Does the Addition of Biologic Agents to Chemotherapy in Patients with Unresectable Colorectal Cancer Metastases Result in a Higher Proportion of Patients Undergoing Resection? A Systematic Review and Meta-analysis.
Bibliographic record
Abstract
Emergency general surgery (EGS) in elderly patients carries significant risk of both morbidity and mortality. The growing population of patients over 65 years of age suggests General Surgeons will be tasked with managing increasing numbers of frail and co-morbid patients who are at higher risk compared to younger and non-emergent patients.An electronic literature search of PubMed, MEDLINE, EMBASE and the Cochrane Database of Collected Research was performed from 1990 to 2016. The search included u201cfrail,u201d u201celderly,u201d u201coctogenarian,u201d u201coldu201d and was limited to English papers within emergency general surgery. Observational and experimental studies were included if they included patients over 65 years of age, case reports were excluded. The New-Castle Ottawa scale was used to assess study quality.In twelve studies which met inclusion criteria five were case series, six retrospective cohorts, including two utilizing ACS-NSQIP and one prospective cohort study. Case composition indicated a higher proportion of small/large bowel surgery compared to non-elderly patients. Mortality after EGS ranged from 12-38% with morbidity ranging from 28-70%. In studies directly comparing patients older than 65 years of age to younger patients undergoing EGS, mortality was almost three times higher. Elderly patients undergoing EGS should be considered higher risk than younger patients not only based on age but on frailty and functional status. Case composition, high failure to rescue rate and delayed diagnosis may help explain the elevated mortality rate. Further study is required to identify potentially modifiable risk factors and potential process measures to improve outcomes.
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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.037 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".