Bibliographic record
Abstract
PURPOSE OF REVIEW: Sepsis leads to a complex intramyocardial inflammatory response that results in sepsis-induced myocardial dysfunction. Here, recent findings are reviewed in a physiologic context. RECENT FINDINGS: Decreased systolic contractility during sepsis limits ventricular ejection and stroke volume. Initially, this effect is compensated for by increased diastolic filling during volume resuscitation. Reduced afterload due to arterial vasodilation also compensates so that cardiac output can be maintained or increased. Recent results recognize the importance of diastolic dysfunction, reduced ventricular diastolic compliance that impedes ventricular filling. Diastolic dysfunction becomes increasingly important as severity of septic shock increases. When impaired ventricular ejection is coupled with limited diastolic filling, stroke volume must decrease. Accordingly, diastolic dysfunction is more closely related to mortality than systolic dysfunction. Recent trials of beta-adrenergic agonists and levosimendan have been disappointing, while approaches to modulating the intramyocardial inflammatory response show promise. SUMMARY: Sepsis-induced myocardial dysfunction is increasingly recognized as a major contributor to outcome of septic shock. Significant strides have been made in understanding the intramyocardial inflammatory response that causes myocardial dysfunction. A number of novel approaches show promise by modulating the intramyocardial inflammatory response.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".