Management of intra-abdominal-infections: 2017 World Society of Emergency Surgery guidelines summary focused on remote areas and low-income nations
Bibliographic record
Abstract
BACKGROUND: Most remote areas have restricted access to healthcare services and are too small and remote to sustain specialist services. In 2017, the World Society of Emergency Surgery (WSES) published guidelines for the management of intra-abdominal infections. Many hospitals, especially those in remote areas, continue to face logistical barriers, leading to an overall poorer adherence to international guidelines. METHODS: The aim of this paper is to report and amend the 2017 WSES guidelines for the management of intra-abdominal infections, extending these recommendations for remote areas and low-income countries. A literature search of the PubMed/MEDLINE databases was conducted covering the period up until June 2020. RESULTS: The critical shortages of healthcare workers and material resources in remote areas require the use of a robust triage system. A combination of abdominal signs and symptoms with early warning signs may be used to screen patients needing immediate acute care surgery. A tailored diagnostic step-up approach based on the hospital's resources is recommended. Ultrasound and plain X-ray may be useful diagnostic tools in remote areas. The source of infection should be totally controlled as soon as possible. CONCLUSIONS: The cornerstones of effective treatment for intra-abdominal infections in remote areas include early diagnosis, prompt resuscitation, early source control, and appropriate antimicrobial therapy. Standardization in applying the guidelines is mandatory to adequately manage intra-abdominal infections.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".