Cardiac consequences of spinal cord injury: systematic review and meta-analysis
Bibliographic record
Abstract
Objective Conduct a meta-analysis to determine the impact of traumatic spinal cord injury (SCI) on echocardiographic measurements of left ventricular (LV) structure and function. Methods MEDLINE and Embase were used for primary searches of studies reporting LV echocardiographic data in individuals with SCI. Of 378 unique citations, 36 relevant full-text articles were retrieved, and data from 27 studies were extracted for meta-analyses. Literature searches, article screening and data extraction were completed by two independent reviewers and compared for agreement. Primary analyses compared echocardiographic indices between individuals with SCI and able-bodied individuals, using a random effects model. Results Data are reported as pooled effect estimates (95% CI). Data from 22 articles (474 participants) were included in the primary meta-analysis. Compared with able-bodied individuals, individuals with SCI had reductions to LV stroke volume of 11.8 mL (95% CI −17.8 to −5.9, p<0.001), end-diastolic volume of 19.6 mL (95% CI −27.2 to −11.9, p<0.001) and LV massindex of −7.7 g/m2 (95% CI −11.6 to −3.8, p<0.001), but ejection fraction was not different between the groups (95% CI −2.6% to 0.6%, p=0.236). Individuals with SCI also had altered indices of diastolic function, specifically a lowered ratio of early-to-late filling velocities (p=0.039), and augmented ratio of early diastolic flow-to-tissue velocities (p=0.021). Conclusions Individuals with SCI have smaller LV volumes and mass, and altered systolic and diastolic function. While this meta-analysis demonstrates important alterations to echocardiographic measures of cardiac structure and function at rest, future work should consider the impacts of SCI on the heart’s capacity or ‘reserve’ to respond to physiological challenges. PROSPERO registration number CRD42017072333.
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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 | 0.014 | 0.031 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.047 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".