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Record W2053513938 · doi:10.1007/dcr.0b013e3181a74d2e

Colorectal Cancer Surgery in Elderly Patients: Presentation, Treatment, and Outcomes

2009· article· en· W2053513938 on OpenAlexaff
Karen Devon, Omar Vergara‐Fernández, J. Charles Victor, Robin S. McLeod

Bibliographic record

VenueDiseases of the Colon & Rectum · 2009
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsLunenfeld-Tanenbaum Research InstituteMount Sinai HospitalPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsMedicineColorectal cancerColorectal surgeryCancerSurgical oncologyStage (stratigraphy)American society of anesthesiologistsInternal medicineAge groupsSurgeryAbdominal surgeryDemography

Abstract

fetched live from OpenAlex

PURPOSE: This study was designed to characterize the presentation, care, and outcomes of persons older than 75 years, compared with persons 50 to 74 years of age, selected for colorectal cancer. METHODS: Patients over the age of 50 years who had surgery for colon or rectal cancer at the Mount Sinai Hospital between 1997 and 2006 were identified. Data were obtained from a colorectal cancer database and from office and hospital records. Patients were assigned to two groups: 50 to 74 years old and 75 years and older. RESULTS: There were 623 patients in the younger group (mean age, 62.6 years) and 275 in the older group (mean age, 81.5 years). The in-hospital mortality rate was 1% in the younger group compared with 4.2% in the older (P = 0.002). The overall five-year survival was 68.7% and 57.3% in the younger and older groups, respectively, whereas colorectal cancer-specific five-year survival was not significantly different (74.0% vs. 74.7%). There were significant differences between the two groups with respect to cancer location, American Society of Anesthesiologists' score, stage, proportion detected by screening, length of stay, and use of chemotherapy. CONCLUSIONS: Long-term colorectal cancer-related outcomes in the older group are similar to the outcomes in younger patients, suggesting that the decision to operate should not be based on age alone.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.308

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.292
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations69
Published2009
Admission routes1
Has abstractyes

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