1. Author: Sándor Szabolcs - student Coordinator: Dr. Barabás Hajdu Enikő – Assistant Professor

2.  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 2 nd adult woman is affected by UTI once in her lifetime. [2]  The #1 cause for UTI is E. coli infection.

3.  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.

4.  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 1 st May 2012- 1 st March 2015

5.  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

6. 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.

7. 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) aminopenicilins Cephalosporins fluoroquinolones Sulphonamid broad-spectrum bacteriostatic drug aminoglycoside nitrofurane quinolone

8. AB201220132014AMP 51.11% 53.33%57.78% CTX 0.00% 5.56% AMC 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% 6 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%

9. Antibiotic resistance evolution per year

10.  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.

11. AMP  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)

12. LEV/CIP  P= 0.046 - S  Diff = 18.89% (increase of +170%)  Fastest yearly increase – 80.01% between 2012-2013

13. AMC  p=0.035-S (although 2012-2014 p= 0.17 – NS)  Diff = 4.95% (decrease of 59,78%)

14. GN p= 0.18 (NS) although the steady increase is obvious

15. NOR  p= 0.17 (NS) - [2012- 2014]  BUT the values of 2015 may increase

16. NA  p= 0.0728 – Not quite significant (NQS) [2012-2014]

17. SXT  p= 0.26 (NS) - [2012- 2014]

19. AMPAMC

22. CIP/LEV NOR

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

37. 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.

38. FebruaryMarchSeptemberOctober Mean peaks (°C)6.514.725.316.3 Maximum peak(°C) 19243125

39. increasing 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 P significantP not significant due to lack of cases P not significant but cannot be excluded yet AMPGNNOR LEV/CIPNA SXT

40. 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.

41. 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]

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

44. 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

45.  [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/