Infective Endocarditis: Preliminary Results of a Cohort Study in the Southern Italian Population
Bibliographic record
Abstract
Background Infective endocarditis (IE) is an uncommon disease with an involved interplay of clinical and surgical team management. We aimed to define diagnosis parameters and delineate in-hospital management in patients with IE admitted in a tertiary hospital of Southern Italian. Materials and methods Fifty-six consecutive patients (42 males, 14 females; age range: 34-85 years) admitted for IE in the Infectious Diseases, Cardiac Surgery, and Cardiology units, between January 2011 and August 2017, were enrolled. Demographic data, mortality, comorbidities, specimen type, microscopy results, special histological staining performed, and antimicrobial therapy were collected and analyzed. Any comments at the multidisciplinary team meetings were recorded in minutes of and approved. Results We found 83.9% of patients with positive blood cultures. The four most common bacteria were methicillin-resistant Staphylococcus aureus (MRSA: 21.3%), methicillin-sensitive Staphylococcus aureus (MSSA: 17%), Streptococci (14.9%), and Enterococci (14.9%). Both in the univariate and multivariate analysis, we observed a significant positive correlation between surgery and complications. Particularly in the univariate analysis only, surgery was positively correlated to males and C-reactive protein (CPR) at baseline. Also, considering the most common bacteria, it resulted in a positive correlation between surgery and MRSA and Streptococci spp. and between complications and MSSA. Finally, the male gender was positively correlated to MSSA and heart complications, major arterial embolism, septic pulmonary emboli, splenic infarction, and cerebral embolism. Conclusions A blood culture test remains a critical factor for the diagnosis of IE and the antibiotic treatment of susceptible and emerging resistant bacteria. Male gender and heart complications are red flags for prompt operative management.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".