Factors that influence outcome in non-invasive and invasive treatment in polycystic liver disease patients
Bibliographic record
Abstract
AIM: To evaluate the factors that influence outcome of both non-invasive and invasive treatment of polycystic liver disease. METHODS: Analysis of clinical files of patients with complete follow-up from July 1986 to June 2006. RESULTS: Forty-one patients (male, 7; female, 34), 47.8 +/- 11.9 years age, and 5.7 +/- 6.7 years follow-up, were studied. Alkaline phosphatase (AP) elevation (15% of patients) was associated with the requirement of invasive treatment (IT, P = 0.005). IT rate was higher in symptomatic than non-symptomatic patients (65.4% vs 14.3%, P = 0.002), and in women taking hormonal replacement therapy (HRT) (P = 0.001). Cysts complications (CC) were more frequent (22%) in the symptomatic patients group (P = 0.023). Patients with body mass index (BMI) > 25 (59%) had a trend to complications after IT (P = 0.075). Abdominal pain was the most common symptom (56%) and indication for IT (78%). Nineteen patients (46%) required a first IT: 12 open fenestration (OF), 4 laparoscopic fenestration (LF) and 3 fenestration with hepatic resection (FHR). Three required a second IT, and one required a third procedure. Complications due to first IT were found in 32% (OF 16.7%, LF 25%, FHR 66.7%), and in the second IT in 66.7% (OF 100%). Follow-up mortality rate was 0. CONCLUSION: Presence of symptoms, elevated AP, and CC are associated with IT requirement. HRT is associated with presence of symptoms and IT requirement. Patients with BMI > 25 have a trend be susceptible to IT complications. The proportions of complications are higher in FHR and second IT groups. RS is more frequent after OF.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".