Utility of routine nurse assessment of the risk of chemotherapy-induced febrile neutropenia
Bibliographic record
Abstract
Evidence-based guidelines recommend that patients at high risk (> or = 20%) for febrile neutropenia (FN) should receive prophylactic colony-stimulating factors (Aapro et al., 2006; Kouroukis et al., 2008; National Comprehensive Cancer Network [NCCN], 2008; Smith et al., 2006). We studied the utility of having nurses routinely assess FN risk in new patients before the initiation of chemotherapy. Fifteen nurses used a standardized tool to evaluate FN risk in 150 patients. In 94% of patients studied, nurses detected risk factors that prompted interventions to reduce the incidence of FN. On final evaluation, 67% of nurses said the use of a standardized tool helped them to identify patients at risk for FN, and 73% planned to assess FN risk routinely. Thus, it is feasible and valuable for nurses to assess FN risk using a standardized checklist prior to the initiation of chemotherapy.
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How this classification was reachedexpand
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) | 0.000 | 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 | 0.001 |
| 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 teacher head, 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".