Effects of aerobic, strength, and combined training during pregnancy in the blood pressure: A systematic review and meta-analysis
Bibliographic record
Abstract
Gestational hypertension can lead to fetal complications, and, if untreated, high blood pressure during pregnancy may cause eclampsia and even death in the mother and fetus. Exercise is a strategy for preventing blood pressure disorders. There is little knowledge about the physiological impacts of different physical types of training on blood pressure during pregnancy. For that, this meta-analysis aimed to compare the effects of different physical exercise modalities (i.e., aerobic training—AT, strength training—ST, and combined training—AT + ST) on systolic blood pressure (SBP) and diastolic blood pressure (DBP) of pregnant women. A search was performed on PUBMED, LILACS, CINAHL, Sport discus, EMBASE, SCOPUS, and Cochrane Central Register of Controlled Trials to identify researchers. From 3,450 studies, 20 and 19 were included in the qualitative and quantitative analyses. AT studies presented a medium effect size (ES) on SBP [−0.29 (−2.95 to 2.36) p = 0.83], with substantial heterogeneity (I 2 = 64%), and had a large impact on DBP [−1.34 (−2.98 to 0.30) p = 0.11], with moderate heterogeneity (I 2 = 30%). ST researchers showed a large ES on SBP [−1.09 (−3.66 to 1.49) p = 0.41], with a reduced heterogeneity (I 2 = 0%), and a medium ES on DBP [−0.26 (−2.77 to 2.19) p = 0.83] with moderate heterogeneity (I 2 = 38%). AT + ST studies had a large ES on SBP [−1.69 (−3.88 to 0.49) p = 0.13] and DBP [−01.29 (−2.26 to 0.31) p = 0.01] with considerable (I 2 = 83%) and moderate heterogeneity (I 2 = 47%), respectively. These findings are essential for developing new research protocols to avoid gestational hypertension and preeclampsia. AT + ST had a large impact on the SBP and DBP reduction; however, there is a need for more similar procedures to reduce heterogeneity between studies, promoting consensual results. Systematic Review Registration: [ PROSPERO ], identifier [CRD42021256509].
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.015 | 0.002 |
| 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 | 0.001 |
| 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".