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Record W3197314078 · doi:10.1093/ndt/gfab252

A snapshot of European registries on chronic kidney disease patients not on kidney replacement therapy

2021· editorial· en· W3197314078 on OpenAlexfundno aff
Kitty J. Jager, Anders Åsberg, Frédéric Collart, Cécile Couchoud, Marie Evans, Patrik Finne, Ileana Peride, Ivan Rychlík, Ziad A. Massy

Bibliographic record

VenueNephrology Dialysis Transplantation · 2021
Typeeditorial
Languageen
FieldMedicine
TopicChronic Kidney Disease and Diabetes
Canadian institutionsnot available
FundersEmissions Reduction Alberta
KeywordsMedicineRenal replacement therapyKidney diseaseSnapshot (computer storage)NephrologyInternal medicineIntensive care medicine

Abstract

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Traditionally, renal registries collect and report population-based epidemiological data on patients with kidney failure who are treated by kidney replacement therapy (KRT), i.e. dialysis or transplantation. Over the past decade, a number of these registries have started to widen the inclusion of patients to those with kidney failure treated with comprehensive conservative management and in some cases to earlier stages of chronic kidney disease (CKD), leading to, for example, CKD Stages 4–5 registries. As a result, they are increasing their value by not only providing numbers on those receiving or refraining from extremely expensive therapies, but also to stages of CKD in which kidney failure may still be prevented. The European Renal Association (ERA) Registry currently collects data on patients treated by KRT and uses them for comparison and collaborative research. In this article we report the current status of CKD registries in Europe in relation to their data collection on patients not on KRT so that in the future we may investigate to what extent their data may be used for similar purposes, such as collaborative research on CKD trajectories and patient outcomes. Information was collected from six existing CKD registries and one in preparation. Most had been started by the boards of the national KRT registry with which they formed one registry, but in Romania the CKD registry was separate from that on KRT (Table 1). The Czech registry was fully funded by non-governmental sources, whereas five others—those in French-speaking Belgium, France, Norway, Romania and Sweden—managed to secure at least partial funding from their ministries of health or other healthcare system authorities, mostly for the set-up or maintenance of their web-based data collection platforms. In the majority of cases, data collection was voluntary. CKD registry characteristics, as of March 2021 French KRT Registry (REIN; data collection system); and hospitals (labour force for data entry) Romanian Association of Nephrology, Dialysis and Vascular Access and Ministry of Health (set-up and maintenance of data collection system) and hospitals (labour force for data entry) French KRT Registry (REIN; data collection system); and hospitals (labour force for data entry) Romanian Association of Nephrology, Dialysis and Vascular Access and Ministry of Health (set-up and maintenance of data collection system) and hospitals (labour force for data entry) QI benchmarks: blood pressure (percentage <140/90 mm/Hg), phosphate (percentage <1.6 mmol/L), haemoglobin 10–12 g/dL if on erythropoiesis-stimulating agent, percentage diagnosed with PRD, percentage on angiotensin-converting enzyme inhibitor/angiotensin II recpetor blocker if diabetic kidney disease. eGFR determined by the Chronic Kidney Diease Epidemiology Collaboration equation available for further distribution of CKD stages. CKD registry characteristics, as of March 2021 French KRT Registry (REIN; data collection system); and hospitals (labour force for data entry) Romanian Association of Nephrology, Dialysis and Vascular Access and Ministry of Health (set-up and maintenance of data collection system) and hospitals (labour force for data entry) French KRT Registry (REIN; data collection system); and hospitals (labour force for data entry) Romanian Association of Nephrology, Dialysis and Vascular Access and Ministry of Health (set-up and maintenance of data collection system) and hospitals (labour force for data entry) QI benchmarks: blood pressure (percentage <140/90 mm/Hg), phosphate (percentage <1.6 mmol/L), haemoglobin 10–12 g/dL if on erythropoiesis-stimulating agent, percentage diagnosed with PRD, percentage on angiotensin-converting enzyme inhibitor/angiotensin II recpetor blocker if diabetic kidney disease. eGFR determined by the Chronic Kidney Diease Epidemiology Collaboration equation available for further distribution of CKD stages. While most registries aimed to conduct epidemiological and clinical research now or in the future, health economics research was also among their objectives. Four registries—those from French-speaking Belgium, Czech Republic, Norway and Sweden—specifically