Gastrointestinal Symptom Distress is Associated With Worse Mental and Physical Health-Related Quality of Life
Bibliographic record
Abstract
Background: The prevalence of self-reported gastrointestinal (GI) symptoms and distress is high, but few studies have quantified their impact on health-related quality of life (HRQoL). Methods: We conducted a prospective cohort study of patients with HIV in care in Ontario, Canada (2007-2014). General linear mixed models were used to assess the impact of GI symptoms (diarrhea/soft stool, nausea/vomiting, bloating/painful abdomen, loss of appetite, weight loss/wasting) and distress (range: 0-4) on physical and mental HRQoL summary scores (range: 0-100) measured by the Medical Outcomes Survey SF-36. Results: A total of 1787 participants completed one or more questionnaires {median 3 [interquartile range (IQR): 1-4]}. At baseline, 59.0% were men who had sex with men, 53.7% white, median age 45 (IQR: 38-52), median CD4 count 457 (IQR: 315-622), and 71.0% had undetectable HIV viremia. The mean (standard deviation [SD]) mental and physical HRQoL scores were 49.2 (8.6) and 45.3 (13.0), respectively. In adjusted models, compared with those reporting no symptoms, all GI symptom distress scores from 2 ("have symptom, bothers me a little") to 4 ("have symptom, bothers a lot") were associated with lower mental HRQoL. Loss of appetite distress scores ≥ 1; scores ≥ 2 for diarrhea, nausea/vomiting, and bloating; and a score ≥ 3 for weight loss were independently associated with lower physical HRQoL scores (P < 0.0001). Increasing GI symptom distress is associated with impaired mental and physical HRQoL (P < 0.0001). Conclusions: Increasing GI symptom distress is associated with impaired mental and physical HRQoL. Identifying, treating, and preventing GI symptoms may reduce overall symptom burden and improve HRQoL for patients with HIV.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".