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Awareness of Hypertension and Proteinuria in Randomly Selected Patients in 11 Italian Cities. A 2005 Report of the National Kidney Foundation of Italy

2009· article· en· W2022721019 on OpenAlexaff
Diego Brancaccio, Mario Cozzolino, Guido Bellinghieri, U. Buoncristianí, F. Cavatorta, Ludovica D’Apice, Biagio Di Iorio, Loreto Gesualdo, Salvatore Gianni, Biagio Ricciardi, Domenico Russo, Vittorio E. Andreucci

Bibliographic record

VenueJournal of Clinical Hypertension · 2009
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsImperial Oil (Canada)
Fundersnot available
KeywordsProteinuriaMedicineKidney diseaseBlood pressureInternal medicineDiabetes mellitusDiseaseKidneyIntensive care medicineEndocrinology

Abstract

fetched live from OpenAlex

Arterial hypertension and proteinuria are risk factors for chronic kidney disease. A mobile clinic was parked in a central plaza of 11 Italian cities to check blood pressure (BP), prescribe antihypertensive drugs, assess for proteinuria, and provide awareness about hypertension. Among 3757 patients, 56% were hypertensive, 37% were not diabetic nor proteinuric with BP >or=140/90 mm Hg, 17% were diabetic or proteinuric with BP >or=130/80 mm Hg, and 11% were on treatment with BP at target. Among 1204 treated patients, 400 (33%) had controlled BP. Among all 2114 hypertensive patients, only 1344 (64%) were aware of their hypertension. Awareness was greater among treated patients at target (99%). As many as 523 (14%) patients had proteinuria >or=30 mg/dL. The authors conclude that awareness of people walking in the street about their BP and proteinuria is insufficient. Mobile screening clinics may increase public awareness and detection of hypertension and proteinuria in the general community and detect patients at risk for chronic kidney disease.

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)0.001
metaresearch head score (Gemma)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.078
GPT teacher head0.350
Teacher spread0.272 · 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

Citations6
Published2009
Admission routes1
Has abstractyes

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