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Record W2111091687

Blood pressure targets in the very old: development of a tool in a geriatric day hospital.

2014· article· en· W2111091687 on OpenAlexaffabout
Barbara Farrell, Anne Monahan, Naomi Dore, Kate Walsh

Bibliographic record

VenuePubMed · 2014
Typearticle
Languageen
FieldHealth Professions
TopicHealth, psychology, and well-being
Canadian institutionsWomen's College HospitalUpper Grand Family Health TeamBruyère
Fundersnot available
KeywordsAuditMedicineBlood pressureConsistency (knowledge bases)Care of the elderlyHealth careProcess (computing)NursingInternal medicineComputer scienceManagement
DOInot available

Abstract

fetched live from OpenAlex

PROBLEM ADDRESSED: Canadian hypertension guidelines do not address blood pressure (BP) targets in the very old (older than 85 years of age), making BP management in this group difficult. OBJECTIVE OF PROGRAM: To develop a BP target tool and implementation process in order to facilitate management of BP in the very old at the Bruyère Continuing Care Geriatric Day Hospital in Ottawa, Ont. PROGRAM DESCRIPTION: A BP target tool and implementation process were developed to target, monitor, and communicate BP goals within the care team, to the patient and family, and to other prescribers. An audit was conducted of the first 10 weeks of the tool's implementation and illustrated good use with areas for improvement noted. CONCLUSION: The development and use of a BP target tool increased prescriber consistency and confidence in managing BP in the very old. The tool filled a gap in the absence of guidelines specific to BP management in the very old. The BP target tool has implications for practice, as well as for the training of health care professionals involved in treating and monitoring BP in very old patients.

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)0.023
metaresearch head score (Gemma)0.053
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.053
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.022
GPT teacher head0.317
Teacher spread0.295 · 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 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

Citations5
Published2014
Admission routes2
Has abstractyes

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