Adverse drug reactions evaluation of antimicrobials in COVID-19 inpatients using Modified Trigger Tool and Naranjo Algorithm
DOI:
https://doi.org/10.46542/pe.2023.232.18Keywords:
Adverse drug reaction, COVID-19, Naranjo scale, Trigger toolAbstract
Background: The use of antimicrobials in COVID-19 treatment might increase the risk of adverse drug reactions (ADR). Therefore, the adverse effect further identification was needed to understand the safety profile of using these medicines.
Objective: The research aims to evaluate the adverse effects of the use of COVID-19 antimicrobial agents, causality analysis, and factors related to this ADR.
Method: Cross-sectional study using random sampling was conducted to obtain the data. The study used samples from COVID-19 adult inpatients in a hospital located in Java from July-December 2020. Adverse events (AE) were detected by a modified trigger tool using medication and laboratory result module triggers with 21 total triggers. Causality analysis of ADR was conducted using Naranjo Scale.
Result: Of the 107 patients examined in this study, 92 patients had triggers. A total of 274 adverse events were found, where 265 adverse events were detected using the trigger tool, and 9 adverse events were detected without the trigger tool. The results of the ADR analysis using the Naranjo algorithm were obtained from as many as 126 ADRs in 60 patients with possible (94.4%) and probable (5.6%) scoring. The most common antimicrobials that cause ADR were azithromycin and oseltamivir. The most effective trigger in detecting ADR was the use of sedation with a positive predictive value of 0.67. The statistical analysis results showed no relationship between gender, age, comorbidities, severity, and body mass index on the incidence of ADR (p>0.05).
Conclusion: Adverse drug reactions were commonly found in the use of azithromycin and oseltamivir for COVID-19 patients, so it is necessary to consider the choice of this therapy. The trigger tool and Naranjo algorithm were adequate to help the ADR monitoring process.
References
Bassi, P.U., Osakwe, A.I., Ogar, C.K., Elagbaje, C., Nwankwo, B.B., Balogun, S.T., Ntadom, G.N. & Isah, A.O. (2017). Impact of comorbidity on adverse drug reaction profile in a cohort of patients treated with artemisinin combination therapies for uncomplicated malaria in Nigeria. Pharmacology research & perspectives, 5(2), e00302. https://doi.org/10.1002/prp2.302
Belhekar, M.N., Taur, S.R., & Munshi, R.P. (2014). A study of agreement between the Naranjo algorithm and WHO-UMC criteria for causality assessment of adverse drug reactions. Indian Journal of Pharmacology. 46(1). https://doi.org/10.4103/0253-7613.125192
Bleyzac, N., Goutelle, S., Bourguignon, L., & Tod, M. (2020). Azithromycin for COVID-19: More Than Just an Antimicrobial? Clinical Drug Investigation. 40(8):683-686. https://doi.org/10.1007/s40261-020-00933-3
Cai, Q., Chen, F., Wang, T., Luo, F., Liu, X., Wu, Q., He, Q., Wang, Z., Liu, Y., Liu, L., Chen, J. Xu, L. (2020). Obesity and COVID-19 Severity in a Designated Hospital in Shenzhen, Chin. Diabetes Care. https://doi.org/10.2337/dc20-0576
Classen, D.C., Resar, R., Griffin, F., Federico, F., Frankel, T., Kimmel, N., Whittington, J.C., Frankel, A., Seger, A., James, B. C. (2011). 'Global trigger tool' shows that adverse events in hospitals may be ten times greater than previously measured. Health Aff (Millwood), 30(4), 581-589. https://doi.org/10.1377/hlthaff.2011.0190
