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Record W1715416462 · doi:10.1111/wrr.12261

Predictive and concurrent validity of the <scp>B</scp>raden scale in long‐term care: A meta‐analysis

2015· review· en· W1715416462 on OpenAlexaff
Machelle Wilchesky, Ovidiu Lungu

Bibliographic record

VenueWound Repair and Regeneration · 2015
Typereview
Languageen
FieldHealth Professions
TopicPressure Ulcer Prevention and Management
Canadian institutionsUniversité de MontréalMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsPredictive validityConcurrent validityMeta-analysisContext (archaeology)MedicineScale (ratio)MEDLINEPredictive valueClinical psychologyPsychologyPsychometricsInternal medicine

Abstract

fetched live from OpenAlex

Pressure ulcer prevention is an important long-term care (LTC) quality indicator. While the Braden Scale is a recommended risk assessment tool, there is a paucity of information specifically pertaining to its validity within the LTC setting. We, therefore, undertook a systematic review and meta-analysis comparing Braden Scale predictive and concurrent validity within this context. We searched the Medline, EMBASE, PsychINFO and PubMed databases from 1985-2014 for studies containing the requisite information to analyze tool validity. Our initial search yielded 3,773 articles. Eleven datasets emanating from nine published studies describing 40,361 residents met all meta-analysis inclusion criteria and were analyzed using random effects models. Pooled sensitivity, specificity, positive predictive value (PPV), and negative predictive values were 86%, 38%, 28%, and 93%, respectively. Specificity was poorer in concurrent samples as compared with predictive samples (38% vs. 72%), while PPV was low in both sample types (25 and 37%). Though random effects model results showed that the Scale had good overall predictive ability [RR, 4.33; 95% CI, 3.28-5.72], none of the concurrent samples were found to have "optimal" sensitivity and specificity. In conclusion, the appropriateness of the Braden Scale in LTC is questionable given its low specificity and PPV, in particular in concurrent validity studies. Future studies should further explore the extent to which the apparent low validity of the Scale in LTC is due to the choice of cutoff point and/or preventive strategies implemented by LTC staff as a matter of course.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.778
Threshold uncertainty score0.659

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.132
GPT teacher head0.426
Teacher spread0.294 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations34
Published2015
Admission routes1
Has abstractyes

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