Pengaruh Faktor Risiko terhadap Waktu Timbulnya Efek Samping Kanamisin pada Tuberkulosis Resistan Obat

Martha Ratna Wati, Reviono Reviono, Wachid Putranto, Yusup Subagio Sutanto, Harsini Harsini

Abstract


Kanamisin adalah obat untuk terapi tuberkulosis resistan obat (TB RO) yang menimbulkan efek samping gangguan pendengaran, gangguan fungsi ginjal, dan gangguan elektrolit terutama hipokalemia. Penelitian bertujuan menilai kesintasan waktu timbulnya efek samping dan pengaruh faktor risiko usia, riwayat terapi streptomisin serta berat badan terhadap efek samping akibat pemberian kanamisin pasien TB RO. Penelitian kohort retrospektif dari data rekam medis pasien TB RO dari Januari 2011 sampai April 2017 di RSUD Dr. Moewardi Surakarta. Analisis pengaruh faktor risiko terhadap efek samping menggunakan uji cox regression. Dari 238 pasien didapatkan gangguan pendengaran 143 pasien, gangguan fungsi ginjal 147 pasien, dan hipokalemia 169 pasien. Usia lebih dari 40 tahun hazard ratio (HR) 2,419 (IK: 95%; 1,716–3,409; p= 0,000) dan jenis kelamin perempuan HR: 1,549 (IK: 95%; 1,089–2,202; p= 0,015) berisiko terjadi gangguan pendengaran. Usia lebih dari 40 tahun HR: 1,892 (IK: 95%; 1,353–2,646; p= 0,000) dan jenis kelamin perempuan HR: 1,667 (IK: 95%; 1,179–2,357; p= 0,004) berisiko terjadi gangguan fungsi ginjal. Riwayat streptomisin sebelumnya dan indeks massa tubuh (IMT) tidak berisiko timbul efek samping akibat pemberian kanamisin. Pengawasan ketat timbulnya efek samping gangguan pendengaran dan gangguan fungsi ginjal pasien usia lebih dari 40 tahun dan perempuan pada pengobatan TB RO.

Kata kunci: Efek samping, gangguan fungsi ginjal, gangguan pendengaran, kanamisin, TB resistan obat

 

Effects of Risk Factors on the Onset of Kanamycin’s Adverse Events in Drug Resistant Tuberculosis

Kanamycin is a therapy for drug-resistant tuberculosis (TB) which may cause hearing loss, impaired kidney function, and electrolyte disorders, especially hypokalemia. The objective of this study was to assess patient survival and the effects of risk factors such as age, previous history of streptomycin therapy, and weight on adverse events due to kanamycin administration in patients with drug resistant TB. A retrospective cohort study was conducted in TB patients by using medical records from January 2011 to April 2017 in Dr. Moewardi Hospital Surakarta. Cox regression analysis was used to analyze the relation between risk factors and adverse events. Of 238 patients, 143 patients experienced hearing loss, 147 patients experienced impaired kidney function, and 169 patients had hypokalemia. Age over 40 and female gender had higher risks for hearing loss and impaired kidney function (HR: 2.419 (95% CI: 1.716–3.409; p= 0,000) and HR: 1,892 (95% CI: 1.353–2.646; p=0,000); HR: 1.549 (95%CI: 1.089–2.202; p=0,015), and HR: 1.667 (95% CI: 1.179–2.357; p=0.004)), respectively. History of streptomycin and body mass index (BMI) were not risk factors for  kanamycin’s adverse events. Therefore, closed monitoring on hearing loss and impaired kidney function is necessary for drug resistant TB patients aged over 40, and female patients.

Key words: Adverse events, drug resistant tuberculosis, hearing loss, impaired kidney function, kanamycin


Keywords


Efek samping, gangguan fungsi ginjal, gangguan pendengaran, kanamisin, TB resistan obat

Full Text:

PDF

References


Moenadjat Y. Luka Bakar: masalah dan tata laksana. Balai Penerbit FKUI. 2009;4:1-38.

