Employment of patients with kidney failure treated with dialysis or kidney transplantation—a systematic review and meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Background Patients with kidney failure treated with dialysis or kidney transplantation experience difficulties maintaining employment due to the condition itself and the treatment. We aimed to establish the rate of employment before and after initiation of dialysis and kidney transplantation and to identify predictors of employment during dialysis and posttransplant. Methods This systematic review and meta-analysis were carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for studies that included employment rate in adults receiving dialysis or a kidney transplant. The literature search included cross-sectional or cohort studies published in English between January 1966 and August 2020 in the PubMed, Embase, and Cochrane Library databases. Data on employment rate, study population, age, gender, educational level, dialysis duration, kidney donor, ethnicity, dialysis modality, waiting time for transplantation, diabetes, and depression were extracted. Quality assessment was performed using the Newcastle–Ottawa Scale. Meta-analysis for predictors for employment, with odds ratios and confidence intervals, and tests for heterogeneity, using chi-square and I 2 statistics, were calculated. PROSPERO registration number: CRD42020188853. Results Thirty-three studies included 162,059 participants receiving dialysis, and 31 studies included 137,742 participants who received kidney transplantation. Dialysis patients were on average 52.6 years old (range: 16–79; 60.3% male), and kidney transplant patients were 46.7 years old (range: 18–78; 59.8% male). The employment rate (weighted mean) for dialysis patients was 26.3% (range: 10.5–59.7%); the employment rate was 36.9% pretransplant (range: 25–86%) and 38.2% posttransplant (range: 14.2–85%). Predictors for employment during dialysis and posttransplant were male, gender, age, being without diabetes, peritoneal dialysis, and higher educational level, and predictors of posttransplant: pretransplant employment included transplantation with a living donor kidney, and being without depression. Conclusions Patients with kidney failure had a low employment rate during dialysis and pre- and posttransplant. Kidney failure patients should be supported through a combination of clinical and social measures to ensure that they remain working.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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 it