MétaCan
Menu
← Back to cohort
Record W4226301126 · doi:10.1177/20543581221081207

A Unique Multi- and Interdisciplinary Cardiology-Renal-Endocrine Clinic: A Description and Assessment of Outcomes

2022· article· en· W4226301126 on OpenAlexaffabout
Lisa Dubrofsky, Jason F. Lee, Parisa Hajimirzarahimshirazi, Hongyan Liu, Alanna Weisman, Patrick R. Lawler, Michael E. Farkouh, Jacob A. Udell, David Z.I. Cherney

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2022
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity Health NetworkUniversity of TorontoToronto General HospitalWomen's College HospitalInstitute for Clinical Evaluative SciencesTed Rogers Centre for Heart Research
Fundersnot available
KeywordsMedicineIntensive care medicineNephrologyInternal medicineCardiologyMedical physics

Abstract

fetched live from OpenAlex

Background: Patients with diabetes and co-existing chronic kidney disease and/or cardiovascular disease have complex medical needs with multiple indications for different guideline-directed medical therapies and require high health care resource utilization. The Cardiac and Renal Endocrine Clinic (C.a.R.E. Clinic) is a multi- and interdisciplinary clinic offering a unique care model to this population to overcome barriers to optimal care. Objective: To describe the patient characteristics and clinical data of consecutive patients seen in the C.a.R.E. Clinic between 2014 and 2020, with a focus on the feasibility, strengths, and challenges of this outpatient care model. Design: Single-center retrospective cohort study. Setting: The C.a.R.E. Clinic is a multi- and interdisciplinary clinic at Toronto General Hospital in Toronto, Canada. Patients: We reviewed the charts of all 118 patients who had been referred to the C.a.R.E. Clinic with type 2 diabetes mellitus, co-existing renal disease, and/or cardiovascular disease. Measurements: Demographic data, medication data, clinic blood pressure measurements, and laboratory data were assessed at the first and last available clinic visit. Methods: Data were extracted via manual chart review of paper and electronic medical records. Results: First and last attended clinic visit data were available for descriptive analysis in 74 patients. There was a significant improvement in low-density lipoprotein (LDL) cholesterol (1.9 mmol/L vs 1.5 mmol/L, P < .01), hemoglobin A1C (7.5% vs 7.1%, P = .02), and the proportion of patients with blood pressure at target (52.7% vs 36.5%, P = .04), but not body mass index (29.7 kg/m² vs 29.6 kg/m², P = .15) between the last and first available clinic visits. There was higher uptake in evidence-based medication use including statins (93.2% vs 81.1%, P = .01), SGLT-2i (35.1% vs 4.1%, P < .01), and GLP-1 receptor agonists (13.5% vs 4.1%, P = .02), while RAAS inhibitor use was already high at baseline (81.8% vs 78.4%, P = .56). There remains a significant opportunity for therapy with sodium-glucose cotransporter-2 inhibitors and glucagon-like peptide-1 receptor agonists. Limitations: This is a retrospective chart review lacking a control group, therefore clinical improvements cannot be causally attributed to the clinic alone. New evidence and changes to guideline-recommended therapies also contributed to practice changes during this time period. Conclusions: A multi- and interdisciplinary clinic is a feasible and potentially effective way to improve evidence-based and patient-centered care for patients with diabetes, kidney, and cardiovascular disease.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.038
GPT teacher head0.359
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Kidney Health and Disease→Same topicDiabetes Treatment and Management→French-language works237,207→