Analysis of Hospitalization after Peritoneal Dialysis Catheter Implantation
Bibliographic record
Abstract
UNLABELLED: ♦ BACKGROUND: Implantation of the peritoneal dialysis catheter (PDC), usually an elective procedure, may necessitate unexpected hospitalization and even transfer to intensive care due to the multiple comorbidities and inherent instability of the end-stage renal disease patient. Information on hospitalization after PDC implantation is limited and details about the reason for hospitalization are lacking. ♦ METHODS: We performed a cohort study in consecutive patients who underwent PDC implantation at a single institution from September 2007 to September 2013. Clinical characteristics of enrolled patients, technique of the implantation procedure, and all-cause unexpected hospitalization and morbidity within 14 days after implantation were analyzed. ♦ RESULTS: Excluding the patients with pre-arranged admission, a total of 246 patients receiving 252 PDC implantations during the 6 years were studied. After 39 procedures (15.5%), patients had an unexpected hospital stay or re-admission due to operative complications (33.3%), worsening of disease (35.9%), or a single-night hospital stay for observation (30.8%). Compared with discharged patients, the patients with unexpected hospitalization were older (p = 0.001), experienced higher rates of previous episodes of heart failure (p = 0.006) and heart disease (p < 0.001), had more use of general anesthesia (GA) (p = 0.046), underwent more added procedures during the implantation (p = 0.02), and had more episodes of flow obstruction and peritonitis after implantation (p = 0.012 and p < 0.001, respectively). Using a multivariable logistic regression, we showed that age, cardiac morbidity, use of general anesthesia, PDC flow problems and peritonitis after implantation were independent predictors of all-cause unexpected hospitalization. ♦ CONCLUSIONS: For the first time, our study analyzed the predictors of unplanned hospitalization after PDC implantation and identified the salient risk factors. Increased focus to identify patients at greatest risk for hospitalization, evaluation of processes of care, and implementation of preventive strategies may be helpful to reduce unplanned hospitalization after catheter insertion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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 teacher head, 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".