Determination of Potential Drug-Drug Interactions in Patients Using Quinolone Group Antibiotics

Yıl 2024, Cilt: 34 Sayı: 3, 371 - 375, 30.06.2024

Cengizhan Ceylan Erdenay Erden Cansu Göncüoğlu Harun Kızılay Şeyma Tetik Rama Yeşim Şerife Bayraktar Jale Bengi Çelik Görkem Yılmazer Esranur Kıratlı Nazlım Aktuğ Demir Şua Sümer Onur Ural

https://doi.org/10.54005/geneltip.1439326

Öz

Aim: The aim of the study was to determine the potential drug drug interactions of patients receiving inpatient treatment in the intensive care unit and infectious diseases ward and using quinolone group antibiotics by using different interaction software programs.
Material and Methods: The prescriptions of 100 patients who received inpatient treatment in infectious diseases service and intensive care unit at Selçuk University Faculty of Medicine Hospital between January 2022 and December 2022 and who were treated with quinolone group antibiotics during treatment were analyzed retrospectively.
Results: Of the patients included in the study, 62 were male and 38 were female. The mean age of men was 65.76 ± 16.22 years, while the mean age of women was 68.63 ± 16.29 years. While Medscape® detected a total of 1776 interactions, this number was 1432 in Lexicomp® and 1693 in Drugs®.While 0.33% of the interactions detected in the Medscape® software program were contraindicated, 3.77% of the interactions were contraindicated in Lexicomp®. Kendall W coefficient 0.94, Chi-Square test 281.12, p <0.001 were found to be statistically significant. The software programs used to detect pDDIs are highly compatible with each other.
Conclusion: High agreement was found between software programs used to detect potential drug-drug interactions. Interaction classifications between software programs are different. Therefore, clinicians may benefit from different software programs.

Anahtar Kelimeler

Drug interactions, Software, Quinolone, Antibiotics

Kinolon Grubu Antibiyotik Kullanan Hastalarda Potansiyel İlaç-İlaç Etkileşimlerinin Belirlenmesi

Öz

Amaç: Çalışmanın amacı, yoğun bakım ünitesi ve enfeksiyon hastalıkları servisinde yatarak tedavi gören ve kinolon grubu antibiyotik kullanan hastaların potansiyel ilaç etkileşimlerinin farklı etkileşim yazılım programları kullanılarak belirlenmesidir.
Yöntem: Ocak 2022-Aralık 2022 tarihleri arasında Selçuk Üniversitesi Tıp Fakültesi Hastanesi Enfeksiyon Hastalıkları Servisi ve Yoğun Bakım Ünitesi’nde yatarak tedavi gören ve tedavi sırasında kinolon grubu antibiyotiklerle tedavi edilen 100 hastanın reçeteleri retrospektif olarak incelenmiştir.
Bulgular: Çalışmaya dahil edilen hastaların 62’si erkek, 38’i kadındı. Erkeklerin yaş ortalaması 65,76 ± 16,22 iken kadınların yaş ortalaması 68,63 ± 16,29’dur. Medscape® toplam 1776 etkileşim tespit ederken, bu sayı Lexicomp®’ta 1432, Drugs®’ta ise 1693’tür. Medscape® yazılım programında tespit edilen etkileşimlerin %0,33’ü kontrendike iken, Lexicomp®’ta etkileşimlerin %3,77’si kontrendike bulunmuştur. Kendall W katsayısı 0.94, Ki-Kare testi 281.12, p<0.001 istatistiksel olarak anlamlı bulunmuştur. Potansiyel ilaç-ilaç etkileşimlerini tespit etmek için kullanılan yazılım programları birbirleriyle yüksek uyum içerisindedir.
Sonuç: Potansiyel ilaç-ilaç etkileşimlerini tespit etmek için kullanılan yazılım programları arasında yüksek uyum bulunmuştur. Yazılım programları arasındaki etkileşim sınıflandırmaları farklıdır. Bu nedenle, klinisyenler farklı yazılım programlarından faydalanabilirler.

