Macrocirculatory and Microcirculatory Endpoints in Sepsis Resuscitation
Bibliographic record
Abstract
Sepsis is a common disease process encountered by physicians. Sepsis can lead to septic shock, which carries a hospital mortality rate in excess of 40%. Although the Surviving Sepsis Guidelines recommend targeting a mean arterial pressure (MAP) of 65 mmHg and normalization of lactate, these endpoints do not necessarily result in tissue perfusion in states of shock. While MAP and lactate are commonly used markers in resuscitation, clinicians may be able to improve their resuscitation by broadening their assessment of the microcirculation, which more adequately reflects tissue perfusion. As such, in order to achieve a successful resuscitation, clinicians must optimize both macrocirculatory (MAP, cardiac output) and microcirculatory (proportion of perfused vessels, lactate, mottling, capillary refill time) endpoints. This review will summarize various macrocirculatory and microcirculatory markers of perfusion that can be used to guide the initial resuscitation of patients with sepsis.
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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 | 0.002 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".