A Systematic Literature Review of Coordinated Care in Cardiovascular-Kidney-Metabolic Conditions
Bibliographic record
Abstract
Objective: To assess coordinated cardiovascular-kidney-metabolic (CKM) care programs, including program types, components, and outcomes. Patients and Methods: We searched Embase and Medline for studies from January 1, 2015 through March 9, 2023, and congress abstracts from January 1, 2021 through March 9, 2023. For inclusion, patients were required to have ≥2 CKM conditions and the coordinated care program assessed the effectiveness of either treatment, monitoring, or risk reduction of all 3 conditions. Two reviewers extracted and assessed the data for accuracy. Randomized controlled trials were assessed for potential bias in the design, conduct, and reporting of clinical trials risk of bias using the Cochrane risk of bias tool, version 2. Observational studies were assessed using the Newcastle-Ottawa Scale. Results: A total of 22 international studies met our inclusion criteria; interventions included patient visits to multidisciplinary team (MDT) care clinics (n=9), pharmacist integration (n=5), patient engagement and education (n=6), or MDT/multispecialty team meetings (n=2). The sample size of studies ranged from 14 to 9601. Overall, results showed greater patient satisfaction and fewer health-related problems with coordinated care programs versus usual care, with increased attendance rates and decreased health care costs for virtual consultations, and further reductions for programs integrating telehealth. Conclusion: Coordinated care for patients with CKM conditions may improve clinical outcomes and reduce healthcare costs. Future research is needed to develop programs with standard reporting, to assess overall effectiveness, and to identify best practices for implementing coordinated care programs. Limitations included heterogeneity in the interventions' design, delivery, CKM population, and outcomes assessed. Trial Registration: PROSPERO Identifier: CRD42023409731.
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".