Fechamento sequencial da parede abdominal com tração fascial contínua (mediada por tela ou sutura) e terapia a vácuo
Bibliographic record
Abstract
The last decade was marked by a multiplication in the number of publications on (and usage of) the concept of damage control laparotomy, resulting in a growing number of patients left with an open abdomen (or peritoneostomy). Gigantic hernias are among the dreaded consequences of damage control and the impossibility of closing the abdomen during the initial hospital admission. To minimize this sequela, the literature has proposed many different strategies. In order to explore this topic, the "Evidence-based Telemedicine - Trauma & Acute Care Surgery" (EBT -TACS) conducted a literature review and critically appraised the most relevant articles on the topic. No commercially available systems for the closure of peritoneostomies were analyzed, except for negative pressure therapy. Three relevant and recently published studies on the sequential closure of the abdominal wall (with mesh or sutures) plus negative pressure therapy were appraised. For this appraisal 2 retrospective and one prospective study were included. The EBT-TACS meeting was attended by representatives of 6 Universities and following recommendations were generated: (1) the association of negative pressure therapy and continuous fascia traction with mesh or suture and adjusted periodically appears to be a viable surgical strategy to treat peritoneostomies. (2) the primary dynamic abdominal closure with sutures or mesh appears to be more efficient and economically sound than leaving the patient with a gigantic hernia to undergo complex repair at a later date. New studies including larger number of patients classified according to their different presentations and diseases are needed to better define the best surgical treatment for patients with peritoneostomies.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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; both teacher heads 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".