Telehealth and Palliative Care for Patients With Cancer: Implications of the COVID-19 Pandemic
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
It has been reported that the incidence of SARS-CoV-2 infection is higher in patients with cancer than in the general population and that patients with cancer are at an increased risk of developing severe life-threatening complications from COVID-19. Increased transmission and poor outcomes noted in emerging data on patients with cancer and COVID-19 call for aggressive isolation and minimization of nosocomial exposure. Palliative care and oncology providers are posed with unique challenges due to the ongoing COVID-19 pandemic. Telepalliative care is the use of telehealth services for remotely delivering palliative care to patients through videoconferencing, telephonic communication, or remote symptom monitoring. It offers great promise in addressing the palliative and supportive care needs of patients with advanced cancer during the ongoing pandemic. We discuss the case of a 75-year-old woman who was initiated on second-line chemotherapy, to highlight how innovations in technology and telehealth-based interventions can be used to address patients' palliative and supportive care needs in the ongoing epidemic.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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