Changes in Body Weight and Serum Albumin Levels in Patients Requiring Home Long-term Oxygen Therapy
Bibliographic record
Abstract
Purpose: To investigate the long-term changes in body weight and serum albumin levels in patients with respiratory failure, and those with chronic heart failure, who were treated with home long-term oxygen therapy (LTOT) to understand the current status and contribute to future measures. Methods: Patients with chronic obstructive pulmonary disease (COPD), those with interstitial pneumonia (IP), and those with chronic heart failure (CHF) undergoing home LTOT for 6 months or more between January 2011 and January 2019 were included in the study. Body weight and serum albumin levels were assessed at the start of home LTOT and at the end of the observation period, a minimum of 6 months after commencing home LTOT. Results: Sixty-two patients (29 COPDs, 23 IPs, and 10 CHFs) were included. In COPD patients and IP patients, body weight decreased (P = 0.0017, P = 0.0018, respectively, Wilcoxon signed-rank test). Serum albumin levels decreased in IP patients (P = 0.0185) but not in COPD patients. There was neither significant decrease in body weight nor serum albumin levels in patients with CHF. Conclusion: Chronic respiratory failure patients who have home LTOT were likely to have a decreased nutritional status. In order to provide prolonged home LTOT, medical staff need to pay close attention to the nutritional status of patients receiving home LTOT.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".