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Systemic Lupus Erythematosus ( SLE ) is an autoimmune disease that results in inflammation in many organs. The prevalenceof SLE is increasing and the mortality rate was high. Etiology of SLE has not known. However , several risk factors could be expected to affect the incidence of SLE . One of them is a history of drug allergies, especially antibiotics. This study aimed to determine the relationship between antibiotic allergy history and SLE after controlled by family history,other autoimmune disease, age of menarche, and smoking behavior in Dr. Hasan Sadikin Hospital Bandung. This study was conducted from April to July 2014 using case-control design. Cases were women SLE patients who went to Rheumatology Department Dr. Hasan Sadikin Hospital Bandung. Control were a female patient who went to Internist Department with individually matched at the age ( 3 years range ), and region. Data were analyzed with univariate, bivariate , and multivariate conditional logistic regression. The results showed that a history of antibiotic allergy tends to increase the incidence of SLE for 2.34 times ( OR = 2.34 , 95 % CI 0.66 to 8.22 ) after controlled by SLE family history, history of autoimmune, and smoking behavior. For the class of penicillin/cephalosporin, the risk increased to 2.75 times ( OR = 2.75 , 95 % CI 0.65 to 11.59) . Keywords : SLE , antibiotic allergy , matched case-control
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.
Tuberculosis (TB) is an infectious disease that remains a significant public health problem in Indonesia, particularly in West Java. Bogor Regency, Bandung City, and Bekasi City are among the regions with the highest number of TB cases in the province. Environmental factors such as population density, altitude, and healthy housing coverage, are suspected to contribute to the incidence of TB. This study aims to describe the incidence of TB, examine the correlation between environmental factors and TB cases, and analyze the spatial distribution to identify high-risk areas for targeted intervention. This ecological study used secondary data from 2022 to 2024 obtained from the Health Office, Statistics Indonesia (BPS), and the Geospatial Information Agency (BIG). Analyses were conducted using descriptive statistics, correlation tests, spatial mapping, and vulnerability assessment through SPSS and QGIS applications. The results showed an increasing trend in TB cases across all three regions. A significant correlation was found between population density and healthy housing coverage with TB incidence in Bogor and Bandung, but not in Bekasi. Altitude was not associated with TB incidence in any of the regions. The spatial distribution revealed variations in environmental factors related to TB incidence between regions. Bandung City was identified as having the highest level of TB vulnerability. Area-based TB control interventions are therefore necessary, particularly in densely populated and high-risk areas. It is recommended to strengthen active epidemiological surveillance (active case finding), develop a real-time spatial TB information system integrated with surveillance data, establish cross-sectoral collaboration, evaluate the standards for healthy housing assessment, promote local regulations related to TB control, and enhance community participation in TB prevention, especially in densely populated and high-risk areas.