Inflammatory Status in Moderate and Severe COPD Patients: What Are the Related Factors?
Bibliographic record
Abstract
Background: Systemic inflammation is believed to have an important role in pathogenesis of Chronic Obstructive Pulmonary Disease (COPD) and its related factors should be considered in monitoring of the disease. In the current study, possible link between inflammatory status and various related factors in patients with COPD was assessed. Method: Sixty-one COPD patients according to the inclusion criteria participated in this study. For assessing nutritional status, SGA (subjective global assessment) and 24-hour dietary recall method were used and Health-related quality of life (HRQoL) was assessed by St. George’s respiratory questionnaire (SGRQ), instrumental activities of daily living scales (IADLs), and Katz Index. Moreover, Anthropometric and body composition measurements including weight, height, BMI, FFM, and FFMI were measured by standard methods and BIA. Additionally, muscle strength was assessed using a hydraulic hand dynamometer. Finally, blood samples were collected to assess biochemical factors including TNF-α, IL-6, MDA, vitamin C, magnesium, and Glutathione. Stepwise model was performed for evaluating the relationship between inflammatory markers (TNF-α and IL-6) and associated markers mentioned above. Characteristics of participants were expressed in percentage and mean ±SD and analyzed by SPSS software. Results: The results of the current study showed that the intake of PUFA and vegetables, plasma vitamin C and serum MDA could possibly affect inflammation according to IL-6 and TNF- α concentrations. On the other hand, systemic inflammation (IL-6 and TNF-) aggravated mean right and left handgrip strength, Katz index and nutritional status (SGA score) significantly (P <0.05). Conclusion: To sum up, our results confirmed the inter-relationship between inflammatory markers and intake of some dietary components, oxidative stress biomarkers, muscle function, and nutritional status in COPD patients. These factors might affect over each other and further studies are needed to better elucidate this issue. Background: Systemic inflammation is believed to have an important role in pathogenesis of Chronic Obstructive Pulmonary Disease (COPD) and its related factors should be considered in monitoring of the disease. In the current study, possible link between inflammatory status and various related factors in patients with COPD was assessed. Method: Sixty-one COPD patients according to the inclusion criteria participated in this study. For assessing nutritional status, SGA (subjective global assessment) and 24-hour dietary recall method were used and Health-related quality of life (HRQoL) was assessed by St. George’s respiratory questionnaire (SGRQ), instrumental activities of daily living scales (IADLs), and Katz Index. Moreover, Anthropometric and body composition measurements including weight, height, BMI, FFM, and FFMI were measured by standard methods and BIA. Additionally, muscle strength was assessed using a hydraulic hand dynamometer. Finally, blood samples were collected to assess biochemical factors including TNF-α, IL-6, MDA, vitamin C, magnesium, and Glutathione. Stepwise model was performed for evaluating the relationship between inflammatory markers (TNF-α and IL-6) and associated markers mentioned above. Characteristics of participants were expressed in percentage and mean ±SD and analyzed by SPSS software. Results: The results of the current study showed that the intake of PUFA and vegetables, plasma vitamin C and serum MDA could possibly affect inflammation according to IL-6 and TNF- α concentrations. On the other hand, systemic inflammation (IL-6 and TNF-) aggravated mean right and left handgrip strength, Katz index and nutritional status (SGA score) significantly (P <0.05). Conclusion: To sum up, our results confirmed the inter-relationship between inflammatory markers and intake of some dietary components, oxidative stress biomarkers, muscle function, and nutritional status in COPD patients. These factors might affect over each other and further studies are needed to better elucidate this issue.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".