aimed for quality improvement making use of benchmarking. Patient inclusion was mostly restricted to CKD Stages 4 and 5 patients from nephrology departments. In Norway, however, the inclusion was limited to CKD Stage 5 patients, whereas in French-speaking Belgium and Romania the registry was set up to include all stages of CKD. With an estimated 75%, the coverage of the CKD patients treated by nephrologists was highest in Sweden, followed by Norway, which also included more than half of the patients. Undoubtedly the difficulty in reaching full coverage is caused by the relatively high number of patients suffering from this condition and by the fact that a substantial number of them may be followed by non-nephrologists or in whom the condition may go unrecognized. This may result in a risk of selection bias, e.g. in epidemiological research. All registries collected demographic data, primary renal disease (PRD), comorbidities and height and weight at baseline, but in France and Norway this was extended to information on care plans (Table 2). Most collected medications, often accompanied by their Anatomical Therapeutic Chemical codes. Additionally, all registries gathered baseline and follow-up data on estimated glomerular filtration rate (eGFR). In contrast, only three registries collected data on urinary albumin:creatinine ratio. All countries with functioning registries collected at least some laboratory test results (Table 3), frequently by linkage to national or regional laboratory databases. Data collection besides laboratory test results Collection of medications data through Anatomical Therapeutic Chemical or similar codes. For bundle payment.+, positive; −, negative; TBD, to be determizned. Data collection besides laboratory test results Collection of medications data through Anatomical Therapeutic Chemical or similar codes. For bundle payment.+, positive; −, negative; TBD, to be determizned. Data collection with respect to laboratory test results Mandatory. For bundle payment.+, positive; −, negative; ACR, albumin:creatinine ratio; CRP, C-reactive protein; HbA1c, haemoglobin A1c; PTH, parathyroid hormone; TBD, to be determined; TSAT, transferrin saturation. Data collection with respect to laboratory test results Mandatory. For bundle payment.+, positive; −, negative; ACR, albumin:creatinine ratio; CRP, C-reactive protein; HbA1c, haemoglobin A1c; PTH, parathyroid hormone; TBD, to be determined; TSAT, transferrin saturation. The outcomes studied included CKD progression, dialysis and transplantation (including pre-emptive transplantation), date and cause of death, sometimes supplemented with data on (pre-emptive) transplant waitlisting, hospitalization and complications. The Swedish registry also collected patient-reported outcomes in the form of RAND-36 data. Given the importance of obtaining knowledge on patients with advanced CKD, it is not unexpected but still disappointing that the results of this inventory show that in Europe only six countries or large regions have engaged in routine data collection on patients with CKD Stages 4–5 who are under the care of nephrologists and Finland is making preparations to do so. Most are collecting data on a growing number of patients while facing challenging issues in registry management, such as the efforts needed for data collection. As a next step, we will explore whether the data quality and potential differences in methods and definitions used by the countries will allow collaboration in a European CKD registry under the umbrella of the ERA Registry with the purpose of joint scientific analyses to advance our knowledge of treatments and outcomes in advanced CKD. The ERA Registry is funded by the ERA. This article was written by K.J.J., A.Å., F.C., C.C., M.E., P.F., I.P., I.R. and Z.A.M. on behalf of the ERA Registry, which is an official body of the ERA. The results presented in this article have not been published previously in whole or part. K.J.J. reports grants from the ERA. F.C. reports lecture fees from Baxter, Fresenius Medical Care and Vifor.

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)0.025
metaresearch head score (Gemma)0.057
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.025
Threshold uncertainty score0.134

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.057
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.008
Science and technology studies0.0010.001
Scholarly communication0.0050.006
Open science0.0020.002
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0040.002

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 head0.011
GPT teacher head0.258
Teacher spread0.247 · 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 designNot applicable
Domainnot available
GenreEditorial

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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Citations13
Published2021
Admission routes1
Has abstractyes

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