Anahtar Kelimeler

İlaç etkileşimleri, Yazılım, Kinolon, Antibiyotik

Kaynakça

• BÜYÜKOKUROĞLU ME, TANYERİ P, KELEŞ R. İlaç-ilaç etkileşimleri konusunda farkındalık. Online Türk Sağlık Bilimleri Dergisi. 2019;4(3):377-91.
• Peng Y, Cheng Z, Xie F. Evaluation of pharmacokinetic drug–drug interactions: a review of the mechanisms, in vitro and in silico approaches. Metabolites. 2021;11(2):75.
• Palleria C, Di Paolo A, Giofrè C, Caglioti C, Leuzzi G, Siniscalchi A, et al. Pharmacokinetic drug-drug interaction and their implication in clinical management. J Res Med Sci. 2013;18(7):601-10.
• Krähenbühl-Melcher A, Schlienger R, Lampert M, Haschke M, Drewe J, Krähenbühl S. Drug-related problems in hospitals: a review of the recent literature. Drug Saf. 2007;30(5):379-407.
• Pitman SK, Hoang UTP, Wi CH, Alsheikh M, Hiner DA, Percival KM. Revisiting Oral Fluoroquinolone and Multivalent Cation Drug-Drug Interactions: Are They Still Relevant? Antibiotics (Basel). 2019;8(3).
• Shakeri-Nejad K, Stahlmann R. Drug interactions during therapy with three major groups of antimicrobial agents. Expert Opin Pharmacother. 2006;7(6):639-51.
• Brouwers JR. Drug interactions with quinolone antibacterials. Drug Saf. 1992;7(4):268-81.
• Neuhauser MM, Weinstein RA, Rydman R, Danziger LH, Karam G, Quinn JP. Antibiotic resistance among gram-negative bacilli in US intensive care units: implications for fluoroquinolone use. Jama. 2003;289(7):885-8.
• Freifeld AG, Bow EJ, Sepkowitz KA, Boeckh MJ, Ito JI, Mullen CA, et al. Clinical practice guideline for the use of antimicrobial agents in neutropenic patients with cancer: 2010 update by the infectious diseases society of america. Clin Infect Dis. 2011;52(4):e56-93.
• Bratzler DW, Dellinger EP, Olsen KM, Perl TM, Auwaerter PG, Bolon MK, et al. Clinical practice guidelines for antimicrobial prophylaxis in surgery. Surg Infect (Larchmt). 2013;14(1):73-156.
• Asuman İ, DAĞLI Ö, Akçay SŞ, Engin DÖ, Karagül E, Özyürek SÇ. Antibiotic use and cost in a teaching hospital in İstanbul. Journal of Microbiology and Infectious Diseases. 2011;1(03):128-33.
• Usluer G, Ozgunes I, Leblebicioglu H, tr TAUSGhoe. A multicenter point-prevalence study: antimicrobial prescription frequencies in hospitalized patients in Turkey. Annals of clinical Microbiology and Antimicrobials. 2005;4:1-5.
• Zarb P, Amadeo B, Muller A, Drapier N, Vankerckhoven V, Davey P, et al. Identification of targets for quality improvement in antimicrobial prescribing: the web-based ESAC Point Prevalence Survey 2009. J Antimicrob Chemother. 2011;66(2):443-9.
• Davey P, Brown E, Charani E, Fenelon L, Gould IM, Holmes A, et al. Interventions to improve antibiotic prescribing practices for hospital inpatients. Cochrane Database Syst Rev. 2013(4):Cd003543.
• Jafarova Demirkapu M, Pinar Kara S. Potential drug-drug interactions in University Hospital Medical Intensive Care Unit patients in Turkey. Eur Rev Med Pharmacol Sci. 2021;25(22):7108-14.
• Koeck JA, Hilgarth H, von Ameln-Mayerhofer A, Meyn D, Warlich R, Münstedt A, et al. Clinically Relevant Interactions with Anti-Infectives on Intensive Care Units-A Multicenter Delphi Study. Antibiotics (Basel). 2021;10(11).
• Sancar M, Kaşik A, Okuyan B, Batuhan S, Izzettin FV. Determination of Potential Drug-Drug Interactions Using Various Software Programs in a Community Pharmacy Setting. Turk J Pharm Sci. 2019;16(1):14-9.
