Analysis of factors predicting survival of a second peritoneal dialysis catheter.
Bibliographic record
Abstract
Many studies have examined the survival of the first peritoneal dialysis (PD) catheter. However, data are scarce about the factors that influence the function and survival time of a second PD catheter. The purpose of the present study was to calculate the survival time of the second PD catheter and to examine factors that predict removal of that catheter. We conducted a retrospective study of second PD catheters inserted at our institution over a 10-year period from May 1992 to April 2002. The endpoint consisted of removal of the second catheter. Voluntary change to hemodialysis, kidney transplantation, transfer to another center, and death with a functioning catheter were censored observations. Catheter survival was analyzed by the Kaplan-Meier method. During the study period, 106 patients (59 men, 47 women) received a second catheter. The mean age of the patients was 55 +/- 14.9 years. One third of the patients had diabetes. The reasons for removal of the first catheter and insertion of the second one were peritonitis (n = 50), catheter malfunction (n = 20), catheter leak (n = 11), exit site or tunnel infection (n = 21), and failed kidney transplantation with resumption of PD (n = 4). The median survival of the second catheter was 48 months (95% confidence interval: 38 months to 59 months). On univariate analysis, increasing patient age and peritonitis as cause for removal of the first catheter were associated with an increased risk of removal of the second catheter. However, on multivariate analysis, only increasing patient age was associated with a greater risk to survival of the second catheter.
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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 | 0.006 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".