Role of Continuous Drainage of Tense Ascites in Peritoneal Dialysis: Mehandru/Masud Technique
Bibliographic record
Abstract
Insertion of a peritoneal dialysis (PD) catheter in end-stage renal disease (ESRD) patients with cirrhosis and tense ascites remains a challenge for nephrologists. Ascitic fluid leak at the surgical site, a common postoperative occurrence, leads to the disqualification of many patients who could be otherwise great candidates for PD. The ascitic fluid leak has been described to occur during or immediately after surgery even after the entire volume of ascitic fluid has been drained. In this study, we report a case study of three patients with ESRD, liver cirrhosis, and tense ascites on hemodialysis. The patients required super large volume paracentesis (SLVP), draining 9,000 - 15,000 cc of ascitic fluid twice weekly in an interventional radiology setup. Besides ascitic fluid drainage, the patients needed in-center hemodialysis (ICHD) 3 days a week, leading to their engagement in procedures 5 days a week. In addition, intradialytic symptomatic hypotension, hypoalbuminemia, and other adverse effects of hemodialysis lead to their poor lifestyle. To improve their lifestyle, all patients desired to switch to PD from ICHD. Upon the PD catheter insertion and drainage of the entire ascitic fluid, leaks developed at the insertion site within a few hours. To overcome these leaks, PD catheters of all three patients were attached via a transfer set to a bag for continuous drainage of ascitic fluid for about 2 weeks. No leak or complication was noted, leading to complete healing of insertion site. We recommend, for the patients with tense ascites requiring SLVP, approximately 2 weeks of healing period continuously be performed till initiation of PD training,.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".