Euphemia Seto - Academia.edu (original) (raw)

Papers by Euphemia Seto

Research paper thumbnail of Diagnostic Test of a Scoring System for Frailty Syndrome in the Elderly According to Cardiovascular Health Study, Study of Osteoporotic Fracture and Comprehensive Geriatric Assessment Based Frailty Index Compared with Frailty Index 40 Items

Acta Medica Indonesiana, 2015

to get a recommendation on the best frailty syndrome diagnostic tools, that will be able to be pr... more to get a recommendation on the best frailty syndrome diagnostic tools, that will be able to be practiced on a daily setting in Indonesia. this is a cross-sectional study with diagnostic test approach, conducted to patients in the Geriatric Outpatient Clinic of Cipto Mangunkusumo National Referral Hospital on May-June 2013. Each subject underwent a frailty evaluation using CHS, SOF, FI-CGA and FI-40 scoring systems. Then, we calculate the sensitivity, specificity, PPV, NPV, LR+ and LR- of each scoring system compared to FI-40. the proportion of frail, pre-frail and fit according to FI-40 are 25.3%, 71% and 3.7% respectively. In terms of differentiation frail to non-frail, CHS had 41.2% sensitivity, 95% specificity, PPV 73.7%, NPV 82.7%, LR+ 8.41 and LR- 0.62. SOF scoring system had 17.6% sensitivity, 99.5% specificity, PPV 92.3%, NPV 78.1%, LR+ 35.2 and LR- 0.83. Furthermore FI-CGA had 8.8% sensitivity, 100% specificity, PPV 100%, NPV 76.4%, LR+ and LR- 0.91. There is no better scori...

Research paper thumbnail of Frailty state among Indonesian elderly: prevalence, associated factors, and frailty state transition

BMC Geriatrics, Jul 3, 2019

Background: Information about frailty status and its transition is important to inform clinical d... more Background: Information about frailty status and its transition is important to inform clinical decisions. Predicting frailty transition is beneficial for its prevention. While Indonesia is the 4th largest geriatric population in Asia, data about frailty transition is limited. This study aimed to obtain data on prevalence of frailty, its risk factors, frailty state transition and its prognostic factors, as well as to develop prognostic score for frailty state transition. Methods: Multicenter study on subjects aged ≥60 years old was done to obtain the prevalence of frailty status and to identify risk factors of frailty. Prospective cohort over 12 months was done to obtain data on frailty state transition. Multiple logistic regression analysis was performed to identify its prognostic factors from several clinical data, which then were utilized to develop prognostic score for frailty state worsening. Results: Cross-sectional data from 448 subjects showed that 25.2% of the subjects were frail based on Frailty index-40 items. Risk factors of frailty were age (OR 2.72; 95% CI 1.58-4.76), functional status (OR 2.89; 95% CI 1.79-4.67), and nutritional status (OR 3.75; 95% CI 2.29-6.13). Data from the 162 subjects who completed the cohort showed 27.2% of the cohort had frailty state worsening. Prognostic factors for frailty state worsening were being 70 years or older (OR 3.9; 95% CI 1.2-12.3, p < 0.05), negative QoL, i.e., fair and poor QoL (OR 2.5; 95% CI 1.1-5.9, p < 0.05), and slow gait speed (OR 2.8; 95% CI 1.3-6.4, p < 0.05). The internal validation of the prognostic score consisted of those three variables showed good performance. Conclusion: The prevalence of frailty in this study among Indonesian elderly in outpatient setting was 25.2%. The risk factors of frailty were age, functional status and nutritional status. The prognostic factors for frailty state worsening were being 70 years old or older, negative QoL (fair or poor quality of life), and slow gait speed. A prognostic score to predict frailty state worsening in 12 months had been developed.