Coleman, J.J., Pontefract, S.K. (2016). Adverse drug reactions Clinical Medicine, 16(5), 481–485. https://doi.org/10.7861%2Fclinmedicine.16-5-481
de Almeida, S.M., Romualdo, A., de Abreu Ferraresi, A., Zelezoglo, G.R., Marra, A.R., & Edmond, M.B. (2017). Use of a trigger tool to detect adverse drug reactions in an emergency department. BMC Pharmacology and Toxicology, 18(1), 71. https://doi.org/10.1186/s40360-017-0177-y
Eftekhar, S.P., Kazemi, S., Barary, M., Javanian, M., Ebrahimpour, S., & Ziaei, N. (2021). Effect of Hydroxychloroquine and Azithromycin on QT Interval Prolongation and Other Cardiac Arrhythmias in COVID-19 Confirmed Patients. Cardiovascular therapeutics. https://doi.org/10.1155/2021/6683098
Esnal, D.E., Ontiyuelo, C.M., Rouco, M.E., Cusco, M.D.-A., Ferrandez, O., Horjacada, J.P., & Grau, S. (2020). Azithromycin in the treatment of COVID-19: a review. Expert Review of Anti-Infective Therapy. 19(2), 147-163. https://doi.org/10.1080/14787210.2020.1813024
Gadde, R. S., Dhanenkula, D. T., & Kammila, S. (2018). Trigger Tool Based Detection of Adverse Drug Reactions in a Tertiary Care Teaching Hospital: A Prospective Observational Study. Indian Journal of Pharmacy Practice. https://doi.org/10.5530/ijopp.11.2.18
Gbinigie, K., & Frie, K. (2020). Should azithromycin be used to treat COVID-19? A rapid review. British Journal of General Practitioners Open, 4(2). https://doi.org/10.3399/bjgpopen20x101094
Gor, A.P., & Desai, S.V. (2008). Adverse Drug Reactions (ADR) in the inPatients of Medicine Department of a Rural Tertiary Care Teaching Hospital and Influence of Pharmacovigilance in Reporting ADR. Indian Journal of Pharmacology.40(1), 37-40. https://doi.org/10.4103/0253-7613.40488
Griffin, F. A., & Resar, R. K. (2009). IHI Global Trigger Tool for Measuring Adverse Events. Available at: https://www.ihi.org/resources/Pages/IHIWhitePapers/IHIGlobalTriggerToolWhitePaper.aspx
Guo, W., Li, M., Dong, Y., Zhou, H., Zhang, Z., Tian, C., Qin, R., Wang, H., Shen, Y., Du, K., Zhao, L., Fan, H., Luo, S., Hu, D. (2020). Diabetes is a risk factor for the progression and prognosis of COVID-19. Diabetes Metabolism Research and Review. 36(7). https://doi.org/10.1002/dmrr.3319
Gyselinck, I., Janssens, W., Verhamme, P., Vos, R. (2021). Rationale for azithromycin in COVID-19: an overview of existing evidence. BMJ Open Respiratory Research, 8(1). https://doi.org/10.1136/bmjresp-2020-000806
Kalil, A. C. (2020). Treating COVID-19—Off-Label Drug Use, Compassionate Use, and Randomized Clinical Trials During Pandemics. Journal of the American Medical Association, 323(19), 1897-1898. https://doi.org/10.1001/jama.2020.4742
Joshi, S., Parkar, J., Ansari, A., Vora, A., Talwar, D., Tiwaskar, M., Patil, S., Barkate, H. (2021). Role of favipiravir in the treatment of COVID-19. Elsevier. 102, 501-508. https://doi.org/10.1016/j.ijid.2020.10.069
Malik, V.S., Ravindra, K., Attri, S.V., Bhadada, S.K., & Singh, M. (2020). Higher body mass index is an important risk factor in COVID-19 patients: a systematic review and meta-analysis. Springer, 27(33), 42115-42123. https://doi.org/10.1007/s11356-020-10132-4
Mukherjee, S., & Pahan, K. (2021). Is COVID-19 Gender-sensitive? Journal of Neuroimmune Pharmacology, 16(1):38-47. https://doi.org/10.1007/s11481-020-09974-z
Naessens, J.M., O'Byrne, T.J., Johnson, M.G., Vansuch, M.B., McGlone, C.M., & Huddleston, J.M. (2010).
