Echocardiographic changes in the right ventricle during chemotherapy - a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Introduction Cancer therapy-induced cardiotoxicity (CTRCD) is a significant adverse effect of oncologic treatment, associated with considerable morbidity and mortality. Among CTRCD, heart failure stands out in prevalence and severity, with left ventricular dysfunction being the focus of most studies. Right ventricle (RV) may also be damaged by CTRCD, however the effects of CTRCD on RV function (RVF) have not been elucidated. Objective We aimed to conduct a systematic review and meta-analysis evaluating RV echocardiographic parameters in patients undergoing chemotherapy. Methods PubMed, Embase and Cochrane were searched for studies that evaluated RV parameters during cancer therapy. Statistical analysis was performed using the R statistical software. We computed pooled mean differences (MD), adopting a random-effects model, with a significance level of 0.05. A conservative correlation coefficient of 0.5 was assumed for paired measurement, when necessary. Heterogeneity was assessed using the I² statistic. Results We included 1520 patients from 25 studies, 73% of whom were women and with a mean age of 51.1±16.5 years. RVF was significantly lower after CTRCD, with reduction in fractional area change (MD=-2.29% [95% CI: -3.63,-0.95]) - Figure 1A, RV global longitudinal strain (MD=2.49% [95% CI: 1.73, 3.25]) - Figure 1B, and RV free wall strain (MD=3.21% [95% CI: 2.32, 4.11]) - Figure 1C. Additionally, tricuspid annular plane systolic excursion was significantly reduced (MD=-1.44mm [95% CI: -1.94, -0.95]) - Figure 2A, and pulmonary artery systolic pressure was significantly higher (MD=1.60mmHg [95% CI: 0.64, 2.56]) - Figure 2B, after chemotherapy. Conclusion The assessment of RVF is important in CTRCD, and its quantification should be included in clinical follow-up during cancer treatment. Further research is needed to elucidate the underlying factors contributing to RV dysfunction and to develop methods for its early detection.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".