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"Latar belakang: Severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) adalah virus menyebabkan infeksi saluran pernafasan dan memiliki manifestasi klinis ringan sampai berat serta dapat menyebabkan kematian. Tingginya angka morbiditas dan mortalitas akibat infeksi COVID 19 menyebabkan diperlukannya stratifikasi resiko terhadap pasien saat masuk ke rumah sakit serta prediktor terjadinya luaran buruk pada pasien. Tujuan: Mengetahui kemampuan skor mortalitas 4C dan kadar leptin dalam memprediksi luaran buruk pasien COVID 19 terkonfirmasi selama perawatan. Metode: Penelitian ini merupakan kohort prospektif dari 375 pasien COVID-19 yang dirawat di RSUPN Cipto Mangunkusumo sejak November 2020 hingga April 2021. Pasien dilakukan pemeriksaan fisik, CRP, Ureum  serta pemeriksaan kadar leptin saat admisi. Dilakukan analisis multivariat regresi logistik untuk menilai kemampuan skor mortalitas 4C dan leptin untuk memprediksi luaran buruk komposit yang mencakup ARDS dan mortalitas. Analisis korelasi dan regresi linier dengan STATA 15. Hasil: Dari analisis data pada 375 pasien didapatkan skor mortalitas 4C dapat memprediksi luaran buruk pasien COVID 19 selama rawat inap dengan area under curve (AUC) 0,68 (IK 0,61-0,75) dan titik potong skor mortalitas 4C adalah 6. Dari analisis multivariat didapatkan leptin tidak dapat memprediksi luaran buruk pasien COVID 19 selama rawat inap dengan area under curve (AUC) 0,52 (IK 0,44-0,60). Kesimpulan: Skor mortalitas 4C mampu memprediksi luaran buruk pasien COVID 19 terkonfirmasi selama perawatan sedangkan leptin tidak mampu menjadi prediktor luaran buruk pasien COVID 19 selama perawatan.

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Background:  The high morbidity and mortality rates due to COVID-19 infection require risk stratification for patients when admitted to the hospital as well as predictors of poor patient outcomes. While obesity has been reported to be associated with poor outcomes, the role of leptin, a proinflammatory cytokines released by the adipose tissue, has never been assessed. Objective: To determine the ability of the leptin levels and 4C mortality score to predict poor outcomes in confirmed COVID-19 patients. Method: This study is a prospective cohort of 375 COVID-19 patients treated at Cipto Mangunkusumo National Referal Hospital from November 2020 to April 2021, as part of the CARAMEL study. Subjects who were 18 years old and above and had confirmed COVID-19 status through COVID-19 polymerase chain reaction (PCR) from oropharyngeal swabs were included. Subjects when admitted to the hospital required non-invasive ventilation, mechanical ventilation, ECMO and those who refused to participate in the study were excluded. A multivariate logistic regression analysis was performed to assess the ability of the 4C mortality score and leptin to predict composite adverse outcomes, including ARDS and mortality. Results: Our study observed that while the 4C mortality score could predict poor outcomes for COVID-19 patients during hospitalization with an AUC of 0.68 (CI 0.61-0.75), leptin levels could not predict poor outcomes [(AUC of 0.52 (CI 0.44-0.60)]. Conclusion: Leptin levels were not associated with the development of poor outcomes in hospitalised Covid-19 patients."

