Global disease burden of conditions requiring emergency surgery
Bibliographic record
Abstract
BACKGROUND: Surgical disease is inadequately addressed globally, and emergency conditions requiring surgery contribute substantially to the global disease burden. METHODS: This was a review of studies that contributed to define the population-based health burden of emergency surgical conditions (excluding trauma and obstetrics) and the status of available capacity to address this burden. Further data were retrieved from the Global Burden of Disease Study 2010 and the University of Washington's Institute for Health Metrics and Evaluation online data. RESULTS: In the index year of 2010, there were 896,000 deaths, 20 million years of life lost and 25 million disability-adjusted life-years from 11 emergency general surgical conditions reported individually in the Global Burden of Disease Study. The most common cause of death was complicated peptic ulcer disease, followed by aortic aneurysm, bowel obstruction, biliary disease, mesenteric ischaemia, peripheral vascular disease, abscess and soft tissue infections, and appendicitis. The mortality rate was higher in high-income countries (HICs) than in low- and middle-income countries (LMICs) (24.3 versus 10.6 deaths per 100,000 inhabitants respectively), primarily owing to a higher rate of vascular disease in HICs. However, because of the much larger population, 70 per cent of deaths occurred in LMICs. Deaths from vascular disease rose from 15 to 25 per cent of surgical emergency-related deaths in LMICs (from 1990 to 2010). Surgical capacity to address this burden is suboptimal in LMICs, with fewer than one operating theatre per 100,000 inhabitants in many LMICs, whereas some HICs have more than 14 per 100,000 inhabitants. CONCLUSION: The global burden of surgical emergencies is described insufficiently. The bare estimates indicate a tremendous health burden. LMICs carry the majority of emergency conditions; in these countries the pattern of surgical disease is changing and capacity to deal with the problem is inadequate. The data presented in this study will be useful for both the surgical and public health communities to plan a more adequate response.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".