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Record W7128126413

Point of Care Ultrasonography in Physiotherapy Research and Practice

2022· dissertation· en· W7128126413 on OpenAlexfundno aff
Karen Strike

Bibliographic record

VenueMacSphere (McMaster University) · 2022
Typedissertation
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsnot available
FundersPfizer CanadaHamilton Health SciencesStrongChildren's Hospital FoundationMcMaster UniversityPfizer
KeywordsCurriculumPoint of care ultrasoundUltrasonographyMEDLINEClinical PracticeModality (human–computer interaction)Health careObjective structured clinical examinationPhysical examination
DOInot available

Abstract

fetched live from OpenAlex

Point of care ultrasonography (POCUS) is a non-ionizing imaging modality that is performed and interpreted by a primary health care professional in combination with a physical examination in a clinical setting. POCUS can provide time sensitive clinical information to assist in diagnosis of pathology and to monitor response to treatment. POCUS is emerging in physiotherapy clinical practice, education, and research. This dissertation explores physiotherapist performed POCUS and consists of two scoping reviews and an inter-professional agreement study. The first scoping review systematically mapped the research literature to describe the breadth and depth of physiotherapists performed POCUS. Two hundred and nine studies were included, and the majority of the included studies were measurement studies that assessed the psychometric properties of POCUS in adult patients, were published in the United States of America, and imaged the abdominal lumbo-pelvic region. POCUS was found to be a recent application of sonography in physiotherapy practice. This review identified a wide variety of practice settings and a diverse number of patient conditions in which physiotherapists are performing POCUS. This breadth and depth of this review highlighted the need for improved reporting of study methodology and key areas of future research in physiotherapist performed POCUS. The second scoping review explored physiotherapy pre- and post-licensure curricula and pedagogical approaches for POCUS. Fifteen studies were identified. These showed that progress in the development of physiotherapy-specific, competency based, standardized education curricula and pedagogical approaches for POCUS has been limited. There was considerable variability both pre- and post licensure and further research is needed to assess the outcomes of different pedagogical approaches on theoretical knowledge and practical scanning competence. There is a need for internationally accepted terminology for physiotherapist performed POCUS and clear guidelines from local regulatory colleges and licensing bodies. The third study was an inter-professional agreement pilot study between a physiotherapist and a sonographer for the assessment of acute hemarthrosis in 13 patients with hemophilia using POCUS. In this study, the physiotherapist participated in the McMaster University Mohawk College POCUS Training Program for Acute Hemarthrosis and Synovitis. The results indicated a high level of agreement between the physiotherapist and the sonographer performed POCUS for the binary decision on the presence or absence of blood within the joint. The physiotherapist-acquired images demonstrated quality comparable to an expert sonographer. This study provides support that following a short formal training program, a trained physiotherapist can become proficient in the acquisition and interpretation of POCUS images for the assessment of hemarthrosis in patients with hemophilia.

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)0.087
metaresearch head score (Gemma)0.286
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.087
Threshold uncertainty score0.458

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0870.286
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0130.016
Science and technology studies0.0030.010
Scholarly communication0.0150.012
Open science0.0030.009
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0110.003

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 head0.039
GPT teacher head0.373
Teacher spread0.334 · 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 designNot applicable
Domainnot available
GenreMethods

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
Published2022
Admission routes1
Has abstractyes

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