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Record W4397000775 · doi:10.1681/asn.20203110s123d

Hospitalization and Day of the Week: Comparing Peritoneal Dialysis, Home Hemodialysis, and In-Center Hemodialysis

2020· article· en· W4397000775 on OpenAlexaffabout
Karthik Tennankore, Annie‐Claire Nadeau‐Fredette, Kara Matheson, Christopher T. Chan, Emilie Trinh, Jeffrey Perl

Bibliographic record

VenueJournal of the American Society of Nephrology · 2020
Typearticle
Languageen
FieldMedicine
TopicHospital Admissions and Outcomes
Canadian institutionsMcGill UniversityDalhousie UniversityToronto General HospitalSt. Michael's HospitalHôpital Maisonneuve-RosemontNova Scotia Health Authority
Fundersnot available
KeywordsHemodialysisHome hemodialysisMedicinePeritoneal dialysisCenter (category theory)DialysisIntensive care medicineEmergency medicineInternal medicine

Abstract

fetched live from OpenAlex

Background: Studies have shown that there are daily variations in mortality for patients receiving in-center hemodialysis (HD) but not home HD, peritoneal dialysis or more frequent in-center HD. Less is known about daily variations in hospitalization according to dialysis modality. Methods: We analyzed all chronic dialysis patients in Canada (excluding Manitoba and Quebec) from 1 Jan 2005 to 31 Dec 2014 using the Canadian Organ Replacement Register (CORR). Dialysis modalities were defined (using CORR) as peritoneal dialysis, conventional HD or frequent HD (nocturnal or short daily) and HD modalities were furthered categorized as home versus in-center. All switches between modalities after dialysis initiation were included provided the duration of the switch was >30 days. The absolute number of hospitalizations for each day of the week was reported for each treatment type and differences in the distribution of hospitalizations were compared using the Chi-Square test. Results: The cohort consisted of 36,334 individuals. Median age was 67 and 61% were of male sex. A total of 81% of patients were receiving hemodialysis at dialysis initiation and the cause of end-stage kidney disease was secondary to diabetes in 37%. Overall, there were 119,466 hospitalizations over the observation period. The cumulative number of hospitalizations was highest for conventional in-center HD (92,707) and lowest for conventional home HD (701). Day of the week admissions for each treatment type are noted in Table 1 (P<0.001). Hospitalizations were least frequent on saturday and sunday for all groups. The proportion of admissions was highest on monday or tuesday for conventional HD (regardless of location) and frequent in-center HD. In contrast, frequent home HD had a higher proportion of admissions on wednesday. Conclusions: There are daily variations in hospitalization comparing dialysis modalities. Future planned analyses will evalute whether there are adjusted differences in day of the week hospitalization across modalities accounting for differences in patient characteristics. - Treatment Group Total Sunday Monday Tuesday Wednesday Thursday Friday Saturday Conventional In-Center HDa 92707 8971 (10) 15496 (17) 16138 (18) 14643 (16) 14108 (15) 13508 (16) 9843 (11) Frequent In-Center HD 1426 137 (10) 262 (18) 228 (16) 211 (15) 219 (15) 201 (14) 168 (12) Conventional Home HD 701 60 (9) 137 (20) 129 (18) 115 (16) 93 (13) 95 (14) 72 (10) Frequent Home HD 1439 149 (10) 213 (15) 231 (16) 273 (19) 230 (16) 191 (13) 152 (11) Peritoneal Dialysis 23193 2562 (11) 3684 (16) 3800 (16) 3727 (16) 3533 (15) 3473 (15) 2414 (10) aHemodialysis Day of the week hospitalization for each dialysis treatment type (N, %)

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 score0.150
Threshold uncertainty score0.298

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.015
GPT teacher head0.257
Teacher spread0.242 · 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".

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Citations0
Published2020
Admission routes2
Has abstractyes

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