febr

uary

March

April

MayJu

ne July

Augus

t

Sept

embe

r

Octob

er

Novem

ber

Decem

ber

0

0.2

0.4

0.6

0.8

1

1.2

2015201420132012

Results IV.F- seasonal antibiotic resistance values

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 280

0.2

0.4

0.6

0.8

1

1.2

Results IV.F- linear resistance evolution per month during 2012-

2015

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 240

0.2

0.4

0.6

0.8

1

1.2

Results IV.FEP- linear resistance evolution per month during

2013-2015

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 250

0.5

1

1.5

2

2.5

Results IV.GN- linear resistance evolution per month during

2013-2015

Janu

ary

Feb

ruar

y

Mar

ch

Apr

il

May

June

July

Augus

t

Sept

embe

r

Octob

er

Novem

ber

Decem

ber

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

2013

2014

2015

201320142015

Results IV. FEP- seasonal antibiotic resistance values

Janu

ary

Febr

uary

March

April

MayJu

ne July

Augus

t

Sept

embe

r

Octob

er

Novem

ber

Decem

ber

0

0.5

1

1.5

2

2.5

201220142015

Results IV.GN- comparison of resistance evolution during 2012-2015 per year and month

There doesn’t seem to be any cyclicity among individual antibiotic resistances regarding time or season.

Results IV.

Results V.Peak value Summary of the examined periods (2012-2014)

The sum of peaks for each antibiotic shows the following:

antibiotic resistance values seem to peak during the warmer months, while during the cold months the number of cases diminish drastically.

Most peaks: September 9/43.

Least peaks: February and December 0/43.

Jan

Mar

chMay Ju

ly

Sept

embe

r

Novem

ber

0

2

4

6

8

10

February March September October

Mean peaks (°C)

6.5 14.7 25.3 16.3

Maximum peak(°C)

19 24 31 25

Why do we consider March and September a warm month? [4]

1. Antibiotic resistance values seem to be increasing on a year to year basis [5]

2.In case of CIP/LEV the increase of resistance during the last few years has almost tripled

Conclusion

P significant P not significant due to lack of cases

P not significant but cannot be excluded yet

AMP GN NOR

LEV/CIP NA

SXT

3. E. coli strains do not show signs of time/season dependent resistances for individual antibiotics, but as a whole, they seem to increase gradually during the warmer months, peaking in September.

Conclusion

4. Due to the aforementioned results Antibiotic Sensitivity Tests need to be performed on every case of UTI, especially during summer because:

A. High probability of resistance B. Avoid creating more resistant strains C. Improper Antibiotic treatment and long lasting

UTIs can lead to multiple serious complications ( ascending spreading, nephritis…etc.)

D. Ever increasing number of people with risk factors [6]

Conclusion

5. In order to guarantee the precision and efficacy of further studies and evaluations we encourage the continuation of regular AST testing and registration.

Conclusion

Thank you for your attention

Special thank you to: Dr. Teodora Chigir – carried out the urine

cultures and AST tests during 2012-2013 Dr. Barabás Hajdu Enikő - coordinator

The entire County Hospital Laboratory department

[1] - Dr. Mártha Orsolya – Urológia, 2008 – pp. 64-65 [2] -Dumitru Buiuc,Marian Negut - Tratat de

microbiologie Clinica,2009 – pp. 255 [3] - Dumitru Buiuc,Marian Negut - Tratat de

microbiologie Clinica,2009 – pp. 263 [4] -http://www.accuweather.com/ro/ro/bucharest [5] -

http://www.sciencedirect.com/science/article/pii/S0924857906001063

[6] - http://www.diabetes.org/diabetes-basics/statistics/

References