IMPACT OF CHRONIC KIDNEY DISEASE ON CARDIOVASCULAR RISK IN MIDDLE-AGED ADULTS: A SYSTEMATIC REVIEW
Bibliographic record
Abstract
Background: Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in patients with chronic kidney disease (CKD), yet the specific risk burden among middle-aged adults remains underexplored. While previous studies have established a general link between CKD and cardiovascular complications, limited data focus on early-stage renal impairment in the 35–65 age group. This review addresses a critical gap in understanding the cardiovascular implications of CKD in this population. Objective: This systematic review aims to evaluate the association between chronic kidney disease and cardiovascular risk in middle-aged adults, with a focus on outcomes such as hypertension, left ventricular hypertrophy, and ischemic events. Methods: A systematic review was conducted following PRISMA guidelines. Four databases—PubMed, Scopus, Web of Science, and Cochrane Library—were searched for studies published in the last five years. Inclusion criteria comprised observational studies, cohort studies, and review articles involving adults aged 35–65 years with diagnosed CKD. Data extraction was performed using standardized forms, and study quality was assessed using the Newcastle-Ottawa Scale. Results: Eight studies met the inclusion criteria. Findings consistently demonstrated that CKD in middle-aged adults significantly increases the risk of cardiovascular events. One population-based cohort study reported adjusted hazard ratios of 2.26 for ischemic heart disease and 8.57 for heart failure in CKD patients compared to controls. Other studies emphasized mechanisms such as vascular calcification, oxidative stress, and systemic inflammation as contributors to cardiovascular pathology in CKD. Conclusion: CKD is an independent and substantial risk factor for cardiovascular complications in middle-aged adults. These findings highlight the need for early cardiovascular risk assessment and intervention in this population. While evidence is robust, further prospective studies are needed to confirm causality and refine management strategies.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".