Parallel 16: Access, Delivery, and Cost of Care
Bibliographic record
Abstract
255A p <0.05), better maintenance of MAP (93.8% vs. 72.5%,p=0.02) with cessation of vasopressor requirement (50% versus 25% p=0.03) at 48 hours, improved urine output at 24 hours (59% versus 36%, p=0.05) and no variceal bleed (0% versus 15.45%, p=0.03) without significantly increased adverse effects (40.6% vs. 22.5%, p=0.12).Terlipressin use showed delayed resolution of Acute Kidney Injury on fifth day (59.4% vs. 16.75, p=0.08) with improved lactate clearance, Central Venus Oxygen saturation and CO2 gradient in Venous -arterial blood gases (p=NS).An early survival advantage was seen with the use of terlipressin (93.5% vs. 75%, p=0.02) in the first 48 hours, but not at 28 days.Conclusion: Terlipressin as a vasopressor is non-inferior to noradrenaline with greater hemodynamic stability, early survival benefit, improved urine output, reduced variceal bleed and decreased incidence of nosocomial SBP with nonfatal and reversible adverse effects.Its use is recommended in decompensated cirrhotics presenting with septic shock.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.159 | 0.008 |
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".