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"Coronavirus disease atau COVID-19 merupakan pandemi global yang mudah menular melalui droplet dan populasi yang paling berisiko adalah lansia dengan tingkat kematian akibat COVID-19 di Indonesia per 27 Juni 2020 adalah sebanyak 42,9%. Hal tersebut dapat menimbulkan kecemasan tersendiri bagi lansia, terlebih lagi secara psikologis lansia lebih mudah cemas daripada populasi lain. Kecemasan diketahui merupakan salah satu faktor penting penyebab kerentanan terinfeksi Coronavirus. Maka dari itu penulisan ini dibuat untuk menemukan gambaran ansietas pada 10 lansia sebelum tindakan swab PCR SARS CoV-2 di RSUI. Data yang dipakai adalah data umum, data skrining COVID-19, riwayat penyakit dalam, riwayat merokok, dan kuesioner kecemasan menggunakan Geriatric Anxiety Inventory Short Form (GAI-SF). Berdasarkan data yang didapatkan, terdapat banyak faktor yang mungkin mempengaruhi munculnya ansietas pada lansia seperti kecemasan terhadap hasil swab PCR. Hasil pengkajian GAI-SF juga menyatakan bahwa semua lansia mengalami ansietas dengan dua diantaranya memiliki gejala GAD. Antar pasien juga memiliki beberapa kesamaan terkait COVID-19 dan hubungannya dengan kecemasan. Sebagai kesimpulan, masalah ansietas pada lansia terkait COVID-19 sebelum tindakan swab PCR memiliki nilai yang tinggi disebabkan karena beberapa faktor sehingga perlu diberikan rekomendasi khusus. Penulis merekomendasikan penyediaan kursi prioritas untuk lansia, bilik swab khusus lansia dengan aromaterapi dan musik relaksasi jika memungkinkan, dan edukasi terkait COVID-19 oleh perawat melalui selebaran maupun follow up secara daring.

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Coronavirus disease or called COVID-19 is a global pandemic that is easily transmitted through droplets and the population with higher risk of it are the elderly within death rate in Indonesia per June 27, 2020 is 42.9%. This problem can cause anxiety in the elderly even more as psychologically the elderly are more vulnerable to feel anxious than other populations. Whereas anxiety is one of the important factors causing decreased immunity which makes the elderly more susceptible to Coronavirus. Therefore, this paper was made to find an overview of anxiety in 10 elderly people before the swab polymerase chain reaction severe acute respiratory syndrome coronavirus-2 or swab PCR SARS CoV-2 procedure at RSUI. The data used are general data, COVID-19 screening data, history disease, smoking history, and anxiety questionnaires using Geriatric Anxiety Inventory Short Form (GAI-SF). Based on the data obtained, there are many factors that might influence the emergence of anxiety in the elderly such as anxiety about the swab PCR results. The results of the GAI-SF also stated that all respondents were experiencing anxiety with two of them were having general anxiety disorder symptoms. Furthermore, inter-patients also have some similarities related to COVID-19 and anxiety. In conclusion, the anxiety problem among elderly related to COVID-19 before the swab PCR procedure has a high value due to several factors so that special recommendations for the elderly should be given. The recommendation are using priority seats for the elderly, special swab PCR’s room with aromatheraphy and music of relaxation if possible, and nurses could give COVID-19 educations through flyer or follow up them within online educations"

"Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) merupakan agen penyebab Coronavirus Disease 2019 (COVID-19) yang telah menginfeksi hampir dua ratus juta orang dan menyebabkan hampir empat juta kematian di dunia. Saat ini, belum ada obat yang spesifik ditemukan untuk virus ini. Drug repurposing merupakan salah satu alternatif strategi pengembangan obat di masa pandemi. Pada penelitian ini, non-structural protein 3 (NSP3) dan non-structural protein 13 (NSP13) SARS-CoV-2, yang mengkode papain-like protease dan helikase, terpilih sebagai target potensial yang berperan penting dalam replikasi virus. Drug repurposing berbasis pemodelan farmakofor dilakukan menggunakan program LigandScout. Ligan kokristal NSP3 dan NSP13 SARS-CoV-2 dari Protein Data Bank dipilih sebagai training set. Sebelumnya, sekuens protein disejajarkan dengan Clustal Omega dan interaksi protein-ligan diidentifikasi dengan Protein-Ligand Interaction Profiler. Model farmakofor divalidasi menggunakan test set yang terdiri dari ligan terpilih sebagai senyawa aktif dan decoy dari A Database of Useful Decoys-Enhanced sebagai senyawa inaktif. Model farmakofor NSP3 pada akhirnya tidak terbentuk karena sedikitnya ligan yang tersedia. Model farmakofor NSP13 yang memiliki satu cincin aromatik (AR), satu daerah hidrofobik (H), satu akseptor ikatan hidrogen (HBA), dan satu donor ikatan hidrogen (HBD) dengan penambahan feature tolerance sebesar 0,15 Å dan feature weight sebesar 0,1 pada fitur AR, H, dan HBA menghasilkan nilai AUC100%, EF1%, EF5%, sensitivitas, dan spesifisitas sebesar 0,83; 21,2; 8,8; 0,792; dan 0,790. Model ini digunakan sebagai kueri penapisan terhadap obat yang telah disetujui FDA dari The Binding Database. Ticarcillin, sulfisoxazole, lacosamide, sulfathiazole, cefaclor, penicillin G, cephalexin, carbenicillin, atenolol, dan tolazoline diperoleh sebagai senyawa kandidat dengan pharmacophore-fit score tertinggi.

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Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), causal agent of Coronavirus Disease 2019 (COVID-19), has infected almost two hundred millions of people and caused nearly four millions of deaths worldwide. Currently, no treatment has been identified to be effective against the virus. In the outbreak, drug repurposing emerges as a promising strategy to develop efficient therapeutics. This study selected SARS-CoV-2 non-structural protein 3 (NSP3) and non-structural protein 13 (NSP13), that encodes papain-like protease and helicase, respectively, as potential targets based on their crucial role in virus replication. Drug repurposing was carried out by LigandScout pharmacophore modeling using SARS-CoV-2 NSP3 and NSP13 co-crystallized ligands from Protein Data Bank as training set. Prior to that, crystal structures were aligned by Clustal Omega and analyzed by Protein-Ligand Interaction Profiler for interaction profiling. Generated pharmacophore model was validated by a test set consisting of above-mentioned ligands as actives and A Database of Useful Decoys-Enhanced decoys as inactives. Unfortunately, NSP3 model cannot be generated due to insufficient ligands. NSP13 model that has one aromatic ring (AR), one hydrophobic area (H), one hydrogen bond acceptor (HBA), and one hydrogen bond donor (HBD) features with 0,15 Å feature tolerance and 0,1 feature weight additions on AR, H, and HBA resulted AUC100%, EF1%, EF5%, sensitivity, and specificity of 0,83; 21,2; 8,8; 0,792; and 0,790. This model was chosen for screening against FDA-approved drugs from The Binding Database. Ticarcillin, sulfisoxazole, lacosamide, sulfathiazole, cefaclor, penicillin G, cephalexin, carbenicillin, atenolol, and tolazoline were obtained as hits with the highest pharmacophore-fit score."