Evidence map›Paper›PMID 35207666›Full record

ArticleJournal of personalized medicine2022

Antidepressants Drug Use during COVID-19 Waves in the Tuscan General Population: An Interrupted Time-Series Analysis.

Ippazio Cosimo Antonazzo, Carla Fornari, Sandy Maumus-Robert, Eleonora Cei, Olga Paoletti, Pietro Ferrara, Sara Conti, Paolo Angelo Cortesi, Lorenzo Giovanni Mantovani, Rosa Gini and 1 more

Open access · goldAbstract read
In one paragraph

Article in Journal of personalized medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 15% of its field
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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Observational
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 4 institutions in 2 countries.

Ippazio Cosimo AntonazzoResearch Centre on Public Health (CESP), University of Milan-Bicocca, 20900 Monza, Italy.ORCID 0000-0001-8046-4574
Carla FornariResearch Centre on Public Health (CESP), University of Milan-Bicocca, 20900 Monza, Italy.ORCID 0000-0002-9609-9556
Sandy Maumus-RobertTeam Pharmacoepidemiology, Bordeaux Population Health Research Center, Inserm U1219, University of Bordeaux, F-33000 Bordeaux, France.
Eleonora CeiResearch Centre on Public Health (CESP), University of Milan-Bicocca, 20900 Monza, Italy.
Olga PaolettiRegional Agency for Healthcare Services of Tuscany, Epidemiology, 50141 Florence, Italy.
Pietro FerraraResearch Centre on Public Health (CESP), University of Milan-Bicocca, 20900 Monza, Italy.ORCID 0000-0002-0349-3221
Sara ContiResearch Centre on Public Health (CESP), University of Milan-Bicocca, 20900 Monza, Italy.ORCID 0000-0002-5774-3740
Paolo Angelo CortesiResearch Centre on Public Health (CESP), University of Milan-Bicocca, 20900 Monza, Italy.
Lorenzo Giovanni MantovaniResearch Centre on Public Health (CESP), University of Milan-Bicocca, 20900 Monza, Italy.
Rosa GiniRegional Agency for Healthcare Services of Tuscany, Epidemiology, 50141 Florence, Italy.ORCID 0000-0002-6250-877X
Giampiero MazzagliaResearch Centre on Public Health (CESP), University of Milan-Bicocca, 20900 Monza, Italy.
University of Milano-Bicocca · ITMultiMedica · ITAgenzia Regionale di Sanità della Toscana · ITUniversité de Bordeaux · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In Italy, during the COVID-19 waves two lockdowns were implemented to prevent virus diffusion in the general population. Data on antidepressant (AD) use in these periods are still scarce. This study aimed at exploring the impact of COVID-19 lockdowns on prevalence and incidence of antidepressant drug use in the general population. A population-based study using the healthcare administrative database of Tuscany was performed. We selected a dynamic cohort of subjects with at least one ADs dispensing from 1 January 2018 to 27 December 2020. The weekly prevalence and incidence of drug use were estimated across different segments: pre-lockdown (1 January 2018-8 March 2020), first lockdown (9 March 2020-15 June 2020), post-first lockdown (16 June 2020-15 November 2020) and second lockdown (16 November 2020-27 December 2020). An interrupted time-series analysis was used to assess the effect of lockdowns on the observed outcomes. Compared to the pre-lockdown we observed an abrupt reduction of ADs incidence (Incidence-Ratio: 0.82; 95% Confidence-Intervals: 0.74-0.91) and a slight weekly decrease of prevalence (Prevalence-Ratio: 0.997; 0.996-0.999). During the post-first lockdown AD use increased, with higher incidence- and similar prevalence values compared with those expected in the absence of the outbreak. This pandemic has impacted AD drug use in the general population with potential rebound effects during the period between waves. This calls for future studies aimed at exploring the mid-long term effects of this phenomenon.

Indexed as

antidepressantsCOVID-19healthcare administrative databaselockdownpharmacoepidemiology

Identifiers

PMID35207666
PMCPMC8879880
OpenAlexW4214583279

What OpenQuestion holds

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Registered trials

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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.