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Record W2805649467 · doi:10.1177/2054358118780372

Hospitalizations in Dialysis Patients in Canada: A National Cohort Study

2018· article· en· W2805649467 on OpenAlexaffabout
Amber O. Molnar, Louise Moist, Scott Klarenbach, Jean‐Philippe Lafrance, Soojin Kim, Karthik Tennankore, Jeffrey Perl, Joanne Kappel, Michael Terner, Jagbir Gill, Manish M. Sood

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2018
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity of OttawaUniversity of British ColumbiaUniversity of AlbertaCanadian Institute for Health InformationDalhousie UniversityWestern UniversityUniversity of TorontoUniversity Health NetworkUniversity of SaskatchewanUniversité de MontréalSt. Michael's HospitalMcMaster UniversityImpact
Fundersnot available
KeywordsMedicineCohortDialysisIntensive care medicineNephrologyCohort studyPeritoneal dialysisInternal medicineEmergency medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Hospitalizations of chronic dialysis patients have not been previously studied at a national level in Canada. Understanding the scope and variables associated with hospitalizations will inform measures for improvement. OBJECTIVE: To describe the risk of all-cause and infection-related hospitalizations in patients on dialysis. DESIGN: Retrospective cohort study using health care administrative databases. SETTING: Provinces and territories across Canada (excluding Manitoba and Quebec). PATIENTS: Incident chronic dialysis patients with a dialysis start date between January 1, 2005, and March 31, 2014. Patients with a prior history of kidney transplantation were excluded. MEASUREMENTS: Patient characteristics were recorded at baseline. Dialysis modality was treated as a time-varying covariate. The primary outcomes of interest were all-cause and dialysis-specific infection-related hospitalizations. METHODS: Crude rates for all-cause hospitalization and infection-related hospitalization were determined per patient year (PPY) at 7 and 30 days, and at 3, 6, and 12 months postdialysis initiation. A stratified, gamma-distributed frailty model was used to assess repeat hospital admissions and to determine the inter-recurrence dependence of hospitalizations within individuals, as well as the hazard ratio (HR) attributed to each covariate of interest. RESULTS: A total of 38 369 incident chronic dialysis patients were included: 38 088 adults and 281 pediatric patients (age less than 18 years). There were 112 374 hospitalizations, of which 11.5% were infection-related hospitalizations. The all-cause hospitalization rate was similar for all adult age groups (age 65 years and older: 1.40, 1.35, and 1.18 admissions PPY at 7 days, 30 days, and 6 months, respectively). The all-cause hospitalization rate was higher for pediatric patients (1.67, 2.48, and 2.47 admissions PPY at 7 days, 30 days, and 6 months, respectively; adjusted HR: 2.73, 95% confidence interval [CI]: 2.37-3.15, referent age group: 45-64 years). Within the first 7 days after dialysis initiation, patients on peritoneal dialysis had a higher risk of all-cause hospitalization (HR: 1.27, 95% CI: 1.07-1.50) and infection-related hospitalization (HR: 2.05, 95% CI: 1.19-3.55) compared with patients on hemodialysis. Beyond 7 days, the risk did not differ significantly by dialysis modality. Female sex and Indigenous race were significant risk factors for all-cause hospitalization. LIMITATIONS: The cohort had too few home hemodialysis patients to examine this subgroup. The outcome of infection-related hospitalization was determined using diagnostic codes. Dialysis patients from Manitoba and Quebec were not included. CONCLUSIONS: In Canada, the rates of hospitalization were not influenced by dialysis modality beyond the initial 7-day period following dialysis initiation; however, the rate of hospitalization in pediatric patients was higher than in adults at every time frame examined.

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)0.007
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 score0.129
Threshold uncertainty score0.880

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.009
GPT teacher head0.256
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 teacher head, 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

Citations47
Published2018
Admission routes2
Has abstractyes

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