Commentary: Complex medical conditions in pregnancy need appropriate multidisciplinary input
Bibliographic record
Abstract
Introduction: COPD is a condition of global importance, characterised by accelerated lung function decline and an abnormal inflammatory response. Exacerbations account for much of the morbidity and the mortality in COPD. Leptin is a protein that is synthesised and secreted by white adipose tissue while resistin is a cysteine-rich adipose-derivedpeptide hormone that in humans is encoded by the RETN gene. Objectives: To record and analyse parameters such as biomarkers, lung functions and dyspnea level on the 1st day of a COPD exacerbation, at discharge and 6 weeks after. Methods: 35 patients (mean age 67,5 years) hospitalised for exacerbation of COPD are included so far in the study. Biomarkers such as adiponectin, leptin, resistin, IL6, IL8 and CRP were measured at admission, at discharge and 6 weeks after discharge. Lung function and dyspnea level were studied and measured at discharge and 6 weeks later. Results: Leptin levels at admission (mean=41,28 ng/ml) were decreased at discharge (33,2) (p=0,015) and further decreased 6 weeks after discharge (mean=29,94 and compared to the admission levels p=0,002). Similar results were observed with resistin, (admission levels mean=23,76, discharge levels 17,64 p=0,064 and levels 6 weeks were 11,66 and compared to the admission levels p=0,001). Statistical significant differences were also observed at the levels of CRP at admission and discharge (p<0,001) and at the levels of FEV1 % at discharge and 6 weeks after(p=0,003) as expected. Conclusion: Levels of Leptin and Resistin are found significantly decreased at discharge and 6 weeks after discharge compared to the admission levels fact that indicates that they may be valuable biomarkers for the assessment of COPD severity along with FEV1 and CRP.
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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 | 0.004 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.034 | 0.033 |
| Insufficient payload (model declined to judge) | 0.028 | 0.011 |
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".