Gender, low <scp>K</scp>t/<scp>V</scp>, and mortality in <scp>J</scp>apanese hemodialysis patients: Opportunities for improvement through modifiable practices
Bibliographic record
Abstract
Guidelines have recommended single pool Kt/V > 1.2 as the minimum dose for chronic hemodialysis (HD) patients on thrice weekly HD. The Dialysis Outcomes and Practice Patterns Study (DOPPS) has shown that "low Kt/V" (<1.2) is more prevalent in Japan than many other countries, though survival is longer in Japan. We examined trends in low Kt/V, dialysis practices associated with low Kt/V, and associations between Kt/V and mortality overall and by gender in Japanese dialysis patients. We analyzed 5784 HD patients from Japan DOPPS (1999-2011), restricted to patients dialyzing for >1 year and receiving thrice weekly dialysis. Logistic regression models estimated the relationships of patient characteristics with Kt/V. Logistic models also were used to estimate the proportion of low Kt/V cases attributable to various treatment practices. Multivariable Cox regression was used to estimate the associations of low Kt/V, blood flow rate (BFR), and treatment time (TT), with all-cause mortality. From 1999 to 2009, the prevalence of low Kt/V declined in men (37-27%) and women (15-10%). BFR <200 mL/min, TT <240 minutes, and dialyzate flow rate (DFR) < 500 mL/min were common (35, 13, and 19% of patients, respectively) and strongly associated with low Kt/V. Fifteen percent of low Kt/V cases were attributable to BFR <200 and 13% to TT <240, compared to only 3% for DFR <500. Lower Kt/V was associated with elevated mortality, more so among women (hazard ratio [HR] = 1.13 per 0.1 lower Kt/V, 95% CI: 1.07-1.20) than among men (HR = 1.06 per 0.1 lower Kt/V, 95% CI: 1.00-1.12). The relatively large proportion of low Kt/V cases in Japanese facilities may potentially be reduced 30% by increasing BFR to 200 mL/min and TT to 4 hours thrice weekly in HD patients. Associations of low Kt/V with elevated mortality suggest that modification of these practices may further improve survival for Japanese HD patients.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".