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Record W4378554182 · doi:10.14740/cr1492

The Daily Activity of Patients With Heart Failure During COVID-19 Pandemic

2023· article· en· W4378554182 on OpenAlexvenueno aff
Christine Sykalo, Ugochukwu Egolum, Hua Ling

Bibliographic record

VenueCardiology Research · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCoronavirus disease 2019 (COVID-19)PandemicCardiologyInternal medicine2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Heart failureEmergency medicineVirologyOutbreakDisease

Abstract

fetched live from OpenAlex

Background: Sedentary behavior is thought to contribute to worsening heart failure syndromes. Here, we examined whether the shelter-in-place order during the coronavirus disease 2019 (COVID-19) pandemic changed daily activity duration, which was monitored by an implantable cardiac device-based multisensor index and alert algorithm called HeartLogic. Methods: We performed a retrospective review of the HeartLogic data from patients with heart failure managed at our clinic and compared the individual daily activity duration 90 days prior to vs. after implementation of the shelter-in-place order. The activity data were prepared by Boston Scientific. Demographic data were extracted from our electronic medical record. Results: In total, 29 patients were included in the analysis. Among them, 14 patients did not have any significant changes in daily activity duration compared to their baseline before the shelter-in-place order (108.62 ± 45 min vs. 107.71 ± 48.6 min, P = 0.723). Among the rest 15 patients with significant changes, seven patients had a significant reduction in activity duration; meanwhile, eight patients had a significant increase in activity duration. Overall, the mean daily activity duration 90 days before and after the shelter-in-place order are 98.21 ± 60.83 min, and 100.03 ± 68.18 min (P = 0.753). Conclusions: No significant changes in terms of activity duration were observed in our patients during the COVID-19 pandemic.

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)0.001
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 score0.023
Threshold uncertainty score0.317

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.068
GPT teacher head0.379
Teacher spread0.311 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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