Evaluasi Penggunaan Antibiotik Pada Pasien Sepsis Neonatus Di Rawat Inap Perinatologi RSUD Tarakan
Bibliographic record
Abstract
Sepsis neonatus atau sepsis pada bayi baru lahir adalah sindrom klinis akibat infeksi aliran darah yang bersifat invasif, yang terjadi dalam satu bulan pertama kehidupan dan ditandai dengan adanya mikroorganisme patogen dalam darah, cairan sumsum tulang atau air kemih. Mikroorganisme patogen tersebut dapat berupa bakteri, virus, jamur, dan protozoa. Penelitian ini bertujuan untuk mengetahui ketepatan penggunaan antibiotik dengan kriteria tepat jenis obat, tepat dosis, dan tepat lama pemberian yang diberikan pada pasien sepsis neonatus di Rawat Inap Perinatologi RSUD Tarakan periode Mei sampai Juli 2017. Jenis penelitian ini adalah deskriptif dan pengambilan data dilakukan secara retrospektif terhadap data rekam medis seluruh pasien diagnosis sepsis neonatus. Sampel penelitian ini adalah 75 pasien sepsis neonatus yang memenuhi kriteria inklusi dan eksklusi penelitian. Evaluasi ketepatan penggunaan antibiotik dilakukan dengan melihat standar pengobatan sepsis neonatus berdasarkan panduan sepsis pada neonatus RSUD Tarakan (2016), IDAI (2009), WHO (2012), Sepsis Management Guidelines for Neonates (2016), Neonatology Sixth Edition (2009), dan British National Formulary for Children (2014). Hasil penelitian menunjukkan bahwa analisis ketepatan penggunaan antibiotik pada pasien sepsis neonatus di Rawat Inap Perinatologi RSUD Tarakan ketepatan jenis obat sebanyak 91,18%, ketepatan dosis sebanyak 91,18%, dan ketepatan lama pemberian sebanyak 92,94%.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.014 |
| Insufficient payload (model declined to judge) | 0.038 | 0.001 |
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; both teacher heads agree on what is shown here.
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".