90 Vol. 1. No. 2 May–August 2010 Antibiotic Resistance Control Program in Pediatric Hematology and Oncology Patients at Dr. Soetomo Hospital in 2006–2007 Mia ratwita andarsini, i dewa Gede ugrasena, Bambang permono Division of Hematology and Oncology Department of Child Health,Medical Faculty,Airlangga University-dr. Soetomo Hospital Correspondence: Mia Ratwita Andarsini, dr, SpA, E-mail: miaratwita_spa@yahoo.com Telp: 0315501688; fax: 0315501748. abstract Antibiotic resistance has been increasing since the first years of the clinical usage. It caused by inappropriate usage and uncontrol of antibiotic drugs. Therfore an Antibiotic Resistance Control Program (ARCP) is needed to overcome the problem. The purpose of this study is to know microorganism pattern and evaluate antibiotic use. Phase 1 (before ARCP), retrospective study by medical record of pediatric hematology-oncology patients with suspision of infection and admitted at dr Soetomo Hospital from June–August 2006 was carried out. Phase 2 (during ARCP), a prospective observational study was done from November 2006 to January 2007. We were evaluated the isolated microorganism, quantity of antibiotic were determined by Defined Daily Doses (DDD)/100 patients-days, quality of antibiotics usage were assessed with Glyssen classification, and the cost calculation of antibiotic therapy. Twenty seven patients were enrolled in phase 1 and 28 patients in phase 2. Coagulase-negative Staphylococci and Acinetobacter Sp as isolated microorganism was reported. Phase 1, the most sensitive antibiotic was Cefoperazone-Sulbactam and the most resistant was Penicillin G. Phase 2, Meropenem was the most sensitive antibiotic and Cotrimoxazole was the most resistant antibiotic. The use of antibiotics were decreased 6 vs 12 and DDD/100 patients-days were 14.52 vs 45.04. There were improving of Glyssen classification. The cost calculation of antibiotics therapy were decreased. ARCP can improve antibiotic use in pediatric hematology-oncology patients. Keywords: pediatric hematology-oncology, antibiotic resistance control program, antibiotic evaluation introduction Antibiotic resistance is one of the health problem in the world. Uncontrolled and inappropriate of antibiotic use can increase morbidity and mortality, and also give impact in the quality of health services.1,2 Antibiotic resistance appear through selection process because of antibiotic overuse and quickly spreading through human contacts.3 Today, there is many program in the world to overcome antibiotic resistance spreading.4 Study of Antimicrobial Resistance in Indonesia (AMRIN study) at Dr. Soetomo hospital was done in 2000– 2004. Antibiotic resistance and inappropriate antibiotic use was found, on the other hand infection control has not been done properly.5 As follow up, Antibiotic Resistency Control Program (ARCP) was performed with Pediatric Hematology Oncology division as a pilot project. The purpose of this study is to know microorganism pattern and evaluate antibiotic use. methods The study consisted of 2 phase. In phase 1 (before ARCP), retrospective study was done through medical record during June-August 2006. In phase 2 (during ARCP), prospective study was done in November 2006–January 2007. Pediatric hematology oncology patients who were admitted with suspicion of infection were subject of the study. Inclusion criteria were body temperature >38o C or < 36o C, lekocyte count > 12000/cmm or < 4000/cmm, presence of takicardia and/or takipneu. Patients who met the criteria were enrolled the study. In phase 2, will follow antibiotic guidance below (figure 1). Data study were include patients’ characteristic and diagnosis, microorganism isolate from the cultures and result of antibiotic sensitivity