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Human Immunodeficiency Virus (HIV) is still an issue in health sector in the world, particularly in Indonesia. Progression of disease is influenced by various factors including age, genetic, and other infectious diseases such as tuberculosis and hepatitis, nutritional factors, and immunological status. ARV therapy has not been able to cure the disease yet is able to control the progression of HIV/AIDS by suppressing viral replication which reduce the incidence of opportunistic infections. Although the program has been implemented, the deaths from HIV continue to occur, especially in the first year of ARV treatment. This study aims to investigate the predictors related to death in HIV-AIDS patients with ARV therapy in Dr. H. Marzoeki Mahdi Hospital in Bogor in 2008-2012. The study design was retrospective cohort using ART registration data and Medical Record. Number of samples were 396 HIV patients with ARV therapy. Data analysis was performed using Cox Regression. The multivariate analysis showed that the predictors of deaths in HIV-AIDS patients with ARV therapy were functional baring status (RR = 2.34, 95% CI: 1.32-4.11), heavy IO category (RR = 2.11, 95% CI : 1.26-3.54), and anemia status (RR = 2.56, 95% CI: 1.74-3.77). Special attention and monitoring are required for HIV/AIDS patients taking antiretroviral medications with functional status of baring, anemia, and having severe opportunistic infections. Keywords: ARV; HIV-AIDS; Retrospective cohort; Death; Predictors.
The number of new HIV infections in Indonesia is still high, reaching 46,000 and number of deaths caused by HIV is 38,000 in 2018. Hepatitis C coinfection in HIV patients is high, ranging from 2-15%. This study aims to examine the effect of hepatitis C coinfection on survival of HIV patients receiving antiretroviral therapy at Tebet Regional Public Hospital (RSUD) in 2015-2020. This research used retrospectif cohort design with survival analysis and used total sampling as much as 284 HIV patients. Data were analyzed univariately to see the frequency distribution of each variable studied. Bivariate analysis was performed to see the relationship of each independent variable with the survival of HIV. Multivariate analysis was performed to obtain robust and parsimonius models with Cox Regression. The results of research found cumulatif survival of HIV patients in RSUD Tebet were 85,4 %. The Effect of Hepatitis C Coinfection on Survival HIV Patients Who Receive Antiretroviral Therapy in RSUD Tebet from 2015 until 2020 had HR 1,94 (95% CI 0,81-4,6) after adjusted with body mass index and working status. There were no corelation from Hepatitis C Coinfection on Survival HIV Patients Who Receive Antiretroviral Therapy in RSUD Tebet from 2015 until 2020.
Sepsis neonatal merupakan salah satu penyebab morbiditas dan mortalitas tersering pada neonatus. Ketepatan pemberian antibiotik empirik memegang peranan penting dalam keberhasilan terapi. Kegagalan terapi antibiotik yang biasanya dikaitkan dengan terapi empirik, terjadi jika tujuan pemberian antibiotik untuk mengatasi infeksi tidak tercapai, yang ditandai dengan menetapnya atau bahkan memburuknya manifestasi klinis infeksi pada pasien, namun definisi pasti belum ditetapkan. Penelitian ini bertujuan untuk mengidentifikasi dan mengembangkan model prediksi dari faktor-faktor yang berhubungan dengan kegagalan terapi antibiotik empirik lini I pada pasien sepsis neonatal di RSUP dr. Soeradji Tirtonegoro. Penelitian dilakukan dengan desain kohort retrospektif pada 237 pasien dengan sepsis neonatal. Analisis multivariat dengan regressi poisson dilakukan untuk mendapatkan model akhir dari faktor-faktor yang berhubungan. Selanjutnya dilakukan konversi nilai koefisien β menjadi nilai skor untuk membentuk model prediksi. Model akhir yang didapat dilakukan analisis diskriminasi dengan menilai area under curve (AUC) pada kurva receiver operating characteristics (ROC) dan titik potong yang optimal akan ditentukan berdasarkan total skor. Hasil penelitian diperoleh proporsi kegagalan terapi antibiotik empirik lini I sebesar 46,41%. Faktor yang berhubungan dengan kegagalan terapi antibiotik empirik lini I adalah berat lahir < 2500 gram (aRR 1,46, p-value 0,028, IK95% 1,04-2,05), tidak mendapat ASI (aRR 1,66, p-value <0,005, IK95% 1,28-2,14), rujukan (aRR 1,25, p-value 0,090, IK95% 0,96-1,63), leukosit yang tidak normal (aRR 1,31, p-value 0,080, IK95% 0,96-1,79), trombosit yang tidak normal (aRR 1,66, p-value <0,005, IK95% 1,30-2,12) dan netrofil yang tidak normal (aRR 1,47, p-value 0,003, IK95% 1,14-1,89). Model prediksi ini mempunyai nilai AUC 0,7661 (IK95% 0,70890 – 0,82013). Ditetapkan titik potong sebesar ≥ 29 dengan nilai sensitifitas 80,00% dan spesifisitas 62,20%. Kesimpulan penelitian ini adalah model prediksi yang diperoleh cukup baik untuk memprediksi kegagalan terapi antibiotik empirik lini I. Perlu dilakukan penelitian lebih lanjut dengan desain penelitian yang lebih baik menggunakan prediktor yang lebih spesifik.
