Evidence map›Paper›PMID 22706616›Full record

ArticleEuropean journal of clinical pharmacology2013

A nationwide prospective study on prescribing pattern of antidepressant drugs in Italian primary care.

Gianluca Trifirò, Silvia Tillati, Edoardo Spina, Carmen Ferrajolo, Marianna Alacqua, Eugenio Aguglia, Laura Rizzi, Achille P Caputi, Claudio Cricelli, Fabio Samani

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Article in European journal of clinical pharmacology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Gianluca TrifiròDepartment of Clinical and Experimental Medicine and Pharmacology, University of Messina, Via Consolare Valeria Gazzi, 98125 Messina, Italy. trifirog@unime.it
Silvia Tillati
Edoardo Spina
Carmen Ferrajolo
Marianna Alacqua
Eugenio Aguglia
Laura Rizzi
Achille P Caputi
Claudio Cricelli
Fabio Samani

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeOur purpose was to explore antidepressant drug (AD) prescribing patterns in Italian primary care.

methodsOverall, 276 Italian general practitioners (GPs) participated in this prospective study, recruiting patients >18 years who started AD therapy during the enrolment period (January 2007 to June 2008). During visits at baseline and 3, 6, and 12 months, data about patients' characteristics and AD treatments were collected by the GPs. Discontinuation rate among new users of AD classes [i.e., selective serotonin reuptake inhibitors (SSRI); tricyclics (TCAs); other ADs) were compared. Logistic regression analyses were performed to identify predictors of AD discontinuation.

resultsSSRIs were the most frequently prescribed ADs (N = 1,037; 75.3 %), especially paroxetine and escitalopram. SSRIs were more likely to be prescribed because of depressive disorders (80 %), and by GPs (51.1 %) rather than psychiatrists (31.8 %). Overall, 27.5 % (N = 378) of AD users discontinued therapy during the first year, mostly in the first 3 months (N = 242; 17.6 %), whereas 185 (13.4 %) were lost to follow-up. SSRI users showed the highest discontinuation rate (29 %). In patients with depressive disorders, younger age, psychiatrist-based diagnosis, and treatment started by GPs were independent predictors of SSRI discontinuation.

conclusionsIn Italy, ADs-especially SSRIs-are widely prescribed by GPs because of depressive/anxiety disorders. Active monitoring of AD users in general practice might reduce the AD discontinuation rate.

Indexed as

AdolescentAdultAgedAged, 80 and overAntidepressive AgentsAnxiety DisordersDepressive DisorderFemaleHumansItalyMaleMiddle AgedPractice Patterns, Physicians'Primary Health CareProspective StudiesSelective Serotonin Reuptake InhibitorsAntidepressive AgentsSelective Serotonin Reuptake Inhibitors

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.