[Bilirubin removal with Coupled Plasma Filtration and Adsorption in patients affected by hilar cholangiocarcinoma].
Bibliographic record
Abstract
BACKGROUND: Patients affected by hilar cholangiocarcinoma are eligible for surgery only in the 20-30% of the cases and postoperative mortality is 40-50%. Many specialists are involved in the treatment of this disease, like surgeons, gastroenterologists, oncologists and radiotherapists. Recent studies have shown that preoperative bilirubinaemia is a predictor of morbidity and mortality after surgery. Coupled Plasma Filtration and Adsorption (CPFA) is a blood purification extracorporeal therapy recommended for sepsis and able to reduce bilirubinaemia. METHODS: We treated 10 patients referred to our centre affected by hilar cholangiocarcinoma complicated by obstructive jaundice with 34 CPFA sessions to test its ability to reduce preoperative bilirubin levels and we checked for mortality at 90 days. RESULTS: CPFA reduced preoperative bilirubin of 30% for session; it also improved others inflammation and coagulation tests. Mortality at 90 days was 40%. CONCLUSIONS: CPFA is an effective therapy for hyperbilirubinaemia. Lowering preoperative bilirubinaemia and improvement of coagulation tests subsidized the management of the patients but in our study did not affect postoperative mortality. Further studies to evaluate the indications for treatments that remove bilirubin in this setting are needed.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".