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Record W4412084497 · doi:10.34067/kid.0000000866

Long-Term Outcomes of COVID-19 in Patients Receiving Maintenance Dialysis

2025· article· en· W4412084497 on OpenAlexaffabout
Kevin Yau, Sarah E. Bota, Eric McArthur, Kyla L. Naylor, Hiten Naik, Sara Wing, Peter G. Blake, Michelle Hladunewich, Adeera Levin, Matthew J. Oliver

Bibliographic record

VenueKidney360 · 2025
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreOntario Stroke NetworkUniversity of British ColumbiaWestern UniversityInstitute for Clinical Evaluative SciencesLondon Health Sciences CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineDialysisHazard ratioPopulationCohortCoronavirus disease 2019 (COVID-19)Cohort studyConfoundingProportional hazards modelInternal medicineIntensive care medicineEmergency medicinePediatricsConfidence intervalDiseaseInfectious disease (medical specialty)Environmental health

Abstract

fetched live from OpenAlex

Key Points In maintenance dialysis patients, 90-day coronavirus disease 2019 (COVID-19) survivors did not have a higher long-term risk of death or adverse health outcomes. Prior COVID-19 infection was associated with a lower risk for subsequent COVID-19 infection. Background There is concern regarding the long-term impact of coronavirus disease 2019 (COVID-19) on the maintenance dialysis population. This study describes the long-term morbidity and mortality of COVID-19 among patients receiving maintenance dialysis in comparison with uninfected controls. Methods We conducted a population-based cohort study of patients receiving maintenance dialysis in Ontario, Canada, between March 14, 2020, and December 1, 2021 (pre-Omicron), with follow-up until March 31, 2023. We accounted for confounding using propensity scores to match each patient with COVID-19 to four uninfected controls. The primary outcome was all-cause mortality, whereas secondary outcomes included subsequent COVID-19 infection, COVID-19–associated death, a composite of cardiovascular (CV)-related death or hospitalization, all-cause hospitalization, and admission to long-term care or complex continuing care. Results Our matched cohort included 3340 maintenance dialysis patients: 668 with COVID-19 and 2672 controls. Over a median of 1.8 years of follow-up, the rate of long-term all-cause mortality for 90-day COVID-19 survivors was 11.9 deaths per 100 person-years which did not differ from 13.9 deaths per 100 person-years in those without COVID-19 infection (hazard ratio [HR] 0.86; 95% confidence interval [CI], 0.72 to 1.03). Similarly, no significant difference was observed on a composite outcome of CV death or hospitalization, all-cause hospitalization, long-term care, or complex continuing care placement. Prior COVID-19 infection was associated with a reduced risk of subsequent COVID-19 infection (HR, 0.75; 95% CI, 0.63 to 0.88). Subsequent COVID-19 infection was associated with a higher rate of death (HR, 1.68; 95% CI, 1.42 to 1.98). Conclusions Individuals receiving maintenance dialysis who survived their initial COVID-19 infection did not have an increased long-term risk of death, all-cause hospitalization, or CV disease compared with those without COVID-19. Subsequent COVID-19 infection during follow-up, however, was associated with increased mortality.

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)0.008
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 score0.009
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.041
GPT teacher head0.387
Teacher spread0.346 · 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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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