Dyspnea on Exercise Is Associated with Overall Symptom Burden in Patients with Chronic Respiratory Insufficiency
Bibliographic record
Abstract
Background: Patients with chronic respiratory insufficiency suffer from many symptoms together with dyspnea. Objective: We evaluated the association of dyspnea on exercise with other symptoms in patients with chronic respiratory insufficiency due to chronic obstructive pulmonary disease or interstitial lung disease. Design: This retrospective study included 101 patients in Tampere University Hospital, Finland. Dyspnea on exercise was assessed with modified Medical Research Council (mMRC) dyspnea questionnaire, and other symptoms were assessed with Edmonton Symptom Assessment System (ESAS) and Depression Scale (DEPS). The study was approved by Regional Ethics Committee of Tampere University Hospital, Finland (approval code R15180/December 1, 2015). Results: Patients with mMRC 4 (most severe dyspnea) compared with those with mMRC 0–3 reported higher symptom scores on ESAS in shortness of breath (median 8.0 [IQR 6.0–9.0] vs. 4.0 [2.0–6.0], p < 0.001), dry mouth (7.0 [4.0–8.0] vs. 3.0 [1.0–6.0], p < 0.001), tiredness (6.0 [3.0–7.0] vs. 3.0 [1.0–5.0], p < 0.001), loss of appetite (3.0 [0.0–6.0] vs. 1.0 [0.0–3.0], p = 0.001), insomnia (3.0 [1.0–7.0] vs. 2.0 [0.0–3.0], p = 0.027), anxiety (3.0 [0.0–5.5] vs. 1.0 [0.0–3.0], p = 0.007), and nausea (0.0 [0.0–2.0] vs. 0.0 [0.0–0.3], p = 0.027). Patients with mMRC 4 were more likely to reach the DEPS threshold for depression than those scoring mMRC 0–3 (42.1% vs. 20.8%, p = 0.028). Conclusions: Patients with chronic respiratory insufficiency need comprehensive symptom screening with relevant treatment, as they suffer from broad symptom burden worsening with increased dyspnea on exercise.
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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 | 0.002 |
| 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 | 0.001 | 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".