Preoperative optimization: Physical and cognitive pre-habilitation and management of chronic medication
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Surgery is a significant stressor for older patient. Most are at higher risk of complications due to frailty and comorbidities. This article will review the impact of surgery on the older patient, perioperative risk assessment and stratification, prehabilitation, and specific screenings and interventions. Electronic searches of PubMed were conducted to identify relevant literature using the following search terms: prehabilitation, sarcopenia, osteosarcopenia, frailty, perioperative evaluation, and polypharmacy. Using the frailty phenotype allows for the early identification of geriatric syndromes and potential targets for interventions. However, it does not inform on potential cognitive impairment, which must be assessed separately. Prehabilitation, especially using multimodal interventions, aims to increase functional capacity during the preoperative period in anticipation of the upcoming stress of surgery and the metabolic cost of recovery. It comprises aerobic and resistance training, dietary interventions, psychological interventions, and cessation of adverse health behaviors. Addressing polypharmacy is also important during the perioperative period. Several frailty assessment tools exist, and special tests only take minutes to perform such as the gait speed and chair stand test. Early identification by surgeons leads to early referral to prehabilitation, which needs about four to six weeks to improve function. The decision to enroll patients in a prehabilitation program is based on the understanding of the needs to maintain a structured and personalized intervention taking into consideration the patient's health status, the type of surgery, and the state of the disease. Perioperative evaluation and prehabilitation for older adults are evolving fields, which are generating clinical and scientific interest. This article will review relevant topics to help clinicians adapt usual perioperative care to older patients' particular needs.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it