Part I: Minimum Quality Threshold in Preclinical Sepsis Studies (MQTiPSS) for Study Design and Humane Modeling Endpoints
Bibliographic record
Abstract
Preclinical animal studies are mandatory before new treatments can be tested in clinical trials. However, their use in developing new therapies for sepsis has been controversial because of limitations of the models and inconsistencies with the clinical conditions. In consideration of the revised definition for clinical sepsis and septic shock (Sepsis-3), a Wiggers-Bernard Conference was held in Vienna in May 2017 to propose standardized guidelines on preclinical sepsis modeling. The participants conducted a literature review of 260 most highly cited scientific articles on sepsis models published between 2003 and 2012. The review showed, for example, that mice were used in 79% and euthanasia criteria were defined in 9% of the studies. Part I of this report details the recommendations for study design and humane modeling endpoints that should be addressed in sepsis models. The first recommendation is that survival follow-up should reflect the clinical time course of the infectious agent used in the sepsis model. Furthermore, it is recommended that therapeutic interventions should be initiated after the septic insult replicating clinical care. To define an unbiased and reproducible association between a new treatment and outcome, a randomization and blinding of treatments as well as inclusion of all methodological details in scientific publications is essential. In all preclinical sepsis studies, the high standards of animal welfare must be implemented. Therefore, development and validation of specific criteria for monitoring pain and distress, and euthanasia of septic animals, as well as the use of analgesics are recommended. A set of four considerations is also proposed to enhance translation potential of sepsis models. Relevant biological variables and comorbidities should be included in the study design and sepsis modeling should be extended to mammalian species other than rodents. In addition, the need for source control (in case of a defined infection focus) should be considered. These recommendations and considerations are proposed as "best practices" for animal models of sepsis that should be implemented.
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 | 0.338 | 0.446 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.010 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.009 | 0.007 |
| Research integrity | 0.021 | 0.014 |
| Insufficient payload (model declined to judge) | 0.014 | 0.017 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".