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Record W4283808224 · doi:10.9778/cmajo.20210301

Visits to the emergency department by community-dwelling people with dementia during the first 2 waves of the COVID-19 pandemic in Ontario: a repeated cross-sectional analysis

2022· article· en· W4283808224 on OpenAlexafffundvenueabout
Laura C. Maclagan, Xuesong Wang, Abby Emdin, Aaron Jones, R. Liisa Jaakkimainen, Michael J. Schull, Nadia Sourial, Isabelle Vedel, Richard H. Swartz, Susan E. Bronskill

Bibliographic record

VenueCMAJ Open · 2022
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsMcMaster UniversityMcGill UniversityUniversité de MontréalMcGill University Health CentreSunnybrook Health Science Centre
FundersCanadian Institutes of Health Research
KeywordsPandemicEmergency departmentCoronavirus disease 2019 (COVID-19)DementiaCross-sectional study2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)MedicineGerontologyVirologyPsychiatryInfectious disease (medical specialty)PathologyDisease

Abstract

fetched live from OpenAlex

<h3>Background:</h3> Community-dwelling people with dementia have been affected by COVID-19 pandemic health risks and control measures that resulted in worsened access to health care and service cancellation. One critical access point in health systems is the emergency department. We aimed to determine the change in weekly rates of visits to the emergency department of community-dwelling people with dementia in Ontario during the first 2 waves of the COVID-19 pandemic compared with historical patterns. <h3>Methods:</h3> We conducted a population-based repeated cross-sectional study and used health administrative databases to compare rates of visits to the emergency department among community-dwelling people with dementia who were aged 40 years and older in Ontario during the first 2 waves of the COVID-19 pandemic (March 2020–February 2021) with the rates of a historical period (March 2019–February 2020). Weekly rates of visits to the emergency department were evaluated overall, by urgency and by chapter from the <i>International Statistical Classification of Diseases and Related Health Problems, 10th Revision</i>. We used Poisson models to compare pandemic and historical rates at the week of the lowest rate during the pandemic period and the latest week. <h3>Results:</h3> We observed large immediate declines in rates of visits to the emergency department during the COVID-19 pandemic (rate ratio [RR] 0.50, 95% confidence interval [CI] 0.47–0.53), which remained below historical levels by the end of the second wave (RR 0.88, 95% CI 0.83–0.92). Rates of both nonurgent (RR 0.33, 95% CI 0.28–0.39) and urgent (RR 0.51, 95% CI 0.48–0.55) visits to the emergency department also declined and remained low (RR 0.68, 95% CI 0.59–0.79, RR 0.91, 95% CI 0.86–0.96), respectively. Visits for injuries, and circulatory, respiratory and musculoskeletal diseases declined and remained below historical levels. <h3>Interpretation:</h3> Prolonged reductions in visits to the emergency department among people with dementia during the first 2 pandemic waves raise concerns about patients who delay seeking acute care services. Understanding the long-term effects of these reductions requires further research.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.070
GPT teacher head0.379
Teacher spread0.309 · 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.

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

Citations16
Published2022
Admission routes4
Has abstractyes

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