Objective. This study aims to identify predictors of 72-hour mortality in patients with diabetic ketoacidosis (DKA).Methodology. In this retrospective cohort study, data were obtained from medical records of adult patients with DKA in Cipto Mangunkusumo General Hospital from January 2011 to June 2017. Associations of predictors (age, type of diabetes, history of DKA, comorbidities, level of consciousness, renal function, bicarbonate, potassium, lactate, betahydroxybutyrate levels, and anion gap status) and 72-hour mortality were analyzed. The mortality prediction model was formulated by dividing the coefficient B by the standard error for all variables with p<0.05 in the multivariate analysis.Results. Eighty-six of 301 patients did not survive 72 hours after hospital admission. Comorbidities (HR 2.407; 95% CI 1.181-4.907), level of consciousness (HR 10.345; 95% CI 4.860-22.019), history of DKA (HR 2.126; 95% CI 1.308-3.457), and lactate level (HR 5.585; 95% CI 2.966-10.519) were significant predictors from multivariate analysis and were submitted to the prediction model. The prediction model had good performance. Patients with total score less than 3 points were at 15.41 % risk of mortality, 3 -4 points were 78.01% and 5 -6 points were 98.22% risk of mortality. Conclusion.The 72-hour mortality rate in Cipto Mangunkusumo General Hospital was 28.57%. The mortality prediction model had a good performance and consisted of comorbidities, history of DKA, level of consciousness and lactate level.

Introduction: Frailty syndrome is a predictor of all-cause mortality among older adults living in nursing homes. Data about the prevalence of frailty among individuals living in nursing homes particularly in middle-income countries are limited. Thus, this study aimed to identify the prevalence of frailty and its associated factors among older adults living in nursing homes in Indonesia. Methods: A cross-sectional study of older adults living in six nursing homes in Indonesia was conducted between May 2019 and December 2019. Data on demographic characteristics, physical activity (Physical Activity Scale for the Elderly), cognitive status (Abbreviated Mental Test), nutritional status (Mini Nutritional Assessment Short-form), depression (Geriatric Depression Scale), comorbidity, frailty state (Cardiovascular Health Study criteria), dietary pattern (24-h food recall), hand grip strength, and gait speed were evaluated. Bivariate and multivariate analyses were performed to identify factors independently associated with frailty Result: In total, 214 participants with a mean age of 73.68 (standard deviation: 4.30) years were recruited in this study. The prevalence rates of frailty and malnutrition were 46.5% and 58%, respectively. Results showed that physical frailty was associated with malnutrition (odd ratio: 4.23, 95% confidence interval: 1.730-10.380). Conclusion:Frailty is prevalent and strongly associated with malnutrition among older adults living in nursing homes in Indonesia.

