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Record W2153742438 · doi:10.1186/s40697-014-0026-5

Canadian Organ Replacement Register (CORR): Reflecting the Past and Embracing the Future

2014· article· en· W2153742438 on OpenAlexafffundabout
Louise Moist, Stanley Fenton, Joseph S. Kim, John S. Gill, Frank Ivis, Eric de, Juliana Wu, Ahmed A. Al‐Jaishi, Manish M. Sood, Scott Klarenbach, Joanne Kappel

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2014
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsUniversity of SaskatchewanUniversity of AlbertaOttawa HospitalUniversity of British ColumbiaUniversity of TorontoUniversity of CalgaryVictoria HospitalLawson Health Research InstituteCanadian Institute for Health InformationLondon Health Sciences CentreWestern University
FundersHealth CanadaKidney Foundation of CanadaCanadian Blood Services
KeywordsMedicineDialysisRenal replacement therapyPeritoneal dialysisTransplantationKidney transplantationOrgan transplantationPopulationKidney diseaseIntensive care medicineInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

INTRODUCTION: The Canadian Organ Replacement Register (CORR) is the only Canadian information system on kidney and extra-kidney organ failure and transplantation in Canada. CORR's mandate is to record and analyze the level of activity and outcomes of vital organ transplantation and treatment of end stage kidney disease using dialysis, either hemodialysis or peritoneal dialysis, activities across Canada. The Canadian Organ Replacement Register was officially launched in 1987, and it included transplantation of extra-renal vital organs (liver, heart, lung, pancreas, bowel), in addition to renal transplantation and replacement therapy, with new financial support from the provinces. OBJECTIVE: This manuscript describes the process of data acquisition and reporting, focusing on the patients with end stage kidney disease on dialysis, with data reported from the 2014 CORR Annual Data Report and the Center-Specific Reports on Clinical Measures. METHODS: CORR is currently housed in the Canadian Institute for Health Information and collects data from hospital dialysis programs, regional transplant programs, organ procurement organizations and kidney dialysis services offered at independent health facilities. Data on patients is collected by completion of survey forms for each patient at the start of dialysis or receiving a transplant, using the Initial Registration form, and yearly follow up forms, which collects data on the status of the patient as of October 31(st). RESULTS: The incident rate per million population (RPMP) has remained stable with the exception of the 65+ age group with has experience a modest decrease since 2001. However, there has been an increasing prevalence of ESKD diagnoses, with the highest rate per million population (RPMP) amongst the age group 65+ years. This is likely attributed to gradual improving patient survival. Between 2003 and 2012, nearly 90% of dialysis patients younger than <18 and 26% of patients 75+ years survived for at least five years. CONCLUSION: As the number of people treated for end-stage organ failure grows, so does the importance of understanding their treatment and outcomes. In 2014, CORR continues to evolve and support the important information need to advance ESRD research and clinical practice.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.714
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

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

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 head0.018
GPT teacher head0.298
Teacher spread0.279 · 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 teacher head, not a consensus.

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

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

Citations41
Published2014
Admission routes3
Has abstractyes

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