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Record W2920912058 · doi:10.1111/nep.13574

Effect of centre‐ and patient‐related factors on uptake of haemodiafiltration in Australia and New Zealand: A cohort study using ANZDATA

2019· article· en· W2920912058 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNephrology · 2019
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilMinistry of Health, British ColumbiaKidney Health Australia
KeywordsMedicineConfidence intervalOdds ratioLogistic regressionBody mass indexDialysisCohortInternal medicine

Abstract

fetched live from OpenAlex

ABSTRACT Background The use of haemodiafiltration (HDF) for the management of patients with end‐stage kidney failure is increasing worldwide. Factors associated with HDF use have not been studied and may vary in different countries and jurisdictions. The aim of this study was to document the pattern of increase and variability in uptake of HDF in Australia and New Zealand, and to describe patient‐ and centre‐related factors associated with its use. Methods Using the Australian and New Zealand Dialysis and Transplant Registry, all incident patients commencing haemodialysis (HD) between 2000 and 2014 were included. The primary outcome was HDF commencement over time, which was evaluated using multivariable logistic regression stratified by country. Results Of 27 433 patients starting HD, 3339 (14.4%) of 23 194 patients in Australia and 810 (19.1%) of 4239 in New Zealand received HDF. HDF uptake increased over time in both countries but was more rapid in New Zealand than Australia. In Australia, HDF use was more likely in males (odds ratio (OR) 1.13, 95% confidence interval (CI) = 1.03–1.24, P = 0.009) and less likely with older age (reference <40 years; 40–54 years OR = 0.85; 95% CI = 0.72–0.99; 55–69 years OR = 0.79; 95% CI = 0.67–0.91; >70 years OR = 0.48; 95% CI = 0.41–0.56); higher body mass index (body mass index (BMI) < 18.5 kg/m 2 OR = 0.62; 95% CI = 0.46–0.84; 18.5–29.9 kg/m 2 reference; >30 kg/m 2 OR = 1.46; 95% CI = 1.33–1.61), chronic lung disease (OR = 0.84; 95% CI = 0.76–0.94; P < 0.001), cerebrovascular disease (OR = 0.76; 95% CI = 0.67–0.85; P < 0.001) and peripheral vascular disease (OR = 0.77; 95% CI = 0.70–0.85; P < 0.001). No association was identified with race. In New Zealand, HDF use was more likely in Maori and Pacific Islanders (OR = 1.32; 95% CI = 1.05–1.66) and Asians (OR = 1.75; 95% CI = 1.15–2.68) compared to Caucasians, and less likely in males (OR = 0.76; 95% CI = 0.62–0.94; P = 0.01). No association was identified with BMI or co‐morbidities. In both countries, centres with a higher ratio of HD to peritoneal dialysis (PD) were more likely to prescribe HDF. Larger Australian centres were more likely to prescribe HDF (36–147 new patients/year OR = 26.75, 95% CI = 18.54–38.59; 17–35/year OR = 7.51, 95% CI = 5.35–10.55; 7–16/year OR = 3.00; 95% CI = 2.19–4.13; ≤6/year reference). Conclusion Haemodiafiltration uptake is increasing, variable and associated with both patient and centre characteristics. Centre characteristics not explicitly captured elsewhere explained 36% of variability in HDF uptake in Australia and 48% in New Zealand.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.003
Threshold uncertainty score0.259

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.285
Teacher spread0.267 · 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