Ventricular structure, function, and mechanics at high altitude: chronic remodeling in Sherpa vs. short-term lowlander adaptation
Bibliographic record
Abstract
Short-term, high-altitude (HA) exposure raises pulmonary artery systolic pressure (PASP) and decreases left-ventricular (LV) volumes. However, relatively little is known of the long-term cardiac consequences of prolonged exposure in Sherpa, a highly adapted HA population. To investigate short-term adaptation and potential long-term cardiac remodeling, we studied ventricular structure and function in Sherpa at 5,050 m (n = 11; 31 ± 13 yr; mass 68 ± 10 kg; height 169 ± 6 cm) and lowlanders at sea level (SL) and following 10 ± 3 days at 5,050 m (n = 9; 34 ± 7 yr; mass 82 ± 10 kg; height 177 ± 6 cm) using conventional and speckle-tracking echocardiography. At HA, PASP was higher in Sherpa and lowlanders compared with lowlanders at SL (both P < 0.05). Sherpa had smaller right-ventricular (RV) and LV stroke volumes than lowlanders at SL with lower RV systolic strain (P < 0.05) but similar LV systolic mechanics. In contrast to LV systolic mechanics, LV diastolic, untwisting velocity was significantly lower in Sherpa compared with lowlanders at both SL and HA. After partial acclimatization, lowlanders demonstrated no change in the RV end-diastolic area; however, both RV strain and LV end-diastolic volume were reduced. In conclusion, short-term hypoxia induced a reduction in RV systolic function that was also evident in Sherpa following chronic exposure. We propose that this was consequent to a persistently higher PASP. In contrast to the RV, remodeling of LV volumes and normalization of systolic mechanics indicate structural and functional adaptation to HA. However, altered LV diastolic relaxation after chronic hypoxic exposure may reflect differential remodeling of systolic and diastolic LV function.
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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 | 0.000 |
| 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 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".