Symptom Distress Profiles in Hospitalized Patients in Sweden: A Cross‐Sectional Study
Bibliographic record
Abstract
Symptom distress profiles of patients with a variety of diagnoses at two hospitals in Sweden were examined using a point-prevalence cross-sectional survey design. The sample included 710 patients present on internal medicine, surgery, geriatric, and oncology acute care hospital wards of each hospital on a single day. Symptom distress data were collected via structured interviews using a 0-10 numeric rating scale (NRS). Fatigue was the most prevalent symptom, experienced by 76.2% of the patients, followed by pain (65.2%) and sleeping difficulties (52.8%). Symptoms were fairly distressing (median NRS 5-6). Patients experiencing high distress from fatigue and pain were more likely to be female, living alone, and to have more symptoms. Latent class analysis revealed three symptom distress profiles that differed with respect to the degree of distress and number of symptoms. The profiles were not substantially differentiated by diagnoses. Symptom distress needs to be assessed and treated on an individual basis, rather than predicting distress levels based on diagnosis alone.
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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 | 0.002 | 0.000 |
| 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 | 0.000 | 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 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".