Eccentric Exercise in Patients with Chronic Health Conditions: A Systematic Review
Bibliographic record
Abstract
PURPOSE: The capacity of eccentric actions to produce muscle hypertrophy, strength gains, and neural adaptations without stressing the cardiopulmonary system has led to the prescription of eccentric training programmes in patients with low tolerance to exercise, such as elders or those with chronic health conditions. The purpose of this systematic review was to analyze the evidence regarding the effectiveness and suitability of eccentric training to restore musculoskeletal function in patients with chronic diseases. SUMMARY OF KEY POINTS: Relevant articles were identified from nine databases and from the reference lists of key articles. Articles were assessed to determine level of evidence and scientific rigour. Nine studies met the inclusion criteria. According to Sackett's levels of evidence, 7 studies were graded at level IIb, 1 study at level IV, and the remaining study at level V. Articles were also graded for scientific rigour according to the PEDro scale. One study was rated as high quality, 4 studies were rated as moderate, and 2 studies were graded as poor quality. CONCLUSIONS: Eccentric training may be safely used to restore musculoskeletal function in patients with some specific chronic conditions. However, the heterogeneity of diseases makes it very difficult to extrapolate results and to standardize clinical recommendations for adequate implementation of this type of exercise. More studies are needed to establish the potential advantages of eccentric training in chronic conditions.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".