Intra-abdominal hypertension: Definitions, monitoring, interpretation and management
Bibliographic record
Abstract
This review will describe the definitions on intra-abdominal hypertension (IAH) and abdominal compartment syndrome (ACS). In order to understand these definitions the reader must be aware of the interactions between intra-abdominal pressure (IAP) and intra-abdominal volume (IAV), explaining why dramatic IAP increases can be observed in some patients related to anthropomorphic measurements, body positioning, use of positive pressure ventilation, or relatively small accumulations of fluid or blood. The adverse effects related to increased IAP have been named IAH for moderate cases and ACS for advanced cases. In order to improve clinical communication as well as evaluation of the scientific literature, the World Society for the Abdominal Compartment Syndrome (WSACS) has published its first guidelines and definitions in 2006. The definitions and guidelines have recently been revised according to evidence based medicine and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology. This review will be based on the revised guidelines. The standard method to measure IAP is via the bladder and as experience with IAP measurement has evolved considerably, a number of tips and potential pitfalls are listed.
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) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".