Bibliographic record
Abstract
The insertion of non-tunneled temporary hemodialysis catheters (NTHCs) is a core procedure of nephrology practice. While urgent dialysis may be life-saving, mechanical and infectious complications related to the insertion of NTHCs can be fatal. In recent years, various techniques that reduce mechanical and infectious complications related to NTHCs have been described. Evidence now suggests that ultrasound guidance should be used for internal jugular and femoral vein NTHC insertions. The implementation of evidence-based infection-control 'bundles' for central venous catheter insertions has significantly reduced the incidence of bloodstream infections in the intensive care unit setting with important implications for how nephrologists should insert NTHCs. In addition, the Cathedia Study has provided the first high-level evidence about the optimal site of NTHC insertion, as it relates to the risk of infection and catheter dysfunction. Incorporating these evidence-based techniques into a simulation-based program for training nephrologists in NTHC insertion has been shown to be an effective way to improve the procedural skills of nephrology trainees. Nonetheless, there are some data suggesting nephrologists have been slow to adopt evidence-based practices surrounding NTHC insertion. This mini review focuses on techniques that reduce the complications of NTHCs and are relevant to the practice and training of nephrologists.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".