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Record W2396727063 · doi:10.3138/ptc.2010-30-cc

Clinician's Commentary on LaPier

2012· article· en· W2396727063 on OpenAlexaffvenueabout
Mireille Landry

Bibliographic record

VenuePhysiotherapy Canada · 2012
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsWomen's College Hospital
Fundersnot available
KeywordsComputer scienceMedicinePhysical medicine and rehabilitationPhysical therapy

Abstract

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Meta-analyses and systemic reviews have shown exercise-based cardiac rehabilitation (CR) to be effective in reducing total and cardiovascular mortality and hospital admissions. Although more recent trials were included in the latest (2011) Cochrane Review, however, such conclusions are still based on a predominantly male, middle-aged, and low-risk population.2 As a result, several questions remain regarding the effectiveness of CR for older adults. The effect of CR on outcomes such as physical function, functional impairment, and disability needs to be clarified. Patients with coronary heart disease (CHD) have generally higher rates of disability than those without CHD,3 but the burden of disability is heavier for older CHD patients, particularly women, as disability rates increase with advanced age.4 Longer hospitalizations after a cardiac event in older persons relative to their younger counterparts can result in greater subsequent disability and mobility limitations.3–5 Therefore, preventing or limiting the rate of disability progression is a major goal of CR for older adults.6–8 Early detection of physical limitations and appropriate physical-activity intervention are important in preventing or delaying physical disability for many patients. Assessment of physical function plays a central role in the early recognition of physical limitations and in disability prevention. Traditionally, in CR, exercise tolerance has been used as a marker of overall physical function. However, exercise tolerance has been shown to be a poor predictor of a person's ability to perform activities of daily living,9 as cardiovascular fitness is only one of several parameters of physical function. Other performance-based measures, such as timed walk tests, sit-to-stand tests, walking speed, and stair-climbing ability, are frequently used clinically.10 The Late-Life Function and Disability Instrument (LLFDI) was developed to measure function and level of participation in community-dwelling older adults and to address the limitations of existing outcome measures. Many self-report tools that measure function and disability are not sensitive to small changes or have a ceiling effect in populations with diverse abilities, including patients with CHD.11 More sensitive outcome measures are needed for patients who are at a higher functional status, and the LLFDI appears to address this limitation of existing outcomes. LaPier successfully demonstrates that the LLFDI is valid in older adults (>60 y) with CHD and that it can be completed independently by self-report instead of having to be administered by clinicians, which improves its clinical utility. However, she acknowledges the shortcoming of the study population—mostly male and Caucasian—recruited as a small convenience sample. The sample is representative of the CHD population currently attending CR, but not of the population living with CHD. Guidelines are being implemented to help with automatic referral in Canada, with the goal of reducing CR referral and attendance barriers for special populations such as women, very old adults, and those with varied ethnic and racial backgrounds. The validity of the LLFDI in these diverse populations should therefore be examined. Although valid, the LLFDI—like other self-report instruments on physical function—may provide inaccurate information when discrepancies exist between patients' perceptions of their physical function and their actual ability to perform certain tasks. When used alone, self-report measures may paint a biased picture of the patient's physical function; in addition, they provide little information about the type of impairment affecting the individual, and in general are not sensitive to subtle but clinically relevant changes. These two limitations may be particularly problematic in a CR setting if the objective is to design and evaluate an intervention aimed at improving specific aspects of physical function. The greatest barrier to using the LLFDI in a clinical setting is the response burden and administration time, which may reduce the measure's use by clinicians. LaPier suggests that the LLFDI could replace a currently used outcome measure for use with all or some CR participants. However, an advantage of generic measures such as the Medical Outcomes Study 36-Item Short Form Health Survey (SF-36), and of timed walk tests such as the 6-Minute Walk Test (6MWT), is that they permit comparisons across disease conditions or diagnoses. Despite the LLFDI's moderate correlation with the 6MWT and other performance-based measures, the rich information outside of the actual scores of these measures (e.g., indicators of prognosis, mobility, and safety) would be difficult to replicate without performance assessment. Among CR patients, gains in directly observed physical function (with performance-based measures) do not always translate into gains in self-reported physical function. LaPier's findings offer additional support for the theory that self-report and performance-based measures of physical function do not measure exactly the same construct and that performance-based measures are more sensitive to change than self-report measures.10 The population of community-dwelling older adults includes a sub-group of high-functioning patients who “can often benefit from physical therapy services, but demonstrating baseline functional limitation and participation restriction, as well as improvement with intervention is often challenging.”1(p.54) However, accessing affordable community-based rehabilitation services can be difficult for older adults on limited income. In my clinical experience, a well-designed aerobic and strengthening programme in the CR setting, by physical therapists in particular, helps with return to function without the need for external referrals to manage specific impairments. Physical therapists are movement and function specialists, and through exercise prescription, education, and counselling can empower and assist older persons with CHD in returning to and maximizing function safely and appropriately.

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)0.014
metaresearch head score (Gemma)0.128
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.045
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.128
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0060.005
Bibliometrics0.0040.004
Science and technology studies0.0040.005
Scholarly communication0.0080.007
Open science0.0110.004
Research integrity0.0450.042
Insufficient payload (model declined to judge)0.0420.025

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 head0.017
GPT teacher head0.365
Teacher spread0.348 · 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
GenreCommentary

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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Citations2
Published2012
Admission routes3
Has abstractyes

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