Safety in Bariatric Patient Transfers§
Bibliographic record
Abstract
Background: Bariatric patients are being seen more frequently in health care.Transferring these patients is a challenging and risky task.Objectives: To analyze safety and reduce risks for the musculoskeletal system of bariatric patients and health care workers during transfers from bed to wheelchair and back.Methods: Clinical intervention study of patient transfers using portable and ceiling lifts.The study was conducted in the largest freestanding rehabilitation center in North America.Forty transfers from bed to wheelchair and back involving eight bariatric patients (age: 46-62y, BMI: 42-48kg/m 2 ) were observed systematically, and four were video-recorded to illustrate the analysis.Two proactive risk assessments were performed and compared using a scoring system to evaluate the risks during the processes of transfers using portable and ceiling lifts.Results: The bariatric patient transfer system using portable lifts was replaced by installing and using ceiling lifts.The safety of the processes involving the two systems was compared in relation to risk of injuries to staff and patients.Using of ceiling lifts as opposed to portable lifts resulted in 28% reduction of low detectability incidents, 26% reduction of moderate effect incidents, and decreased both high and moderate probability incidents (22% and 30% reduction, respectively).Finally, it resulted in approximately 25% reduction on the sum of risk scores for the failure modes and causes requiring action. Conclusions:The results suggest that using ceiling lifts is safer than using portable lifts for bariatric patient transfers.The remaining risks were alleviated by training the staff and elaborating standardized procedures to perform these transfers.
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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 | 0.004 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 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".