The effect of pranayama on dyspnea and fatigue in third trimester of pregnancy
Bibliographic record
Abstract
Background: Dyspnea and fatigue are common physiological complaints during the third trimester of pregnancy due to hormonal, cardiovascular, and respiratory adaptations. These symptoms can significantly affect maternal comfort, functional capacity, and quality of life. Non-pharmacological interventions such as pranayama have been suggested to improve respiratory efficiency and reduce perceived exertion and fatigue, yet scientific evidence in pregnant populations remains limited. The aim of the study is to evaluate the effect of pranayama on dyspnea and fatigue in women during the third trimester of pregnancy. Methodology: An Experimental study design was conducted on 30 pregnant women in their third trimester who met the inclusion criteria. Baseline assessment of dyspnea and fatigue was performed using the Modified Borg Dyspnea Scale and Multidimensional Assessment of Fatigue (MAF) Scale, respectively. Participants underwent a structured pranayama program for 6 weeks. Data were analyzed using appropriate statistical tests to compare pre- and post-intervention scores. Results: The results demonstrated a statistically significant reduction in dyspnea scores measured by Modified Borg Dyspnea Scale and fatigue levels measured by the Multidimensional Assessment of Fatigue scale following 6 weeks of pranayama intervention. This indicates an improvement in respiratory comfort and a reduction in overall fatigue among third-trimester pregnant women. Conclusion: The study concludes that pranayama is an effective and safe intervention for reducing dyspnea and fatigue in women during the third trimester of pregnancy. Incorporation of pranayama into routine antenatal physiotherapy programs may enhance maternal well-being and functional tolerance.
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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) | 0.000 | 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".