46 NURSING LED PHONE CLINIC FOR PATIENTS DURING THE ONE-MONTH PERIOD BETWEEN CONCURRENT CHEMORADIOTHERAPY AND ADJUVANT TREATMENT: A PILOT PROJECT
Bibliographic record
Abstract
Abstract Brain Cancer Canada Travel Award Recipient BACKGROUND After concurrent chemoradiation for a high-grade glioma patients will typically have a one-month break before commencing adjuvant chemotherapy. During this time, patients will wean off steroids and recover from acute toxicity of treatment. Our clinical team observed that many patients were having a significant decline in physical or emotional wellbeing. Often the decrease in function would lead to a delay in starting adjuvant therapy. We hypothesized that a phone appointment with our CNS nursing team would allow treatments to be implemented to prevent performance status decline by treating or triaging medical needs, refer appropriately for social needs and encourage physical wellbeing. METHODS After a one-year preliminary phase we investigated the clinic by reviewing all charts in the clinic for the 6-week period of July 31, 2024 to September 4, 2024. We evaluated the number of patients in this clinic weekly. We evaluated all interventions in clinic. This included medical interventions and social/emotional interventions. RESULTS One CNS nurse was placed in this clinic ½ day a week. 3 Patients were seen weekly (range 2-6) 18 patients in total 4 patient had minor medication adjustments (with informing of primary physician team) 2 patients had major medical intervention (with support of primary physician team and ED) 4 patients had referral for social /emotional well being DISCUSSION The period after chemoradiation and before adjuvant chemotherapy for patients with high grade gliomas represents a dynamic medical period. By providing a planned touch point with the cancer centre, we were able to intervene with medical and social / emotional interventions in the majority of patients. Many of these interventions prevented patients from presenting to acute care (ED, urgent care) or delay of adjuvant therapy. Further prospective studies are needed to better define this benefit.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".