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Record W3130740102 · doi:10.31372/20200504.1113

Changes in Body Weight and Serum Albumin Levels in Patients Requiring Home Long-term Oxygen Therapy

2021· article· en· W3130740102 on OpenAlexvenueno aff
Naomi Kayauchi, Eiji Ojima, Katsunori Kagohashi, Hiroaki Satoh

Bibliographic record

VenueAsian/Pacific Island Nursing Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCOPDRespiratory failureAlbuminInternal medicineHeart failureSerum albuminOxygen therapyRespiratory systemPneumoniaPulmonary diseaseIntensive care medicine

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.147
Threshold uncertainty score0.972

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.294
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueAsian/Pacific Island Nursing JournalSame topicChronic Obstructive Pulmonary Disease (COPD) ResearchFrench-language works237,207