New conditions identified through a comprehensive geriatric assessment in cancer patients.
Bibliographic record
Abstract
133 Background: Chronologic age cannot be used to predict the degree of comorbidity and of functional deterioration of older adults. Assessment of older adults includes health, functional status, nutrition, cognition, socio-economic and mood disorders evaluations. This multidisciplinary assessment is referred to as comprehensive geriatric assessment (CGA). The risk of comorbid conditions increases with age and may result in under diagnosis: in older patients, new symptoms may not be clearly recognized by the patient and may be dismissed by practitioners as manifestations of preexisting conditions. Methods: We conducted a retrospective cohort analysis, of older adult patients (aged 70 years of age and older) evaluated at the Program for Healthy Aging at MD Anderson from January 1, 2013 through December 31, 2014. Assessment was conducted using Katz’ ADLs, Lawton’s IADLs, PHQ-9, the short physical performance battery, the Montreal cognitive assessment, mini nutritional assessment and Charlson co-morbidity index. Medication review and social assessment were also included. Analysis: cross tabulations were performed in SAS 9.4 (SAS Institute INC, Cary, NC) Results: We evaluated 198 patients, (n = 99, 51.6% females). Most common malignancies evaluated included hematologic malignancies (n = 62, 33%), breast cancer (n = 32, 13.2 %), prostate cancer (n = 19, 10 %) and other solid malignancies (n = 85, 43%). The comprehensive geriatric assessment identified a mean of 3 new conditions (range 1-10). The most commonly identified conditions included cognitive impairment and dementia (n = 148, 77%), low bone mass and osteoporosis (n = 67, 34%), malnutrition (n = 65, 34%), frailty (n = 58, 30.2%), and polypharmacy (n = 64, 33%). These conditions are relevant in the management of such patients and could lead to recurring admissions if left unaddressed. Conclusions: A CGA program in a cancer center allows for the identification of medical conditions that directly contribute to clinical outcomes. A CGA allows for the development of a comprehensive plan of care that addresses such issues preventing adverse consequences.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".