Influence of sarcopenia and frailty in the management of elderly patients with acute appendicitis
Bibliographic record
Abstract
In developed countries, the average life expectancy has been increasing and is now well over 80 years. Increased life expectancy is associated with an increased number of emergency surgical procedures performed in later age groups. Acute appendicitis is one of the most common surgical diseases, with a lifetime risk of 8%. A growing incidence of acute appendicitis has been registered in the elderly population and in the oldest groups (> 80 years). Among patients > 50-year-old who present to the emergency department for acute abdominal pain, 15% have acute appendicitis. In these patients, emergency surgery for acute appendicitis is challenging, and some important aspects must be considered. In the elderly, surgical treatment outcomes are influenced by sarcopenia. Sarcopenia must be considered a precursor of frailty, a risk factor for physical function decline. Sarcopenia has a negative impact on both elective and emergency surgery regarding mortality and morbidity. Aside from morbidity and mortality, the most crucial outcomes for older patients requiring emergency surgery are reduction in function decline and preoperative physical function maintenance. Therefore, prediction of function decline is critical. In emergency surgery, preoperative interventions are difficult to implement because of the narrow time window before surgery. In this editorial, we highlight the unique aspects of acute appendicitis in elderly patients and the influence of sarcopenia and frailty on the results of surgical treatment.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".