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Record W2024932622 · doi:10.1136/ebn.10.2.52

Addition of peak flow monitoring to symptom monitoring did not improve healthcare visits, quality of life, or lung function in older adults with moderate-to-severe asthma

2007· letter· en· W2024932622 on OpenAlexaff
Lisa Cicutto

Bibliographic record

VenueEvidence-Based Nursing · 2007
Typeletter
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLung functionAsthmaMedicineQuality of life (healthcare)Health careIntensive care medicineEmergency medicineLungInternal medicineNursing

Abstract

fetched live from OpenAlex

Buist AS, Vollmer WM, Wilson SR, et al . A randomized clinical trial of peak flow versus symptom monitoring in older adults with asthma. Am J Respir Crit Care Med 2006;174:1077–87.[OpenUrl][1][CrossRef][2][PubMed][3] Q In older adults with moderate-to-severe asthma, is symptom monitoring plus peak flow monitoring (PFM) (used as part of a comprehensive management plan) better than symptom monitoring alone for healthcare utilisation, quality of life, and lung function? ### ![Graphic][4] Design: randomised controlled trial. ### ![Graphic][5] Allocation: {concealed}.* ### ![Graphic][6] Blinding: blinded (data collectors and {healthcare providers}*). ### ![Graphic][7] Follow up period: up to 2 years. ### ![Graphic][8] Setting: a large managed care organisation in Oregon, USA. ### ![Graphic][9] Patients: 296 adults 50–92 years of age (mean age 66 y, 52% women) who had physician diagnosed asthma, medication use suggestive of moderate-to-severe asthma, bronchodilator reversibility (>8% of baseline forced expiratory volume in 1 sec [FEV1 … [1]: {openurl}?query=rft.jtitle%253DAmerican%2BJournal%2Bof%2BRespiratory%2Band%2BCritical%2BCare%2BMedicine%26rft.stitle%253DAm.%2BJ.%2BRespir.%2BCrit.%2BCare%2BMed.%26rft.volume%253D174%26rft.issue%253D10%26rft.spage%253D1077%26rft.epage%253D1087%26rft.atitle%253DA%2BRandomized%2BClinical%2BTrial%2Bof%2BPeak%2BFlow%2Bversus%2BSymptom%2BMonitoring%2Bin%2BOlder%2BAdults%2Bwith%2BAsthma.%26rft_id%253Dinfo%253Adoi%252F10.1164%252Frccm.200510-1606OC%26rft_id%253Dinfo%253Apmid%252F16931634%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1164/rccm.200510-1606OC&link_type=DOI [3]: /lookup/external-ref?access_num=16931634&link_type=MED&atom=%2Febnurs%2F10%2F2%2F52.atom [4]: /embed/inline-graphic-1.gif [5]: /embed/inline-graphic-2.gif [6]: /embed/inline-graphic-3.gif [7]: /embed/inline-graphic-4.gif [8]: /embed/inline-graphic-5.gif [9]: /embed/inline-graphic-6.gif

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)0.003
metaresearch head score (Gemma)0.008
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 score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.005
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0100.000

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 head0.037
GPT teacher head0.335
Teacher spread0.299 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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