10. The Association of Intravenous Nitrates Dosing Regimens on Blood Pressure Reduction and ICU Admission Rates among Acute Hypertensive Heart Failure Patients in Emergency Settings: A Systematic Review, Meta Analysis, and Meta-Regression
Bibliographic record
Abstract
Background: In acute hypertensive heart failure (AHHF), optimizing preload and afterload is vital. Higher doses of intermittent intravenous bolus (IVB) nitrates have shown promise in reducing cardiac afterload. Objective: We evaluate impact of varying IV nitrate dosing regimens on MAP reduction and ICU admission rates in emergency AHHF. Method: We followed PRISMA 2020 guidelines, searching 8 databases. We included experimental or observational studies from inception to December 8, 2023, focusing on intravenous nitrates in emergency AHHF patients, in which studies documenting MAP reduction and ICU admission rates. Random effects meta-analyses and meta-regression for age, MAP, dosing regimens were employed. Studies qualities were evaluated using ROBINS-I and Newcastle-Ottawa-Scale. Result: The search yielded 595 articles, including 2 single-arm trials and 5 cohorts. Meta-analysis revealed that a combined IVB and CIV regimen led to a significant MAP reduction (-48.27mmHg), compared to intermittent IVB alone (-23.113mmHg). MAP difference favored the combined regimen, with a significant value of -25.16mmHg(95%CI, -35.86 to -14.45, p=0.00001). Meta-analysis revealed a 39.6% ICU admission rate for combined IVB and CIV, compared to 11.8% for intermittent IVB, resulting in a risk difference of 37%(95%CI, 29%-45%, p=0.00001). Meta-regression analyses found no significant associations between covariates and ICU admission rates. No publication bias was detected (rank correlation p=0.23, regression p=0.17). Conclusion: Our study revealed lower MAP reduction with combined regimens, and AHHF patients receiving intermittent IVB nitrates alone showed lower ICU admission rates. Meta-regression found no significant association between dose amounts and ICU admissions, indicating comparable impacts for both regimens. Larger-scale, double-arm studies are needed for further clarification.
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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 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.061 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".