Usefulness of three-dimensional spherical index to assess different types of left ventricular remodeling
Bibliographic record
Abstract
BACKGROUND: Left ventricular (LV) remodeling after myocardial injury, volume or pressure overload is characterized by a change in LV shape from an ellipse to more of a sphere. The usefulness of 3-dimensional (3D) sphericity index (SpI) for accurate evaluation of LV remodeling remains uncertain despite extensive research. METHODS: We searched Pubmed, Embase, Web of Science, and Cochrane databases to identify relevant studies from January 1, 1990 to August 1, 2016. The quality of each study was evaluated using the Newcastle-Ottawa Scale. Meta regression and sensitivity and subgroup analyses based on patterns of LV remodeling were performed. RESULTS: Thirteen studies with a total of 1064 patients were included in this meta-analysis. There was evidence of obvious heterogeneity (I = 82.4%; P < .001), which was mainly accounted for by the pattern of remodeling according to meta-regression. The result of subgroup meta-analyses suggested that SpI in patients with eccentric remodeling was significantly higher compared with control group (95% confidence interval [CI], 0.78-1.10). No statistic difference was found in LV SpI between healthy controls and patients with concentric hypertrophy (95% CI, -0.89 to 0.16) or myocardial injury (95% CI, -0.13 to 0.41). CONCLUSION: 3D SpI can be widely used to assess LV remodeling in patients with eccentric remodeling, but has limitations in predicting concentric hypertrophy and regional or chronic myocardial injury.
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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 | 0.026 | 0.053 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.021 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".