EFEKTIVITAS DEKSAMETASON PRAOPERATIF SEBAGAI TERAPI PENCEGAHAN NYERI TENGGOROKAN PASCAINTUBASI ENDOTRAKEAL
Bibliographic record
Abstract
Nyeri tenggorokan pascaintubasi endotrakeal ( postoperative sore throat /POST) merupakan komplikasi pasca operasi yang umum terjadi pada 18% hingga 65% pasien yang menjalani anestesi umum dengan intubasi endotrakeal, biasanya terjadi pada 12-24 jam setelah operasi. Studi sebelumnya menunjukkan konflik terkait efektivitas pemberian deksametason praoperatif sebagai terapi pencegahan POST. Tinjauan sistematis ini bertujuan untuk menemukan apakah pemberian deksametason praoperatif efektif dalam mencegah kejadian nyeri tenggorokan pascaintubasi endoktrakeal. Penelusuran dilakukan melalui database online seperti Pubmed®, Scopus®, Science Direct®, dan Cochrane®. Telaah kritis terhadap artikel ilmiah yang memenuhi kriteria inklusi dan eksklusi dilakukan berdasarkan jenis penelitian. Systematic review dinilai dengan menggunakan Centre for Evidence-Based Medicine Toronto Systematic Review (of Therapy) Critical Appraisal Worksheet . Telaah RCT menggunakan Centre for Evidence-Based Medicine Toronto Therapy Critical Appraisal Worksheet . Delapan studi yang memenuhi kriteria inklusi dan eksklusi ditelaah pada studi ini. Enam systematic review menunjukkan deksametason dapat mencegah kejadian nyeri tenggorokan pascaintubasi 24 jam setelah operasi sebesar 35%-61% dari total pasien (OR/RR 0,39-0,65). Dua RCT menunjukkan deksametason mencegah kejadian nyeri tenggorokan pasca intubasi 24 jam setelah operasi secara signifikan (P 0,02-0,039). Deksametason preoperatif dapat mencegah nyeri tenggorokan pascaintubasi endotrakeal pada pasien setelah menjalani anestesi umum dan memiliki implikasi ekonomi yang baik, kenyamanan pasien serta penyembuhan yang lebih cepat.
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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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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; 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".