Detection of Adverse Drug Reactions in hospitalized patients: a network analysis approach
DOI:
https://doi.org/10.59681/2175-4411.v16.2024.1116Palavras-chave:
Drug-Related Side Effects and Adverse Reactions, Inpatients, Drug Therapy, Observational StudyResumo
Objective: We aimed to investigate whether network analysis can be used to estimate patterns of Adverse Drug Reactions and drugs involved. Methods: Patients admitted from 18 years of age or older, hospitalized for more than 24 hours, and using at least one drug during hospitalization were included. Results: 8060 patients were observed, and 358 cases of Adverse Drug Reactions were identified (4.43%). The network graph shows that the occurrence of hypotension induced by furosemide, spironolactone and enalapril is related to serum changes in potassium and the occurrence of renal failure. Centered around nausea and vomiting node, there is a great variety of drugs from different classes involved with this Adverse Drug Reaction and without other connections. Conclusion: Network analysis is a promising strategy for identifying patterns that correlate adverse reactions to drugs administered during hospitalization.
Referências
Pedrós C, Quintana B, Rebolledo M, Porta N, Vallano A, Arnau JM. Prevalence, risk factors and main features of adverse drug reactions leading to hospital admission. Eur J Clin Pharmacol. 2013 Mar;70(3):361-7. DOI: https://doi.org/10.1007/s00228-013-1630-5
Miguel A, Azevedo LF, Araújo M, Pereira AC. Frequency of adverse drug reactions in hospitalized patients: a systematic review and meta-analysis. Pharmacoepidemiol Drug Saf. 2012 Nov;21(11):1139-54. DOI: https://doi.org/10.1002/pds.3309
Nebeker JR, Barach P, Samore MH. Clarifying adverse drug events: a clinician's guide to terminology, documentation, and reporting. Ann Intern Med. 2004 May 18;140(10):795. DOI: https://doi.org/10.7326/0003-4819-140-10-200405180-00009
Onder G, Petrovic M, Tangiisuran B, Meinardi MC, Markito-Notenboom WP, Somers A, et al. Development and Validation of a Score to Assess Risk of Adverse Drug Reactions Among In-Hospital Patients 65 Years or Older. Arch Intern Med. 2010 Jul 12;170(13):1142-8. DOI: https://doi.org/10.1001/archinternmed.2010.153
Klopotowska JE, Wierenga PC, Smorenburg SM, Stuijt CCM, Arisz L, Kuks PFM, et al. Recognition of adverse drug events in older hospitalized medical patients. Eur J Clin Pharmacol. 2012 Jan;69(1):75-85. DOI: https://doi.org/10.1007/s00228-012-1316-4
Edwards IR, Aronson JK. Adverse drug reactions: definitions, diagnosis, and management. Lancet. 2000 Oct 14;356(9237):1255-9. DOI: https://doi.org/10.1016/S0140-6736(00)02799-9
Bastian M, Heymann S, Jacomy M. Gephi: An Open Source Software for Exploring and Manipulating Networks. Proceedings of the International AAAI Conference on Web and Social Media. 2009;3(1):361-2. DOI: https://doi.org/10.1609/icwsm.v3i1.13937
World Health Organization. The importance of pharmacovigilance [Internet]. apps.who.int. 2002. Available from: https://apps.who.int/iris/handle/10665/42493.
Griffin F, Resar R. IHI Global Trigger Tool for Measuring Adverse Events. IHI Innovation Series white paper. Cambridge, MA: Institute for Healthcare Improvement, 2009.
Naranjo CA, Busto U, Sellers EM, Sandor P, Ruiz I, Roberts EA, et al. A method for estimating the probability of adverse drug reactions. Clin Pharmacol Ther. 1981;30(2):239-45. DOI: https://doi.org/10.1038/clpt.1981.154
Scott J. Social Network Analysis. Sociology. 1988;22(1):109-127. DOI: https://doi.org/10.1177/0038038588022001007
Dehmer M, Basak SC. Statistical and Machine Learning Approaches for Network Analysis. John Wiley & Sons: Hoboken, NJ, USA; 2012. ISBN 978-1-118-34698-3. DOI: https://doi.org/10.1002/9781118346990
Cherven K. Mastering Gephi Network Visualization. Packt Publishing Ltd, Birmingham; 2015. 349 pages.
Hu Y. Efficient, high-quality force-directed graph drawing. Math J. 2006;10(1):37-71.
Bultinck J, Lievens S, Tavernier J. Protein-protein interactions: network analysis and applications in drug discovery. Curr Pharm Des. 2012;18(30):4619-29. DOI: https://doi.org/10.2174/138161212802651562
Zhao S, Iyengar R. Systems pharmacology: network analysis to identify multiscale mechanisms of drug action. Annu Rev Pharmacol Toxicol. 2012;52:505-21. DOI: https://doi.org/10.1146/annurev-pharmtox-010611-134520
Leopoldino RW, Costa HT, Costa TX, et al. Potential drug incompatibilities in the neonatal intensive care unit: a network analysis approach. BMC Pharmacol Toxicol. 2018;19(1):83. DOI: https://doi.org/10.1186/s40360-018-0265-7
Lehman L, Saeed M, Moody G, et al. Hypotension as a Risk Factor for Acute Kidney Injury in ICU Patients. Comput Cardiol. 2010;37:1095-1098.
Mas-Font S, Ros-Martinez J, Pérez-Calvo C, et al. Prevention of acute kidney injury in Intensive Care Units. Med Intensiva. 2017;41(2):116-126. DOI: https://doi.org/10.1016/j.medin.2016.12.004
Regulski M, Regulska K, Stanisz BJ, et al. Chemistry and Pharmacology of Angiotensin-Converting Enzyme Inhibitors. Curr Pharm Des. 2015;21(13):1764-75. DOI: https://doi.org/10.2174/1381612820666141112160013
DiNicolantonio JJ, Lavie CJ, Fares H, et al. Meta-Analysis of Carvedilol Versus Beta 1 Selective Beta-B (Atenolol, Bisoprolol, Metoprolol, and Nebivolol). Am J Cardiol. 2013;111(5):765-9. DOI: https://doi.org/10.1016/j.amjcard.2012.11.031
Tramadol (2019). In Micromedex (Columbia Basin College Library ed.) [Electronic version]. Greenwood Village, CO: Truven Health Analytics. Available from: https://www.micromedexsolutions.com/micromedex2/librarian/PFDefaultActionId/evidencexpert.DoIntegratedSearch?navitem=headerLogout. Accessed on June 28, 2019.
Donsa K, Beck P, Höll B, et al. Impact of errors in paper-based and computerized diabetes management with decision support for hospitalized patients with type 2 diabetes. A post-hoc analysis of a before and after study. Int J Med Inform. 2016;90:58-67. DOI: https://doi.org/10.1016/j.ijmedinf.2016.03.007
Boroumand M, Goodarzynejad H. Monitoring of Anticoagulant Therapy in Heart Disease: Considerations for the Current Assays. J Tehran Heart Cent. 2010;5(2):57-68.
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Direitos de Autor (c) 2024 Sara Iasmin Vieira Cunha Lima, Valdjane Saldanha, Ivonete Batista de Araújo, Amaxsell Thiago Barros de Souza, Vivian Nogueira Silbiger, Isabelle Cristina Clemente dos Santos, Antonio Gouveia Oliveira, Rand Randall Martins
Este trabalho encontra-se publicado com a Licença Internacional Creative Commons Atribuição-NãoComercial-CompartilhaIgual 4.0.
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