Preserving residual renal function: Is interdialytic acupuncture an add-on option? A case series report
Bibliographic record
Abstract
BACKGROUND: Whether acupuncture therapy contributes to preserving residual renal function (RRF) remains largely unknown. This case series demonstrated the potential beneficial effects of acupuncture for preserving RRF in five patients with end-stage renal disease undergoing hemodialysis (HD) treatment. PARTICIPANTS: HD patients received eight sessions of weekly 30 min interdialytic acupuncture (Inter-A) at ten selected acupoints, namely Yintang (GV29), Yingxiang (LI20), Shuijin (Tung's Acupuncture), Lianquan (CV23), Shangqu (KI17), Tianshu (ST25), Siman (KI14), Hegu (LI4), Zusanli (ST36) and Sanyingjao (SP6). Residual urine volume (rUV) and residual glomerular filtration rate (rGFR) were recorded once every two weeks Outcomes: Changes in rUV and rGFR were calculated using 24 h urine collection data to assess RRF. Variations in hemoglobin, urea Kt/V and serum albumin levels were measured monthly to evaluate HD adequacy. RESULTS: at 2- and 4-week follow-up, respectively. The mean percentage difference increased by 31% in the rUV and 37% in the rGFR. Routine measurements of HD adequacy also showed improvements. CONCLUSIONS: Acupuncture might be an optional add-on treatment for HD population with poor control of water; however, further well-designed controlled trials are warranted.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".