Clinical Variables Related to Functional Capacity and Exertional Desaturation in Patients with COVID-19
Bibliographic record
Abstract
Impaired functional capacity is one of the most commonly reported consequences among post-COVID-19 patients. This study aimed to analyse the clinical variables related to functional capacity and exertional desaturation in post-COVID-19 patients at the time of hospital discharge. A cross-sectional study was conducted on patients recovering from COVID-19 pneumonia. The main outcomes measures were functional capacity, assessed using the 1 min sit-to-stand test (1 min STST), and exertional desaturation, defined as a drop of ≥4% in the arterial oxygen saturation. Factors used to characterise the participant outcomes included the use of a high-flow nasal cannula (HFNC), prolonged hospitalisation, occurrence of pulmonary embolism during hospitalisation, and underlying comorbidities. A total of 381 participants (mean age = 53.7 ± 13.2 years, 65.6% men) were included. Participants completed a mean of 16.9 ± 6.2 repetitions in the 1 min STST. Exertional desaturation was observed in 51% of the patients. Higher odds of exertional desaturation were found in the participants who used a HFNC (OR = 3.6; 95%CI: 1.6 to 7.8), were admitted in the hospital >10 days (OR = 4.2; 95%CI: 2.6 to 6.8), and had a pulmonary embolism (OR = 3.5; 95%CI: 2.2. to 5.3). Use of a HFNC (β = -3.4; 95%CI: -5.3 to -1.44), a hospital stay >10 days (β = -2.2; 95%CI: -3.4 to -0.9), and a history of pulmonary embolism (β = -1.4; 95%CI: -2.6 to -0.2) were also negatively associated with the 1 min STST. Most post-COVID-19 patients exhibited reduced functional capacity at the time of hospital discharge, and approximately half had exertional desaturation after the 1 min STST. The use of a HFNC, prolonged hospitalisation and pulmonary embolism were the main clinical variables associated with worse a 1 min STST performance and a higher likelihood of exertional desaturation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".