tes. Antibiotic usage were evaluated quantitatively with Defined Daily Dose (DDD)/100 patients-days and qualitatively with Gyssen Case Report 91Andarsini et al.: Antibiotic resistance control program classification.6 The DDD represent the average therapeutic dose for an adult for the standard indication. The cost analysis was also evaluated. results and discussions Twenty seven patients were enrolled in the phase 1, with average age 101,22 (33–108) month-old and average length of stay 29,7 (8–69) days. In phase 2, 28 patients enrolled the study, average age 54,64 (8–69) month-old and average length of stay 29,5 (6–84) days. More than 50% were acute lymphoblastic leukemia patients. In phase 1, 27 blood cultures was collected, positive results were only found in 17 (37%) cultures. Meanwhile in phase 2, 75 cultures were collected, consisted of 39 blood culture, 19 urine cultures and 7 fecal cultures. Positive results found in 24 (32%) cultures. Similarly study shiwed that positive culture only found in 11 put of 67 patients (16,4%) with febrile neutropenia.7 Coagulase-negative Staphylococci was found in 50% blood culture in phase 1 and 44,4% in phase 2. Microorganism isolated in urine cultures were E coli ESBL, Klebsiella pneumoniae, Enterobacter aerogenes, Pseudomonas and Acinetobacter sp. E coli pathogen serotype 1–11 were found in all of the fecal cultures. Al-ahwal study showed that 5 out of 11 positive cultures were due to gram-positive microorganism (coagulase- negative Staphylococci and Staphylococcus aureus), 5 due to gram-negative microorganism (E coli, Klebsiella and P aeruginosa).7 In malignancy patients, the primary anatomic site of infecton is the gastrointestinal tract, where mucosal damage from chemotherapy allows invasion fo microorganism. Damage to the skin from invasive procedures, such as intravascular devices, similarly provides portals of entry for microbes. Bacterial pathogens commonly implicated in neutropenic fever are gram-positive microorganism (Staphylococcal sp, Streptococcus sp, Enterococcal sp and Corynebacterium sp) and gram-negative microorganism (E coli, klebsiella sp, Pseudomonas aeruginosa, Enterobacter sp and Acinetobacter sp).8 Sensitivity tes was perfomed. In phase 1, sensitive antibiotics were cefoperazone sulbactam, netilmycin and gentamycin. In phase 2, the result were change into meropenem, ciprofloxacin, piperacillin tazobactam and amikacin. Resistent antibiotics in phase 1 were Penicilin G, erithromycin and cotrimoxazole. In phase 2, cotrimoxazole was still resistent followed by cefotaxime and ceftriaxone. Quantitative and qualitative antibiotic evaluation were done in both phase. Quantity of antibiotics usage were determined by counting DDD/100 patient-days (table 1). table 1. Quantitative Antibiotik evaluation Antibiotics DDD/100 patient-days Phase 1 Phase 2 Cefotaxime Meropenem Amikacin Ceftazidime Cloxacillin Cefepime Ciprofloxacin Ceftriaxone Clindamycin Cotrimoxazole Gentamycin Cefoperazone sulb. 10.6 3.6 2.7 3,0 7.66 0.35 6.3 1.34 0.37 7.15 0.25 1.72 7.84 3.40 0.50 0.40 -0 -0 -0 -0 -0 1.50 -0 0.88 Total 45.04 14.52 fiuture 1. Antibiotic Guideline during Antibiotic resistance Control Program (ARCP) NEW PATIENTS Inclussion criteria temperature > 380C or < 360C Leukocyte count > 12.000/mm3 or < 4.000/mm3 Takikardi (HR > Normal for age) Takipnea (RR > Normal for age) Yes Blood/urine culture Empirical Antibiotic CEFOTAXIM 3 days Evaluation No without antibiotic Fulfill inclussion criteria Improved (+) Continued until 7 days Improved ( ) MEROPENEM or based on culture result 3 hari Evaluation Improved (+) Continued until 7 days improved ( ) Alternative antibiotic based on culture result 3 days Evaluation Improved (+) Continued until 7 days Perbaikan ( ) Add antifungal (FLUCONAZOLE) 3 days Evaluation Improved (+) Continued until 10 14 days Improved ( ) Repeat blood/urine culture 92 Indonesian Journal of Tropical and Infectious Disease, Vol. 1. No. 2 May–August 2010: 69-68 Quantity of antibiotics usage was decreased from 12 to 6 type of antibiotics. DDD/100 patient-days calculation was also decreased from 45,04 (phase 1) to 14,52 (phase 2). The main problem with DDD is that DDD was made for adults, therefore the result of this study can not be compared with other study in adults. table 2. Quality Antibiotic Evaluation Classification Phase 1 Phase 2 I (definitely appropriate) IIA (improper dosage) IIB (improper dosage interval) IIC (improper route) IIIA (excessive length) IIIB (duration too short) IVA (more effective alternative agent) IVB (less toxic alternative agent) IVC (less expensive alternative agent) IVD (less broad spectrum alternative agent) V (unjustified) VI (record insufficient for categorization) 22% 0% 0% 0% 46% 1.6% 4.7% 0% 9.6% 11.1% 5% 0% 38% 0% 0% 0% 30.2% 1.6% 11.1% 0% 11.1% 3.2% 4.8% 0% Quality of antibiotic used were assessed with Gyssen clasification (table 2). There was decreased of procentage were found in classification IIIA, IIIB, IVD and V. Increased of procentage was found in clasification I, IVA and IVC. Similar study by Gyssen in surgery ward showed improvement or quality antibiotics usage. There were increased of category I from 31% to 47% and was decreased of category V form 16% to 8%.9 The cost analysis was calculated including cultures and antibiotics usage. This study showed that implementation ARCP could save around Rp 13,135,000 for 27 patients. Gyssen study also found total cost saving of 11% after intervention.9 conclusion From this study we conclude that antibiotic intervention trough ARCP resulted in an improvement of the quantity and quality of antibiotic regimen and in term of costs. references 1. D. Widodo, “Kebijaksanaan Penggunaan Antibiotika Bertujuan Meningkatkan Kualitas Pelayanan Pasien dan Mencegah Peningkatan Resistensi Kuman”, Cermin Dalam Kedokteran, Vol. 37, No. 1, 2010, pp. 7–10. 2. A. Sadiumenge, E. Diaz, A. Rodriguez, L. Vidaur, L. Canadell, M. Olona, “Impact of Diversity of Antibiotic Use on the Development of Antimicrobial Resistance”, J Antimicrob Chemother, Vol. 57, 2006, pp. 1197–204. 3. EL. Larson, D. Quiros, T. Giblin, S. Lin, “Relationship of Antimicrobial Control Policies and Hospital and Infection Control Characteristic to Antimicrobial Resistance Rates”, Am J Crit Care, Vol. 16, 2007, pp. 110–20. 4. LE. Nicholle, Ïnfection Control Programmes to Contain Antimicrobial Resistance”, available at www.wpro.who.int, accessed on July 2010. 5. U. Hadi, DO. Duerink, ES. Lestari, NJ. Nagelkerke, S. Werter, M. Keuter, et al, “Survey of Antibiotic Use of Individual Visiting Public Healthcare facilities in Indonesia”, available at https://openaccess. leidenuniv.nl/bitstream/1887/13821/8/03.pdf, accessed on July 2010. 6. IC. Gyssens, PJ. van der Broek, BJ. Kullberg, YA. Hekster, JWM. Van der Meer, “Optimizing Antimicrobial Therapy. A Method for Antimicrobial Drug Evaluation”, J Antimicrob Chemother, Vol. 30, 1992, pp. 724–7. 7. MS. Al-ahwal, “Pattern of Febrile Neutropenia in Solid Tumor – a Hospital based study”, Park J Med Sci, Vol. 21, No. 3, 2005, pp. 249–52. 8. S. Kannangara, “Management of Febril Neutropenia”, Commun Oncol, Vol. 3, 2006, pp. 585–91. 9. IC. Gyssen, IEJ. Geerligs, JMJ. Dony, JA van der Vliet, A. van Kampen, PJ. Van den Broek, et al, “Optimising Antimicrobial drug Use in Surgery: an Intervention atudy in a Dutch University Hospital”, J Antimicrob Chemother, Vol. 38, 1996, pp. 1001–1012. IJTID vol 1 no 2 May-Aug 2010.38.pdf IJTID vol 1 no 2 May-Aug 2010.39.pdf IJTID vol 1 no 2 May-Aug 2010.40.pdf