Mexican Hispanics show significant improvement in lung function approximately 1 year after having severe COVID‐19
Bibliographic record
Abstract
The long-term effects of COVID-19 on lung function are not understood, especially for periods extending beyond 1 year after infection. This observational, longitudinal study investigated lung function in Mexican Hispanics who experienced severe COVID-19, focusing on how the length of recovery affects lung function improvements. At a specialized COVID-19 follow-up clinic in Yucatan, Mexico, lung function and symptoms were assessed in patients who had recovered from severe COVID-19. We used z-scores, and Wilcoxon's signed rank test to analyse changes in lung function over time. Lung function was measured twice in 82 patients: the first and second measurements were taken a median of 94 and 362 days after COVID-19 diagnosis, respectively. Initially, 61% of patients exhibited at least one of several pulmonary function abnormalities (lower limit of normal = -1.645), which decreased to 22% of patients by 390 days post-recovery. Considering day-to-day variability in lung function, 68% of patients showed improvement by the final visit, while 30% had unchanged lung function from the initial assessment. Computed tomography (CT) scans revealed ground-glass opacities in 33% of patients. One year after infection, diffusing capacity of the lungs for carbon monoxide z-scores accounted for 30% of the variation in CT fibrosis scores. There was no significant correlation between the length of recovery and improvement in lung function based on z-scores. In conclusion, 22% of patients who recovered from severe COVID-19 continued to show at least one lung function abnormality 1 year after recovery, indicating a prolonged impact of COVID-19 on lung health.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".