Screening, Diagnosis, and Treatment of Cardiometabolic Risk in Persons With Spinal Cord Injury/Disease: A Scoping Review
Bibliographic record
Abstract
Objectives: To map and categorize evidence related to cardiometabolic disease (CMD) risk in persons with spinal cord injury/disease (SCI/D) and to assess the proportion of studies reporting on sociodemographic variables. Data Sources: A scoping review of scientific evidence was conducted. MEDLINE, CINAHL, and EMBASE databases were searched using primary constructs (SCI/D, CMD) from inception to July 1, 2024. Study Selection: Articles must meet the following criteria: (1) full-length article, (2) available in English, (3) SCI/D population aged ≥18 years, and (4) diagnosed CMD and/or evaluated CMD strategies/interventions. Data Extraction: The following information was extracted from the included articles: title, country in which the study was conducted, participant characteristics, sociodemographic variables reported, objective/purpose statement, study design, study type, intervention type, CMD risk factors evaluated, assessment time point(s), additional non-CMD outcome measures, use of clinical practice guidelines for risk stratification, summary of results, and report of clinical implications. Data Synthesis: Of the 1726 studies screened, 120 met the inclusion criteria. Definitions from the Users' Guide to the Medical Literature were used to categorize studies under Diagnosis (n=75; 62.5%), Therapy (n=27; 22.5%), Prognosis (n=14; 11.7%), and Harm (n=4; 3.3%). Diagnosis studies commonly assessed the presence/absence of CMD using screening tools or biomarkers, although only 25 (20.7%) reported on sociodemographic variables, of which race (24.0%), ethnicity (17.3%), and education (13.3%) were most frequently reported. Positive findings for reducing the risk of obesity, hypertension, dyslipidemia, and diabetes mellitus were found across Therapy studies. Most (85.2%) incorporated health-promoting behaviors such as physical activity, nutritional counseling, and behavior change interventions. Four studies (14.8%) evaluated different pharmacologic treatments (atorvastatin, fenofibrate, α-lipoic acid, semaglutide) to target CMD risk factors. Conclusions: Most of the literature on CMD in persons with SCI/D pertains to Diagnosis, reinforcing the increased prevalence and risk compared with the general population. Physical activity was the most studied therapeutic intervention to manage CMD after SCI/D; however, the limited number of therapy studies demonstrates a need to explore the efficacy of tailored interventions and multipronged approaches. Sociodemographic reporting was poor across all study types, highlighting a gap in understanding subgroup risk. Future research should prioritize addressing these gaps to improve CMD care.
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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 | 0.018 | 0.090 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.019 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".