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Record W3033303100 · doi:10.1093/ndt/gfaa142.p0687

P0687DO ALL PATIENTS BENEFIT FROM MULTIDISCIPLINARY CHRONIC KIDNEY DISEASE CLINICS?

2020· article· en· W3033303100 on OpenAlexaffabout
Bhanu Prasad, Maryam Jafari, Lexis Gordon, Navdeep Tangri, Joanne Kappel

Bibliographic record

VenueNephrology Dialysis Transplantation · 2020
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsSt. Paul's HospitalSeven Oaks General HospitalRegina General HospitalUniversity of SaskatchewanSaskatchewan HealthSaskatchewan Health Authority
Fundersnot available
KeywordsMedicineKidney diseasePsychological interventionMultidisciplinary approachDialysisNephrologySpecialtyIntensive care medicinePolypharmacyHealth careInternal medicineFamily medicineEmergency medicineNursing

Abstract

fetched live from OpenAlex

Abstract Background and Aims: Multidisciplinary clinics (MDC’s) were established in Canada to offer a variety of support systems (diabetes care, social support, easy access to pharmacists, dietitians, specialty trained nurses), to monitor and delay progression through timed lab investigations and visits in conjunction with the Nephrologist. The reasons for better outcomes have been identified as better education, focus on self-care, dietary interventions, timely transplant referrals, modality education, lower hospitalizations and mortality. Treating all patients with chronic kidney disease (CKD) as part of a multidisciplinary care team runs the risk of adding unwarranted labs, interventions, polypharmacy and costs. Kidney Failure Risk Equation (KFRE) uses routine laboratory and clinical data, to stratify patients into three risk categories (low, medium, and high risk) of progression. KFRE has been shown to accurately estimate progression to kidney failure in adults with CKD. The objectives of the study were to i) validate the KFRE in our CKD patients, ii) evaluate health care utilization of patients based on the risk of progression in our province, Saskatchewan. iii) identify the subgroup of patients that benefit most from follow up in MDC. Methods: We conducted a retrospective study on 1007 patients with CKD stages G3 and G4 in two CKD multidisciplinary clinics in the province of Saskatchewan, Canada (January 2004-December 2012). The predicted risk of kidney failure (low, medium high) for each patient was calculated using the 8-variable KFRE. Patients were followed for five years to validate the KFRE; data on initiation of dialysis or death was collected. Cost of delivery of care per patient per year in the CKD clinic was determined. Health care utilization was evaluated by measuring the number/cost of hospital admissions, cardiovascular and thoracic (CVT) surgery, non-nephrology specialist appointments, and medications. Results: There were more patients in G 3 (n= 533) than in G 4 (n=474). 313 (59%), 150 (28%), and 70 (13%) were in low, medium and high-risk categories for G 3 CKD. 275 (58%), 86 (18%), and 113 (24%) were in similar categories for G 4. The mean age (SD) was 71 (12.8) years. The number of patients > 65 years of age was 75%. 57% were men, mean GFR (mls/min/1.73m2) for G3 was 40 (7.8) and 23 (4) for G4. Of the G3 patients, 4% of low risk, 11% of the medium risk and 26% of the high risk progressed to dialysis by 5 years. In G 4 patients, 7% of low risk, 17% of medium risk and 48% of high risk progressed to dialysis over 2 years. These results validate the KFRE in our population. The cost of care per patient in MDC was $ 3800 (CAD) per year. There was a difference in the cost of medications, number and cost of (inpatient hospitalizations, cardiovascular surgeries, non-Nephrology specialist visits, and day surgeries) between low risk patients vs high risk patients in G4 patients. Conclusion: We performed a cost-effectiveness analysis of our MDC’s and show that very few patients at low-risk of progression advance to ESRD. They are also unlikely to benefit from intensive care management and better managed in primary care with advice from tertiary centres. Individual programs have significant opportunity to improve health care delivery by identifying the sub- groups that benefit the most from MDC based on the risk of progression to allow optimal utilization of resources. At $ 3800 (CAD) per patient, we suggest that MDC’s are best utilized by patients with medium and high risk of progression. Further, we show that patients that the low-risk patients were older, had fewer inpatient visits, had lesser drug costs, underwent fewer cardiovascular surgeries, had fewer day surgery visits, and fewer non-nephrology specialist visits. This is the first study to our knowledge that focuses on health care utilization based on the risk of disease progression rather than the stage of CKD.

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)0.000
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 score0.138
Threshold uncertainty score0.275

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.057
GPT teacher head0.353
Teacher spread0.296 · 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".

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Citations0
Published2020
Admission routes2
Has abstractyes

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