Yuce Y, Acar HA, Erkal KH, Tuncai E. Can we make an early ‘do not resuscitate’ decision in severe burn patients?. J Ulus Travma Acil Cerrahi Derg. 2017;23(2):139–43 .

Brusselaers N, Monstrey S, Vogelaers D, Hoste E, Blot S. Severe burn injury in europe: a systematic review of the incidence, etiology, morbidity, and mortality. J Critical Care. 2010;14(5):R188.

El Mehrat AM, Ghareeb FM, Keshk F, El Sheikh YM, Ibrahim AH. Retrospective study of mortality and causes of death in menofia university burn center. Menoufia Med J. 2014;27(2):290–5.

Dokter J, Meijs J, Irma MMH, Oen, Eva BM, Vlies C, dkk. external validation of the revised baux score for the prediction of mortality in patients with acute burn injury. Lippincott Williams & Wilkins. J Trauma Acute Care Surgery.2014;76(3): 840–5.

Brusselaers N, Juhasz I, Erdei I, Monstrey S, Blot S. Evaluation of mortality following severe burns injury in Hungary: external validation of a prediction model developed on belgian burn data. Burns J. 2009;35(7):1009–14.

Karlie J, Wardhana A. External validation of Belgian outcome of burn injury score on burned patient in burn unit cipto mangunkusumo general hospital. New Ropanasuri J Surg. 2017;2(1):90–6.

Pujisriyani, Wardana A. Epidemiology of burn injuries in cipto mangunkusumo hospital from 2009 to 2010. Jurnal Plastik Rekonstruksi. 2012;1(5):528–31.

Salehi SH, As’adi K, Abbaszadeh KA, Isfeedvajani MS, Khodaei N. Comparison of six outcome prediction models in an adult burn population in a developing country. J Annals Burns Fire Disasters. 2017;30(1):13–7.

Sheppard NN, Gorse SH, Shelley OP, Philp B,Dziewulski P. Prognostic Scoring systems in burns: a review. Burns J. 2011;37(8):1288–95.

Al Ibran E, Mirza FH, Memon AA, Farooq MZ, Hasan M. Mortality associated with burn injury- a cross sectional study from Karaci, Pakistan. BMC Res Notes. 2013;6:545.

Zarei MR, Dianat S, Eslami V, Harirchi I, Boddouhi N, Zandieh A, dkk. Factors associated with mortality in adult hospitalized burn patients in Tehran. Turkish J Trauma Emerg Surg. Ulus Travma Acil Cerrahi Derg. 2011;17(1):61–5.

Dahal P, Ghimire S, Maharjan NK, Man Rai S. Baux’s and abbreviated burn severity score for the prediction of mortality in patients with acute burn injury. J College Med Sciences-Nepal. 2015;11(4):24–7.

Colohan S. Predicting prognosis in thermal burns with associated inhalational injury: a systematic review of prognostic factors in adult burn victims. J Burn Care Res. 2010; 31(4):529–39.

Pantet O, Fouzi M, Brusselaers N, Vemay A, Berger MM. Comparison of mortality prediction models and validation of SAPS II in critically ill burns patients. Annals Burns Fire Disaster. 2016;29(2):123–9.

Kumar S, Ali W, Pandey A, Rathore S. Epidemiology and mortality of burns in the Lucknow region, India-a 5 Year Study. Burns. 2013;30(4):8–15.

Brusselaers N, Agbenorku P, Hoyte-Williams PE. Assessment of mortality prediction models in Ghanaian burn population. Burns J. 2013;39(5):997–1003.

El-Helbawy RH, Ghareeb FM. Inhalation injury as a prognostic factor for mortality in burn patients. Annals Burns Fire Disasters. 2011;24(2):82–8.

Blot S. Development and validation of a model for prediction of mortality in patients with acute burn injury: the Belgian outcome in burn injury study group. British J Surg. 2009;96(1):111–7.




DOI: https://doi.org/10.15395/mkb.v50n2.1297

Article Metrics

Abstract view : 2057 times
PDF - 1873 times

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.


 


Creative Commons License
MKB is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

 


View My Stats