78. Chronicles of Risk: Unveiling the Significance Cardiovascular, Renal, and Metabolic Diseases - A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Introduction: Individuals with a reduction of over 10% in nocturnal blood pressure (BP) are classified as “dippers”, while those with a lower decrease are ”non-dippers”. Numerous studies suggest a connection between a non-dipper BP profile and an increased risk of target-organ damage. Objectives: The purpose of this study was to evaluate the association of non-dipping hypertension with the risk of cardiovascular, renal, and metabolic diseases. Methods: The outcome of interest included laboratory parameters such as total triglycerides (TG), low-density lipoprotein (LDL), serum creatinine, glomerular filtration rate (GFR), and fasting plasma glucose (FPG) levels, along with occurrences of cardiovascular disease (CVD) and type 2 diabetes mellitus (DMT2). Quality appraisal was done using Newcastle-Ottawa scale (NOS), while meta-analysis was done using RevMan 5.4. Results: A thorough search of five databases identified 20 articles, with quality assessment indicating 15 low-risk and five intermediate-risk studies. Laboratory analysis revealed that non-dipping hypertension is linked to increased total TG (2.52 mg/dl) and LDL (3.96 mg/dl), decreased GFR (3.54 ml/min), and elevated FPG (0.62 mg/dl) compared to dipping hypertension. No significant difference in serum creatinine was observed. Disease event analysis based on available studies indicated higher DMT2 occurrences in non-dipping hypertension, while CVD events were lower compared to dipping hypertension, noting high heterogeneity. Conclusion: Non-dipping hypertension is associated with more adverse values of laboratory measures, thereby elevating the risk of cardiovascular, renal, and metabolic diseases. Further research is needed to thoroughly investigate the specific interrelationship between non-dipping hypertension and those diseases.
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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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.012 |
| Bibliometrics | 0.000 | 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".