Emergency Room Visits and Hospital Admission Rates After Curative Chemotherapy for Breast Cancer
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
PURPOSE: Curative chemotherapy for breast cancer is associated with significant toxicities including emergency room (ER) visits and hospital admissions (HAs), events that are underreported in clinical trials. This study examined the reasons for, and factors associated with, ER visits and HA after curative chemotherapy for breast cancer in a tertiary Ontario hospital. PATIENTS AND METHODS: A retrospective study of all patients who completed at least one cycle of curative chemotherapy for breast cancer in 2011 and 2012 was conducted. We recorded ER visits and HAs within 30 days of any chemotherapy. We collected demographics, comorbidities, surgical data, tumor characteristics, chemotherapy type and cycles, and use of granulocyte colony-stimulating factors (G-CSF). RESULTS: A total of 149 patients underwent curative chemotherapy. Mean age was 58.6 years. Adjuvant chemotherapy was received by 85% of patients and G-CSF by 88.6%. At least one ER visit occurred in 53% of patients, and 13% required HA. The most common causes of ER visits were fever without neutropenia (23.3%), pain (12.8%), and febrile neutropenia (9%). Stage of breast cancer was the only factor statistically significantly associated with ER visits (P = .045); tumor size (P = .019), adjuvant chemotherapy (P = .045), and lower number of chemotherapy cycles (P = .005) were significantly associated with HA. CONCLUSION: Future research should focus on identifying the patient, provider, and health system factors associated with ER visits and HAs after chemotherapy for breast cancer, to minimize them and lessen the burden on the health care system.
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 | 0.001 |
| 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