Bibliographic record
Abstract
The advent of modern antimicrobial therapy following the discovery of penicillin during the 1940s yielded remarkable improvements in case fatality rate of serious infections including septic shock. Since then, pathogens have continuously evolved under selective antimicrobial pressure resulting in a lack of significant improvement in clinical effectiveness in the antimicrobial therapy of septic shock despite ever more broad-spectrum and potent drugs. In addition, although substantial effort and money has been expended on the development novel non-antimicrobial therapies of sepsis in the past 30 years, clinical progress in this regard has been limited. This review explores the possibility that the current pathophysiologic paradigm of septic shock fails to appropriately consider the primacy of the microbial burden of infection as the primary driver of septic organ dysfunction. An alternate paradigm is offered that suggests that has substantial implications for optimizing antimicrobial therapy in septic shock. This model of disease progression suggests the key to significant improvement in the outcome of septic shock may lie, in great part, with improvements in delivery of existing antimicrobials and other anti-infectious strategies. Recognition of the role of delays in administration of antimicrobial therapy in the poor outcomes of septic shock is central to this effort. However, therapeutic strategies that improve the degree of antimicrobial cidality likely also have a crucial role.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".