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"Latar Belakang: Osteosarkoma merupakan keganasan tulang primer dengan beragamsubtipe dan memerlukan pendekatan multidisiplin dalam diagnosis dan tatalaksananya.Hingga saat ini belum ada alat diagnostik yang terbukti dapat mendekaticlinicopathological conference (CPC) sebagai standar baku emas. Keterbatasan fasilitas,biaya, dan antrian pemeriksaan yang panjang sering kali menunda diagnosisosteosarkoma. Penelitian ini bertujuan untuk membuat model sistem skoring berdasarkantemuan klinis, laboratorium, radiografi konvensional, dan histopatologis untukmendiagnosis osteosarkoma secara cepat dan tepat.Metode: Penelitian ini dilakukan dalam dua tahap. Tahap pertama bertujuan untukmemformulasikan sistem skoring untuk mendiagnosis osteosarkoma menggunakan datasekunder secara retrospektif di RS. Dr. Cipto Mangunkusumo tahun 2016 hingga 2020.Studi ini melibatkan semua pasien dengan suspek keganasan tulang primer dandidiagnosis akhir berdasarkan CPC. Uji analisis dilakukan secara univariat, bivariat, danmultivariat menggunakan regresi logistik backward stepwise dilanjutkan dengan ujikalibrasi dan diskriminasi menggunakan uji Hosmer-Lemeshow dan kurva receivingoperator characteristic (ROC), serta menentukan titik potong pada model. Tahap keduaditujukan untuk mengevaluasi model sistem skoring yang diformulasi pada tahap pertamasecara prospektif menggunakan data primer sejak September 2022 hingga Desember2022 di poliklinik Orthopaedi dan Traumatologi RS. Dr. Cipto Mangunkusumo.Hasil: Penelitian tahap pertama melibatkan 120 subjek dan menghasilkan dua modelsistem skoring, yaitu dengan mempertimbangkan riwayat pijat (model 1) dan tanpamempertimbangkan riwayat pijat (model 2). Dari hasil analisis multivariat, didapatkansembilan variabel yang dimasukan dalam model sistem skoring yaitu usia, indeks massatubuh (IMT), onset, riwayat pijat, lokasi tumor, kadar alkaline phosphatase (ALP), laktatdehidrogenase (LDH), letak lesi berdasarkan radiografi konvensional, serta gambaranhistopatologis berdasarkan fine needle aspiration biopsy (FNAB). Uji kalibrasi model 1dan 2 menunjukan kalibrasi yang baik (p=0,498 dan p=0,917). Uji diskriminasi padamodel sistem skoring menunjukan nilai area under the curve (AUC) 0,818 dengan nilaip<0,001 pada model 1 dan 2. Titik potong pada model 1 dan 2 berturut-turut adalah 19dan 11 poin. Penelitian tahap kedua melibatkan 34 subjek dan menunjukan sensitivitas,spesifisitas, dan akurasi model 1 dan 2 berturut turut sebesar 81,25% dan 87,5%, 100%dan 100%, dan 91,1% dan 94,1%.Kesimpulan: Didapatkan dua model sistem skoring yang mampu mendiagnosisosteosarkoma dengan cepat dan tepat dibandingkan dengan CPC. Lokasi tumor di lututdan gambaran sel pleiomorfik dengan atau tanpa matriks osteoid ganas merupakan faktoryang paling berpengaruh terhadap diagnosis osteosarkoma.

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Introduction : Osteosarcoma, being one of the most prevalent among the primary bone

malignancies, consists of multiple subtypes and requires a multidisciplinary approach for

proper diagnosis and treatment. Lately, there have not been a diagnostic tool that is able

to rival the accuracy of clinicopathological conference (CPC) as a gold standard in

determining the diagnosis and treatment of osteosarcoma. Limitations in budgeting, as

well as the time taken for each patient to undergo supporting examinations often leads to

a delayed diagnosis. This research aims to create a scoring system that is based on clinical

symptoms, laboratory results, conventional radiology, as well as histopathological results

to establish a quick and accurate diagnosis for osteosarcoma.

Method: This research was conducted in two stages; the first stage aims to formulate the

scoring system for diagnosing osteosarcoma by using a retrospective, secondary data

obtained from Dr. Cipto Mangunkusumo Hospital from 2016 up to 2020. This study

involved all patients with suspected bone malignancies that was eventually diagnosed

with osteosarcoma by means of CPC. The analysis was done with univariate, bivariate,

and multivariate analysis using backward stepwise logistic regression method followed

by calibration and discrimination test using Hosmer-Lemeshow test and receiving

operator characteristic (ROC) curve analysis, and determined the cut-off point in the

scoring system model. The second stage was aimed to prospectively evaluate the

previously formulated scoring system model in the first stage using primary data from

September 2022 to December 2022 at Orthopaedic and Traumatology outpatient clinic

Dr. Cipto Mangunkusumo Hospital.