Research paper thumbnail of Diagnostic Test of a Scoring System for Frailty Syndrome in the Elderly According to Cardiovascular Health Study, Study of Osteoporotic Fracture and Comprehensive Geriatric Assessment Based Frailty Index Compared with Frailty Index 40 Items

Acta medica Indonesiana, 2015

AIM to get a recommendation on the best frailty syndrome diagnostic tools, that will be able to b... more AIM to get a recommendation on the best frailty syndrome diagnostic tools, that will be able to be practiced on a daily setting in Indonesia. METHODS this is a cross-sectional study with diagnostic test approach, conducted to patients in the Geriatric Outpatient Clinic of Cipto Mangunkusumo National Referral Hospital on May-June 2013. Each subject underwent a frailty evaluation using CHS, SOF, FI-CGA and FI-40 scoring systems. Then, we calculate the sensitivity, specificity, PPV, NPV, LR+ and LR- of each scoring system compared to FI-40. RESULTS the proportion of frail, pre-frail and fit according to FI-40 are 25.3%, 71% and 3.7% respectively. In terms of differentiation frail to non-frail, CHS had 41.2% sensitivity, 95% specificity, PPV 73.7%, NPV 82.7%, LR+ 8.41 and LR- 0.62. SOF scoring system had 17.6% sensitivity, 99.5% specificity, PPV 92.3%, NPV 78.1%, LR+ 35.2 and LR- 0.83. Furthermore FI-CGA had 8.8% sensitivity, 100% specificity, PPV 100%, NPV 76.4%, LR+ and LR- 0.91. CONC...

Research paper thumbnail of Frailty Status and Its Associated Factors Among Indonesian Elderly People

Innovation in Aging, Jun 30, 2017

Research paper thumbnail of Pengaruh Penggunaan Proton Pump Inhibitor Jangka Panjang terhadap Sindrom Frailty pada Pasien Usia Lanjut

Jurnal Penyakit Dalam Indonesia

Pendahuluan. Sindrom frailty berkaitan dengan angka morbiditas dan kematian yang lebih tinggi, se... more Pendahuluan. Sindrom frailty berkaitan dengan angka morbiditas dan kematian yang lebih tinggi, sehingga dipakai sebagai prediktor kesehatan pada orang usia lanjut (usila). Polifarmasi sebagai salah satu faktor risiko sindrom frailty dapat berkaitan dengan obat Proton Pump Inhibitor (PPI) yang sering diberikan pada usila atas indikasi adanya keluhan gangguan saluran cerna bagian atas. Sampai saat ini belum ada penelitian yang mempelajari hubungan PPI jangka panjang dan sindrom frailty pada usila.Metode. Studi kasus kontrol pada pasien usila di Rumah Sakit dr. Cipto Mangunkusumo (RSCM), Jakarta. Kelompok kasus adalah usila terdiagnosis Frailty menurut FI-40 item dan kontrol adalah usila yang tidak frail berdasarkan instrumen yang sama. Data yang digunakan pada penelitian ini berasal dari data sekunder status frailty berdasarkan penelitian sebelumnya dan data rekam medis poliklinik Geriatri dan poliklinik diabetes RSCM.Hasil. Didapatkan 225 subjek (75 kasus: 150 kontrol), 59,6% berjeni...

Research paper thumbnail of Poor Sleep Quality of Hospitalized Geriatric Patients in General Hospital in Karawaci, Tangerang, Banten Province, Indonesia

Medicinus

Background: In Indonesia, geriatric population in the year 2005 was 15.8 million (7.2 % populatio... more Background: In Indonesia, geriatric population in the year 2005 was 15.8 million (7.2 % population), and expected to reach 11.34% in the year 2020. There was growing evidence for poor sleep as an independent risk factor for poor physical and mental health. Geriatric population may be particularly vulnerable to effects of sleep disturbance due to significant age-related changes in both sleep and inflammatory regulationObjective: To study the epidemiological (gender, age group) and health status (co-morbidities), sleep quality according to Pittsburgh Sleep Quality Index (PSQI) and its associations in geriatric population hospitalized in General Hospital in Karawaci, Tangerang, Banten Province, Indonesia.Materials and Methods: A hospital based cross sectional study was conducted from January to June 2014. A total of 92 subjects aged 60 years and above were selected consecutively from hospitalized geriatric patients for this study. The data was analyzed by means and proportions.Results:...