• Kheshti R, Aalipour M, Namazi S. A comparison of five common drug-drug interaction software programs regarding accuracy and comprehensiveness. J Res Pharm Pract. 2016;5(4):257-63.
• van der Sijs H, Lammers L, van den Tweel A, Aarts J, Berg M, Vulto A, et al. Time-dependent drug–drug interaction alerts in care provider order entry: software may inhibit medication error reductions. Journal of the American Medical Informatics Association. 2009;16(6):864-8.
• Al-Ramahi R, Raddad AR, Rashed AO, Bsharat A, Abu-Ghazaleh D, Yasin E, et al. Evaluation of potential drug-drug interactions among Palestinian hemodialysis patients. BMC nephrology. 2016;17:1-6.
• Bektay MY, Seker Z, Eke HK, Turk HM, Izzettin FV. Comparison of different decision support software programs in perspective of potential drug–drug interactions in the oncology clinic. Journal of Oncology Pharmacy Practice. 2023;29(5):1178-86.
• Vanham D, Spinewine A, Hantson P, Wittebole X, Wouters D, Sneyers B. Drug-drug interactions in the intensive care unit: do they really matter? Journal of critical care. 2017;38:97-103.
• Kuscu F, Ulu A, Inal AS, Suntur BM, Aydemir H, Gul S, et al. Potential Drug-Drug Interactions with Antimicrobials in Hospitalized Patients: A Multicenter Point-Prevalence Study. Med Sci Monit. 2018;24:4240-7.
• Emre K, Tecen-Yücel K, Özdemir N, İnkaya AÇ, Bayraktar-Ekincioğlu A, Demirkan K, et al. Yoğun bakım hastalarında antibiyotiklerin diğer ilaçlarla etkileşimlerinin değerlendirilmesi. Sürekli Tıp Eğitimi Dergisi. 2019;28(6):404-9.
• Öksüz E, Buğday MS, Soyalp C, Karaaslan E, Oto G, Temelli Göçeroğlu R, et al. Drug-drug interactions in intensive care units and potential clinical consequences of these interactions. 2019.
• Hamadouk RM, Alshareif EM, Hamad HM, Yousef BA. The Prevalence and Severity of Potential Drug–Drug Interactions in Internal Medicine Ward at Soba Teaching Hospital. Drug, Healthcare and Patient Safety. 2023:149-57.
• Farooqui R, Hoor T, Karim N, Muneer M. Potential Drug-Drug Interactions among Patients prescriptions collected from Medicine Out-patient Setting. Pak J Med Sci. 2018;34(1):144-8.
• Liu Y, Wang J, Gong H, Li C, Wu J, Xia T, et al. Prevalence and associated factors of drug-drug interactions in elderly outpatients in a tertiary care hospital: a cross-sectional study based on three databases. Annals of Translational Medicine. 2023;11(1).
• Suriyapakorn B, Chairat P, Boonyoprakarn S, Rojanarattanangkul P, Pisetcheep W, Hunsakunachai N, et al. Comparison of potential drug-drug interactions with metabolic syndrome medications detected by two databases. PloS one. 2019;14(11):e0225239.
• Hadjibabaie M, Badri S, Ataei S, Moslehi AH, Karimzadeh I, Ghavamzadeh A. Potential drug–drug interactions at a referral hematology–oncology ward in Iran: a cross-sectional study. Cancer chemotherapy and pharmacology. 2013;71:1619-27.
• Roblek T, Vaupotic T, Mrhar A, Lainscak M. Drug-drug interaction software in clinical practice: a systematic review. European journal of clinical pharmacology. 2015;71:131-42.
• Alkhalid Z, Birand N. Determination and comparison of potential drug–drug interactions using three different databases in northern cyprus community pharmacies. Nigerian Journal of Clinical Practice. 2022;25(12):2005-9.