A systematic review and meta-analysis of early diagnosis and treatment of hypertensive stroke under calcium channel blockers
Bibliographic record
Abstract
BACKGROUND: A systematic evaluation of the therapeutic effects of calcium channel blockers (CCB) on stroke is carried out to provide clinical evidence for their application. METHODS: A search for randomized controlled trials (RCTs) of CCB in the treatment of stroke patients in the electronic databases of PubMed, Embase, Medline, Spring, and Ovid from their establishment to January 31, 2021 was performed, and the collected studies were then screened for the exclusion criteria. The Cochrane Handbook version 5.0.2 system evaluation writing manual was adopted to evaluate the risk of bias for the included literature, and a meta-analysis using Review Manager 5.3 software was applied. RESULTS: A total of 13 RCTs were included, comprising 1,067 subjects. The meta-analysis showed that the recurrence rate of stroke in patients from the observation group reduced sharply after CCB treatment [mean difference (MD) =0.41, 95% confidence interval (CI): 0.24-0.70, Z=3.31, P=0.0009], the Mini-Mental State Examination (MMSE) score improved markedly (MD =2.82, 95% CI: 1.69-3.95, Z=4.89, P<0.00001), and the Montreal Cognitive Assessment (MoCA) score was obviously increased (MD =6.07, 95% CI: 0.34-11.81, Z=2.08, P=0.04). Moreover, the diastolic blood pressure of the observation group decreased steeply after CCB treatment (MD =-1.11, 95% CI: -2.06-0.15, Z=2.27, and P=0.02). However, the effective rate of clinical treatment did not increase hugely (MD =1.70, 95% CI: 0.50-5.83, Z=0.85, P=0.40), and systolic blood pressure did not drop sharply (MD =-1.24, 95% CI: -2.85-0.37, Z=1.51, P=0.13). DISCUSSION: CCB treatment of stroke effectively prevented stroke recurrence, and showed faster recovery of cognitive function, and better lowering of blood pressure, all of which makes CCBs suitable for the treatment of stroke.
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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 | 0.020 | 0.047 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.037 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".