Result: The first stage of the study involved 120 subjects and resulted two models of

scoring system, namely by considering massage history (model 1) and without

considering massage history (model 2). From multivariate analysis, nine variables were

included in the scoring system model, including age, body mass index (BMI), onset,

massage history, tumor location, alkaline phosphatase (ALP) levels, lactate

dehydrogenase (LDH), location of the lesion based on conventional radiography, and

histopathological finding based on fine needle aspiration biopsy (FNAB). Calibration

tests for models 1 and 2 showed good calibration (p=0.498 and p=0.917). The

discrimination test on the scoring system model showed an area under the curve (AUC)

value of 0.818 with a p-value <0.001 in both models 1 and 2. The cut-off points in model

1 and 2 were 19 and 11, respectively. The second stage of the study involved 34 subjects

with the sensitivity, specificity, and accuracy of models 1 and 2 showing 81.25% and

87.5%, 100% and 100%, and 91.1% and 94.1%, respectively.

Conclusion: This study has proposed two models of scoring systems that can be used

for a more rapid and accurate diagnosis of osteosarcoma when compared to CPC; the

location of the tumor mass in the knee joint and the appearance of pleomorphic cells, with

or without the appearance of malignant osteoids, both being significant factors in

diagnosing osteosarcoma"

"Terbukti bahwa karakteristik ibu berpengaruh secara uji statistik untuk menyebabkan terjadinya BBLR. Dampak yang ditimbulkan sangatlah fatal, BBLR berisiko tinggi mengalami kecacatan organ hingga kematian. Pada masa kehidupan selanjutnya, BBLR berisiko menderita penyakit degeneratif. Penelitian ini bertujuan mendapatkan sistem skoring faktor risiko kejadian BBLR berdasarkan model akhir analisis multivariat penelitian terdahulu. Sistem skoring tersebut digunakan untuk uji skrining kejadian BBLR pada responden penelitian ini sehingga menghasilkan cut off point dengan sensitivitas dan spesifisitasnya. Penelitian ini menggunakan desain studi skrining retrospektif. Penelitian dilakukan dengan mengobservasi data sekunder formulir antenatal care di PKM Jagakarsa Jakarta Selatan tahun 2010. Hasil studi ini mendapatkan sebuah sistem skoring untuk empat faktor risiko kejadian BBLR dengan cut off point 2,0 dan memiliki nilai sensitivitas 60% dan spesifisitas 53%. Dengan demikian studi ini merekomendasikan sistem skoring prediksi BBLR menggunakan karakteristik ibu untuk digunakan sebagai skrining non-invasif.

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Proved that maternal characteristics have an effect on the statistic test for the cause of low birthweight. The Impact of low birthweight is fatal, lowbirthweight have a high risk in experiencing disability organ up to death. In the future, low birthweight risk of suffering from degenerative diseases. This research aims to obtain a scoring system of low birthweight risk factors based on Last Model Multivariate Analysis of old research. That scoring system applying for low birthweight screening test to the sample of this research and with that result produce a cut off point with sensitivity and specificity. This research used a retrospective screening study design. This research done by observing the secondary data of antenatal care form at Puskesmas Kecamatan Jagakarsa South Jakarta in 2010. The Result of this research is found out a scoring system for four risk factors of low birthweight with the cut off point 2,0 and have 60% sensitivity and 53% specificity. Thus, this research recommends the scoring system in predicting low birthweight using maternal characteristics to be used as a noninvasive screening test."

"Latar Belakang. COVID-19 menyebar hampir ke seluruh dunia. Di Indonesia, pada 2 Maret 2020 telah dilaporkan dua kasus COVID-19 pertama yang terkonfirmasi positif. Karena banyaknya kasus COVID-19 yang terjadi di Indonesia terutama pada tenaga kesehatan, KEMENKES menerbitkan pedoman pencegahan dan pengendalian COVID- 19 sebagai acuan untuk meminimalisasi terjadinya penularan COVID-19.Tujuan. Penelitian ini bertujuan untuk merancang sistem skoring untuk memprediksi terjadinya infeksi COVID-19 pada tenaga kesehatan di Rumah Sakit Umum Pusat Nasional (RSUPN CM).Metode. Penelitian ini menggunakan metode total sampling. subyek penelitian ini adalah tenaga kesehatan yang bekerja di RSUPN Dr. Cipto Mangunkusumo. Pengumpulan data menggunakan kuisioner. Analisa data dengan analisis multivariat untuk melihat faktor risiko yang ada dapat dijadikan sebagai prediktor terjadinya infeksi berbahaya.Hasil. Desain penelitian ini adalah potong lintang dengan jumlah subjek sebanyak 125 orang. Tenaga kesehatan yang dinyatakan positif COVID-19 sebanyak 48,7% dari seluruh jumlah tenaga kesehatan di RSUPN Dr. Cipto Mangunkusumo periode bulan Maret sampai Oktober 2020 yang memenuhi kriteria inklusi. Faktor risiko yang dapat digunakan sebagai prediktor yaitu usia, tempat bekerja di RSCM, riwayat kontak erat dan status merokok.Kesimpulan. Sistem skoring dalam penelitian ini dapat digunakan sebagai prediktor tenaga kesehatan terhadap kemungkinan berisiko tinggi atau rendah terinfeksi COVID- 19.