Research paper thumbnail of Frailty state among Indonesian elderly: prevalence, associated factors, and frailty state transition

BMC Geriatrics

Background: Information about frailty status and its transition is important to inform clinical d... more Background: Information about frailty status and its transition is important to inform clinical decisions. Predicting frailty transition is beneficial for its prevention. While Indonesia is the 4th largest geriatric population in Asia, data about frailty transition is limited. This study aimed to obtain data on prevalence of frailty, its risk factors, frailty state transition and its prognostic factors, as well as to develop prognostic score for frailty state transition. Methods: Multicenter study on subjects aged ≥60 years old was done to obtain the prevalence of frailty status and to identify risk factors of frailty. Prospective cohort over 12 months was done to obtain data on frailty state transition. Multiple logistic regression analysis was performed to identify its prognostic factors from several clinical data, which then were utilized to develop prognostic score for frailty state worsening. Results: Cross-sectional data from 448 subjects showed that 25.2% of the subjects were frail based on Frailty index-40 items. Risk factors of frailty were age (OR 2.72; 95% CI 1.58-4.76), functional status (OR 2.89; 95% CI 1.79-4.67), and nutritional status (OR 3.75; 95% CI 2.29-6.13). Data from the 162 subjects who completed the cohort showed 27.2% of the cohort had frailty state worsening. Prognostic factors for frailty state worsening were being 70 years or older (OR 3.9; 95% CI 1.2-12.3, p < 0.05), negative QoL, i.e., fair and poor QoL (OR 2.5; 95% CI 1.1-5.9, p < 0.05), and slow gait speed (OR 2.8; 95% CI 1.3-6.4, p < 0.05). The internal validation of the prognostic score consisted of those three variables showed good performance. Conclusion: The prevalence of frailty in this study among Indonesian elderly in outpatient setting was 25.2%. The risk factors of frailty were age, functional status and nutritional status. The prognostic factors for frailty state worsening were being 70 years old or older, negative QoL (fair or poor quality of life), and slow gait speed. A prognostic score to predict frailty state worsening in 12 months had been developed.

Research paper thumbnail of Diagnostic Test of a Scoring System for Frailty Syndrome in the Elderly According to Cardiovascular Health Study, Study of Osteoporotic Fracture and Comprehensive Geriatric Assessment Based Frailty Index Compared with Frailty Index 40 Items

Acta medica Indonesiana, 2015

to get a recommendation on the best frailty syndrome diagnostic tools, that will be able to be pr... more to get a recommendation on the best frailty syndrome diagnostic tools, that will be able to be practiced on a daily setting in Indonesia. this is a cross-sectional study with diagnostic test approach, conducted to patients in the Geriatric Outpatient Clinic of Cipto Mangunkusumo National Referral Hospital on May-June 2013. Each subject underwent a frailty evaluation using CHS, SOF, FI-CGA and FI-40 scoring systems. Then, we calculate the sensitivity, specificity, PPV, NPV, LR+ and LR- of each scoring system compared to FI-40. the proportion of frail, pre-frail and fit according to FI-40 are 25.3%, 71% and 3.7% respectively. In terms of differentiation frail to non-frail, CHS had 41.2% sensitivity, 95% specificity, PPV 73.7%, NPV 82.7%, LR+ 8.41 and LR- 0.62. SOF scoring system had 17.6% sensitivity, 99.5% specificity, PPV 92.3%, NPV 78.1%, LR+ 35.2 and LR- 0.83. Furthermore FI-CGA had 8.8% sensitivity, 100% specificity, PPV 100%, NPV 76.4%, LR+ and LR- 0.91. There is no better scori...

Research paper thumbnail of P0022 Clinical characteristics of young Indonesian colorectal cancer patients: A preliminary study

