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Record W2799419695 · doi:10.1097/mbp.0000000000000323

Diagnostic precision of mentally estimated home blood pressure means

2018· article· en· W2799419695 on OpenAlex
Franck Ouattara, Mikhael Laskine, Nathalie Ng Cheong, Leora Birnbaum, Robert Wistaff, Michel E. Bertrand, Paul Nguyen, Christophe Kolan, Madéleine Durand, Félix Rinfret, Maxime Lamarre-Cliché

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBlood Pressure Monitoring · 2018
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsMcGill University Health CentreMontreal Clinical Research InstituteCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineBlood pressureChartDiastoleEmergency medicineStatisticsInternal medicineMathematics

Abstract

fetched live from OpenAlex

CONTEXT: Paper home blood pressure (HBP) charts are commonly brought to physicians at office visits. The precision and accuracy of mental calculations of blood pressure (BP) means are not known. METHODS: A total of 109 hypertensive patients were instructed to measure and record their HBP for 1 week and to bring their paper charts to their office visit. Study section 1: HBP means were calculated electronically and compared to corresponding in-office BP estimates made by physicians. Study section 2: 100 randomly ordered HBP charts were re-examined repetitively by 11 evaluators. Each evaluator estimated BP means four times in 5, 15, 30, and 60 s (random order) allocated for the task. BP means and diagnostic performance (determination of therapeutic systolic and diastolic BP goals attained or not) were compared between physician estimates and electronically calculated results. RESULTS: Overall, electronically and mentally calculated BP means were not different. Individual analysis showed that 83% of in-office physician estimates were within a 5-mmHg systolic BP range. There was diagnostic disagreement in 15% of cases. Performance improved consistently when the time allocated for BP estimation was increased from 5 to 15 s and from 15 to 30 s, but not when it exceeded 30 s. CONCLUSION: Mentally calculating HBP means from paper charts can cause a number of diagnostic errors. Chart evaluation exceeding 30 s does not significantly improve accuracy. BP-measuring devices with modern analytical capacities could be useful to physicians.

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.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.405
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.032
GPT teacher head0.292
Teacher spread0.260 · 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