Buerger Allen Exercise In Type 2 Diabetes Mellitus Patients: A Literature Review
Bibliographic record
Abstract
An effort that might be made to prevent complications of Diabetes Mellitus (DM) is by increasing peripheral blood circulation through the Buerger Allen exercise (BAE). Previous studies recommend reviewing the standard procedure of the BAE. Research related to the review of the effectiveness of BAE application on type 2 DM, which is summarized from various studies in latest original research is still lacking. The aim of this study is to describe the standard form of the Buerger Allen implementation that has been evaluated its effectiveness in patients with type 2 DM patients with complications. This literature review was performed with PICO keywords in 4 databases, including PubMed, Springer Link, Wiley Online Library, and Google Scholar in 2011-2022. We have concluded that the standard procedure for implementing the BAE consists of 5 stages and three main steps for each cycle. The steps are supine position (pre-exercise), elevation, Hanging, flexion-extension, and horizontal (post-exercise) steps. Each session consists of at least 3 to 6 cycles with approximately 30 minutes. Fifteen articles analyzed showed significant changes in lower peripheral perfusion of patients with type 2 DM. BAE is a simple non-pharmacological intervention that is considered an effective method for managing lower peripheral perfusion.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".