"Latar Belakang: Pandemi COVID-19 telah menjadi ancaman kesehatan global dengan tingginya kasus dan kematian di seluruh dunia. Untuk membantu dokter dan pasien dalam mengambil keputusan terkait perawatan dan tindak lanjut, skor prognosis telah digunakan untuk memprediksi risiko kematian pasien dengan COVID-19. Saat ini terdapat beberapa skor prognostik dan mortalitas yang digunakan untuk COVID-19 yang bervariasi dalam pengaturan, ukuran hasil yang diprediksi dan parameter klinis yang disertakan. Penelitian membandingkan akurasi aplikasi prediksi luaran Clinical Assessment Tool (CAT) COVID dan Coronavirus Clinical Characterisation Consortium (4C) Mortality Score Pada Pasien COVID-19 Terkonfirmasi Pada Perawatan Di Rumah Sakit Universitas Indonesia: Tinjauan Hubungan Status Vaksinasi. Metode: Penelitian ini adalah suatu penelitian observasional dengan metode potong lintang menggunakan data rekam medis pasien COVID-19 di RS Universitas Indonesia Depok. Proses pengumpulan data dimulai sejak Oktober 2023. Pasien dengan status vaksin COVID-19 yang datang ke RSUI dengan keluhan mengarah ke COVID-19 pada periode Januari - Desember 2022 dengan kriteria subjek berusia >18 tahun diambil secara consecutive sampling sebanyak 344 subjek. Hasil: Jumlah subjek pada penelitian ini sebanyak 91. Aplikasi prediksi 4C lebih baik yaitu dengan nilai AUC 73.5% (sensitivitas 78.9% dan spesifisitas 68%) dibandingkan CAT COVID dengan AUC 52.1% (sensitivitas 74% dan spesifisitas 30%). Nilai kesesuaian antara aplikasi CAT COVID dengan aplikasi 4C mortality score dengan uji kappa adalah sebesar 0.094. Bila dinilai dari jumlah subjek, kedua aplikasi prediksi memiliki penilaian prediksi dengan hasil yang sama pada 47 subjek dan terdapat perbedaan prediksi pada 44 subjek. Kesimpulan: Aplikasi prediksi kematian 4C mortality score terjangkau dan mudah untuk digunakan pada fasilitas kesehatan dalam memprediksi kematian sehingga tenaga kesehatan bisa menentukan perawatan dan tindak lanjut untuk pasien serta edukasi mengenai prognosis kepada pasien dan keluarga pasien. Aplikasi 4C mortality score memiliki variabel yang sederhana dengan hasil berupa tingkatan kelompok prediksi risiko kematian ringan, sedang, berat dan sangat berat.

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Background: The corona virus disease 19 (COVID-19) pandemic has become a significant global health threat, with cases and deaths increasing in the worldwide. To assist doctors and patients in making decisions regarding treatment and follow-up, prognosis scores have been used to predict the risk of death in patients with COVID-19. Currently, there are several prognostic and mortality scores used for COVID-19 that vary in setting, predicted outcome measures, and included clinical parameters. Research comparing the accuracy of outcome prediction applications, such as the Clinical Assessment Tool (CAT) COVID, and the Coronavirus Clinical Characterisation Consortium (4C) Mortality Score in Confirmed COVID-19 Patients Under Treatment at Universitas Indonesia Hospital: A Review on Vaccination Status Relationship. Method: This study is an observational research employing a cross-sectional method utilizing medical record data of COVID-19 patients at Universitas Indonesia Hospital in Jakarta. The data collection process commenced in October 2023. Patients with COVID-19 vaccine status presenting to RSUI with complaints suggestive of COVID-19 during the period of January to December 2022, with the criteria of subjects aged > 18 years, were consecutively sampled, totalling 344 subjects. Results: The total number of subjects in this study was 91. The 4C mortality score application performed better, with an accuracy of 73.5% (sensitivity 78.9% and specificity 68%) compared to CAT COVID with an AUC of 52.1% (sensitivity 74% and specificity 30%). The concordance value between CAT COVID application and 4C mortality score application with kappa test was 0.094. When assessed by the number of subjects, both prediction applications had the same prediction outcome in 47 subjects, and there was a difference in prediction in 44 subjects. Conclusion: The 4C mortality score prediction applications are accessible and affordable in healthcare facilities for predicting mortality, allowing healthcare professionals to determine treatment and follow-up for patients as well as provide prognosis education to patients and their families. The 4C mortality score application has simple variables with prediction results in the form of risk group prediction levels low, intermediate, high and very high."