European Journal of Cancer, 2015

Research paper thumbnail of Pulmonary Arterial Hypertension in Graves’ Disease

Journal of Hypertension, 2015

ABSTRACT Background Cardiovascular manifestations in Graves’ disease (GD) occur frequently with v... more ABSTRACT Background Cardiovascular manifestations in Graves’ disease (GD) occur frequently with various phenotypes. A link between GD and pulmonary hypertension has been reported. There is limited data about prevalence PAH and related factors in GD in Indonesia. Objective To identify the prevalence and related factors of PAH in GD. Method This retrospective study is using secondary data from transthoracic echocardiographic database of General Hospital since last year. PAH was measured by continuous-wave Doppler echocardiography (pulmonary artery systolic pressure &gt; 35 mmHg). Sixty five patients who were diagnosed as GD were enrolled to study participant. Results Of 65 eligible participants consist of 52 female and 13 male and median ages 42 year old (18-66 year old). Cardiac abnormalities were encountered in 79% participant of which consist of PAH in 15.4%. The patients with pulmonary hypertension had significantly higher pulmonary vascular resistance (PVR), cardiac output compared to those without (p&lt;0.001 and p&lt;0.021 respectively). The possible explanations in addition to the effect of thyroid hormone on the cardiovascular system, autoimmune-mediated pulmonary vascular remodeling may play a role in Graves’ disease-linked elevated pulmonary artery systolic pressure. Conclusion The prevalence of PAH in GD was 15.4%. There is still needed future research to know the factors related to PAH especially related to clinical and laboratory abnormalities in GD.

Research paper thumbnail of Resident Medical Officer′s Knowledge of Sepsis: A Qualitative Study

Journal of Global Infectious Diseases, 2014

is frequent and is responsible for high mortality. [1] Mortality in the hospital ranges 20.7-55.2... more is frequent and is responsible for high mortality. [1] Mortality in the hospital ranges 20.7-55.2% for severe sepsis and 40.9-60.5% for septic shock. [2,3] To overcome this problem, the Surviving Sepsis Campaign guidelines were developed and published in 2004 and then updated in 2008 and 2012. [4] Observation of clinical signs such as consciousness, heart rate, blood pressure, respiratory rate, body temperature, and urine output is essential to make an early intervention in the care of sepsis patients. However, early detection of clinical signs of the critically ill patient by hospital staff was frequently delayed. [5] This qualitative study was performed in a general hospital in Karawaci District, Banten Province, Indonesia in September 2014. Its aim was to investigate the knowledge of 25 resident medical offi cers (RMOs), as a component of hospital staff, of sepsis based on the 2012 Surviving Sepsis Campaign guidelines. RMOs are physicians attending patients in the emergency unit, the wards, and the intensive care unit (ICU). Characteristics of RMOs who participated in the survey are shown in Table 1.

Research paper thumbnail of Frailty state among Indonesian elderly: prevalence, associated factors, and frailty state transition

BMC Geriatrics, Jul 3, 2019

Background: Information about frailty status and its transition is important to inform clinical d... more Background: Information about frailty status and its transition is important to inform clinical decisions. Predicting frailty transition is beneficial for its prevention. While Indonesia is the 4th largest geriatric population in Asia, data about frailty transition is limited. This study aimed to obtain data on prevalence of frailty, its risk factors, frailty state transition and its prognostic factors, as well as to develop prognostic score for frailty state transition. Methods: Multicenter study on subjects aged ≥60 years old was done to obtain the prevalence of frailty status and to identify risk factors of frailty. Prospective cohort over 12 months was done to obtain data on frailty state transition. Multiple logistic regression analysis was performed to identify its prognostic factors from several clinical data, which then were utilized to develop prognostic score for frailty state worsening. Results: Cross-sectional data from 448 subjects showed that 25.2% of the subjects were frail based on Frailty index-40 items. Risk factors of frailty were age (OR 2.72; 95% CI 1.58-4.76), functional status (OR 2.89; 95% CI 1.79-4.67), and nutritional status (OR 3.75; 95% CI 2.29-6.13). Data from the 162 subjects who completed the cohort showed 27.2% of the cohort had frailty state worsening. Prognostic factors for frailty state worsening were being 70 years or older (OR 3.9; 95% CI 1.2-12.3, p < 0.05), negative QoL, i.e., fair and poor QoL (OR 2.5; 95% CI 1.1-5.9, p < 0.05), and slow gait speed (OR 2.8; 95% CI 1.3-6.4, p < 0.05). The internal validation of the prognostic score consisted of those three variables showed good performance. Conclusion: The prevalence of frailty in this study among Indonesian elderly in outpatient setting was 25.2%. The risk factors of frailty were age, functional status and nutritional status. The prognostic factors for frailty state worsening were being 70 years old or older, negative QoL (fair or poor quality of life), and slow gait speed. A prognostic score to predict frailty state worsening in 12 months had been developed.

