P1784Dismal outcomes and high societal burden of mitral valve regurgitation in France in the recent era
Bibliographic record
Abstract
Abstract Background Mitral regurgitation (MR) is the most common heart valve disorder worldwide. The contrast between the large burden of MR and the overall low number of performed mitral valve surgery suggest a marked undertreatment of MR patients. Large and comprehensive contemporary data assessing the management and outcome of patients with MR as well as the societal burden of the disease at the Nationwide level are currently lacking. Methods Based on a French mandatory administrative hospital-discharge database, we collected all admissions in France both in public and private hospitals in 2014 and 2015 with MR as primary or secondary code. Patients with infective endocarditis, congenital or rheumatic disease were excluded. Cost were calculated for patients admitted in public hospitals. Results In 2014–2015, 107,412 patients with MR were admitted in France in 1238 public and private hospitals; 74,098 patients (69%) presented with primary MR (PMR) and 33,314 patients (31%) with secondary MR (SMR). Overall 8,676 patients (8%) were operated on (81% PMR) within 1 year and 98,736 (92%) were conservatively managed and constituted our study population. Mean age was 77±15 years (50% were ≥80 years and 12% ≥90 years) and 53% were female. Most of the patients presented with comorbidities and Charlson Index was ≥2 in 53% of the population. In-hospital and one-year mortality were 4.1% and 14.3% respectively. Readmission were very common and one-year mortality/readmission all cause, and one-year mortality / CHF readmission rates were 67% and 34% respectively and increased with age, Charlson Index, CHF at presentation and SMR etiology but events rate remained notably high in the PMR subset (64% and 28% respectively). The total annual cost in public hospitals (initial hospitalisation and readmissions) was 325,716,311 euros. When only readmissions for heart failure were considered (43% of all readmissions), total annual cost was 202,904,869 euros. Conclusion In this large administrative contemporary nationwide database, 1) MR was a common reason for admission and affected an elderly population with frequent comorbidities, 2) less than 10% of patients were offered any intervention, 3) MR was associated with high mortality and readmissions rates in all subsets; 4) MR represented a major societal burden with an extrapolated annual cost between 250 and 400 million euros. These finding highlight the critical need to develop strategies to improve the overall management and outcomes of patients with both primary and secondary MR. Acknowledgement/Funding Edwards Lifesciences
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".