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Background. COVID-19 has been spread almost all over the world. In Indonesia, on March 2, 2020, the first two confirmed cases of COVID-19 were reported. Due to the large number of COVID-19 cases occurring in Indonesia, especially in healthcare workers, the Ministry of Health issues guidelines for preventing and controlling COVID- 19 as a reference to minimize the occurrence of COVID-19 based on transmission. Objective. This study aims to design a scoring system to predict the occurrence of COVID-19 infection among health workers at RSUPN CM.

Method. This research used total sampling method. The subjects of this study were healthcare workers who worked at RSUPN. Dr. Cipto Mangunkusumo. Data was collected using questionnaires. Then, data was analyzed until multivariate analysis to see whether the existing risk factors can be utilized as predictors of the occurrence of COVID- 19 infection.

Results. This study’s design is cross-sectional with 125 people as an respondent. Health workers who tested positive for COVID-19 as many as 48.7% of the total number of health workers at RSUPN CM for the period from March to October 2020 which meets the inclusion criteria. Risk factors that contributed as predictors including age category, place of work at RSCM, history of close contact and smoking.

Conclusion. The scoring system in this study can be implemented as a predictor of having created by COVID-19 in healthcare workers in RSUPN CM, whether the health worker is in a high or low risk condition of being infected with COVID-19."

"Latar Belakang. Lean NAFLD lebih sering ditemukan di negara Asia dan prevalensinya di Indonesia masih belum diketahui. Tingginya prevalensi, asimptomatik dan baru bergejala setelah timbul komplikasi, dan tingginya mortalitas lean NAFLD menjadikan perlunya deteksi dini pada populasi dewasa dengan IMT <23 kg/m2. Skrining pada populasi umum tidak direkomendasikan karena meningkatkan biaya kesehatan.Tujuan. Membuat sistem skoring untuk penapisan lean NAFLD pada populasi dewasa di Jakarta.Metode. Studi ini menggunakan desain potong lintang dari laporan pemeriksaan kesehatan individu dewasa >18 tahun dengan IMT <23 kg/m2 yang melakukan pemeriksaan kesehatan di klinik. Parameter yang dianalisis antara lain usia, jenis kelamin, lingkar pinggang, kadar GDP, kolesterol total, HDL, LDL, trigliserida, AST, ALT, dan asam urat. Variabel dengan nilai p <0,25 dilanjutkan ke analisis multivariat untuk pembuatan sistem skoring.Hasil. Sebanyak 276 individu diikutsertakan pada penelitian ini dan didapatkan prevalensi lean NAFLD sebesar 9,8%. Lean NAFLD lebih banyak ditemukan pada laki-laki dan memiliki karakteristik usia lebih tua, IMT, lingkar pinggang, kadar GDP, ALT, dan trigliserida lebih tinggi dibanding lean tanpa NAFLD. Analisis bivariat mendapatkan jenis kelamin laki-laki, usia ≥45 tahun, kadar GDP ≥100 mg/dL, ALT ≥35 U/L, dan trigliserida ≥150 mg/dL berhubungan dengan lean NAFLD. Sistem skoring melibatkan 4 parameter yaitu laki-laki, kadar GDP ≥100 mg/dL, ALT ≥35 U/L, dan trigliserida ≥150 mg/dL dengan masing-masing bernilai 1 poin. Model skoring ini memiliki sensitivitas 44,4%, spesifisitas 84,3%, dan AUROC 0,74.Kesimpulan. Parameter jenis kelamin, kadar GDP, ALT, dan trigliserida dapat digunakan sebagai sistem skoring dengan performans menengah untuk penapisan lean NAFLD dewasa......Background. Lean NAFLD is commonly found in Asian countries and its prevalence in Indonesia is still unknown. The high prevalence, asymptomatic until complications occur, and the high mortality of lean NAFLD makes it necessary for early detection in adult with BMI <23 kg/m2. Screening in general population is not recommended due to the high cost burden.Aim. To develop a scoring system for screening lean NAFLD in adults in Jakarta Methods. A cross-sectional study design was conducted from medical examination reports from individual >18 years old and BMI <23 kg/m2 who performed medical check up at the clinic. Several parameters including age, gender, waist circumference (WC), fasting blood glucose (FBG), total cholesterol (TC), HDL, LDL, triglycerides (TG), AST, ALT, and uric acid (UA) were analyzed in this study. Variabels with p-value <0.25 were included in multivariate analysis for the development of scoring systems.Results. A total of 276 people were enrolled in this study. Prevalence of lean NAFLD is 9.8%. Lean NAFLD are more commonly found in men and have older age, higher BMI, WC, GDP, ALT, and TG levels than lean non-NAFLD. In bivariate analysis, male sex, age ≥ 45 years, FBG ≥100 mg/dL, ALT ≥35 U/L, and TG ≥150 mg/dL are associated with lean NAFLD. The scoring system involves four parameters including male, FBG ≥100 mg/dL, ALT ≥35 U/L, and TG ≥150 mg/dL, worth 1 point each. This model has sensitivity 44.4%, specificity 84.3%, and AUROC 0.74.Conclusion. Parameters including gender, FBG, ALT, and TG levels can be used as a scoring system with moderate performance for screening lean NAFLD in adults."