Research paper thumbnail of Diagnostic Test of a Scoring System for Frailty Syndrome in the Elderly According to Cardiovascular Health Study, Study of Osteoporotic Fracture and Comprehensive Geriatric Assessment Based Frailty Index Compared with Frailty Index 40 Items

Acta Medica Indonesiana, 2015

to get a recommendation on the best frailty syndrome diagnostic tools, that will be able to be pr... more to get a recommendation on the best frailty syndrome diagnostic tools, that will be able to be practiced on a daily setting in Indonesia. this is a cross-sectional study with diagnostic test approach, conducted to patients in the Geriatric Outpatient Clinic of Cipto Mangunkusumo National Referral Hospital on May-June 2013. Each subject underwent a frailty evaluation using CHS, SOF, FI-CGA and FI-40 scoring systems. Then, we calculate the sensitivity, specificity, PPV, NPV, LR+ and LR- of each scoring system compared to FI-40. the proportion of frail, pre-frail and fit according to FI-40 are 25.3%, 71% and 3.7% respectively. In terms of differentiation frail to non-frail, CHS had 41.2% sensitivity, 95% specificity, PPV 73.7%, NPV 82.7%, LR+ 8.41 and LR- 0.62. SOF scoring system had 17.6% sensitivity, 99.5% specificity, PPV 92.3%, NPV 78.1%, LR+ 35.2 and LR- 0.83. Furthermore FI-CGA had 8.8% sensitivity, 100% specificity, PPV 100%, NPV 76.4%, LR+ and LR- 0.91. There is no better scori...

Research paper thumbnail of Frailty state among Indonesian elderly: prevalence, associated factors, and frailty state transition

BMC Geriatrics, Jul 3, 2019

Background: Information about frailty status and its transition is important to inform clinical d... more Background: Information about frailty status and its transition is important to inform clinical decisions. Predicting frailty transition is beneficial for its prevention. While Indonesia is the 4th largest geriatric population in Asia, data about frailty transition is limited. This study aimed to obtain data on prevalence of frailty, its risk factors, frailty state transition and its prognostic factors, as well as to develop prognostic score for frailty state transition. Methods: Multicenter study on subjects aged ≥60 years old was done to obtain the prevalence of frailty status and to identify risk factors of frailty. Prospective cohort over 12 months was done to obtain data on frailty state transition. Multiple logistic regression analysis was performed to identify its prognostic factors from several clinical data, which then were utilized to develop prognostic score for frailty state worsening. Results: Cross-sectional data from 448 subjects showed that 25.2% of the subjects were frail based on Frailty index-40 items. Risk factors of frailty were age (OR 2.72; 95% CI 1.58-4.76), functional status (OR 2.89; 95% CI 1.79-4.67), and nutritional status (OR 3.75; 95% CI 2.29-6.13). Data from the 162 subjects who completed the cohort showed 27.2% of the cohort had frailty state worsening. Prognostic factors for frailty state worsening were being 70 years or older (OR 3.9; 95% CI 1.2-12.3, p < 0.05), negative QoL, i.e., fair and poor QoL (OR 2.5; 95% CI 1.1-5.9, p < 0.05), and slow gait speed (OR 2.8; 95% CI 1.3-6.4, p < 0.05). The internal validation of the prognostic score consisted of those three variables showed good performance. Conclusion: The prevalence of frailty in this study among Indonesian elderly in outpatient setting was 25.2%. The risk factors of frailty were age, functional status and nutritional status. The prognostic factors for frailty state worsening were being 70 years old or older, negative QoL (fair or poor quality of life), and slow gait speed. A prognostic score to predict frailty state worsening in 12 months had been developed.

