Predictive value of cardiac magnetic resonance for the diagnosis and surgical relief of pericardial constriction
Bibliographic record
Abstract
Background The diagnosis of pericardial constriction (PC) remains challenging and cardiac magnetic resonance (CMR) is increasingly used as a diagnostic tool. The objective of this study was to evaluate CMR findings for the prediction of subsequent surgical pericardiectomy. Methods CMR studies of 36 patients referred to assess for PC were evaluated retrospectively. Patients were divided into two groups depending on whether they subsequently had their pericardium stripped (n=18) or did not (n=18). IVC and aortic areas were determined by manual contouring on a single axial-SSFP image in maximum systole at the level of the esophageal hiatus. The ratio of IVC to aortic (I:A) area was calculated. Cross-sectional areas were indexed to body surface area (BSA). Quantitative data was assessed with a two-sample t-test and qualitative data was assessed with Fisher’s exact test. A logistic regression model was used to determine the predictive probability of surgical pericardiectomy based on CMR features. Odds ratios (ORs) were calculated and receiver operating characteristic (ROC) analysis was performed. Results Mean age of patients was 53.9±15.3 years, 72% (n=26) male, with no significant difference in mean age between the two groups (p=0.429). In patients with constriction, the underlying etiology was idiopathic (39%, n=7), infectious (28%, n=5), post-surgical (17%, n=3), connective-tissue disease (11%, n=2), and post-radiation (6%, n=1). IVC area, indexed IVC area, I:A ratio, pericardial thickness, RV area and indexed RV area were significantly different in patients who underwent pericardiectomy compared to those who did not (Table 1). Pericardiectomy was significantly associated with pericardial enhancement (p=0.011) as well as septal bounce (p<0.0001). The odds ratio (OR) for undergoing pericardiectomy in patients with septal bounce was 289 (95% confidence interval (CI) (16.681, 5007). Using ROC analysis, the area under the curve (AUC) and 95% CI for the prediction of pericardiectomy was 0.968 (0.92, 1.00) for IVC area, 0.932 (0.86, 1.00) for indexed IVC area and 0.963 (0.91, 1.00) for I:A ratio (Figure 1). An IVC area of 7.0 cm 2 had 92% accuracy (sensitivity=94%, specificity=89%), an indexed IVC area of 3.4 cm 2 /m 2 had 86% accuracy (sensitivity=94%, specificity=78%) and a I:A ratio of 1.8 had 92% accuracy (sensitivity=89%, specificity=94%). Conclusions
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".