Health‐Related Quality of Life in Hemodialysis Patients in Taiwan
Bibliographic record
Abstract
Background: Health‐related quality of life (HRQOL) is an important outcome of medical treatment effectiveness. Objectives: Thirty‐six item short‐Form (SF‐36) first has been used in hemodialysis (HD) patients in Taiwan. Method: HRQOL was measured by using SF‐36 in 497 HD patients in 5 hospitals. Results: Male sex, age less than 50 years, higher education level (EL), marriage, employed status (EPS), less comorbid medical condition (CMC), and non‐diabetic patients were all predicted a better physical component scale (PCS). Age less than 50 years, BMI greater than 18.5, HEL, EPS, and NDP were all predicted a higher mental component scale (MCS). Scales contributing to a summary measure of physical health, the PCS score, was significantly lower in women (35 ± 12.3) than in men (37.9 ± 12.3). There is no difference in MCS score between women and men. In multivariate analysis, age, CMC, diabetes, serum creatinine (SCr), and erythropoietin responsiveness were significant independent predictors of PCS. Diabetes, EL, SCr, and erythropoietic responsiveness were significant independent predictors of MCS. All of the individual scales, PCS and MCS scores were lower in the Taiwan HD patients than values for the US general population. Each of the individual scales and MCS scores were substantially lower in Taiwan HD group than in the US HD cohort. But the bodily pain of PCS was significantly higher in Taiwan HD group in spite of mean PCS scores for Taiwan HD group and US HD study participants were nearly equal at 36.3 and 36.1, respectively. Conclusion: Physical and mental aspects of quality of life are substantially reduced among Taiwan HD patients, but higher bodily pain tolerance. A number of demographic and clinical characteristics significantly impact on HRQOL in Taiwan HD patients. To our knowledge, this is the first time we demonstrate the HRQOL by using SF‐36 in Chinese 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".