Research paper thumbnail of Diagnostic Test of a Scoring System for Frailty Syndrome in the Elderly According to Cardiovascular Health Study, Study of Osteoporotic Fracture and Comprehensive Geriatric Assessment Based Frailty Index Compared with Frailty Index 40 Items

Acta medica Indonesiana, 2015

AIM to get a recommendation on the best frailty syndrome diagnostic tools, that will be able to b... more AIM to get a recommendation on the best frailty syndrome diagnostic tools, that will be able to be practiced on a daily setting in Indonesia. METHODS this is a cross-sectional study with diagnostic test approach, conducted to patients in the Geriatric Outpatient Clinic of Cipto Mangunkusumo National Referral Hospital on May-June 2013. Each subject underwent a frailty evaluation using CHS, SOF, FI-CGA and FI-40 scoring systems. Then, we calculate the sensitivity, specificity, PPV, NPV, LR+ and LR- of each scoring system compared to FI-40. RESULTS the proportion of frail, pre-frail and fit according to FI-40 are 25.3%, 71% and 3.7% respectively. In terms of differentiation frail to non-frail, CHS had 41.2% sensitivity, 95% specificity, PPV 73.7%, NPV 82.7%, LR+ 8.41 and LR- 0.62. SOF scoring system had 17.6% sensitivity, 99.5% specificity, PPV 92.3%, NPV 78.1%, LR+ 35.2 and LR- 0.83. Furthermore FI-CGA had 8.8% sensitivity, 100% specificity, PPV 100%, NPV 76.4%, LR+ and LR- 0.91. CONC...

Research paper thumbnail of Frailty Status and Its Associated Factors Among Indonesian Elderly People

Innovation in Aging, Jun 30, 2017

Research paper thumbnail of Pengaruh Penggunaan Proton Pump Inhibitor Jangka Panjang terhadap Sindrom Frailty pada Pasien Usia Lanjut

Jurnal Penyakit Dalam Indonesia

Pendahuluan. Sindrom frailty berkaitan dengan angka morbiditas dan kematian yang lebih tinggi, se... more Pendahuluan. Sindrom frailty berkaitan dengan angka morbiditas dan kematian yang lebih tinggi, sehingga dipakai sebagai prediktor kesehatan pada orang usia lanjut (usila). Polifarmasi sebagai salah satu faktor risiko sindrom frailty dapat berkaitan dengan obat Proton Pump Inhibitor (PPI) yang sering diberikan pada usila atas indikasi adanya keluhan gangguan saluran cerna bagian atas. Sampai saat ini belum ada penelitian yang mempelajari hubungan PPI jangka panjang dan sindrom frailty pada usila.Metode. Studi kasus kontrol pada pasien usila di Rumah Sakit dr. Cipto Mangunkusumo (RSCM), Jakarta. Kelompok kasus adalah usila terdiagnosis Frailty menurut FI-40 item dan kontrol adalah usila yang tidak frail berdasarkan instrumen yang sama. Data yang digunakan pada penelitian ini berasal dari data sekunder status frailty berdasarkan penelitian sebelumnya dan data rekam medis poliklinik Geriatri dan poliklinik diabetes RSCM.Hasil. Didapatkan 225 subjek (75 kasus: 150 kontrol), 59,6% berjeni...

Research paper thumbnail of Poor Sleep Quality of Hospitalized Geriatric Patients in General Hospital in Karawaci, Tangerang, Banten Province, Indonesia

Medicinus

Background: In Indonesia, geriatric population in the year 2005 was 15.8 million (7.2 % populatio... more Background: In Indonesia, geriatric population in the year 2005 was 15.8 million (7.2 % population), and expected to reach 11.34% in the year 2020. There was growing evidence for poor sleep as an independent risk factor for poor physical and mental health. Geriatric population may be particularly vulnerable to effects of sleep disturbance due to significant age-related changes in both sleep and inflammatory regulationObjective: To study the epidemiological (gender, age group) and health status (co-morbidities), sleep quality according to Pittsburgh Sleep Quality Index (PSQI) and its associations in geriatric population hospitalized in General Hospital in Karawaci, Tangerang, Banten Province, Indonesia.Materials and Methods: A hospital based cross sectional study was conducted from January to June 2014. A total of 92 subjects aged 60 years and above were selected consecutively from hospitalized geriatric patients for this study. The data was analyzed by means and proportions.Results:...