Measuring hospital adverse events: assessing inter-rater reliability and trigger performance of the Global Trigger Tool. International Journal for Quality Health Care. 22(4), 266-74. https://doi.org/10.1093/intqhc/mzq026
Naranjo, C.A., Busto, U., Sellers, E.M., Sandor, P., Ruiz, I., Roberts, E.A., Janecek, E., Domecq C., Greenblatt, D.J. (1981). A method for estimating the probability of adverse drug reactions. 30(2), 239-45. https://doi.org/10.1038/clpt.1981.154
Pandya, A.D., Patel, K., Rana, D., Gupta, S.D., Malhotra, S.D., & Patel, P. (2020). Global Trigger Tool: Proficient Adverse Drug Reaction Autodetection Method in Critical Care Patient Units. Indian Journal of Critical Care Medicine, 24(3):172-178. https://doi.org/10.5005/jp-journals-10071-23367
PDPI, PERKI, PAPDI, PERDATIN, & IDAI. (2020). Pedoman Tatalaksana COVID-19 Edisi 3. Jakarta. Available at: https://www.papdi.or.id/pdfs/983/Buku%20Pedoman%20Tatalaksana%20COVID-19%205OP%20Edisi%203%202020.pdf
Saltiel, A.R., & Olefsky, J.M. (2017). Inflammatory mechanisms linking obesity and metabolic disease. The Journal of Clinical Investigation. 127(1), 1-4. https://doi.org/10.1172/jci92035
Satuan Tugas Penanganan COVID-19. (2021). Peta Sebaran. COVID-19 Indonesia. Available at: https://covid19.go.id/peta-sebaran
Schnader, K.E., Pieper, C.F., Sloane, R., Ruby, C.M., Twersky, J., Francis, S.D., Branch L.G., Lindblad, C.I. (2004). Effects of Geriatric Evaluation and Management on Adverse Drug Reactions and Suboptimal Prescribing in the Frail Elderly. Elsevier, 116(6):394-401. https://doi.org/10.1016/j.amjmed.2003.10.031
Setiadi, A.P., Wibowo, Y.I., Halim, S.V., Brata, C., Presley, B., & Setiawan, E. (2020). Tata Laksana Terapi Pasien dengan COVID-19: Sebuah Kajian Naratif. Jurnal Farmasi Klinik Indonesia. Available at: https://jurnal.unpad.ac.id/ijcp/article/view/26774
Shah, H., Khan, S.H., Dhurandhar, N., & Hedge, V. (2020). The triumvirate: why hypertension, obesity, and diabetes are risk factors for adverse effects in patients with COVID 19. Acta Diabetologica. 58(7), 831-843. https://doi.org/10.1007/s00592-020-01636-z
Shereen, M.A., Khan, S., Kazmi, A., Bashi, N., & Siddique, R. (2020). COVID-19 infection: Origin, transmission, and characteristics of human coronaviruses. Journal of Advanced Research. 24, 91-98. https://doi.org/10.1016/j.jare.2020.03.005
Strong, M., Burrows, J., Stedman, E., & Redgrave, P. (2009). Adverse drug effects following oseltamivir mass treatment and prophylaxis in a school outbreak of 2009 pandemic influenza A(H1N1) in June 2009, Sheffield, United Kingdom separator. Eurosurveillance, 15(19). Available at: https://pubmed.ncbi.nlm.nih.gov/20483106/
Sun, J., Deng, X., Chen, X., Huang, J., Huang, S., Li, Y., Feng, J., Liu, J., He, G. (2020). Incidence of Adverse Drug Reactions in COVID-19 Patients in China: An Active Monitoring Study by Hospital Pharmacovigilance System. American Society for Clinical Pharmacology & Theraupetics. 108(4):791-797. https://doi.org/10.1002/cpt.1866
Yadav, P., Rohane, S., & Velhal, A. (2021). Adverse Drug Reactions and Comorbidities in Patient Treated for COVID-19. Asian Journal of Research in Chemistry, 14(6), 451-454. https://doi.org/10.52711/0974-4150.2021.00079
