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Record W4397043082 · doi:10.1681/asn.20233411s1374a

Prevalence and Outcomes of CKD in England (CaReMe CKD UK)

2023· article· en· W4397043082 on OpenAlexaboutno aff
Ruiqi Zhang, Jil Billy Mamza, He Gao, Kiera C. Lochead, Nicola Milne, Bhautesh Jani, James Chess, Smeeta Sinha, Naresh Kanumilli, Patrick B. Mark

Bibliographic record

VenueJournal of the American Society of Nephrology · 2023
Typearticle
Languageen
FieldMedicine
TopicBariatric Surgery and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineKidney diseaseInternal medicine

Abstract

fetched live from OpenAlex

Background: The CaReMe CKD study indicates that one in ten adults in Europe and Canada likely have chronic kidney disease (CKD). In England, 6.5% of the population has been diagnosed with CKD, but rates of possible and undiagnosed cases remain unknown. To address this, we updated the analysis with more comprehensive electronic health records (EHR) to determine the prevalence of diagnosed and potentially undiagnosed CKD and associated clinical adverse outcomes in England. Methods: Patients were identified using linked national EHR (Clinical Practice Research Datalink, Hospital Episode Statistics and Office for National Statistics) by either having a CKD diagnosis or a single pathological value of eGFR <60 ml/min/1.73 m2 or urine albumin-creatinine ratio (UACR) ≥30 mg/g before 1st November 2020. CKD stages were defined in accordance with Kidney Disease: Improving Global Outcomes (KDIGO) criteria. CKD was categorized into three groups based on laboratory values or diagnosis codes (Figure). One year cardiovascular and renal event rates were determined using the first recorded in-hospital diagnosis at the main position. Results: In a background population of 10,363,493, the prevalence of possible CKD was 9.2% (mean age 71, 55% women, 32% diabetes, 46% using renin-angiotensinaldosterone system inhibitors); while one out of three did not have a corresponding CKD-specific diagnostic code, half could not be confirmed with KDIGO criteria. Prevalence of CKD was consistently higher in females across definitions. Among CKD patients confirmed by KDIGO criteria, the majority (64%) were in KDIGO stage 3A, 3% were stages one or two. Adverse events were common and 6.7%-8.7% died annually (Figure). Conclusions: One in ten adults in England is affected by CKD, which leads to significant adverse outcomes. Diagnosis rates underestimates the actual prevalence of CKD. There is significant public health potential to identify and treat those who currently remain undiagnosed. Funding: Commercial Support - AstraZenecaPrevalence, outcomes and definitions.

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)0.004
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 score0.160
Threshold uncertainty score0.318

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.290
Teacher spread0.269 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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