Lower limb blood flow and mean arterial pressure during standing and seated work: Implications for workplace posture recommendations
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
Sit-stand workstations are a popular workplace intervention. Organizations often require a medical professional's guidance for implementation. Therefore, it is important to understand potential negative outcomes associated with standing work, such as lower limb discomfort and peripheral vascular issues. The objective of this study was to compare changes in lower limb discomfort, blood pressure and blood flow accumulation during a light-load repetitive upper limb work task accomplished from seated and standing postures. At the Jewish Rehabilitation Hospital (Laval, Quebec, Canada), 16 participants were outfitted with Laser Doppler Flow (LDF) electrodes to measure blood flow in the lower limb, and a sphygmomanometer to measure lower limb mean arterial blood pressure (MAP). Participants completed simulated work over 34 min in standing and seated conditions. Repeated measures ANOVAs (Posture x Time) were used to assess the differences. There were significant effects for both Posture (p = 0.003) and Time (p = 0.007) for LDF-measured of blood flow accumulation in the soleus and the foot, with a mean increase of 77% blood flow over time in the standing posture, when compared to seated work. There was a significant 'Posture × Time' (p = 0.0034) interaction effect and a significant Posture (p = 0.0001) effect for MAP, with higher values in the standing posture by a mean of 37.2 mmHg. Posture had a significant effect (p < 0.001) on lower limb discomfort, with standing posture reporting higher levels. These results suggest that recommendations for using static standing work postures should be tempered, and physicians' guidance on workstation changes should consider the impacts on the lower limb.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 it