Abstract 16736: Medical vs. Surgical Management of Perivalvular Abscess in Infective Endocarditis: A Propensity Analysis From the International Collaboration on Endocarditis Prospective Cohort Study (ICE-PCS)
Bibliographic record
Abstract
Introduction Myocardial abscess is generally regarded as an indication for surgical intervention in infective endocarditis (IE). There is little information, however, comparing outcomes with medical vs. surgical management of such periannular complications of IE. This study used the database of the ICE-PCS to perform a propensity analysis, comparing one year mortality in patients with IE and abscess subjected to either medical or surgical treatment. Methods ICE-PCS enrolled 4794 patients between 2000 and 2006, from 64 centers in 28 countries. There were 699 cases of IE with abscess. A statistical model was built to predict surgery in this cohort.158 patients who underwent surgery for abscess were matched to 158 patients who did not. These 316 patients formed the basis of the analysis. Results In the unadjusted group of 699 patients, the one-year survival with medical treatment was 45%, vs. 67% with surgical management (p<.0001). Differences favoring surgery were similar whether or not the patients had poor prognostic indicators (S. aureus infection; prosthetic valve involvement; CHF). Patients with strep viridans infection, however, had similar survival with medical or surgical management (70%, 14/20 vs.77%, 65/84). In the propensity analysis, the one-year survival with medical management was 44%, compared to 58% in the surgical group (p=.0021). (See graph). Conclusion One-year survival of IE patients with abscess was superior with surgical compared to medical management. These findings support current recommendations that surgical management of perivalvular extension of infection is generally the preferred approach. Patients with strep viridans infection, however, seem to fare equally well with medical or surgical treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".