Self-reported symptom experience of critically ill cancer patients receiving intensive care
Bibliographic record
Abstract
OBJECTIVE: To characterize the symptom experience of a cohort of intensive care unit (ICU) patients at high risk for hospital death. DESIGN: Prospective analysis of patients with a present or past diagnosis of cancer who were consecutively admitted to a medical ICU during an 8-month period. SETTING: Academic, university-affiliated, tertiary-care, urban medical center. PATIENTS: One hundred cancer patients treated in a medical ICU. INTERVENTION: Assessment of symptoms. MEASUREMENTS: Patients' self-reports of symptoms using the Edmonton Symptom Assessment Scale (ESAS), and ratings of pain or discomfort associated with ICU diagnostic/therapeutic procedures and of stress associated with conditions in the ICU. MAIN RESULTS: Hospital mortality for the group was 56%. Fifty patients had the capacity to respond to the ESAS, among whom 100% provided symptom reports. Between 55% and 75% of ESAS responders reported experiencing pain, discomfort, anxiety, sleep disturbance, or unsatisfied hunger or thirst that they rated as moderate or severe, whereas depression and dyspnea at these levels were reported by approximately 40% and 33% of responders, respectively. Significant pain, discomfort, or both were associated with common ICU procedures, but most procedure-related symptoms were controlled adequately for a majority of patients. Inability to communicate, sleep disruption, and limitations on visiting were particularly stressful among ICU conditions studied. CONCLUSIONS: Among critically ill cancer patients, multiple distressing symptoms were common in the ICU, often at significant levels of severity. Symptom assessment may suggest more effective strategies for symptom control and may direct decisions about appropriate use of ICU therapies.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".