Tata Laksana Komprehensif Terkini Penanganan Re-Emergensi Hand, Foot, and Mouth Disease (HFMD) di Indonesia: Tinjauan Lingkup
Bibliographic record
Abstract
Hand, foot, and mouth disease (HFMD) merupakan penyakit eksantema dengan manifestasi utama berupa erupsi ruam makulopapular pada tangan, kaki, dan mulut disertai demam dengan berbagai komplikasi berbahaya yang dapat timbul pada anak usia di bawah lima tahun. Indonesia memiliki siklus wabah HFMD berulang menjadikannya sebagai penyakit re-emergensi yang perlu diwaspadai. Penulis melakukan pencarian sistematis penelitian pada 3 database, yaitu Pubmed, Wiley Online Library, dan Science Direct, dengan kata kunci “Hand, Foot, and Mouth Disease”, “enterovirus”, and “therapy” yang dipublikasikan hingga Oktober 2023. Sebanyak 791 penelitian masuk dalam analisis dan kualitasnya dinilai menggunakan Newcastle-Ottawa Scale. Tata laksana komprehensif HFMD yang tersedia hingga kini mencakup upaya pencegahan, terapi, dan manajemen komplikasi. Penelitian terkini belum berhasil mengungkap pengobatan antivirus definitif, sehingga penatalaksanaan bersifat simtomatik, diikuti isolasi serta perawatan mulut dan kulit yang baik. Pada kasus berat, intervensi kasus kritis meliputi terapi antivirus, imunoglobulin intravena, serta dukungan sistem pernapasan dan sirkulasi darah. Vaksin enterovirus A71 (EV-A71) yang dinonaktifkan terbukti menjadi pilihan paling efektif dan hemat biaya untuk perlindungan jangka panjang terhadap HFMD terkait EV-A71. Namun, evolusi epidemiologi enterovirus menyebabkan intervensi yang hanya didasarkan satu agen tidak memadai, diperlukan pengembangan tata laksana definitif dan vaksin multivalen yang efektif.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".