Protocol of a systematic review with meta-analysis: The effects of physical exercise/activity on body composition of individuals with cardiometabolic multimorbidity v1
Bibliographic record
Abstract
Multimorbidity can be defined as the combination of 2 or more chronic diseases and affects an increasing number of individuals worldwide. Among the various chronic conditions, cardiometabolic diseases stand out as the main causes of death in the world and their management has been increasingly discussed, from the need for specialized clinics, to the creation of a new medical specialty, to the need for effective interventions. The regular practice of physical activity is an important tool recommended to treat and prevent the worsening of the health status of patients with cardiometabolic diseases. In addition, comprehensive monitoring of cardiometabolic parameters such as body composition is necessary to understand the individual's health status, as well as verify the effectiveness of drug treatments and interventions. It is known that exercise has a beneficial effect on these components, but there is still little evidence exploring its effect on the coexistence of diseases and treatments for populations with cardiometabolic multimorbidity. Thus, the objective of the systematic review is to explore the effects of physical exercise and physical activity on body composition in individuals with cardiometabolic multimorbidity. For this, we will carry out a systematic review with meta-analysis in digital databases (PUBMED, EMBASE, CINAHL, Sportsdiscuss and Prospero).
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.
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 | 0.079 | 0.130 |
| Meta-epidemiology (narrow) | 0.008 | 0.006 |
| Meta-epidemiology (broad) | 0.030 | 0.028 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.070 | 0.009 |
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".