Pendahuluan. Major adverse cardiac event (MACE) adalah komplikasi akut utama yang terjadi pada pasien infark miokard, meliputi gagal jantung akut, syok kardiogenik, dan aritmia fatal. Diperlukan biomarker yang akurat, mudah dilakukan, dan cost-effective untuk memprediksi MACE dan kematian. Cedera hati hipoksik atau HLI (hypoxic liver injury) adalah salah satu biomarker potensial menggunakan kadar enzim hati transaminase (serum glutamic-oxaloacetic transaminase/SGOT) sebagai parameter. Penelitian ini bertujuan untuk mengetahui peran HLI sebagai prediktor MACE pada pasien infark miokard tanpa gambaran EKG elevasi segmen ST (NSTEMI).Metode. Penelitian ini merupakan penelitian potong lintang dengan luaran berupa MACE dan kohort retrospektif dengan keluaran kematian selama masa perawatan. Populasi penelitian adalah semua pasien NSTEMI yang menjalani perawatan di ICCU Rumah Sakit Cipto Mangunkusumo (RSCM). Sampel penelitian adalah pasien NSTEMI yang menjalani perawatan di ICCU RSCM pada tahun 2006-2016 dan memenuhi kriteria penelitian. Penentuan titik potong HLI berdasarkan kadar SGOT yang dapat memprediksi MACE dan kematian dihitung dengan kurva ROC. Analisis multivariat dilakukan menggunakan regresi logistik untuk mendapatkan nilai prevalence odds ratio (POR) terhadap MACE dengan memasukkan kovariat. Analisis bivariat mengenai sintasan pasien terhadap kematian dilakukan dengan menggunakan kurva Kaplan-Meier dan diuji dengan log-rank.Hasil. Sebanyak 277 subjek diikutsertakan pada penelitian ini. Proporsi subjek dengan MACE pada penelitian ini adalah 51,3% (gagal jantung akut 48,4%, aritmia fatal 6,5%, syok kardiogenik 7,2%) dan angka kematian sebesar 6,13%. Median nilai SGOT adalah 35 U/L pada seluruh subjek, 40 (rentang 8-2062) U/L pada subjek dengan MACE dan 31 (rentang 6-1642) U/L pada subjek tanpa MACE (p = 0,003). Nilai titik potong yang diambil untuk memprediksi MACE adalah 101,0 U/L (sensitivitas 21,8%; spesifisitas 89,6%; POR 2,727 (IK 95%: 1,306-5,696), p = 0,006). Pada analisis multivariat tidak didapatkan hubungan yang bermakna antara HLI dengan MACE. Nilai titik potong untuk memprediksi kesintasan terhadap kematian adalah 99,0 U/L (sensitivitas 23,5%; spesifisitas 83,8%; likelihood ratio +1,46). Tidak didapatkan perbedaan kesintasan yang bermakna antara subjek dengan nilai HLI di bawah dan di atas titik potong kadar SGOT.Simpulan. Cedera hati hipoksik (HLI) tidak dapat digunakan untuk memprediksi MACE pada pasien NSTEMI kecuali dikombinasikan dengan variabel lain. Tidak terdapat perbedaan kesintasan yang bermakna antara subjek dengan atau tanpa HLI. Kata Kunci: Cedera hati hipoksik, Infark miokard, Kesintasan, MACE, NSTEMI, SGOTHypoxic Liver Injury as Predictor of Major Adverse Cardiac Events in Acute Myocardial Infarction patients admitted to Intensive Coroner Care Unit of Cipto Mangunkusumo National General HospitalIntroduction. Major adverse cardiac events (MACE) is a complicating myocard infarctwhich consist of acute heart failure, cardiogenic shock, and fatal arrhytmia. An accurate, easy and cost-effective biomarker is needed to predict MACE and mortality in patients with myocard infarct. Hypoxic liver injury (HLI) is a potential biomarker using serum glutamic-oxaloacetic transaminase (SGOT) level as the parameter. This study is aimed to discover HLI’s role in predicting MACE in non ST elevation myocard infarct (NSTEMI).Methods. This study was designed as cross sectional to predict MACE and prospective cohort for survival analysis. Study population was all NSTEMI patients admitted to ICCU of Cipto Mangunkusumo Hospital and study sample were NSTEMI patients admitted to ICCU of Cipto Mangunkusumo Hospital that meets all criteria during 2006-2016. Cut-off level of SGOT for HLI to predict MACE and mortality was analyzed using ROC curve and AUC. Survival analysis was done using Kaplan Meier curve and the difference was tested with log-rank. Results. A total of 277 subjects were included in this study. Incidence of MACE in this study was 51.3% (acute heart failure 48.4%, fatal arrhytmia 6.5%, and cardiogenic shock 7.2%).The mortality rate was 6.13%. The median of SGOT level on all subject was 35 U/L, 40 (range 8-2062) U/L in subjects with MACE and 31 (range 6-1642) U/L in subjects without MACE (p = 0.003). Cut-off level for SGOT used to predict MACE was 101 U/L (sensitivity 21.8%; specificity 89.6%; POR 2.727 (CI 95% 1.306-5.696), p = 0.006). In multivariate analysis, HLI was insignificantly related to MACE. Cut-off level for SGOT used to predict survival was 99 U/L (sensitivity 23.5%; specificity 83.8%; likelihood ratio +1.46). There were no significant difference of survival between groups with HLI level below and above the cut-off SGOT level. Conclusion. Hypoxic liver injury (HLI) cannot be used to predict MACE in NSTEMI patients unless combined with other variables. There is no significant difference of survival between subjects with or without HLI.

The COVID-19 pandemic has caused significant morbidity and mortality worldwide, especially among health-care workers. One of the most important preventive measures is vaccination. This study examined factors associated with the incidence rate of SARS-CoV-2 infection after mRNA-1273 booster vaccination (preceded by the CoronaVac primary vaccination) and the antibody profile of health-care workers at one of the tertiary hospitals in Indonesia. This was a combined retrospective cohort and cross-sectional study. Three hundred health-care workers who were given the mRNA-1273 booster vaccine a minimum of 5 months prior to this study were randomly selected. Participants were then interviewed about their history of COVID-19 vaccination, history of SARS-CoV-2 infection, and comorbidities. Blood samples were taken to assess IgG sRBD antibody levels. The median antibody level was found to be 659 BAU/mL (min 37 BAU/mL, max 5680 BAU/mL, QIR 822 BAU/mL) after the booster, and this was not related to age, sex, comorbidities, or adverse events following immunization (AEFI) after the booster. SARS-CoV-2 infection after the booster was correlated with higher antibody levels. In sum, 56 participants (18.6%) experienced SARS-CoV-2 infection after the mRNA-1273 booster vaccination within 5 months. Incidence per person per month was 3.2%. Age, sex, diabetes mellitus type 2, hypertension, obesity, and post-booster AEFI were not related to COVID-19 incidence after the booster. History of SARS-CoV-2 infection before the booster vaccination was significantly associated with a reduced risk of SARS-CoV-2 infection after booster vaccination, with a relative risk (RR) of 0.21 (95% CI 0.09–0.45, p < 0.001).