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Record W4392615909

Prevalence and Determinants of Long-Term Utilization of Antidepressant Drugs: A Retrospective Cohort Study

2020· article· en· W4392615909 on OpenAlexaboutno aff
Carlotta Lunghi, Antonazzo IC, Samir Burato, Emanuel Raschi, V. Zoffoli, Emanuele Forcesi, Elisa Sangiorgi, Marco Menchetti, Pasquale Roberge, Elisabetta Poluzzi

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2020
Typearticle
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsnot available
Fundersnot available
KeywordsAntidepressantRetrospective cohort studyTerm (time)CohortMedicineEnvironmental healthPsychiatryDemographyPharmacologyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Carlotta Lunghi,1– 3 Ippazio Cosimo Antonazzo,2 Sofia Burato,2 Emanuel Raschi,2 Violetta Zoffoli,2 Emanuele Forcesi,2 Elisa Sangiorgi,4 Marco Menchetti,5 Pasquale Roberge,3,6 Elisabetta Poluzzi2 1Department of Health Sciences, Université Du Québec À Rimouski, Lévis, Québec, Canada; 2Department of Medical and Surgical Sciences, Pharmacology Unit, Alma Mater Studiorum, University of Bologna, Bologna, Italy; 3Groupe De Recherche PRIMUS, Centre De Recherche Du CHUS, Université De Sherbrooke, Sherbrooke, Canada; 4Drug Policy Service, Emilia Romagna Region Health Authority, Bologna, Italy; 5Department of Biomedical and Neuromotor Sciences, Alma Mater Studiorum, University of Bologna, Bologna, Italy; 6Faculty of Medicine and Health Sciences, Université De Sherbrooke, Sherbrooke, Québec, CanadaCorrespondence: Carlotta LunghiDepartment of Health Sciences, Université Du Québec À Rimouski, 1595 Boulevard Alphonse Desjardins, Lévis, Québec G6V 0A6, CanadaTel +1 418-833-8800 Ext. 3275Email Carlotta_Lunghi@uqar.caPurpose: Antidepressant consumption has risen in recent years, driven by longer treatment duration. The objective of this study was to measure the prevalence of antidepressant long-term and chronic use in the Bologna area, Italy, and to identify their main determinants.Materials and Methods: We conducted a retrospective claims-based cohort study by using the Bologna Local Health Authority data. A cohort of 18,307 incident users of antidepressant drugs in 2013 was selected, and subjects were followed for three years. A long-term utilization was defined as having at least one prescription claimed during each year of follow-up, while chronic utilization was defined as claiming at least 180 defined daily doses per year. Factors associated with chronic and long-term use were identified by univariate and multivariate logistic regressions.Results: In our cohort, 5448 (29.8%) and 1817 (9.9%) subjects were dispensed antidepressants for a long-term course and in a chronically way, respectively. Older age, antidepressant polytherapy, polypharmacy, and being prescribed the first antidepressant by a hospital physician were all factors independently associated with chronic and long-term prescriptions of antidepressant drugs. Results were reported separately for men and women.Conclusion: Antidepressant long-term and chronic prescriptions are common in the Bologna area. Because longer treatment should be clinically motivated, these results strongly prompt the need to evaluate the actual relevance, as they may indicate potentially inappropriate prescription patterns.Keywords: antidepressants, depression, anxiety, anxiety disorders, primary care, pharmacotherapy, adherence, epidemiology, pharmacoepidemiology, treatment

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)0.002
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 score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.212
GPT teacher head0.537
Teacher spread0.325 · 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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Citations2
Published2020
Admission routes1
Has abstractyes

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