Evidence map›Paper›PMID 30185574›Full record

ArticleBMJ open2018

Demographic and clinical factors associated with different antidepressant treatments: a retrospective cohort study design in a UK psychiatric healthcare setting.

Andrea C Fernandes, David Chandran, Mizanur Khondoker, Michael Dewey, Hitesh Shetty, Rina Dutta, Robert Stewart

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 28% 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

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

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Efficacy and safety ofFood & nutrition research · 2018
    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

7 authors at 3 institutions in 1 country.

Andrea C FernandesInstitute of Psychiatry, Psychology and Neuroscience, King's College London (KCL), London, UK.
David ChandranInstitute of Psychiatry, Psychology and Neuroscience, King's College London (KCL), London, UK.
Mizanur KhondokerDepartment of Medical Statistics, University of East Anglia, Norwich, UK.
Michael DeweyFreelance Health Statistics Consultant and KCL, London, UK.
Hitesh ShettySouth London and Maudsley NHS Foundation Trust, London, UK.
Rina DuttaInstitute of Psychiatry, Psychology and Neuroscience, King's College London (KCL), London, UK.
Robert StewartInstitute of Psychiatry, Psychology and Neuroscience, King's College London (KCL), London, UK.
King's College London · GBSouth London and Maudsley NHS Foundation Trust · GBUniversity of East Anglia · GB

Funding

Medical Research Council MC_PC_17214
6 · The paper itself

Abstract

objectiveTo investigate the demographic and clinical factors associated with antidepressant use for depressive disorder in a psychiatric healthcare setting using a retrospective cohort study design.

settingData were extracted from a de-identified data resource sourced from the electronic health records of a London mental health service. Relative risk ratios (RRRs) were obtained from multinomial logistic regression analysis to ascertain the probability of receiving common antidepressant treatments relative to sertraline.

participantsPatients were included if they received mental healthcare and a diagnosis of depression with antidepressant treatment between March and August 2015 and exposures were measured over the preceding 12 months.

resultsOlder age was associated with increased use of all antidepressants compared with sertraline, except for negative associations with fluoxetine (RRR 0.98; 95% CI 0.96 to 0.98) and a combination of two selective serotonin reuptake inhibitors (SSRIs) (0.98; 95% CI 0.96 to 0.99), and no significant association with escitalopram. Male gender was associated with increased use of mirtazapine compared with sertraline (2.57; 95% CI 1.85 to 3.57). Previous antidepressant, antipsychotic and mood stabiliser use were associated with newer antidepressant use (ie, selective norepinephrine reuptake inhibitors, mirtazapine or a combination of both), while affective symptoms were associated with reduced use of citalopram (0.58; 95% CI 0.27 to 0.83) and fluoxetine (0.42; 95% CI 0.22 to 0.72) and somatic symptoms were associated with increased use of mirtazapine (1.60; 95% CI 1.00 to 2.75) relative to sertraline. In patients older than 25 years, past benzodiazepine use was associated with a combination of SSRIs (2.97; 95% CI 1.32 to 6.68), mirtazapine (1.94; 95% CI 1.20 to 3.16) and venlafaxine (1.87; 95% CI 1.04 to 3.34), while past suicide attempts were associated with increased use of fluoxetine (2.06; 95% CI 1.10 to 3.87) relative to sertraline.

conclusionThere were several factors associated with different antidepressant receipt in psychiatric healthcare. In patients aged >25, those on fluoxetine were more likely to have past suicide attempt, while past use of antidepressant and non-antidepressant use was also associated with use of new generation antidepressants, potentially reflecting perceived treatment resistance.

Indexed as

AdultAge FactorsAntidepressive AgentsCohort StudiesDepressionDrug Therapy, CombinationDrug UtilizationFemaleHumansLondonMaleMental Health ServicesMiddle AgedRetrospective StudiesSelective Serotonin Reuptake InhibitorsSeverity of Illness IndexAntidepressive AgentsSelective Serotonin Reuptake Inhibitorsantidepressant prescriptionantidepressant useclinical factorsdepressive disorderspsychiatric servicesecondary care

Identifiers

PMID30185574
PMCPMC6129089
OpenAlexW2891117581

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.