Diffusing Pulmonary Capacity Measured During Effort: A Possible Early Marker of Pulmonary Involvement In Systemic Sclerosis.
Bibliographic record
Abstract
BACKGROUND: Interstitial lung involvement is common and potentially limits the quality of life in patients with systemic limited sclerosis (SScl). OBJECTIVES: To study the lung carbon monoxide diffusion (DLCO) measured during effort in order to identify a possible subclinical impairment. METHODS: We enrolled 20 SScl patients without interstitial lung involement and 20 healthy controls. At enrolment all subjetcs underwent plethysmography, DLCO by single-breath technique, and evaluation of pulmonary blood flow (Qc) with the rebreathing CO2 method. Skin involvement in the SScl patients was rated using the modified Rodman skin score (mRSS). During exercise on a cycle ergometer, DLCO, DLCO/ alveolar volume (Kco) and Qc were calculated at 25% and 50% of predicted maximum workload (25% pmw and 50% pmw). RESULTS: At baseline two groups did not differ in age, body mass index, lung function or Qc. In the controls, DLCO, Kco and DLCO/Qc measured at 25% pmw and 50% pmw were significantly higher than in SScl patients, while Qc was not different. Based on response to effort, SScl patients were divided into two groups: responders, with an increase of DLCO(25%pmw) and DLCO(50%pmw) at least 5% and 10% respectively, and non-responders. The non-responders showed greater skin involvement and significantly reduced DLCO, Kco and DLCO/Qc values at rest than responders. CONCLUSIONS: Moderate effort in SScl patients may reveal a latent impairment in gas diffusion through the alveolar/capillary membrane, thus confirmig that exertional DLCO can identify lung damage at an earlier stage than DLCO at rest.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".