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Record W3203622234 · doi:10.3390/jcm10194371

Perceived Challenges to Routine Uptake of the Ankle Brachial Index within Primary Care Practice

2021· article· en· W3203622234 on OpenAlexaffabout
Lily Y. C. Chiu, Muzammil H. Syed, Abdelrahman Zamzam, Ori D. Rotstein, Rawand Abdin, Nadine Laraya, Mohammad Qadura

Bibliographic record

VenueJournal of Clinical Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicPeripheral Artery Disease Management
Canadian institutionsSt Joseph's Health CentreMcMaster UniversityUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicinePrimary careContext (archaeology)Clinical PracticeAnkleIndex (typography)General practiceTest (biology)Health careFamily medicineEmergency medicinePhysical therapySurgery

Abstract

fetched live from OpenAlex

(1) Introduction: The ankle-brachial index (ABI) is the most widely used method of diagnosing peripheral arterial disease (PAD). However, the uptake of ABIs has been reported to be low in primary care settings across different various healthcare settings; however, this is yet to be investigated within the Canadian context. (2) Objective: Therefore, we sought to assess the rates of ABI usage as well as perceived barriers among primary care practitioners (PCPs) in Toronto, Canada. (3) Methods: A modified questionnaire was electronically sent to 257 PCPs in the Greater Toronto Area (GTA). Questions pertained to frequency, feasibility, utility, and barriers associated with ABI usage in clinical practice. Responses were collected and tallied. (4) Results: A total of 52 PCPs completed the questionnaire. 79% of PCPs did not routinely perform ABIs within their clinical practice, and 56% deemed ABI usage as unfeasible. Constraints in time and staff personnel, as well as complexity of ABI result interpretation, were cited as the major perceived barriers to ABI usage. The overwhelming majority of PCPs viewed alternative forms of diagnosis, such as a blood test for PAD, as being preferable to ABI, as such an approach would enhance diagnostic simplicity and efficiency. (5) Conclusion: ABI usage rates are poor within primary care practices in Toronto, Canada. Alternative approaches for diagnosing PAD may result in greater adoption rates among PCPs and therefore improve the identification of patients with PAD.

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)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.734
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.396
Teacher spread0.328 · 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

Citations15
Published2021
Admission routes2
Has abstractyes

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