Examining the Association between Hemodialysis Access Type and Mortality: The Role of Access Complications
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: People receiving hemodialysis to treat kidney failure need a vascular access (a fistula, a graft, or a central venous catheter) to connect to the blood purification machine. Higher rates of access complications are considered the mechanism responsible for the excess mortality observed among catheter or graft users versus fistula users. We tested this hypothesis using mediation analysis. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: , thrombosis) and infectious complications of the access (mediator model) and the relationship between access type and time-dependent access complications with 6-month mortality from the creation of the first permanent access (outcome model). In mediation analysis, we formally tested whether access complications explain the association between access type and mortality. RESULTS: Of the 6119 adults that we studied (mean age =64 [SD=15] years old; 58% men; 47% patients with diabetes), 50% had a permanent catheter for vascular access, 37% had a fistula, and 13% had a graft. During the 6-month study follow-up, 2084 participants (34%) developed a noninfectious complication of the access, 542 (8.9%) developed an infectious complication, and 526 (8.6%) died. Access type predicted the occurrence of access complications; both access type and complications predicted mortality. The associations between access type and mortality were nearly identical in models excluding and including access complications (hazard ratio, 2.00; 95% confidence interval, 1.55 to 2.58 versus hazard ratio, 2.01; 95% confidence interval, 1.56 to 2.59 for catheter versus fistula, respectively). In mediation analysis, higher mortality with catheters or grafts versus fistulas was not the result of increased rates of access complications. CONCLUSIONS: Hemodialysis access complications do not seem to explain the association between access type and mortality. Clinical trials are needed to clarify whether these associations are causal or reflect confounding by underlying disease severity.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".