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Record W4318166210 · doi:10.1701/3966.39449

Sviluppo di eventi cardiovascolari in un’ampia popolazione di pazienti affetti da artrite reumatoide con o senza diabete

2023· article· en· W4318166210 on OpenAlexaff
Silvia Calabria, Giulia Ronconi, Letizia Dondi, Carlo Piccinni, Antonella Pedrini, Leonardo Dondi, Irene Dell’Anno, Immacolata Esposito, Alice Addesi, Nello Martini, Aldo P. Maggioni

Bibliographic record

VenueRecenti Progressi in Medicina · 2023
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsHealth Care Foundation
Fundersnot available
KeywordsMedicineDiabetes mellitusInternal medicineDyslipidemiaComorbidityStroke (engine)COPDRheumatoid arthritisCohortCoronary artery diseasePopulationType 2 diabetesDiseaseEndocrinology

Abstract

fetched live from OpenAlex

INTRODUCTION: Rheumatoid arthritis (Ra) and diabetes are often associated with chronic multimorbidity and share the high risk of development of major cardiovascular events (Mace). This study aimed to identify and analyse patients with only Ra, Ra + diabetes, and only diabetes, in terms of comorbidities and new occurrence of Cv events, from the perspective of the Italian national health service (Inhs). METHODS: Starting from the Fondazione ricerca e salute (ReS)'s database, through the record linkage of administrative healthcare data, cohorts with only Ra, Ra + diabetes and only diabetes have been selected, characterized (age and sex), and analysed by comorbidity (depression, dyslipidemia, hypertension, hemorrhagic stroke and ischemic stroke/transient ischemic attack - Tia, coronary artery disease - Cad, heart failure - Hf, chronic liver disease, periphery artery disease - Pad, chronic kidney disease, asthma/chronic obstructive pulmonary disease - Copd, neoplasia) and by new Cv events (Hf, Cad and ischemic stroke/Tia) within two follow-up years (Kaplan-Meier curves). A logistic regression model defined contribution and type of association of some variables on new Cv events. RESULTS: In 2018, from 5.375.531 Inhs beneficiaries in the ReS database, 13.698 (0.25%) were affected by only Ra, 1728 (0.03%) by Ra + diabetes, 347,659 (6.8%) by only diabetes. The only Ra cohort was composed by more females, younger and with less comorbidities patients. Proportions of 79.3%, 70.8% and 38.5% of patients with Ra + diabetes, only diabetes and only Ra were affected by 2 to ≥4 comorbidities: among patients with Ra + diabetes, comorbidities showed the highest frequencies, mainly hypertension, dyslipidemia and asthma/Copd. Within two follow-up years, about 8% of patients with diabetes with/without Ra developed a new Cv event (vs 3% with only Ra). The presence of Ra/diabetes or Ra + diabetes, male sex, older age and comorbidities of interest resulted significantly (p<0.01) associated with a higher Cv risk. CONCLUSIONS: Comorbidities and the co-presence of diabetes in patients with Ra determine a complicated framework with high risk of Cv events. It is worthy include more complex patients in clinical trials, in order to generate evidence useful for even more multidisciplinary medical teams.

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)0.003
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 score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.022
GPT teacher head0.311
Teacher spread0.289 · 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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