"Latar Belakang: Rendahnya ketepatan kultur bakteriologis dan kurangnya fasilitas pencitraan terutama di daerah perifer, mendiagnosis meningitis tuberkulosis (MTB) pada anak menjadi suatu tantangan.Tujuan: untuk membentuk sistem skor yang terdiri dari manifestasi klinis dan pemeriksaan laboratorium sederhana untuk membantu diagnosis MTB pada anak.Metode: Studi retrospektif menggunakan model prediktif diagnostik multivariabel dengan anak usia 3 bulan hingga 18 tahun terdiagnosis meningitis, dirawat inap selama periode Juli 2011 hingga November 2021 di rumah sakit tersier.Hasil: Dari 10 variabel yang memiliki signifikansi statistik dengan TBM, diperoleh 8 variabel untuk membangun model prediksi untuk mengidentifikasi TBM. Variabel ini dibagi menjadi dua bagian skoring yang keduanya memiliki diskriminasi dan kalibrasi yang baik, sistem skoring sistemik (4 parameter, batas nilai skor ³3, sensitivitas 78,8%, spesifisitas 86,6% dengan AUC 89,9% (p<0,001) ) dan sistem skoring neurologis (4 parameter, batas nilai skor ³2, sensitivitas 61,2%, spesifisitas 75,2% dengan AUC 73,3% (p<0,001). Sistem skoring ini bila digunakan bersamaan dan memenuhi batas nilai skor masing-masing, dapat memprediksi diagnosis TBM pada anak dengan baik (sensitivitas 47,1%, spesifisitas 95,1%, dan nilai prediksi positif 90,9%).Kesimpulan: Sistem skoring klinis yang terdiri dari dua bagian, skor sistemik dan skor neurologis, memiliki kemampuan yang baik dalam memprediksi diagnosis TBM pada anak.

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Due to the low accuracy of culture techniques in bacteriological confirmation and the lack of brain imaging facilities especially in peripheral areas, diagnosing tuberculous meningitis (TBM) in children become a challenge

Objective : to establish scoring systems consisting of clinical manifestations and simple laboratory examination to help diagnosing TBM in children.

Method: Retrospective study using a multivariable diagnostic predictive model with children diagnosed as meningitis aged 3 months to 18 years, hospitalized during July 2011 until November 2021 period in a tertiary hospital.

Result: From 10 variables that have statistical significance with TBM, 8 variables were obtained for establishing the predictive model to identify TBM. These variables divided into two scoring parts which both had good discrimination and calibration, the systemic scoring system (4 parameters, total cut-off score ³3, sensitivity of 78.8%, specificity of 86.6% with AUC of 89.9% (p<0.001)) and the neurological scoring system (4 parameters, total cut-off score ³2, sensitivity of 61.2%, specificity of 75.2% with AUC of 73.3% (p<0.001)). Furthermore, these scoring systems when used together and met the cut-off score respectively, can predict the diagnosis of TBM in children well (sensitivity 47.1%, specificity 95.1%, and positive predictive value 90.9%).

Conclusion: a clinical scoring systems consist of two parts, systemic score and neurological score, have good ability in predicting the diagnosis of TBM in children."