Research paper thumbnail of Frailty state among Indonesian elderly: prevalence, associated factors, and frailty state transition

BMC Geriatrics

Background: Information about frailty status and its transition is important to inform clinical d... more Background: Information about frailty status and its transition is important to inform clinical decisions. Predicting frailty transition is beneficial for its prevention. While Indonesia is the 4th largest geriatric population in Asia, data about frailty transition is limited. This study aimed to obtain data on prevalence of frailty, its risk factors, frailty state transition and its prognostic factors, as well as to develop prognostic score for frailty state transition. Methods: Multicenter study on subjects aged ≥60 years old was done to obtain the prevalence of frailty status and to identify risk factors of frailty. Prospective cohort over 12 months was done to obtain data on frailty state transition. Multiple logistic regression analysis was performed to identify its prognostic factors from several clinical data, which then were utilized to develop prognostic score for frailty state worsening. Results: Cross-sectional data from 448 subjects showed that 25.2% of the subjects were frail based on Frailty index-40 items. Risk factors of frailty were age (OR 2.72; 95% CI 1.58-4.76), functional status (OR 2.89; 95% CI 1.79-4.67), and nutritional status (OR 3.75; 95% CI 2.29-6.13). Data from the 162 subjects who completed the cohort showed 27.2% of the cohort had frailty state worsening. Prognostic factors for frailty state worsening were being 70 years or older (OR 3.9; 95% CI 1.2-12.3, p < 0.05), negative QoL, i.e., fair and poor QoL (OR 2.5; 95% CI 1.1-5.9, p < 0.05), and slow gait speed (OR 2.8; 95% CI 1.3-6.4, p < 0.05). The internal validation of the prognostic score consisted of those three variables showed good performance. Conclusion: The prevalence of frailty in this study among Indonesian elderly in outpatient setting was 25.2%. The risk factors of frailty were age, functional status and nutritional status. The prognostic factors for frailty state worsening were being 70 years old or older, negative QoL (fair or poor quality of life), and slow gait speed. A prognostic score to predict frailty state worsening in 12 months had been developed.

Research paper thumbnail of Diagnostic Test of a Scoring System for Frailty Syndrome in the Elderly According to Cardiovascular Health Study, Study of Osteoporotic Fracture and Comprehensive Geriatric Assessment Based Frailty Index Compared with Frailty Index 40 Items

Acta medica Indonesiana, 2015

to get a recommendation on the best frailty syndrome diagnostic tools, that will be able to be pr... more to get a recommendation on the best frailty syndrome diagnostic tools, that will be able to be practiced on a daily setting in Indonesia. this is a cross-sectional study with diagnostic test approach, conducted to patients in the Geriatric Outpatient Clinic of Cipto Mangunkusumo National Referral Hospital on May-June 2013. Each subject underwent a frailty evaluation using CHS, SOF, FI-CGA and FI-40 scoring systems. Then, we calculate the sensitivity, specificity, PPV, NPV, LR+ and LR- of each scoring system compared to FI-40. the proportion of frail, pre-frail and fit according to FI-40 are 25.3%, 71% and 3.7% respectively. In terms of differentiation frail to non-frail, CHS had 41.2% sensitivity, 95% specificity, PPV 73.7%, NPV 82.7%, LR+ 8.41 and LR- 0.62. SOF scoring system had 17.6% sensitivity, 99.5% specificity, PPV 92.3%, NPV 78.1%, LR+ 35.2 and LR- 0.83. Furthermore FI-CGA had 8.8% sensitivity, 100% specificity, PPV 100%, NPV 76.4%, LR+ and LR- 0.91. There is no better scori...

Research paper thumbnail of P0022 Clinical characteristics of young Indonesian colorectal cancer patients: A preliminary study

