Twice-Weekly Hemodialysis and Clinical Outcomes in the China Dialysis Outcomes and Practice Patterns Study
Bibliographic record
Abstract
IntroductionIn China, a quarter of patients are undergoing 2-times weekly hemodialysis. Using data from the China Dialysis Outcomes and Practice Patterns Study (DOPPS), we tested the hypothesis that whereas survival and hospitalizations would be similar in the presence of residual kidney function (RKF), patients without RKF would fare worse on 2-times weekly hemodialysis.MethodsIn our cohort derived from 15 units randomly selected from each of 3 major cities (total N = 45), we generated a propensity score for the probability of dialysis frequency assignment, estimated a survival function by propensity score quintiles, and averaged stratum-specific survival functions to generate mean survival time. We used the proportional rates model to assess hospitalizations. We stratified all analyses by RKF, as reported by patients (urine output <1 vs. ≥1 cup/day).ResultsAmong 1265 patients, 123 and 133 were undergoing 2-times weekly hemodialysis with and without evidence of RKF. Over 2.5 years, adjusted mean survival times were similar for 2- versus 3-times weekly dialysis groups: 2.20 versus 2.23 and 2.20 versus 2.15 for patients with and without RKF (P = 0.65). Hazard ratios for hospitalization rates were similar for 2- versus 3-times weekly groups, with (1.15, 95% confidence interval = 0.66−2.00) and without (1.10, 95% confidence interval 0.68−1.79]) RKF. The normalized protein catabolic rate was lower and intradialytic weight gain was not substantially higher in the 2- versus 3-times weekly dialysis group, suggesting greater restriction of dietary sodium and protein.ConclusionIn our study of patients in China’s major cities, we could not detect differences in survival and hospitalization for those undergoing 2- versus 3-times weekly dialysis, regardless of RKF. Our findings indicate the need for pragmatic studies regarding less frequent dialysis with associated nutritional management.
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 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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".