Symptom burden in hospitalized patients with advanced cancer.
Bibliographic record
Abstract
100 Background: Patients with advanced cancer experience high rates of both physical and psychological morbidity, but data describing patients’ symptoms during hospital admissions are lacking. We sought to describe symptom burden in hospitalized patients with incurable solid and hematologic malignancies. Methods: We prospectively enrolled patients with incurable cancers admitted to the Massachusetts General Hospital from 9/1/2014 through 5/1/2015. Within the first week of their admission, we assessed physical and psychological symptoms using the Edmonton Symptom Assessment System-revised (ESAS-r). Beginning 11/15/2015, we also administered the Patient Health Questionnaire 4 (PHQ-4), scored categorically. Results: We enrolled 457 of 547 (84%) eligible patients. Participants (mean age=63.8 years; n=231, 51% female) had the following malignancies: gastrointestinal (n=149, 33%), lung (n=77, 17%), genitourinary (n=52, 11%), breast (n=33, 7%), hematologic (n=24, 5%), and other solid tumors (n=122, 27%). Using the ESAS-r, tiredness, drowsiness, anorexia, and pain were the most common severe symptoms. Using the PHQ-4, approximately one-third of participants screened positive for depression (91/271, 34%) and anxiety (86/273, 32%). Conclusions: Hospitalized patients with incurable solid and hematologic malignancies experience substantial physical and psychological symptoms. Most patients reported at least moderate tiredness, drowsiness, anorexia and pain. Additionally, a concerning proportion reported depression and anxiety. Our data demonstrate the need for efforts to alleviate the physical symptoms experienced by this population, while also seeking to understand and address their psychological needs. [Table: see text]
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".