Neonatal sepsis is one of the most common causes of morbidity and mortality in neonates. Accuracy in administering antibiotics empirically plays an important role in the success of therapy. Failure of antibiotic therapy, which is usually associated with empiric therapy, occurs if the goal of administering antibiotics to treat infection is not achieved, which is characterized by persistence or even worsening of the clinical infection manifested in the patient, but a definite definition has not been established. This study aims to identify and develop a predictive model of factors associated with failure of first line empiric antibiotic therapy in neonatal sepsis patients at RSUP dr. Soeradji Tirtonegoro. The study was conducted with a retrospective cohort design on 237 patients with neonatal sepsis. Multivariate analysis with Poisson regression was carried out to obtain a final model of related factors. Next, the β coefficient value is converted into a score value to form a predictive model. The final model obtained by discrimination analysis is carried out by assessing the area under curve (AUC) on the receiver operating characteristic (ROC) curve and the optimal cut point will be determined based on the total score. The results of the study showed that the proportion of failure of first line empirical antibiotic therapy was 46.41%. Factors associated with failure of first line empiric antibiotic therapy were birth weight < 2500 grams (aRR 1.46, p-value 0.028, 95%CI 1.04-2.05), not receiving breast milk (aRR 1.66, p -value <0.005, 95%CI 1.28-2.14), outborn (aRR 1.25, p-value 0.090, 95%CI 0.96-1.63), abnormal leucocite (aRR 1.31, p-value 0.080, CI95% 0.96-1.79), abnormal platelet values (aRR 1.66, p-value <0.005, 95%CI 1.30-2.12) and abnormal neutrophils (aRR 1.47, p-value 0.003, 95%CI 1.14-1.89). The predictive model has an AUC value of 0.7661 (95%CI 0,70890 – 0,82013). The cut point was set at ≥ 29 with a sensitivity value of 80.00% and specificity of 62.20%. The conclusion of this study is that the predictive model obtained is good enough to predict failure of first line empirical antibiotic therapy. Further research needs to be carried out with a better research design using more specific predictors.
ABSTRACT
Background. Chemotherapy is a therapeutic modality for elderly with cancer which can pose elderly, especially frail patients, to fatal side effect. To date, there is no prediction model incorporating frailty in clincal practice. This study aims to develop prediction model which includes frailty state evaluation in predicting severe chemotoxicity in elderly. Methods. A retrospective cohort study using secondary data of elderly underwent chemotherapy during 2019-2021 was conducted in Cipto Mangunkusumo Hospital. Data of determinants ( sex, age, polypharmacy, frailty status, nutritional status, depression, cognitive status, cancer type, polychemotherapy, and functional status) and the incidence severe chemotherapy side effect according to grade 3-5 CTCAE were collected. Data was analyzed to develop prediction model with Cox regression using SPSS Results. Of 193 subjects, most of them are male, with median age of 65.6 (IQR 60-82) years old. Severe chemotoxicity was found in 36% of the subjects. Prediction model consists of polypharmacy, number of chemotherapy drugs, cancer type and frailty status was developed. The model has AUC of 0.79 (95% CI 0.70-0.88), p value 0,01 Conclusion. A prognostic Model consists of polypharmacy, number of chemotherapy drugs, cancer type and frailty status can predict incidence of severe chemotoxicity in elderly with AUC 0.79 (95%CI 0.70-0.88)