Improvement in Quality of Life and Decrease in Large‐Volume Paracentesis Requirements With the Automated Low‐Flow Ascites Pump
Bibliographic record
Abstract
The automated low-flow ascites pump (alfapump) is an implantable device that drains ascites directly into the urinary bladder. We studied its safety (absence of serious complications) and efficacy (decreased large-volume paracentesis [LVP] requirement and improved quality of life [QoL]) in the management of ascites in a cohort of North American patients with cirrhosis and recurrent ascites ineligible for transjugular intrahepatic portosystemic shunt (TIPS). QoL was measured by the Chronic Liver Disease Questionnaire (CLDQ) and Ascites Questionnaire (Ascites Q). Following alfapump implantation, patients were monitored for ascites control, laboratory abnormalities, QoL, adverse events, and survival at 12 months. A total of 30 patients (60.0 ± 9.9 years; 57% male; Model for End-Stage Liver Disease score, 11.4 ± 2.7) received an alfapump, mostly by an interventional radiology approach (97%), followed by longterm prophylactic antibiotics. The alfapump removed a mean ascites volume of 230.6 ± 148.9 L/patient at 12 months, dramatically reducing the mean LVP frequency from 2.4 ± 1.4/patient/month before pump implantation to 0.2 ± 0.4/patient/month after pump implantation. All surviving patients had improved QoL (baseline versus 3 months; CLDQ, 3.9 ± 1.21 versus 5.0 ± 1.0; Ascites Q, 51.7 ± 21.9 versus 26.7 ± 18.6; P < 0.001 for both) and a better biochemical index of nutritional status (prealbumin 87.8 ± 37.5 versus 102.9 ± 45.3 mg/L at 3 months; P = 0.04). Bacterial infections (15 events in 13 patients), electrolyte abnormalities (11 events in 6 patients), and renal complications (11 events in 9 patients) were the most common severe adverse events. By 12 months, 4 patients died from complications of cirrhosis. Alfapump insertion may be a definitive treatment for refractory ascites in cirrhosis, especially in patients who are not TIPS candidates.
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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 | 0.001 |
| 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".