European Journal of Cancer, 2015

Research paper thumbnail of Pulmonary Arterial Hypertension in Graves’ Disease

Journal of Hypertension, 2015

ABSTRACT Background Cardiovascular manifestations in Graves’ disease (GD) occur frequently with v... more ABSTRACT Background Cardiovascular manifestations in Graves’ disease (GD) occur frequently with various phenotypes. A link between GD and pulmonary hypertension has been reported. There is limited data about prevalence PAH and related factors in GD in Indonesia. Objective To identify the prevalence and related factors of PAH in GD. Method This retrospective study is using secondary data from transthoracic echocardiographic database of General Hospital since last year. PAH was measured by continuous-wave Doppler echocardiography (pulmonary artery systolic pressure &gt; 35 mmHg). Sixty five patients who were diagnosed as GD were enrolled to study participant. Results Of 65 eligible participants consist of 52 female and 13 male and median ages 42 year old (18-66 year old). Cardiac abnormalities were encountered in 79% participant of which consist of PAH in 15.4%. The patients with pulmonary hypertension had significantly higher pulmonary vascular resistance (PVR), cardiac output compared to those without (p&lt;0.001 and p&lt;0.021 respectively). The possible explanations in addition to the effect of thyroid hormone on the cardiovascular system, autoimmune-mediated pulmonary vascular remodeling may play a role in Graves’ disease-linked elevated pulmonary artery systolic pressure. Conclusion The prevalence of PAH in GD was 15.4%. There is still needed future research to know the factors related to PAH especially related to clinical and laboratory abnormalities in GD.

Research paper thumbnail of Resident Medical Officer′s Knowledge of Sepsis: A Qualitative Study

Journal of Global Infectious Diseases, 2014

is frequent and is responsible for high mortality. [1] Mortality in the hospital ranges 20.7-55.2... more is frequent and is responsible for high mortality. [1] Mortality in the hospital ranges 20.7-55.2% for severe sepsis and 40.9-60.5% for septic shock. [2,3] To overcome this problem, the Surviving Sepsis Campaign guidelines were developed and published in 2004 and then updated in 2008 and 2012. [4] Observation of clinical signs such as consciousness, heart rate, blood pressure, respiratory rate, body temperature, and urine output is essential to make an early intervention in the care of sepsis patients. However, early detection of clinical signs of the critically ill patient by hospital staff was frequently delayed. [5] This qualitative study was performed in a general hospital in Karawaci District, Banten Province, Indonesia in September 2014. Its aim was to investigate the knowledge of 25 resident medical offi cers (RMOs), as a component of hospital staff, of sepsis based on the 2012 Surviving Sepsis Campaign guidelines. RMOs are physicians attending patients in the emergency unit, the wards, and the intensive care unit (ICU). Characteristics of RMOs who participated in the survey are shown in Table 1.

Research paper thumbnail of Frailty state among Indonesian elderly: prevalence, associated factors, and frailty state transition

BMC Geriatrics, Jul 3, 2019

Background: Information about frailty status and its transition is important to inform clinical d... more Background: Information about frailty status and its transition is important to inform clinical decisions. Predicting frailty transition is beneficial for its prevention. While Indonesia is the 4th largest geriatric population in Asia, data about frailty transition is limited. This study aimed to obtain data on prevalence of frailty, its risk factors, frailty state transition and its prognostic factors, as well as to develop prognostic score for frailty state transition. Methods: Multicenter study on subjects aged ≥60 years old was done to obtain the prevalence of frailty status and to identify risk factors of frailty. Prospective cohort over 12 months was done to obtain data on frailty state transition. Multiple logistic regression analysis was performed to identify its prognostic factors from several clinical data, which then were utilized to develop prognostic score for frailty state worsening. Results: Cross-sectional data from 448 subjects showed that 25.2% of the subjects were frail based on Frailty index-40 items. Risk factors of frailty were age (OR 2.72; 95% CI 1.58-4.76), functional status (OR 2.89; 95% CI 1.79-4.67), and nutritional status (OR 3.75; 95% CI 2.29-6.13). Data from the 162 subjects who completed the cohort showed 27.2% of the cohort had frailty state worsening. Prognostic factors for frailty state worsening were being 70 years or older (OR 3.9; 95% CI 1.2-12.3, p < 0.05), negative QoL, i.e., fair and poor QoL (OR 2.5; 95% CI 1.1-5.9, p < 0.05), and slow gait speed (OR 2.8; 95% CI 1.3-6.4, p < 0.05). The internal validation of the prognostic score consisted of those three variables showed good performance. Conclusion: The prevalence of frailty in this study among Indonesian elderly in outpatient setting was 25.2%. The risk factors of frailty were age, functional status and nutritional status. The prognostic factors for frailty state worsening were being 70 years old or older, negative QoL (fair or poor quality of life), and slow gait speed. A prognostic score to predict frailty state worsening in 12 months had been developed.