Risk of hip fracture in patients on dialysis or kidney transplant: a meta-analysis of 14 cohort studies
Bibliographic record
Abstract
Purpose: We aimed to conduct a meta-analysis of published cohort studies to evaluate the risk of hip fracture in patients undergoing dialysis or kidney transplantation (KT). Methods: We identified relevant studies by searching PubMed, EMBASE and Google Scholar databases from their inception to December 31, 2017. Cohort studies evaluating risk of hip fractures in patients undergoing dialysis or KT were considered included. The methodological quality of the cohort studies was assessed using the modified Newcastle-Ottawa scale. Results: In our meta-analysis of 14 retrospective cohort studies, a total of more than 1.5 million patients undergoing dialysis or KT were included, of whom more than 30,000 had hip fractures. After the merger, the proportion of hip fractures was 1.92% (95% CI, 1.38%-2.46%) with significant heterogeneity ( I 2 =99.9%, P =0.000) in all patients, and the incidence rate of hip fractures (per 1,000 person-years) was 8.95 (95% CI, 4.05–13.85) with significant heterogeneity ( I 2 =99.9%, P =0.000). The pooled relative risks (RR) value for dialysis patients compared with the general population were 6.35 (95% CI, 4.53–8.88) for male and 5.57 (95% CI, 4.44–6.99) for female. The pooled RR value for hemodialysis (HD) patients compared with peritoneal dialysis (PD) patients was 1.39 (95% CI, 1.13–1.70) with no heterogeneity ( I 2 =0.0%, P =0.763). Conclusion: In conclusion, the present meta-analysis reveals that about 2% of dialysis or KT patients go on to sustain a hip fracture during follow-up, with the overall hip fracture incidence rates being 8.95 per 1,000 person-years. The overall risk of hip fracture was more than 5-fold higher in dialysis patients than in the general population. Among patients on PD, HD, and KT, HD and KT patients had the highest and the lowest risk of hip fractures, respectively. Keywords: risk, hip fracture, dialysis or kidney transplant, meta-analysis
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".